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22
.github/workflows/build.yml vendored
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@ -145,6 +145,28 @@ jobs:
cd build
ctest -L main --verbose
ubuntu-22-cmake-vulkan:
runs-on: ubuntu-22.04
steps:
- name: Clone
id: checkout
uses: actions/checkout@v3
- name: Dependencies
id: depends
run: |
sudo apt-get update
sudo apt-get install build-essential libvulkan-dev
- name: Build
id: cmake_build
run: |
mkdir build
cd build
cmake -DLLAMA_VULKAN=ON ..
cmake --build . --config Release -j $(nproc)
ubuntu-22-cmake-sycl:
runs-on: ubuntu-22.04

116
awq-py/README.md
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@ -1,116 +0,0 @@
# AWQ: Activation-aware Weight Quantization for LLM - version apply to llamacpp
[[Paper](https://arxiv.org/abs/2306.00978)][[Original Repo](https://github.com/mit-han-lab/llm-awq)][[Easy-to-use Repo](https://github.com/casper-hansen/AutoAWQ)]
**Supported models:**
- [X] LLaMA
- [x] LLaMA 2
- [X] MPT
- [X] Mistral AI v0.1
- [ ] Bloom
- [ ] Mixtral MoE
**TODO:**
- [x] Update version work with both MPT and MPT-AWQ model
- [ ] Add OPT model
- [ ] Add Bloom model
- [ ] Add Mixtral MoE
- [ ] Support w3, w2
## Contents
- [Install](##Install)
- [Convert](##Convert)
- [Quantize](##Quantize)
- [Test](##Test)
- [Benchmark](##Benchmark)
- [Results](##Results)
## Install
Install requirements
```bash
pip install -r requirements.txt
```
Get the pre-computed AWQ search results for multiple model families, including LLaMA, LLaMA2, MPT, OPT
```bash
git clone https://huggingface.co/datasets/mit-han-lab/awq-model-zoo awq_cache
```
## Convert
Example for llama model
```bash
# For llama7b and llama2 models
python convert.py models/llama-7b/ --awq-path awq_cache/llama-7b-w4-g128.pt --outfile models/llama_7b_fp16.gguf
# For mistral and mpt models
python convert-hf-to-gguf.py models/mpt-7b/ --awq-path awq_cache/mpt-7b-w4-g128.pt --outfile models/mpt_7b_fp16.gguf
```
## Quantize
```bash
# We only benchmark and confirm the results on q4_0, q4_1, and q2_k types.
./quantize models/llama_7b_fp16.gguf models/llama_7b_q4_0.gguf q4_0
```
## Test
```bash
# For all models.
./build/bin/main -m models/llama_7b_q4_0.gguf -n 128 --prompt "Once upon a time"
```
## Benchmark
The perplexity measurements in table above are done against the `wikitext2` test dataset (https://paperswithcode.com/dataset/wikitext-2), with context length of 512.
```bash
# For llama and llama2, and mistral models.
./perplexity -m models/llama_7b_q4_0.gguf -f datasets/wikitext-2-raw/wiki.test.raw
```
## Results
Results are run on OpenBLAS (CPU) and CuBLAS (GPU) for fair comparison
We use three types of llamacpp quantization methods to work with our version, including q4_0, q4_1, and q2_k
### Llama 7B (Build with OpenBLAS)
| Model | Measure | F16 | Q4_0 | Q4_1 | Q2_K |
|-----------:|--------------|-------:|-------:|-------:|-------:|
|Llama 7B | perplexity | 5.9066 | 6.1214 | 6.0643 | 6.5808 |
|Llama 7B | file size | 12.9G | 3.5G | 3.9G | 2.7G |
|Llama 7B | bits/weight | 16.0 | 4.5 | 5.0 | 2.6 |
|AWQ-LLama 7B| perplexity | 5.9175 | 6.0252 | 5.9987 | 6.3692 |
|AWQ-LLama 7B| file size | 12.9G | 3.5G | 3.9G | 2.7G |
|AWQ-LLama 7B| bits/weight | 16.0 | 4.5 | 5.0 | 2.6 |
### Llama2 7B (Build with CuBLAS)
| Model | Measure | F16 | Q4_0 | Q4_1 | Q2_K |
|------------:|--------------|-------:|-------:|-------:|-------:|
|Llama2 7B | perplexity | 5.8664 | 6.0260 | 6.0656 | 6.4496 |
|Llama2 7B | file size | 12.9G | 3.5G | 3.9G | 2.7G |
|Llama2 7B | bits/weight | 16.0 | 4.5 | 5.0 | 2.6 |
|AWQ-LLama2 7B| perplexity | 5.8801 | 6.0054 | 5.9849 | 6.3650 |
|AWQ-LLama2 7B| file size | 12.9G | 3.5G | 3.9G | 2.7G |
|AWQ-LLama2 7B| bits/weight | 16.0 | 4.5 | 5.0 | 2.6 |
### Mistral 7B v0.1 (Build with CuBLAS)
| Model | Measure | F16 | Q4_0 | Q4_1 | Q2_K |
|-------------:|--------------|-------:|-------:|-------:|-------:|
|Mistral 7B | perplexity | 5.6931 | 5.8202 | 5.8268 | 6.1645 |
|Mistral 7B | file size | 14.5G | 4.1G | 4.5G | 3.1G |
|Mistral 7B | bits/weight | 16.0 | 4.5 | 5.0 | 2.6 |
|AWQ-Mistral 7B| perplexity | 5.6934 | 5.8020 | 5.7691 | 6.0426 |
|AWQ-Mistral 7B| file size | 14.5G | 4.1G | 4.5G | 3.1G |
|AWQ-Mistral 7B| bits/weight | 16.0 | 4.5 | 5.0 | 2.6 |
### MPT 7B (Build with OpenBLAS)
| Model | Measure | F16 | Q4_0 | Q4_1 | Q2_K |
|---------:|--------------|-------:|-------:|-------:|--------:|
|MPT 7B | perplexity | 8.4369 | 8.7956 | 8.6265 | 11.4913 |
|MPT 7B | file size | 13.7G | 3.9G | 4.3G | 2.8G |
|MPT 7B | bits/weight | 16.0 | 4.5 | 5.0 | 2.6 |
|AWQ-MPT 7B| perplexity | 8.4944 | 8.7053 | 8.6750 | 10.2873|
|AWQ-MPT 7B| file size | 13.7G | 3.9G | 4.3G | 2.8G |
|AWQ-MPT 7B| bits/weight | 16.0 | 4.5 | 5.0 | 2.6 |

254
awq-py/awq/apply_awq.py
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@ -1,254 +0,0 @@
"""
Implements the AWQ for llama.cpp use cases.
Original paper: https://arxiv.org/abs/2306.00978
This code is based on versions of the AWQ implementation found in the following repositories:
* https://github.com/mit-han-lab/llm-awq
* https://github.com/casper-hansen/AutoAWQ
"""
import os
import torch
import torch.nn as nn
from transformers import AutoModelForCausalLM, AutoConfig
from transformers.models.bloom.modeling_bloom import BloomGelu
from transformers.models.llama.modeling_llama import LlamaRMSNorm
from transformers.activations import GELUActivation
class ScaledActivation(nn.Module):
"""
ScaledActivation module wraps an existing activation function and applies a
scale factor to its output.
Args:
module (nn.Module): The activation function to be scaled.
scales (torch.Tensor): A tensor of size (num_features,) containing the initial
scale factors for each feature.
Returns:
torch.Tensor: The scaled output of the activation function.
"""
def __init__(self, module, scales):
super().__init__()
self.act = module
self.scales = nn.Parameter(scales.data)
def forward(self, x):
return self.act(x) / self.scales.view(1, 1, -1).to(x.device)
def set_op_by_name(layer, name, new_module):
"""
Set the new module for given module's name.
Args:
layer (nn.Module): The layer in which to replace the submodule.
name (str): The path to the submodule to be replaced, using dot notation
to access nested modules.
new_module (nn.Module): The new module to replace the existing one.
"""
levels = name.split(".")
if len(levels) > 1:
mod_ = layer
for l_idx in range(len(levels) - 1):
if levels[l_idx].isdigit():
mod_ = mod_[int(levels[l_idx])]
else:
mod_ = getattr(mod_, levels[l_idx])
setattr(mod_, levels[-1], new_module)
else:
setattr(layer, name, new_module)
def get_op_by_name(module, op_name):
"""
Retrieves a submodule within a given layer based on its name.
Args:
module (nn.Module): The layer containing the submodule to find.
op_name (str): The name of the submodule.
Returns:
nn.Module: The requested submodule found within the given layer.
Raises:
ValueError: If the specified submodule cannot be found within the layer.
"""
for name, m in module.named_modules():
if name == op_name:
return m
raise ValueError(f"Cannot find op {op_name} in module {module}")
@torch.no_grad()
def scale_ln_fcs(ln, fcs, scales):
"""
Scales the weights of a LayerNorm and a list of fully-connected layers proportionally.
Args:
ln (nn.LayerNorm): The LayerNorm module to be scaled.
fcs (List[nn.Linear]): A list of fully-connected layers to be scaled.
scales (torch.Tensor): A 1D tensor of size (num_features,).
"""
if not isinstance(fcs, list):
fcs = [fcs]
scales = scales.to(ln.weight.device)
ln.weight.div_(scales)
if hasattr(ln, "bias") and ln.bias is not None:
ln.bias.div_(scales)
for fc in fcs:
fc.weight.mul_(scales.view(1, -1))
for p in ln.parameters():
assert torch.isnan(p).sum() == 0
for fc in fcs:
for p in fc.parameters():
assert torch.isnan(p).sum() == 0
@torch.no_grad()
def scale_fc_fc(fc1, fc2, scales):
"""
Scales the weights of two fully-connected layers in a specific pattern.
Args:
fc1 (nn.Linear): The first fully-connected layer to be scaled.
fc2 (nn.Linear): The second fully-connected layer to be scaled.
scales (torch.Tensor): A 1D tensor of size (num_features,).
"""
assert isinstance(fc1, nn.Linear)
assert isinstance(fc2, nn.Linear)
scales = scales.to(fc1.weight.device)
fc1.weight[-scales.size(0):].div_(scales.view(-1, 1))
if fc1.bias is not None:
fc1.bias.div_(scales.view(-1))
fc2.weight.mul_(scales.view(1, -1))
for p in fc1.parameters():
assert torch.isnan(p).sum() == 0
for p in fc2.parameters():
assert torch.isnan(p).sum() == 0
@torch.no_grad()
def scale_gelu_fc(gelu, fc, scales):
"""
Scales the weight of a GELU activation and a fully-connected layer proportionally.
Args:
gelu (Union[nn.GELU, BloomGelu, GELUActivation]): The GELU activation module to be scaled.
fc (nn.Linear): The fully-connected layer to be scaled.
scales (torch.Tensor): A 1D tensor of size (num_features,).
Raises:
TypeError: If the `gelu` module is not of type `nn.GELU`, `BloomGelu`, or `GELUActivation`.
TypeError: If the `fc` module is not of type `nn.Linear`.
"""
assert isinstance(gelu, (nn.GELU, BloomGelu, GELUActivation))
assert isinstance(fc, nn.Linear)
fc.weight.mul_(scales.view(1, -1).to(fc.weight.device))
for p in fc.parameters():
assert torch.isnan(p).sum() == 0
def apply_scale(module, scales_list, input_feat_dict=None):
"""
Applies different scaling strategies to layers based on their type and hierarchy within a given module.
Args:
module (nn.Module): The module containing the layers to be scaled.
scales_list (List[Tuple[str, List[str], torch.Tensor]]): A list of tuples containing:
* prev_op_name (str): The name of the preceding operation or module,
relative to which the layers to be scaled are located.
* layer_names (List[str]): A list of names of the layers to be scaled, relative to the preceding operation.
* scales (torch.Tensor): A 1D tensor of size (num_features,) containing the scaling factors for each feature.
input_feat_dict (Optional[Dict[str, torch.Tensor]]): A dictionary mapping layer names to their corresponding
input features (optional).
"""
for prev_op_name, layer_names, scales in scales_list:
prev_op = get_op_by_name(module, prev_op_name)
layers = [get_op_by_name(module, name) for name in layer_names]
prev_op.cuda()
for layer in layers:
layer.cuda()
scales.cuda()
if isinstance(prev_op, nn.Linear):
assert len(layers) == 1
scale_fc_fc(prev_op, layers[0], scales)
elif isinstance(prev_op, (nn.LayerNorm, LlamaRMSNorm)) or "rmsnorm" in str(prev_op.__class__).lower():
scale_ln_fcs(prev_op, layers, scales)
elif isinstance(prev_op, (nn.GELU, BloomGelu, GELUActivation)):
new_module = ScaledActivation(prev_op, scales)
set_op_by_name(module, prev_op_name, new_module)
scale_gelu_fc(prev_op, layers[0], scales)
else:
raise NotImplementedError(f"prev_op {type(prev_op)} not supported yet!")
# apply the scaling to input feat if given; prepare it for clipping
if input_feat_dict is not None:
for layer_name in layer_names:
inp = input_feat_dict[layer_name]
inp.div_(scales.view(1, -1).to(inp.device))
prev_op.cpu()
for layer in layers:
layer.cpu()
scales.cpu()
@torch.no_grad()
def apply_clip(module, clip_list):
"""
Applies element-wise clipping to the weight of a specific layer within a given module.
Args:
module (nn.Module): The module containing the layer to be clipped.
clip_list (List[Tuple[str, torch.Tensor]]): A list of tuples containing:
* name (str): The name of the layer to be clipped, relative to the root of the module.
* max_val (torch.Tensor): A 1D or 2D tensor defining the upper bound for each element of the layer's weight.
"""
for name, max_val in clip_list:
layer = get_op_by_name(module, name)
layer.cuda()
max_val = max_val.to(layer.weight.device)
org_shape = layer.weight.shape
layer.weight.data = layer.weight.data.reshape(*max_val.shape[:2], -1)
layer.weight.data = torch.clamp(layer.weight.data, -max_val, max_val)
layer.weight.data = layer.weight.data.reshape(org_shape)
layer.cpu()
def add_scale_weights(model_path, scale_path, tmp_path):
"""
Adds pre-computed Activation Weight Quantization (AWQ) results to a model,
including scaling factors and clipping bounds.
Args:
model_path (str): Path to the pre-trained model to be equipped with AWQ.
scale_path (str): Path to the AWQ scale factors (.pt file).
tmp_path (str): Path to the temporary directory where the equipped model will be saved.
"""
config = AutoConfig.from_pretrained(model_path, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
model_path, config=config, trust_remote_code=True
)
model.eval()
awq_results = torch.load(str(scale_path), map_location="cpu")
apply_scale(model, awq_results["scale"])
apply_clip(model, awq_results["clip"])
model.save_pretrained(str(tmp_path))
os.system(f"cp {str(model_path)}/tokenizer* {str(tmp_path)}")

2
awq-py/requirements.txt
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@ -1,2 +0,0 @@
torch>=2.1.1
transformers>=4.32.0

34
ci/run.sh
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@ -272,19 +272,19 @@ function gg_run_open_llama_3b_v2 {
(time ./bin/main --model ${model_q5_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/main --model ${model_q6_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/perplexity --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/perplexity --model ${model_q8_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/perplexity --model ${model_q4_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/perplexity --model ${model_q4_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/perplexity --model ${model_q5_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/perplexity --model ${model_q5_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/perplexity --model ${model_q2_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/perplexity --model ${model_q3_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/perplexity --model ${model_q4_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/perplexity --model ${model_q5_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/perplexity --model ${model_q6_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/perplexity --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/perplexity --model ${model_q8_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/perplexity --model ${model_q4_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/perplexity --model ${model_q4_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/perplexity --model ${model_q5_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/perplexity --model ${model_q5_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/perplexity --model ${model_q2_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/perplexity --model ${model_q3_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/perplexity --model ${model_q4_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/perplexity --model ${model_q5_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/perplexity --model ${model_q6_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/imatrix --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/imatrix --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/save-load-state --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
@ -343,17 +343,17 @@ function gg_run_open_llama_3b_v2 {
python3 ../convert-lora-to-ggml.py ${path_lora}
# f16
(time ./bin/perplexity --model ${model_f16} -f ${shakespeare} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-f16.log
(time ./bin/perplexity --model ${model_f16} -f ${shakespeare} --lora ${lora_shakespeare} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-f16.log
(time ./bin/perplexity --model ${model_f16} -f ${shakespeare} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-f16.log
(time ./bin/perplexity --model ${model_f16} -f ${shakespeare} --lora ${lora_shakespeare} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-f16.log
compare_ppl "f16 shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-f16.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-f16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log
# q8_0
(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-q8_0.log
(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} --lora ${lora_shakespeare} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-q8_0.log
(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-q8_0.log
(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} --lora ${lora_shakespeare} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-q8_0.log
compare_ppl "q8_0 shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-q8_0.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log
# q8_0 + f16 lora-base
(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} --lora ${lora_shakespeare} --lora-base ${model_f16} -c 128 -b 128 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log
(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} --lora ${lora_shakespeare} --lora-base ${model_f16} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log
compare_ppl "q8_0 / f16 base shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-q8_0.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log
set +e

4
common/common.cpp
View file

@ -1015,7 +1015,7 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
printf(" --ignore-eos ignore end of stream token and continue generating (implies --logit-bias 2-inf)\n");
printf(" --no-penalize-nl do not penalize newline token\n");
printf(" --temp N temperature (default: %.1f)\n", (double)sparams.temp);
printf(" --logits-all return logits for all tokens in the batch (default: disabled)\n");
printf(" --all-logits return logits for all tokens in the batch (default: disabled)\n");
printf(" --hellaswag compute HellaSwag score over random tasks from datafile supplied with -f\n");
printf(" --hellaswag-tasks N number of tasks to use when computing the HellaSwag score (default: %zu)\n", params.hellaswag_tasks);
printf(" --winogrande compute Winogrande score over random tasks from datafile supplied with -f\n");
@ -1281,7 +1281,6 @@ struct llama_context_params llama_context_params_from_gpt_params(const gpt_param
cparams.n_batch = params.n_batch;
cparams.n_threads = params.n_threads;
cparams.n_threads_batch = params.n_threads_batch == -1 ? params.n_threads : params.n_threads_batch;
cparams.mul_mat_q = params.mul_mat_q;
cparams.seed = params.seed;
cparams.logits_all = params.logits_all;
cparams.embedding = params.embedding;
@ -1725,7 +1724,6 @@ void dump_non_result_info_yaml(FILE * stream, const gpt_params & params, const l
fprintf(stream, "n_predict: %d # default: -1 (unlimited)\n", params.n_predict);
fprintf(stream, "n_probs: %d # only used by server binary, default: 0\n", sparams.n_probs);
fprintf(stream, "no_mmap: %s # default: false\n", !params.use_mmap ? "true" : "false");
fprintf(stream, "no_mul_mat_q: %s # default: false\n", !params.mul_mat_q ? "true" : "false");
fprintf(stream, "no_penalize_nl: %s # default: false\n", !sparams.penalize_nl ? "true" : "false");
fprintf(stream, "ppl_output_type: %d # default: 0\n", params.ppl_output_type);
fprintf(stream, "ppl_stride: %d # default: 0\n", params.ppl_stride);

1
common/common.h
View file

@ -115,7 +115,6 @@ struct gpt_params {
bool kl_divergence = false; // compute KL-divergence
bool mul_mat_q = true; // if true, use mul_mat_q kernels instead of cuBLAS
bool random_prompt = false; // do not randomize prompt if none provided
bool use_color = false; // use color to distinguish generations and inputs
bool interactive = false; // interactive mode

7
convert-hf-to-gguf.py
View file

@ -1811,16 +1811,15 @@ class GemmaModel(Model):
tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count)
for name, data_torch in self.get_tensors():
# ref: https://github.com/huggingface/transformers/blob/fc37f38915372c15992b540dfcbbe00a916d4fc6/src/transformers/models/gemma/modeling_gemma.py#L89
if name.endswith("norm.weight"):
data_torch = data_torch + 1
old_dtype = data_torch.dtype
# convert any unsupported data types to float32
if data_torch.dtype not in (torch.float16, torch.float32):
data_torch = data_torch.to(torch.float32)
# ref: https://github.com/huggingface/transformers/blob/fc37f38915372c15992b540dfcbbe00a916d4fc6/src/transformers/models/gemma/modeling_gemma.py#L89
if name.endswith("norm.weight"):
data_torch = data_torch + 1
data = data_torch.squeeze().numpy()
# map tensor names

18
examples/batched-bench/batched-bench.cpp
View file

@ -32,16 +32,15 @@ int main(int argc, char ** argv) {
gpt_params params;
if (argc == 1 || argv[1][0] == '-') {
printf("usage: %s MODEL_PATH [N_KV_MAX] [IS_PP_SHARED] [NGL] [MMQ] <PP> <TG> <PL>\n" , argv[0]);
printf("usage: %s MODEL_PATH [N_KV_MAX] [IS_PP_SHARED] [NGL] <PP> <TG> <PL>\n" , argv[0]);
printf(" <PP>, <TG> and PL are comma-separated lists of numbers without spaces\n\n");
printf(" example: %s ggml-model-f16.gguf 2048 0 999 0 128,256,512 128,256 1,2,4,8,16,32\n\n", argv[0]);
printf(" example: %s ggml-model-f16.gguf 2048 0 999 128,256,512 128,256 1,2,4,8,16,32\n\n", argv[0]);
return 1 ;
}
int n_kv_max = 2048;
int is_pp_shared = 0;
int n_gpu_layers = 0;
int mmq = 0;
std::vector<int> n_pp = { 128, 256, 512, 1024, 2048, 3584, 7680, };
std::vector<int> n_tg = { 128, 256, };
@ -65,19 +64,15 @@ int main(int argc, char ** argv) {
}
if (argc >= 6) {
mmq = std::atoi(argv[5]);
n_pp = parse_list(argv[5]);
}
if (argc >= 7) {
n_pp = parse_list(argv[6]);
n_tg = parse_list(argv[6]);
}
if (argc >= 8) {
n_tg = parse_list(argv[7]);
}
if (argc >= 9) {
n_pl = parse_list(argv[8]);
n_pl = parse_list(argv[7]);
}
// init LLM
@ -106,7 +101,6 @@ int main(int argc, char ** argv) {
ctx_params.seed = 1234;
ctx_params.n_ctx = n_kv_max;
ctx_params.n_batch = 512;
ctx_params.mul_mat_q = mmq;
ctx_params.n_threads = params.n_threads;
ctx_params.n_threads_batch = params.n_threads_batch == -1 ? params.n_threads : params.n_threads_batch;
@ -159,7 +153,7 @@ int main(int argc, char ** argv) {
}
LOG_TEE("\n");
LOG_TEE("%s: n_kv_max = %d, is_pp_shared = %d, n_gpu_layers = %d, mmq = %d, n_threads = %u, n_threads_batch = %u\n", __func__, n_kv_max, is_pp_shared, n_gpu_layers, mmq, ctx_params.n_threads, ctx_params.n_threads_batch);
LOG_TEE("%s: n_kv_max = %d, is_pp_shared = %d, n_gpu_layers = %d, n_threads = %u, n_threads_batch = %u\n", __func__, n_kv_max, is_pp_shared, n_gpu_layers, ctx_params.n_threads, ctx_params.n_threads_batch);
LOG_TEE("\n");
LOG_TEE("|%6s | %6s | %4s | %6s | %8s | %8s | %8s | %8s | %8s | %8s |\n", "PP", "TG", "B", "N_KV", "T_PP s", "S_PP t/s", "T_TG s", "S_TG t/s", "T s", "S t/s");

1
examples/llama-bench/README.md
View file

@ -35,7 +35,6 @@ options:
-mg, --main-gpu <i> (default: 0)
-nkvo, --no-kv-offload <0|1> (default: 0)
-mmp, --mmap <0|1> (default: 1)
-mmq, --mul-mat-q <0|1> (default: 1)
-ts, --tensor_split <ts0/ts1/..> (default: 0)
-r, --repetitions <n> (default: 5)
-o, --output <csv|json|md|sql> (default: md)

30
examples/llama-bench/llama-bench.cpp
View file

@ -176,7 +176,6 @@ struct cmd_params {
std::vector<llama_split_mode> split_mode;
std::vector<int> main_gpu;
std::vector<bool> no_kv_offload;
std::vector<bool> mul_mat_q;
std::vector<std::vector<float>> tensor_split;
std::vector<bool> use_mmap;
int reps;
@ -196,7 +195,6 @@ static const cmd_params cmd_params_defaults = {
/* split_mode */ {LLAMA_SPLIT_MODE_LAYER},
/* main_gpu */ {0},
/* no_kv_offload */ {false},
/* mul_mat_q */ {true},
/* tensor_split */ {std::vector<float>(llama_max_devices(), 0.0f)},
/* use_mmap */ {true},
/* reps */ 5,
@ -221,7 +219,6 @@ static void print_usage(int /* argc */, char ** argv) {
printf(" -mg, --main-gpu <i> (default: %s)\n", join(cmd_params_defaults.main_gpu, ",").c_str());
printf(" -nkvo, --no-kv-offload <0|1> (default: %s)\n", join(cmd_params_defaults.no_kv_offload, ",").c_str());
printf(" -mmp, --mmap <0|1> (default: %s)\n", join(cmd_params_defaults.use_mmap, ",").c_str());
printf(" -mmq, --mul-mat-q <0|1> (default: %s)\n", join(cmd_params_defaults.mul_mat_q, ",").c_str());
printf(" -ts, --tensor_split <ts0/ts1/..> (default: 0)\n");
printf(" -r, --repetitions <n> (default: %d)\n", cmd_params_defaults.reps);
printf(" -o, --output <csv|json|md|sql> (default: %s)\n", output_format_str(cmd_params_defaults.output_format));
@ -383,13 +380,6 @@ static cmd_params parse_cmd_params(int argc, char ** argv) {
}
auto p = split<bool>(argv[i], split_delim);
params.no_kv_offload.insert(params.no_kv_offload.end(), p.begin(), p.end());
} else if (arg == "-mmq" || arg == "--mul-mat-q") {
if (++i >= argc) {
invalid_param = true;
break;
}
auto p = split<bool>(argv[i], split_delim);
params.mul_mat_q.insert(params.mul_mat_q.end(), p.begin(), p.end());
} else if (arg == "-mmp" || arg == "--mmap") {
if (++i >= argc) {
invalid_param = true;
@ -466,7 +456,6 @@ static cmd_params parse_cmd_params(int argc, char ** argv) {
if (params.split_mode.empty()) { params.split_mode = cmd_params_defaults.split_mode; }
if (params.main_gpu.empty()) { params.main_gpu = cmd_params_defaults.main_gpu; }
if (params.no_kv_offload.empty()){ params.no_kv_offload = cmd_params_defaults.no_kv_offload; }
if (params.mul_mat_q.empty()) { params.mul_mat_q = cmd_params_defaults.mul_mat_q; }
if (params.tensor_split.empty()) { params.tensor_split = cmd_params_defaults.tensor_split; }
if (params.use_mmap.empty()) { params.use_mmap = cmd_params_defaults.use_mmap; }
if (params.n_threads.empty()) { params.n_threads = cmd_params_defaults.n_threads; }
@ -486,7 +475,6 @@ struct cmd_params_instance {
llama_split_mode split_mode;
int main_gpu;
bool no_kv_offload;
bool mul_mat_q;
std::vector<float> tensor_split;
bool use_mmap;
@ -518,7 +506,6 @@ struct cmd_params_instance {
cparams.n_batch = n_batch;
cparams.type_k = type_k;
cparams.type_v = type_v;
cparams.mul_mat_q = mul_mat_q;
cparams.offload_kqv = !no_kv_offload;
return cparams;
@ -538,7 +525,6 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
for (const auto & nb : params.n_batch)
for (const auto & tk : params.type_k)
for (const auto & tv : params.type_v)
for (const auto & mmq : params.mul_mat_q)
for (const auto & nkvo : params.no_kv_offload)
for (const auto & nt : params.n_threads) {
for (const auto & n_prompt : params.n_prompt) {
@ -557,7 +543,6 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
/* .split_mode = */ sm,
/* .main_gpu = */ mg,
/* .no_kv_offload= */ nkvo,
/* .mul_mat_q = */ mmq,
/* .tensor_split = */ ts,
/* .use_mmap = */ mmp,
};
@ -580,7 +565,6 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
/* .split_mode = */ sm,
/* .main_gpu = */ mg,
/* .no_kv_offload= */ nkvo,
/* .mul_mat_q = */ mmq,
/* .tensor_split = */ ts,
/* .use_mmap = */ mmp,
};
@ -616,7 +600,6 @@ struct test {
llama_split_mode split_mode;
int main_gpu;
bool no_kv_offload;
bool mul_mat_q;
std::vector<float> tensor_split;
bool use_mmap;
int n_prompt;
@ -639,7 +622,6 @@ struct test {
split_mode = inst.split_mode;
main_gpu = inst.main_gpu;
no_kv_offload = inst.no_kv_offload;
mul_mat_q = inst.mul_mat_q;
tensor_split = inst.tensor_split;
use_mmap = inst.use_mmap;
n_prompt = inst.n_prompt;
@ -713,7 +695,7 @@ struct test {
"n_batch", "n_threads", "type_k", "type_v",
"n_gpu_layers", "split_mode",
"main_gpu", "no_kv_offload",
"mul_mat_q", "tensor_split", "use_mmap",
"tensor_split", "use_mmap",
"n_prompt", "n_gen", "test_time",
"avg_ns", "stddev_ns",
"avg_ts", "stddev_ts"
@ -733,7 +715,7 @@ struct test {
}
if (field == "cuda" || field == "opencl" || field == "vulkan" || field == "kompute" || field == "metal" ||
field == "gpu_blas" || field == "blas" || field == "sycl" ||field == "f16_kv" || field == "no_kv_offload" ||
field == "mul_mat_q" || field == "use_mmap") {
field == "use_mmap") {
return BOOL;
}
if (field == "avg_ts" || field == "stddev_ts") {
@ -767,7 +749,7 @@ struct test {
std::to_string(n_batch), std::to_string(n_threads), ggml_type_name(type_k), ggml_type_name(type_v),
std::to_string(n_gpu_layers), split_mode_str(split_mode),
std::to_string(main_gpu), std::to_string(no_kv_offload),
std::to_string(mul_mat_q), tensor_split_str, std::to_string(use_mmap),
tensor_split_str, std::to_string(use_mmap),
std::to_string(n_prompt), std::to_string(n_gen), test_time,
std::to_string(avg_ns()), std::to_string(stdev_ns()),
std::to_string(avg_ts()), std::to_string(stdev_ts())
@ -931,9 +913,6 @@ struct markdown_printer : public printer {
if (field == "n_threads") {
return "threads";
}
if (field == "mul_mat_q") {
return "mmq";
}
if (field == "no_kv_offload") {
return "nkvo";
}
@ -974,9 +953,6 @@ struct markdown_printer : public printer {
if (params.split_mode.size() > 1 || params.split_mode != cmd_params_defaults.split_mode) {
fields.emplace_back("split_mode");
}
if (params.mul_mat_q.size() > 1 || params.mul_mat_q != cmd_params_defaults.mul_mat_q) {
fields.emplace_back("mul_mat_q");
}
if (params.no_kv_offload.size() > 1 || params.no_kv_offload != cmd_params_defaults.no_kv_offload) {
fields.emplace_back("no_kv_offload");
}

1
examples/server/README.md
View file

@ -30,6 +30,7 @@ The project is under active development, and we are [looking for feedback and co
- `--threads N`, `-t N`: Set the number of threads to use during generation.
- `-tb N, --threads-batch N`: Set the number of threads to use during batch and prompt processing. If not specified, the number of threads will be set to the number of threads used for generation.
- `--threads-http N`: number of threads in the http server pool to process requests (default: `std::thread::hardware_concurrency()`)
- `-m FNAME`, `--model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.gguf`).
- `-a ALIAS`, `--alias ALIAS`: Set an alias for the model. The alias will be returned in API responses.
- `-c N`, `--ctx-size N`: Set the size of the prompt context. The default is 512, but LLaMA models were built with a context of 2048, which will provide better results for longer input/inference. The size may differ in other models, for example, baichuan models were build with a context of 4096.

346
examples/server/server.cpp
View file

@ -46,108 +46,56 @@ struct server_params
int32_t write_timeout = 600;
bool slots_endpoint = true;
bool metrics_endpoint = false;
int n_threads_http = -1;
};
bool server_verbose = false;
bool server_log_json = true;
static size_t common_part(const std::vector<llama_token> &a, const std::vector<llama_token> &b)
{
size_t i;
for (i = 0; i < a.size() && i < b.size() && a[i] == b[i]; i++)
{
}
return i;
}
enum stop_type
{
enum stop_type {
STOP_FULL,
STOP_PARTIAL,
};
static bool ends_with(const std::string &str, const std::string &suffix)
{
return str.size() >= suffix.size() &&
0 == str.compare(str.size() - suffix.size(), suffix.size(), suffix);
}
// TODO: can become bool if we can't find use of more states
enum slot_state {
IDLE,
PROCESSING,
};
static size_t find_partial_stop_string(const std::string &stop,
const std::string &text)
{
if (!text.empty() && !stop.empty())
{
const char text_last_char = text.back();
for (int64_t char_index = stop.size() - 1; char_index >= 0; char_index--)
{
if (stop[char_index] == text_last_char)
{
const std::string current_partial = stop.substr(0, char_index + 1);
if (ends_with(text, current_partial))
{
return text.size() - char_index - 1;
}
}
}
}
return std::string::npos;
}
enum slot_command {
NONE,
LOAD_PROMPT,
RELEASE,
};
// TODO: reuse llama_detokenize
template <class Iter>
static std::string tokens_to_str(llama_context *ctx, Iter begin, Iter end)
{
std::string ret;
for (; begin != end; ++begin)
{
ret += llama_token_to_piece(ctx, *begin);
}
return ret;
}
struct slot_params {
bool stream = true;
bool cache_prompt = false; // remember the prompt to avoid reprocessing all prompt
// format incomplete utf-8 multibyte character for output
static std::string tokens_to_output_formatted_string(const llama_context *ctx, const llama_token token)
{
std::string out = token == -1 ? "" : llama_token_to_piece(ctx, token);
// if the size is 1 and first bit is 1, meaning it's a partial character
// (size > 1 meaning it's already a known token)
if (out.size() == 1 && (out[0] & 0x80) == 0x80)
{
std::stringstream ss;
ss << std::hex << (out[0] & 0xff);
std::string res(ss.str());
out = "byte: \\x" + res;
}
return out;
}
uint32_t seed = -1; // RNG seed
int32_t n_keep = 0; // number of tokens to keep from initial prompt
int32_t n_predict = -1; // new tokens to predict
// convert a vector of completion_token_output to json
static json probs_vector_to_json(const llama_context *ctx, const std::vector<completion_token_output> &probs)
{
json out = json::array();
for (const auto &prob : probs)
{
json probs_for_token = json::array();
for (const auto &p : prob.probs)
{
std::string tok_str = tokens_to_output_formatted_string(ctx, p.tok);
probs_for_token.push_back(json
{
{"tok_str", tok_str},
{"prob", p.prob},
});
}
std::string tok_str = tokens_to_output_formatted_string(ctx, prob.tok);
out.push_back(json{
{"content", tok_str},
{"probs", probs_for_token},
});
}
return out;
}
std::vector<std::string> antiprompt;
struct llama_client_slot
{
json input_prefix;
json input_suffix;
};
struct slot_image {
int32_t id;
bool request_encode_image = false;
float * image_embedding = nullptr;
int32_t image_tokens = 0;
clip_image_u8 * img_data;
std::string prefix_prompt; // before of this image
};
struct server_slot {
int id;
int task_id = -1;
@ -167,8 +115,8 @@ struct llama_client_slot
int32_t i_batch = -1;
int32_t n_predict = -1;
int32_t num_prompt_tokens = 0;
int32_t num_prompt_tokens_processed = 0;
int32_t n_prompt_tokens = 0;
int32_t n_prompt_tokens_processed = 0;
json prompt;
std::string generated_text;
@ -203,8 +151,8 @@ struct llama_client_slot
std::vector<slot_image> images;
// stats
size_t sent_count = 0;
size_t sent_token_probs_index = 0;
size_t n_sent_text = 0; // number of sent text character
size_t n_sent_token_probs = 0;
int64_t t_start_process_prompt;
int64_t t_start_genereration;
@ -216,7 +164,7 @@ struct llama_client_slot
int multitask_id = -1;
void reset() {
num_prompt_tokens = 0;
n_prompt_tokens = 0;
generated_text = "";
truncated = false;
stopped_eos = false;
@ -224,16 +172,15 @@ struct llama_client_slot
stopped_limit = false;
stopping_word = "";
n_past = 0;
sent_count = 0;
sent_token_probs_index = 0;
n_sent_text = 0;
n_sent_token_probs = 0;
infill = false;
ga_i = 0;
n_past_se = 0;
generated_token_probs.clear();
for (slot_image & img : images)
{
for (slot_image & img : images) {
free(img.image_embedding);
if (img.img_data) {
clip_image_u8_free(img.img_data);
@ -245,19 +192,15 @@ struct llama_client_slot
}
bool has_budget(gpt_params &global_params) {
if (params.n_predict == -1 && global_params.n_predict == -1)
{
if (params.n_predict == -1 && global_params.n_predict == -1) {
return true; // limitless
}
n_remaining = -1;
if (params.n_predict != -1)
{
if (params.n_predict != -1) {
n_remaining = params.n_predict - n_decoded;
}
else if (global_params.n_predict != -1)
{
} else if (global_params.n_predict != -1) {
n_remaining = global_params.n_predict - n_decoded;
}
@ -274,8 +217,7 @@ struct llama_client_slot
}
void add_token_string(const completion_token_output &token) {
if (command == RELEASE)
{
if (command == RELEASE) {
return;
}
cache_tokens.push_back(token.tok);
@ -293,10 +235,10 @@ struct llama_client_slot
json get_formatted_timings() { // spelling error changed; only occurs in this file
return json
{
{"prompt_n", num_prompt_tokens_processed},
{"prompt_n", n_prompt_tokens_processed},
{"prompt_ms", t_prompt_processing},
{"prompt_per_token_ms", t_prompt_processing / num_prompt_tokens_processed},
{"prompt_per_second", 1e3 / t_prompt_processing * num_prompt_tokens_processed},
{"prompt_per_token_ms", t_prompt_processing / n_prompt_tokens_processed},
{"prompt_per_second", 1e3 / t_prompt_processing * n_prompt_tokens_processed},
{"predicted_n", n_decoded},
{"predicted_ms", t_token_generation},
@ -315,15 +257,15 @@ struct llama_client_slot
double n_tokens_second = 1e3 / t_prompt_processing * num_prompt_tokens_processed;
//printf("\033[72;0H]");
sprintf(buffer, "prompt eval time = %10.2f ms / %5d tokens (%8.2f ms per token, %8.2f tokens per second)",
t_prompt_processing, num_prompt_tokens_processed,
t_prompt_processing, n_prompt_tokens_processed,
t_token, n_tokens_second);
LOG_INFO(buffer, {
{"slot_id", id},
{"task_id", task_id},
{"t_prompt_processing", t_prompt_processing},
{"num_prompt_tokens_processed", num_prompt_tokens_processed},
{"n_prompt_tokens_processed", n_prompt_tokens_processed},
{"t_token", t_token},
{"n_tokens_second", n_tokens_second}
{"n_tokens_second", n_tokens_second},
});
t_token = t_token_generation / n_decoded;
@ -353,7 +295,7 @@ struct llama_client_slot
}
};
struct llama_metrics {
struct server_metrics {
uint64_t n_prompt_tokens_processed_total = 0;
uint64_t n_tokens_predicted_total = 0;
@ -364,16 +306,14 @@ struct llama_metrics {
uint64_t t_tokens_generation = 0;
void on_prompt_eval(const llama_client_slot &slot) {
n_prompt_tokens_processed_total += slot.num_prompt_tokens_processed;
n_prompt_tokens_processed += slot.num_prompt_tokens_processed;
void on_prompt_eval(const server_slot &slot) {
n_prompt_tokens_processed_total += slot.n_prompt_tokens_processed;
n_prompt_tokens_processed += slot.n_prompt_tokens_processed;
t_prompt_processing += slot.t_prompt_processing;
}
void on_prediction(const llama_client_slot &slot) {
void on_prediction(const server_slot &slot) {
n_tokens_predicted_total += slot.n_decoded;
n_tokens_predicted += slot.n_decoded;
t_tokens_generation += slot.t_token_generation;
}
@ -486,13 +426,13 @@ struct llama_server_context
std::string name_assistant;
// slots / clients
std::vector<llama_client_slot> slots;
std::vector<server_slot> slots;
json default_generation_settings_for_props;
llama_server_queue queue_tasks;
llama_server_response queue_results;
llama_metrics metrics;
server_metrics metrics;
~llama_server_context()
{
@ -569,7 +509,7 @@ struct llama_server_context
LOG_INFO("initializing slots", {{"n_slots", params.n_parallel}});
for (int i = 0; i < params.n_parallel; i++)
{
llama_client_slot slot;
server_slot slot;
slot.id = i;
slot.n_ctx = n_ctx_slot;
@ -666,9 +606,9 @@ struct llama_server_context
// most commonly id = -1 so we deal with that first rather than the specified id > 0
llama_client_slot* get_slot(int id) {
int64_t t_last = ggml_time_us();
llama_client_slot *last_used = nullptr;
server_slot *last_used = nullptr;
for (llama_client_slot & slot : slots)
for (server_slot & slot : slots)
{
//printf("\033[5;0H");
if (slot.id == -1 && slot.available())
@ -696,7 +636,7 @@ struct llama_server_context
return last_used;
}
bool launch_slot_with_data(llama_client_slot* &slot, json data) {
bool launch_slot_with_data(server_slot* &slot, json data) {
slot_params default_params;
llama_sampling_params default_sparams;
@ -984,7 +924,7 @@ struct llama_server_context
clean_kv_cache = false;
}
void update_system_prompt() {
void system_prompt_update() {
kv_cache_clear();
system_tokens.clear();
@ -1029,9 +969,9 @@ struct llama_server_context
system_need_update = false;
}
void notify_system_prompt_changed() {
void system_prompt_notify() {
// release all slots
for (llama_client_slot &slot : slots)
for (server_slot &slot : slots)
{
slot.release();
}
@ -1039,17 +979,17 @@ struct llama_server_context
system_need_update = true;
}
void process_system_prompt_data(const json &sys_props) {
void system_prompt_process(const json &sys_props) {
system_prompt = sys_props.value("prompt", "");
name_user = sys_props.value("anti_prompt", "");
name_assistant = sys_props.value("assistant_name", "");
notify_system_prompt_changed();
system_prompt_notify();
}
static size_t find_stopping_strings(const std::string &text, const size_t last_token_size,
const stop_type type, llama_client_slot &slot)
const stop_type type, server_slot &slot)
{
size_t stop_pos = std::string::npos;
@ -1082,7 +1022,7 @@ struct llama_server_context
return stop_pos;
}
bool process_token(completion_token_output &result, llama_client_slot &slot) {
bool process_token(completion_token_output &result, server_slot &slot) {
// remember which tokens were sampled - used for repetition penalties during sampling
const std::string token_str = llama_token_to_piece(ctx, result.tok);
slot.sampled = result.tok;
@ -1128,7 +1068,7 @@ struct llama_server_context
if (!incomplete)
{
size_t pos = std::min(slot.sent_count, slot.generated_text.size());
size_t pos = std::min(slot.n_sent_text, slot.generated_text.size());
const std::string str_test = slot.generated_text.substr(pos);
bool is_stop_full = false;
size_t stop_pos = find_stopping_strings(str_test, token_str.size(), STOP_FULL, slot);
@ -1138,7 +1078,7 @@ struct llama_server_context
slot.generated_text.erase(
slot.generated_text.begin() + pos + stop_pos,
slot.generated_text.end());
pos = std::min(slot.sent_count, slot.generated_text.size());
pos = std::min(slot.n_sent_text, slot.generated_text.size());
}
else
{
@ -1151,7 +1091,7 @@ struct llama_server_context
{
// no send the stop word in the response
result.text_to_send = slot.generated_text.substr(pos, std::string::npos);
slot.sent_count += result.text_to_send.size();
slot.n_sent_text += result.text_to_send.size();
// add the token to slot queue and cache
}
slot.add_token_string(result);
@ -1195,7 +1135,7 @@ struct llama_server_context
return slot.has_next_token; // continue
}
bool process_images(llama_client_slot &slot) const
bool process_images(server_slot &slot) const
{
for (slot_image &img : slot.images)
{
@ -1275,7 +1215,7 @@ struct llama_server_context
};
}
void send_partial_response(llama_client_slot &slot, completion_token_output tkn)
void send_partial_response(server_slot &slot, completion_token_output tkn)
{
task_result res;
res.id = slot.task_id;
@ -1295,13 +1235,13 @@ struct llama_server_context
{
std::vector<completion_token_output> probs_output = {};
const std::vector<llama_token> to_send_toks = llama_tokenize(ctx, tkn.text_to_send, false);
size_t probs_pos = std::min(slot.sent_token_probs_index, slot.generated_token_probs.size());
size_t probs_stop_pos = std::min(slot.sent_token_probs_index + to_send_toks.size(), slot.generated_token_probs.size());
size_t probs_pos = std::min(slot.n_sent_token_probs, slot.generated_token_probs.size());
size_t probs_stop_pos = std::min(slot.n_sent_token_probs + to_send_toks.size(), slot.generated_token_probs.size());
if (probs_pos < probs_stop_pos)
{
probs_output = std::vector<completion_token_output>(slot.generated_token_probs.begin() + probs_pos, slot.generated_token_probs.begin() + probs_stop_pos);
}
slot.sent_token_probs_index = probs_stop_pos;
slot.n_sent_token_probs = probs_stop_pos;
res.result_json["completion_probabilities"] = probs_vector_to_json(ctx, probs_output);
}
@ -1314,7 +1254,7 @@ struct llama_server_context
queue_results.send(res);
}
void send_final_response(llama_client_slot &slot)
void send_final_response(server_slot &slot)
{
task_result res;
res.id = slot.task_id;
@ -1329,8 +1269,8 @@ struct llama_server_context
{"stop", true},
{"model", params.model_alias},
{"tokens_predicted", slot.n_decoded},
{"tokens_evaluated", slot.num_prompt_tokens},
{"generation_settings", get_formatted_generation(slot)},
{"tokens_evaluated", slot.n_prompt_tokens},
{"generation_settings", get_formated_generation(slot)},
{"prompt", slot.prompt},
{"truncated", slot.truncated},
{"stopped_eos", slot.stopped_eos},
@ -1367,7 +1307,7 @@ struct llama_server_context
queue_results.send(res);
}
void send_embedding(llama_client_slot &slot)
void send_embedding(server_slot &slot)
{
task_result res;
res.id = slot.task_id;
@ -1378,9 +1318,7 @@ struct llama_server_context
const int n_embd = llama_n_embd(model);
if (!params.embedding)
{
LOG_WARNING("embedding disabled", {
{"params.embedding", params.embedding},
});
LOG_WARNING("embedding disabled", {{"params.embedding", params.embedding}});
res.result_json = json
{
{"embedding", std::vector<float>(n_embd, 0.0f)},
@ -1392,7 +1330,7 @@ struct llama_server_context
std::vector<float> embedding(data, data + n_embd);
res.result_json = json
{
{"embedding", embedding },
{"embedding", embedding},
};
}
queue_results.send(res);
@ -1441,7 +1379,7 @@ struct llama_server_context
}
// for multiple images processing
bool ingest_images(llama_client_slot &slot, int n_batch)
bool ingest_images(server_slot &slot, int n_batch)
{
int image_idx = 0;
@ -1480,7 +1418,17 @@ struct llama_server_context
}
const int n_embd = llama_n_embd(model);
llama_batch batch_img = { n_eval, nullptr, (img.image_embedding + i * n_embd), nullptr, nullptr, nullptr, nullptr, slot.n_past, 1, 0, };
llama_batch batch_img = {
n_eval,
nullptr,
(img.image_embedding + i * n_embd),
nullptr,
nullptr,
nullptr,
nullptr,
slot.n_past,
1, 0
};
if (llama_decode(ctx, batch_img))
{
LOG("%s : failed to eval image\n", __func__);
@ -1550,16 +1498,7 @@ struct llama_server_context
switch (task.type)
{
case TASK_TYPE_COMPLETION: {
// we need to sort out the task_server / slots logic which isn't right
// why should task.data already contain a slot_id key when we haven't allocated it?
// because if it doesnt the returned value will be -1; what makes it anything else?
int requested_slot = json_value(task.data, "slot_id", -1);
//printf("\033[5;0H\033[K");
LOG("Task %d requesting slot %d\n", task.id, requested_slot);
// why are we suddenly using 'slot' as a pointer here - confusing?
llama_client_slot *slot = get_slot(requested_slot); // returns nullptr if no slot available
server_slot *slot = get_slot(json_value(task.data, "slot_id", -1));
if (slot == nullptr)
{
// if no slot is available, we defer this task for processing later
@ -1577,10 +1516,10 @@ struct llama_server_context
send_error(task, "system prompt can only be updated when all slots are idle");
break;
}
process_system_prompt_data(task.data["system_prompt"]);
system_prompt_process(task.data["system_prompt"]);
// reset cache_tokens for all slots
for (llama_client_slot &slot : slots)
for (server_slot &slot : slots)
{
slot.cache_tokens.clear();
slot.n_past = 0;
@ -1704,8 +1643,8 @@ struct llama_server_context
bool update_slots() {
if (system_need_update)
{
//LOG_INFO("updating system prompt", {});
update_system_prompt();
LOG_INFO("updating system prompt", {});
system_prompt_update();
}
llama_batch_clear(batch);
@ -1726,7 +1665,7 @@ struct llama_server_context
task.target_id = -1;
queue_tasks.post(task);
for (llama_client_slot &slot : slots)
for (server_slot &slot : slots)
{
if (slot.ga_n == 1) // what is this?
{
@ -1864,23 +1803,28 @@ struct llama_server_context
prompt_tokens = tokenize(slot.prompt, system_prompt.empty() && add_bos_token); // add BOS if there isn't system prompt
}
slot.num_prompt_tokens = prompt_tokens.size();
slot.n_prompt_tokens = prompt_tokens.size();
if (slot.params.n_keep < 0)
{
slot.params.n_keep = slot.num_prompt_tokens;
slot.params.n_keep = slot.n_prompt_tokens;
}
slot.params.n_keep = std::min(slot.n_ctx - 4, slot.params.n_keep);
// if input prompt is too big, truncate it
if (slot.num_prompt_tokens >= slot.n_ctx)
if (slot.n_prompt_tokens >= slot.n_ctx)
{
const int n_left = slot.n_ctx - slot.params.n_keep;
const int n_block_size = n_left / 2;
const int erased_blocks = (slot.num_prompt_tokens - slot.params.n_keep - n_block_size) / n_block_size;
const int erased_blocks = (slot.n_prompt_tokens - slot.params.n_keep - n_block_size) / n_block_size;
std::vector<llama_token> new_tokens(prompt_tokens.begin(), prompt_tokens.begin() + slot.params.n_keep);
new_tokens.insert(new_tokens.end(), prompt_tokens.begin() + slot.params.n_keep + erased_blocks * n_block_size, prompt_tokens.end());
std::vector<llama_token> new_tokens(
prompt_tokens.begin(),
prompt_tokens.begin() + slot.params.n_keep);
new_tokens.insert(
new_tokens.end(),
prompt_tokens.begin() + slot.params.n_keep + erased_blocks * n_block_size,
prompt_tokens.end());
LOG_VERBOSE("input truncated", {
{"n_ctx", slot.n_ctx},
@ -1891,8 +1835,8 @@ struct llama_server_context
slot.truncated = true;
prompt_tokens = new_tokens;
slot.num_prompt_tokens = prompt_tokens.size();
GGML_ASSERT(slot.num_prompt_tokens < slot.n_ctx);
slot.n_prompt_tokens = prompt_tokens.size();
GGML_ASSERT(slot.n_prompt_tokens < slot.n_ctx);
}
if (!slot.params.cache_prompt)
@ -1902,7 +1846,7 @@ struct llama_server_context
slot.n_past = 0;
slot.n_past_se = 0;
slot.ga_i = 0;
slot.num_prompt_tokens_processed = slot.num_prompt_tokens;
slot.n_prompt_tokens_processed = slot.n_prompt_tokens;
}
else
{
@ -1921,7 +1865,7 @@ struct llama_server_context
slot.n_past -= 1;
}
slot.num_prompt_tokens_processed = slot.num_prompt_tokens - slot.n_past;
slot.n_prompt_tokens_processed = slot.n_prompt_tokens - slot.n_past;
if (slot.ga_n != 1)
{
@ -1946,13 +1890,13 @@ struct llama_server_context
{ "slot_id", slot.id },
{ "task_id", slot.task_id },
{ "n_past", slot.n_past },
{ "num_prompt_tokens_processed", slot.num_prompt_tokens_processed }
{ "n_prompt_tokens_processed", slot.n_prompt_tokens_processed }
});
}
slot.cache_tokens = prompt_tokens;
if (slot.n_past == slot.num_prompt_tokens && slot.n_past > 0)
if (slot.n_past == slot.n_prompt_tokens && slot.n_past > 0)
{
// we have to evaluate at least 1 token to generate logits.
LOG_INFO("we have to evaluate at least 1 token to generate logits", {
@ -2008,8 +1952,8 @@ struct llama_server_context
if (has_images && !ingest_images(slot, n_batch))
{
LOG_ERROR("failed processing images", {
"slot_id", slot.id,
"task_id", slot.task_id,
{"slot_id", slot.id},
{"task_id", slot.task_id},
});
// FIXME @phymbert: to be properly tested
// early returning without changing the slot state will block the slot for ever
@ -2169,10 +2113,6 @@ struct llama_server_context
return true;
}
void run_on_all_tasks_finished() {
update_slots();
}
};
static void server_print_usage(const char *argv0, const gpt_params &params,
@ -2185,6 +2125,7 @@ static void server_print_usage(const char *argv0, const gpt_params &params,
printf(" -v, --verbose verbose output (default: %s)\n", server_verbose ? "enabled" : "disabled");
printf(" -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads);
printf(" -tb N, --threads-batch N number of threads to use during batch and prompt processing (default: same as --threads)\n");
printf(" --threads-http N number of threads in the http server pool to process requests (default: hardware concurrency)\n");
printf(" -c N, --ctx-size N size of the prompt context (default: %d)\n", params.n_ctx);
printf(" --rope-scaling {none,linear,yarn}\n");
printf(" RoPE frequency scaling method, defaults to linear unless specified by the model\n");
@ -2502,6 +2443,15 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
}
params.n_threads_batch = std::stoi(argv[i]);
}
else if (arg == "--threads-http")
{
if (++i >= argc)
{
invalid_param = true;
break;
}
sparams.n_threads_http = std::stoi(argv[i]);
}
else if (arg == "-b" || arg == "--batch-size")
{
if (++i >= argc)
@ -2595,14 +2545,6 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
}
#else
LOG_WARNING("llama.cpp was compiled without cuBLAS. It is not possible to set a tensor split.\n", {});
#endif // GGML_USE_CUBLAS
}
else if (arg == "--no-mul-mat-q" || arg == "-nommq")
{
#if defined(GGML_USE_CUBLAS) || defined(GGML_USE_SYCL)
params.mul_mat_q = false;
#else
LOG_WARNING("warning: llama.cpp was compiled without cuBLAS. Disabling mul_mat_q kernels has no effect.\n", {});
#endif // GGML_USE_CUBLAS
}
else if (arg == "--main-gpu" || arg == "-mg")
@ -2724,7 +2666,7 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
std::istreambuf_iterator<char>(),
std::back_inserter(systm_content)
);
llama.process_system_prompt_data(json::parse(systm_content));
llama.system_prompt_process(json::parse(systm_content));
}
else if (arg == "-ctk" || arg == "--cache-type-k") {
params.cache_type_k = argv[++i];
@ -2864,7 +2806,7 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
/* llama.cpp completion api semantics */
static json format_partial_response(
llama_server_context &llama, llama_client_slot *slot, const std::string &content, const std::vector<completion_token_output> &probs
llama_server_context &llama, server_slot *slot, const std::string &content, const std::vector<completion_token_output> &probs
) {
json res = json
{
@ -2919,14 +2861,7 @@ static void log_server_request(const httplib::Request &req, const httplib::Respo
});
}
struct token_translator
{
llama_context * ctx;
std::string operator()(llama_token tok) const { return llama_token_to_piece(ctx, tok); }
std::string operator()(const completion_token_output &cto) const { return (*this)(cto.tok); }
};
static void append_to_generated_text_from_generated_token_probs(llama_server_context &llama, llama_client_slot *slot)
static void append_to_generated_text_from_generated_token_probs(llama_server_context &llama, server_slot *slot)
{
auto & gtps = slot->generated_token_probs;
auto translator = token_translator{llama.ctx};
@ -3703,6 +3638,11 @@ int main(int argc, char **argv)
}*/
//);
if (sparams.n_threads_http > 0) {
log_data["n_threads_http"] = std::to_string(sparams.n_threads_http);
svr.new_task_queue = [&sparams] { return new httplib::ThreadPool(sparams.n_threads_http); };
}
LOG_INFO("HTTP server listening", log_data);
// run the HTTP server in a thread - see comment below
std::thread t([&]()
@ -3720,8 +3660,8 @@ int main(int argc, char **argv)
&llama_server_context::process_single_task, &llama, std::placeholders::_1));
llama.queue_tasks.on_finish_multitask(std::bind(
&llama_server_context::on_finish_multitask, &llama, std::placeholders::_1));
llama.queue_tasks.on_all_tasks_finished(std::bind(
&llama_server_context::run_on_all_tasks_finished, &llama));
llama.queue_tasks.on_run_slots(std::bind(
&llama_server_context::update_slots, &llama));
llama.queue_results.on_multitask_update(std::bind(
&llama_server_queue::update_multitask,
&llama.queue_tasks,

134
examples/server/utils.hpp
View file

@ -180,8 +180,7 @@ struct slot_image
};
// completion token output with probabilities
struct completion_token_output
{
struct completion_token_output {
struct token_prob
{
llama_token tok;
@ -193,6 +192,13 @@ struct completion_token_output
std::string text_to_send;
};
struct token_translator {
llama_context * ctx;
std::string operator()(llama_token tok) const { return llama_token_to_piece(ctx, tok); }
std::string operator()(const completion_token_output &cto) const { return (*this)(cto.tok); }
};
static inline void server_log(const char *level, const char *function, int line, const char *message, const nlohmann::ordered_json &extra) {
static inline void server_log(
const char *level,
const char *function,
@ -276,8 +282,7 @@ static inline void server_log(
//
template <typename T>
static T json_value(const json &body, const std::string &key, const T &default_value)
{
static T json_value(const json &body, const std::string &key, const T &default_value) {
// Fallback null to default value
return body.contains(key) && !body.at(key).is_null()
? body.value(key, default_value)
@ -342,7 +347,7 @@ struct llama_server_queue {
// callback functions
std::function<void(task_server&)> callback_new_task;
std::function<void(task_multi&)> callback_finish_multitask;
std::function<void(void)> callback_all_task_finished;
std::function<void(void)> callback_run_slots;
// Add a new task to the end of the queue
int post(task_server task) {
@ -377,14 +382,14 @@ struct llama_server_queue {
callback_new_task = callback;
}
// Register function to process a multitask
// Register function to process a multitask when it is finished
void on_finish_multitask(std::function<void(task_multi&)> callback) {
callback_finish_multitask = callback;
}
// Register the function to be called when the batch of tasks is finished
void on_all_tasks_finished(std::function<void(void)> callback) {
callback_all_task_finished = callback;
// Register the function to be called when all slots data is ready to be processed
void on_run_slots(std::function<void(void)> callback) {
callback_run_slots = callback;
}
// Call when the state of one slot is changed
@ -409,7 +414,13 @@ struct llama_server_queue {
condition_tasks.notify_all();
}
// Start the main loop. Called from the very end of server.cpp
/**
* Main loop consists of these steps:
* - Wait until a new task arrives
* - Process the task (i.e. maybe copy data into slot)
* - Check if multitask is finished
* - Run all slots
*/
void start_loop() {
running = true;
//LOG("In start_loop have new task number %d.\n", id);
@ -429,7 +440,8 @@ struct llama_server_queue {
LOG_VERBOSE("callback_new_task", {"task_id", task.id});
callback_new_task(task);
}
// process and update all the multitasks
LOG_VERBOSE("update_multitasks", {});
// check if we have any finished multitasks
auto queue_iterator = queue_multitasks.begin();
while (queue_iterator != queue_multitasks.end())
{
@ -446,8 +458,9 @@ struct llama_server_queue {
++queue_iterator;
}
}
// all tasks in the current loop are finished
callback_all_task_finished();
// all tasks in the current loop is processed, slots data is now ready
LOG_VERBOSE("callback_run_slots", {});
callback_run_slots();
}
LOG_VERBOSE("wait for new task", {});
// wait for new task
@ -505,6 +518,7 @@ struct llama_server_response {
std::mutex mutex_results;
std::condition_variable condition_results;
// add the task_id to the list of tasks waiting for response
void add_waiting_task_id(int task_id) {
LOG_VERBOSE("waiting for task id", {"task_id", task_id});
std::unique_lock<std::mutex> lock(mutex_results);
@ -512,6 +526,7 @@ struct llama_server_response {
LOG("Waiting task list size after addition: %2zu.\n", waiting_task_ids.size());
}
// when the request is finished, we can remove task associated with it
void remove_waiting_task_id(int task_id) {
LOG_VERBOSE("remove waiting for task id", {"task_id", task_id});
std::unique_lock<std::mutex> lock(mutex_results);
@ -673,3 +688,96 @@ static std::string gen_chatcmplid()
chatcmplid << "chatcmpl-" << random_string();
return chatcmplid.str();
}
//
// other common utils
//
static size_t common_part(const std::vector<llama_token> &a, const std::vector<llama_token> &b)
{
size_t i;
for (i = 0; i < a.size() && i < b.size() && a[i] == b[i]; i++)
{
}
return i;
}
static bool ends_with(const std::string &str, const std::string &suffix)
{
return str.size() >= suffix.size() &&
0 == str.compare(str.size() - suffix.size(), suffix.size(), suffix);
}
static size_t find_partial_stop_string(const std::string &stop,
const std::string &text)
{
if (!text.empty() && !stop.empty())
{
const char text_last_char = text.back();
for (int64_t char_index = stop.size() - 1; char_index >= 0; char_index--)
{
if (stop[char_index] == text_last_char)
{
const std::string current_partial = stop.substr(0, char_index + 1);
if (ends_with(text, current_partial))
{
return text.size() - char_index - 1;
}
}
}
}
return std::string::npos;
}
// TODO: reuse llama_detokenize
template <class Iter>
static std::string tokens_to_str(llama_context *ctx, Iter begin, Iter end)
{
std::string ret;
for (; begin != end; ++begin)
{
ret += llama_token_to_piece(ctx, *begin);
}
return ret;
}
// format incomplete utf-8 multibyte character for output
static std::string tokens_to_output_formatted_string(const llama_context *ctx, const llama_token token)
{
std::string out = token == -1 ? "" : llama_token_to_piece(ctx, token);
// if the size is 1 and first bit is 1, meaning it's a partial character
// (size > 1 meaning it's already a known token)
if (out.size() == 1 && (out[0] & 0x80) == 0x80)
{
std::stringstream ss;
ss << std::hex << (out[0] & 0xff);
std::string res(ss.str());
out = "byte: \\x" + res;
}
return out;
}
// convert a vector of completion_token_output to json
static json probs_vector_to_json(const llama_context *ctx, const std::vector<completion_token_output> &probs)
{
json out = json::array();
for (const auto &prob : probs)
{
json probs_for_token = json::array();
for (const auto &p : prob.probs)
{
std::string tok_str = tokens_to_output_formatted_string(ctx, p.tok);
probs_for_token.push_back(json
{
{"tok_str", tok_str},
{"prob", p.prob},
});
}
std::string tok_str = tokens_to_output_formatted_string(ctx, prob.tok);
out.push_back(json{
{"content", tok_str},
{"probs", probs_for_token},
});
}
return out;
}

89
ggml-sycl.cpp
View file

@ -12726,6 +12726,7 @@ static void ggml_sycl_op_mul_mat(const ggml_tensor *src0,
GGML_ASSERT(dst->backend != GGML_BACKEND_TYPE_GPU_SPLIT);
GGML_ASSERT(src1->backend != GGML_BACKEND_TYPE_GPU_SPLIT);
GGML_ASSERT(src1->type == GGML_TYPE_F32 || (src1->ne[2] == 1 && src1->ne[3] == 1));
GGML_ASSERT(ne12 >= ne02 && ne12 % ne02 == 0);
@ -13270,11 +13271,11 @@ static void k_compute_batched_ptrs(const sycl::half *src0_as_f16,
int64_t i02 = i12 / r2;
ptrs_src[0*ne23 + i12 + i13*ne12] = (const char *) src0_as_f16 + i02*nb02 + i03*nb03;
ptrs_src[1*ne23 + i12 + i13*ne12] = (const char *) src1_as_f16 + i12*nb12/2 + i13*nb13/2;
ptrs_src[1*ne23 + i12 + i13*ne12] = (const char *) src1_as_f16 + i12*nb12 + i13*nb13;
ptrs_dst[0*ne23 + i12 + i13*ne12] = ( char *) dst + i12*nbd2 + i13*nbd3;
}
static void ggml_sycl_mul_mat_mat_batched_sycl(const ggml_tensor *src0,
static void ggml_sycl_mul_mat_batched_sycl(const ggml_tensor *src0,
const ggml_tensor *src1,
ggml_tensor *dst) try {
GGML_ASSERT(!ggml_is_transposed(src0));
@ -13282,18 +13283,10 @@ static void ggml_sycl_mul_mat_mat_batched_sycl(const ggml_tensor *src0,
GGML_ASSERT(src0->backend != GGML_BACKEND_TYPE_GPU_SPLIT);
GGML_ASSERT(src0->type == GGML_TYPE_F16);
GGML_ASSERT(src1->type == GGML_TYPE_F32);
GGML_TENSOR_LOCALS(int64_t, ne0, src0, ne);
GGML_TENSOR_BINARY_OP_LOCALS
GGML_TENSOR_LOCALS(int64_t, nb0, src0, nb);
GGML_TENSOR_LOCALS(int64_t, ne1, src1, ne);
GGML_TENSOR_LOCALS(int64_t, nb1, src1, nb);
const int64_t ne1 = ggml_nelements(src1);
const int64_t ne = ggml_nelements(dst);
const int64_t ne_dst = ggml_nelements(dst);
SYCL_CHECK(ggml_sycl_set_device(g_main_device));
dpct::queue_ptr main_stream = g_syclStreams[g_main_device_index][0];
@ -13312,11 +13305,16 @@ static void ggml_sycl_mul_mat_mat_batched_sycl(const ggml_tensor *src0,
float * dst_ddf = (float *) dst_extra->data_device[g_main_device_index];
// convert src1 to fp16
sycl_pool_alloc<sycl::half> src1_f16_alloc;
if (src1->type != GGML_TYPE_F16) {
const to_fp16_sycl_t to_fp16_sycl = ggml_get_to_fp16_sycl(src1->type);
const int64_t ne_src1 = ggml_nelements(src1);
src1_f16_alloc.alloc(ne_src1);
GGML_ASSERT(to_fp16_sycl != nullptr);
sycl_pool_alloc<sycl::half> src1_as_f16(ne1);
to_fp16_sycl(src1_ddf, src1_as_f16.get(), ne1, main_stream);
to_fp16_sycl(src1_ddf, src1_f16_alloc.get(), ne_src1, main_stream);
}
sycl::half *src1_f16 = src1->type == GGML_TYPE_F16 ? (sycl::half *)src1_ddf
: src1_f16_alloc.get();
sycl_pool_alloc<sycl::half> dst_f16;
char * dst_t;
@ -13337,20 +13335,12 @@ static void ggml_sycl_mul_mat_mat_batched_sycl(const ggml_tensor *src0,
const void * alpha = &alpha_f16;
const void * beta = &beta_f16;
if (dst->op_params[0] == GGML_PREC_DEFAULT) {
dst_t = (char *) dst_f16.alloc(ne);
// TODO: Renable (dst->op_params[0] =! GGML_PREC_DEFAULT) pathway
// once oneMKL open source supports half, half, float, float: datatypes
dst_t = (char *) dst_f16.alloc(ne_dst);
nbd2 /= sizeof(float) / sizeof(sycl::half);
nbd3 /= sizeof(float) / sizeof(sycl::half);
} else {
dst_t = (char *) dst_ddf;
cu_compute_type = dpct::library_data_t::real_float;
cu_data_type = dpct::library_data_t::real_float;
alpha = &alpha_f32;
beta = &beta_f32;
}
GGML_ASSERT(ne12 % ne02 == 0);
GGML_ASSERT(ne13 % ne03 == 0);
@ -13386,10 +13376,10 @@ static void ggml_sycl_mul_mat_mat_batched_sycl(const ggml_tensor *src0,
*g_sycl_handles[g_main_device_index], oneapi::mkl::transpose::trans,
oneapi::mkl::transpose::nontrans, ne01, ne11, ne10, alpha,
(const char *)src0_as_f16, dpct::library_data_t::real_half,
nb01 / sizeof(sycl::half), src0->nb[2] / sizeof(sycl::half),
(const char *)src1_as_f16.get(), dpct::library_data_t::real_half,
nb11 / sizeof(float), src1->nb[2] / sizeof(float), beta,
(char *)dst_t, cu_data_type, ne01, dst->nb[2] / sizeof(float),
nb01 / nb00, nb02 / nb00,
(const char *)src1_f16, dpct::library_data_t::real_half,
nb11 / nb10, nb12 / nb10, beta,
(char *)dst_t, cu_data_type, ne01, nb2 / nb0,
ne12 * ne13, cu_compute_type)));
} else {
// use syclGemmBatchedEx
@ -13409,44 +13399,35 @@ static void ggml_sycl_mul_mat_mat_batched_sycl(const ggml_tensor *src0,
{sycl::aspect::fp16});
main_stream->submit([&](sycl::handler &cgh) {
const sycl::half *src1_as_f16_get_ct1 = src1_as_f16.get();
const void **ptrs_src_get_ct3 = ptrs_src.get();
void **ptrs_dst_get_ct4 = ptrs_dst.get();
const void **ptrs_src_get = ptrs_src.get();
void **ptrs_dst_get = ptrs_dst.get();
size_t nb12_scaled = src1->type == GGML_TYPE_F16 ? nb12 : nb12 / 2;
size_t nb13_scaled = src1->type == GGML_TYPE_F16 ? nb13 : nb13 / 2;
cgh.parallel_for(sycl::nd_range<3>(block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1) {
k_compute_batched_ptrs(
src0_as_f16, src1_as_f16_get_ct1,
dst_t, ptrs_src_get_ct3,
ptrs_dst_get_ct4, ne12, ne13, ne23,
nb02, nb03, nb12, nb13, nbd2, nbd3, r2,
r3, item_ct1);
src0_as_f16, src1_f16,
dst_t, ptrs_src_get,
ptrs_dst_get, ne12, ne13, ne23,
nb02, nb03, nb12_scaled, nb13_scaled,
nbd2, nbd3, r2, r3, item_ct1);
});
});
}
/*
DPCT1010:95: SYCL uses exceptions to report errors and does not use the
error codes. The call was replaced with 0. You need to rewrite this
code.
*/
SYCL_CHECK(0);
SYCL_CHECK(CHECK_TRY_ERROR(dpct::gemm_batch(
*g_sycl_handles[g_main_device_index], oneapi::mkl::transpose::trans,
oneapi::mkl::transpose::nontrans, ne01, ne11, ne10, alpha,
(const void **)(ptrs_src.get() + 0 * ne23),
dpct::library_data_t::real_half, nb01 / sizeof(sycl::half),
dpct::library_data_t::real_half, nb01 / nb00,
(const void **)(ptrs_src.get() + 1 * ne23),
dpct::library_data_t::real_half, nb11 / sizeof(float), beta,
dpct::library_data_t::real_half, nb11 / nb10, beta,
(void **)(ptrs_dst.get() + 0 * ne23), cu_data_type, ne01, ne23,
cu_compute_type)));
}
#endif
if (dst->op_params[0] == GGML_PREC_DEFAULT) {
const to_fp32_sycl_t to_fp32_sycl = ggml_get_to_fp32_sycl(GGML_TYPE_F16);
to_fp32_sycl(dst_f16.get(), dst_ddf, ne, main_stream);
}
to_fp32_sycl(dst_f16.get(), dst_ddf, ne_dst, main_stream);
}
catch (sycl::exception const &exc) {
std::cerr << exc.what() << "Exception caught at file:" << __FILE__
@ -13491,10 +13472,10 @@ static void ggml_sycl_mul_mat(const ggml_tensor * src0, const ggml_tensor * src1
// KQV single-batch
// GGML_SYCL_DEBUG("ggml_sycl_mul_mat_vec_nc\n");
ggml_sycl_mul_mat_vec_nc(src0, src1, dst);
} else if (!split && all_on_device && use_xmx && src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F32 && !ggml_is_transposed(src0) && !ggml_is_transposed(src1)) {
} else if (!split && all_on_device && use_xmx && src0->type == GGML_TYPE_F16 && !ggml_is_transposed(src0) && !ggml_is_transposed(src1)) {
// KQ + KQV multi-batch
// GGML_SYCL_DEBUG("ggml_sycl_mul_mat_mat_batched_sycl\n");
ggml_sycl_mul_mat_mat_batched_sycl(src0, src1, dst);
// GGML_SYCL_DEBUG("ggml_sycl_mul_mat_batched_sycl\n");
ggml_sycl_mul_mat_batched_sycl(src0, src1, dst);
} else if (src0->type == GGML_TYPE_F32) {
// GGML_SYCL_DEBUG("ggml_sycl_op_mul_mat\n");
ggml_sycl_op_mul_mat(src0, src1, dst, ggml_sycl_op_mul_mat_sycl, false);

40
ggml-vulkan.cpp
View file

@ -1106,7 +1106,9 @@ void ggml_vk_instance_init() {
const std::vector<vk::ExtensionProperties> instance_extensions = vk::enumerateInstanceExtensionProperties();
const bool validation_ext = ggml_vk_instance_validation_ext_available(instance_extensions);
#ifdef __APPLE__
const bool portability_enumeration_ext = ggml_vk_instance_portability_enumeration_ext_available(instance_extensions);
#endif
std::vector<const char*> layers;
@ -1117,13 +1119,17 @@ void ggml_vk_instance_init() {
if (validation_ext) {
extensions.push_back("VK_EXT_validation_features");
}
#ifdef __APPLE__
if (portability_enumeration_ext) {
extensions.push_back("VK_KHR_portability_enumeration");
}
#endif
vk::InstanceCreateInfo instance_create_info(vk::InstanceCreateFlags{}, &app_info, layers, extensions);
#ifdef __APPLE__
if (portability_enumeration_ext) {
instance_create_info.flags |= vk::InstanceCreateFlagBits::eEnumeratePortabilityKHR;
}
#endif
std::vector<vk::ValidationFeatureEnableEXT> features_enable;
vk::ValidationFeaturesEXT validation_features;
@ -5422,7 +5428,8 @@ static void ggml_vk_print_tensor(ggml_backend_vk_context * ctx, const ggml_tenso
ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra;
ggml_vk_buffer_read(ctx, extra->buffer_gpu, extra->offset, tensor_data, tensor_size);
vk_buffer buffer_gpu = extra->buffer_gpu.lock();
ggml_vk_buffer_read(ctx, buffer_gpu, extra->offset, tensor_data, tensor_size);
}
std::cerr << "TENSOR CHECK " << name << " (" << tensor->name << "): " << ggml_op_name(tensor->op) << std::endl;
@ -5534,7 +5541,8 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
for (int i3 = 0; i3 < src0->ne[3]; i3++) {
for (int i2 = 0; i2 < src0->ne[2]; i2++) {
const int idx = i3*src0->ne[2] + i2;
ggml_vk_buffer_read(ctx, extra->buffer_gpu, offset + idx * src0->nb[2], ((char *)src0_clone->data + idx * src0_clone->nb[2]), src0->ne[1] * src0->nb[1]);
vk_buffer buffer_gpu = extra->buffer_gpu.lock();
ggml_vk_buffer_read(ctx, buffer_gpu, offset + idx * src0->nb[2], ((char *)src0_clone->data + idx * src0_clone->nb[2]), src0->ne[1] * src0->nb[1]);
}
}
@ -5544,10 +5552,11 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
src0_clone->nb[i] = src0_clone->nb[i - 1]*src0_clone->ne[i - 1];
}
} else {
if (offset + src0_size >= extra->buffer_gpu->size) {
src0_size = extra->buffer_gpu->size - offset;
vk_buffer buffer_gpu = extra->buffer_gpu.lock();
if (offset + src0_size >= buffer_gpu->size) {
src0_size = buffer_gpu->size - offset;
}
ggml_vk_buffer_read(ctx, extra->buffer_gpu, offset, src0_clone->data, src0_size);
ggml_vk_buffer_read(ctx, buffer_gpu, offset, src0_clone->data, src0_size);
memcpy(src0_clone->nb, src0->nb, sizeof(size_t) * GGML_MAX_DIMS);
}
} else {
@ -5577,7 +5586,8 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
for (int i3 = 0; i3 < src1->ne[3]; i3++) {
for (int i2 = 0; i2 < src1->ne[2]; i2++) {
const int idx = i3*src1->ne[2] + i2;
ggml_vk_buffer_read(ctx, extra->buffer_gpu, offset + idx * src1->nb[2], ((char *)src1_clone->data + idx * src1_clone->nb[2]), src1->ne[1] * src1->nb[1]);
vk_buffer buffer_gpu = extra->buffer_gpu.lock();
ggml_vk_buffer_read(ctx, buffer_gpu, offset + idx * src1->nb[2], ((char *)src1_clone->data + idx * src1_clone->nb[2]), src1->ne[1] * src1->nb[1]);
}
}
@ -5587,10 +5597,11 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
src1_clone->nb[i] = src1_clone->nb[i - 1]*src1_clone->ne[i - 1];
}
} else {
if (offset + src1_size >= extra->buffer_gpu->size) {
src1_size = extra->buffer_gpu->size - offset;
vk_buffer buffer_gpu = extra->buffer_gpu.lock();
if (offset + src1_size >= buffer_gpu->size) {
src1_size = buffer_gpu->size - offset;
}
ggml_vk_buffer_read(ctx, extra->buffer_gpu, offset, src1_clone->data, src1_size);
ggml_vk_buffer_read(ctx, buffer_gpu, offset, src1_clone->data, src1_size);
memcpy(src1_clone->nb, src1->nb, sizeof(size_t) * GGML_MAX_DIMS);
}
} else {
@ -5637,11 +5648,7 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
} else if (tensor->op == GGML_OP_RMS_NORM) {
tensor_clone = ggml_rms_norm(ggml_ctx, src0_clone, *(float *)tensor->op_params);
} else if (tensor->op == GGML_OP_SOFT_MAX) {
if (src1 != nullptr) {
tensor_clone = ggml_soft_max_ext(ggml_ctx, src0_clone, src1_clone, *(float *)tensor->op_params);
} else {
tensor_clone = ggml_soft_max(ggml_ctx, src0_clone);
}
} else if (tensor->op == GGML_OP_DIAG_MASK_INF) {
tensor_clone = ggml_diag_mask_inf(ggml_ctx, src0_clone, *(float *)tensor->op_params);
} else if (tensor->op == GGML_OP_ROPE) {
@ -5747,11 +5754,12 @@ static void ggml_vk_check_results_1(ggml_backend_vk_context * ctx, ggml_compute_
ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra;
if (extra->offset + tensor_size >= extra->buffer_gpu->size) {
tensor_size = extra->buffer_gpu->size - (extra->offset);
vk_buffer buffer_gpu = extra->buffer_gpu.lock();
if (extra->offset + tensor_size >= buffer_gpu->size) {
tensor_size = buffer_gpu->size - (extra->offset);
}
ggml_vk_buffer_read(ctx, extra->buffer_gpu, extra->offset, tensor_data, tensor_size);
ggml_vk_buffer_read(ctx, buffer_gpu, extra->offset, tensor_data, tensor_size);
}
float first_error_result = -1.0f;

108
llama.cpp
View file

@ -1645,7 +1645,6 @@ struct llama_cparams {
float yarn_beta_slow;
float defrag_thold;
bool mul_mat_q;
bool offload_kqv;
bool do_pooling;
@ -7894,9 +7893,9 @@ static int llama_decode_internal(
const auto n_batch = cparams.n_batch;
GGML_ASSERT(n_tokens <= n_batch);
GGML_ASSERT((!batch.token && batch.embd) || (batch.token && !batch.embd)); // NOLINT
int n_threads = n_tokens == 1 ? cparams.n_threads : cparams.n_threads_batch;
GGML_ASSERT((!batch.token && batch.embd) || (batch.token && !batch.embd)); // NOLINT
const int64_t t_start_us = ggml_time_us();
@ -8947,10 +8946,10 @@ struct llm_tokenizer_wpm {
std::vector<uint32_t> codepoints = codepoints_from_utf8(text);
std::vector<uint32_t> nfd_codepoints;
for (uint32_t code : codepoints) {
auto it = nfd_map.find(code);
if (it != nfd_map.end()) {
for (uint32_t c : it->second) {
nfd_codepoints.push_back(c);
auto it = nfd_map.equal_range(code);
if (it.first != it.second) {
for (auto jt = it.first; jt != it.second; jt++) {
nfd_codepoints.push_back(jt->second);
}
} else {
nfd_codepoints.push_back(code);
@ -9001,12 +9000,13 @@ struct llm_tokenizer_wpm {
}
uint32_t to_lower(uint32_t code) {
static const std::locale locale("en_US.UTF-8");
#if defined(_WIN32)
if (code > 0xFFFF) {
return code;
}
#endif
return std::tolower(wchar_t(code), std::locale("en_US.UTF-8"));
return std::tolower(wchar_t(code), locale);
}
bool is_ascii_punct(uint32_t code) {
@ -10062,10 +10062,6 @@ void llama_sample_temp(struct llama_context * ctx, llama_token_data_array * cand
}
}
void llama_sample_temperature(struct llama_context * ctx, llama_token_data_array * candidates_p, float temp) {
llama_sample_temp(ctx, candidates_p, temp);
}
void llama_sample_repetition_penalties(
struct llama_context * ctx,
llama_token_data_array * candidates,
@ -10192,38 +10188,6 @@ void llama_sample_apply_guidance(
ctx->t_sample_us += ggml_time_us() - t_start_sample_us;
}
void llama_sample_classifier_free_guidance(
struct llama_context * ctx,
llama_token_data_array * candidates,
struct llama_context * guidance_ctx,
float scale) {
GGML_ASSERT(ctx);
int64_t t_start_sample_us;
t_start_sample_us = ggml_time_us();
const size_t n_vocab = llama_n_vocab(llama_get_model(ctx));
GGML_ASSERT(n_vocab == candidates->size);
GGML_ASSERT(!candidates->sorted);
std::vector<float> logits_base(n_vocab);
for (size_t i = 0; i < n_vocab; ++i) {
logits_base[i] = candidates->data[i].logit;
}
float * logits_guidance = llama_get_logits(guidance_ctx);
ctx->t_sample_us += ggml_time_us() - t_start_sample_us;
llama_sample_apply_guidance(ctx, logits_base.data(), logits_guidance, scale);
t_start_sample_us = ggml_time_us();
for (size_t i = 0; i < n_vocab; ++i) {
candidates->data[i].logit = logits_base[i];
}
ctx->t_sample_us += ggml_time_us() - t_start_sample_us;
}
llama_token llama_sample_token_mirostat(struct llama_context * ctx, llama_token_data_array * candidates, float tau, float eta, int32_t m, float * mu) {
GGML_ASSERT(ctx);
@ -11668,7 +11632,6 @@ struct llama_context_params llama_context_default_params() {
/*.cb_eval_user_data =*/ nullptr,
/*.type_k =*/ GGML_TYPE_F16,
/*.type_v =*/ GGML_TYPE_F16,
/*.mul_mat_q =*/ true,
/*.logits_all =*/ false,
/*.embedding =*/ false,
/*.offload_kqv =*/ true,
@ -11724,15 +11687,6 @@ bool llama_supports_gpu_offload(void) {
#endif
}
// deprecated:
bool llama_mmap_supported(void) {
return llama_supports_mmap();
}
bool llama_mlock_supported(void) {
return llama_supports_mlock();
}
void llama_backend_init(void) {
ggml_time_init();
@ -11829,7 +11783,6 @@ struct llama_context * llama_new_context_with_model(
cparams.yarn_beta_fast = params.yarn_beta_fast;
cparams.yarn_beta_slow = params.yarn_beta_slow;
cparams.defrag_thold = params.defrag_thold;
cparams.mul_mat_q = params.mul_mat_q;
cparams.offload_kqv = params.offload_kqv;
cparams.do_pooling = params.do_pooling;
@ -12244,15 +12197,6 @@ uint32_t llama_model_quantize(
}
}
int32_t llama_apply_lora_from_file(struct llama_context * ctx, const char * path_lora, float scale, const char * path_base_model, int32_t n_threads) {
try {
return llama_apply_lora_from_file_internal(ctx->model, path_lora, scale, path_base_model, n_threads);
} catch (const std::exception & err) {
LLAMA_LOG_ERROR("%s: failed to apply lora adapter: %s\n", __func__, err.what());
return 1;
}
}
int32_t llama_model_apply_lora_from_file(const struct llama_model * model, const char * path_lora, float scale, const char * path_base_model, int32_t n_threads) {
try {
return llama_apply_lora_from_file_internal(*model, path_lora, scale, path_base_model, n_threads);
@ -12599,8 +12543,8 @@ size_t llama_copy_state_data(struct llama_context * ctx, uint8_t * dst) {
}
// Sets the state reading from the specified source address
size_t llama_set_state_data(struct llama_context * ctx, uint8_t * src) {
uint8_t * inp = src;
size_t llama_set_state_data(struct llama_context * ctx, const uint8_t * src) {
const uint8_t * inp = src;
// set rng
{
@ -12609,7 +12553,7 @@ size_t llama_set_state_data(struct llama_context * ctx, uint8_t * src) {
GGML_ASSERT(rng_size <= LLAMA_MAX_RNG_STATE);
std::string rng_str((char *)inp, rng_size); inp += rng_size;
std::string rng_str((const char *)inp, rng_size); inp += rng_size;
std::istringstream rng_ss(rng_str);
rng_ss >> ctx->rng;
@ -12802,38 +12746,6 @@ bool llama_save_session_file(struct llama_context * ctx, const char * path_sessi
return true;
}
int llama_eval(
struct llama_context * ctx,
llama_token * tokens,
int32_t n_tokens,
int32_t n_past) {
llama_kv_cache_seq_rm(ctx->kv_self, -1, n_past, -1);
const int ret = llama_decode_internal(*ctx, llama_batch_get_one(tokens, n_tokens, n_past, 0));
if (ret < 0) {
LLAMA_LOG_ERROR("%s: failed to decode, ret = %d\n", __func__, ret);
}
return ret;
}
int llama_eval_embd(
struct llama_context * ctx,
float * embd,
int32_t n_tokens,
int32_t n_past) {
llama_kv_cache_seq_rm(ctx->kv_self, -1, n_past, -1);
llama_batch batch = { n_tokens, nullptr, embd, nullptr, nullptr, nullptr, nullptr, n_past, 1, 0, };
const int ret = llama_decode_internal(*ctx, batch);
if (ret < 0) {
LLAMA_LOG_ERROR("%s: failed to decode, ret = %d\n", __func__, ret);
}
return ret;
}
void llama_set_n_threads(struct llama_context * ctx, uint32_t n_threads, uint32_t n_threads_batch) {
ctx->cparams.n_threads = n_threads;
ctx->cparams.n_threads_batch = n_threads_batch;

48
llama.h
View file

@ -255,7 +255,6 @@ extern "C" {
enum ggml_type type_v; // data type for V cache
// Keep the booleans together to avoid misalignment during copy-by-value.
bool mul_mat_q; // if true, use experimental mul_mat_q kernels (DEPRECATED - always true)
bool logits_all; // the llama_eval() call computes all logits, not just the last one (DEPRECATED - set llama_batch.logits instead)
bool embedding; // embedding mode only
bool offload_kqv; // whether to offload the KQV ops (including the KV cache) to GPU
@ -364,9 +363,6 @@ extern "C" {
LLAMA_API bool llama_supports_mlock (void);
LLAMA_API bool llama_supports_gpu_offload(void);
LLAMA_API DEPRECATED(bool llama_mmap_supported (void), "use llama_supports_mmap() instead");
LLAMA_API DEPRECATED(bool llama_mlock_supported(void), "use llama_supports_mlock() instead");
LLAMA_API const struct llama_model * llama_get_model(const struct llama_context * ctx);
LLAMA_API uint32_t llama_n_ctx (const struct llama_context * ctx);
@ -423,14 +419,6 @@ extern "C" {
// The model needs to be reloaded before applying a new adapter, otherwise the adapter
// will be applied on top of the previous one
// Returns 0 on success
LLAMA_API DEPRECATED(int32_t llama_apply_lora_from_file(
struct llama_context * ctx,
const char * path_lora,
float scale,
const char * path_base_model,
int32_t n_threads),
"use llama_model_apply_lora_from_file instead");
LLAMA_API int32_t llama_model_apply_lora_from_file(
const struct llama_model * model,
const char * path_lora,
@ -586,7 +574,7 @@ extern "C" {
// Returns the number of bytes read
LLAMA_API size_t llama_set_state_data(
struct llama_context * ctx,
uint8_t * src);
const uint8_t * src);
// Save/load session file
LLAMA_API bool llama_load_session_file(
@ -606,27 +594,6 @@ extern "C" {
// Decoding
//
// Run the llama inference to obtain the logits and probabilities for the next token(s).
// tokens + n_tokens is the provided batch of new tokens to process
// n_past is the number of tokens to use from previous eval calls
// Returns 0 on success
// DEPRECATED: use llama_decode() instead
LLAMA_API DEPRECATED(int llama_eval(
struct llama_context * ctx,
llama_token * tokens,
int32_t n_tokens,
int32_t n_past),
"use llama_decode() instead");
// Same as llama_eval, but use float matrix input directly.
// DEPRECATED: use llama_decode() instead
LLAMA_API DEPRECATED(int llama_eval_embd(
struct llama_context * ctx,
float * embd,
int32_t n_tokens,
int32_t n_past),
"use llama_decode() instead");
// Return batch for single sequence of tokens starting at pos_0
//
// NOTE: this is a helper function to facilitate transition to the new batch API - avoid using it
@ -800,13 +767,6 @@ extern "C" {
float * logits_guidance,
float scale);
LLAMA_API DEPRECATED(void llama_sample_classifier_free_guidance(
struct llama_context * ctx,
llama_token_data_array * candidates,
struct llama_context * guidance_ctx,
float scale),
"use llama_sample_apply_guidance() instead");
/// @details Sorts candidate tokens by their logits in descending order and calculate probabilities based on logits.
LLAMA_API void llama_sample_softmax(
struct llama_context * ctx,
@ -860,12 +820,6 @@ extern "C" {
llama_token_data_array * candidates,
float temp);
LLAMA_API DEPRECATED(void llama_sample_temperature(
struct llama_context * ctx,
llama_token_data_array * candidates,
float temp),
"use llama_sample_temp instead");
/// @details Apply constraints from grammar
LLAMA_API void llama_sample_grammar(
struct llama_context * ctx,

2
scripts/compare-llama-bench.py
View file

@ -31,7 +31,7 @@ PRETTY_NAMES = {
"model_size": "Model Size [GiB]", "model_n_params": "Num. of Parameters",
"n_batch": "Batch size", "n_threads": "Threads", "type_k": "K type", "type_v": "V type",
"n_gpu_layers": "GPU layers", "main_gpu": "Main GPU", "no_kv_offload": "NKVO",
"mul_mat_q": "MMQ", "tensor_split": "Tensor split"
"tensor_split": "Tensor split"
}
DEFAULT_SHOW = ["model_type"] # Always show these properties by default.

566
unicode.h
View file

@ -1,6 +1,7 @@
#pragma once
#include <cassert>
#include <map>
#include <stdexcept>
#include <string>
#include <unordered_map>
@ -223,266 +224,311 @@ static const std::vector<std::pair<uint32_t, uint32_t>> control_ranges = {
{0x2B81E, 0x2B81F}, {0x2CEA2, 0x2CEAF}, {0x2EBE1, 0x2F7FF}, {0x2FA1E, 0x2FFFF}, {0x3134B, 0xE00FF}, {0xE01F0, 0x10FFFF},
};
static const std::unordered_map<uint32_t, std::vector<uint32_t>> nfd_map = {
{0xC0, {0x41, 0x300}}, {0xC1, {0x41, 0x301}}, {0xC2, {0x41, 0x302}}, {0xC3, {0x41, 0x303}}, {0xC4, {0x41, 0x308}}, {0xC5, {0x41, 0x30A}}, {0xC7, {0x43, 0x327}}, {0xC8, {0x45, 0x300}},
{0xC9, {0x45, 0x301}}, {0xCA, {0x45, 0x302}}, {0xCB, {0x45, 0x308}}, {0xCC, {0x49, 0x300}}, {0xCD, {0x49, 0x301}}, {0xCE, {0x49, 0x302}}, {0xCF, {0x49, 0x308}}, {0xD1, {0x4E, 0x303}},
{0xD2, {0x4F, 0x300}}, {0xD3, {0x4F, 0x301}}, {0xD4, {0x4F, 0x302}}, {0xD5, {0x4F, 0x303}}, {0xD6, {0x4F, 0x308}}, {0xD9, {0x55, 0x300}}, {0xDA, {0x55, 0x301}}, {0xDB, {0x55, 0x302}},
{0xDC, {0x55, 0x308}}, {0xDD, {0x59, 0x301}}, {0xE0, {0x61, 0x300}}, {0xE1, {0x61, 0x301}}, {0xE2, {0x61, 0x302}}, {0xE3, {0x61, 0x303}}, {0xE4, {0x61, 0x308}}, {0xE5, {0x61, 0x30A}},
{0xE7, {0x63, 0x327}}, {0xE8, {0x65, 0x300}}, {0xE9, {0x65, 0x301}}, {0xEA, {0x65, 0x302}}, {0xEB, {0x65, 0x308}}, {0xEC, {0x69, 0x300}}, {0xED, {0x69, 0x301}}, {0xEE, {0x69, 0x302}},
{0xEF, {0x69, 0x308}}, {0xF1, {0x6E, 0x303}}, {0xF2, {0x6F, 0x300}}, {0xF3, {0x6F, 0x301}}, {0xF4, {0x6F, 0x302}}, {0xF5, {0x6F, 0x303}}, {0xF6, {0x6F, 0x308}}, {0xF9, {0x75, 0x300}},
{0xFA, {0x75, 0x301}}, {0xFB, {0x75, 0x302}}, {0xFC, {0x75, 0x308}}, {0xFD, {0x79, 0x301}}, {0xFF, {0x79, 0x308}}, {0x100, {0x41, 0x304}}, {0x101, {0x61, 0x304}}, {0x102, {0x41, 0x306}},
{0x103, {0x61, 0x306}}, {0x104, {0x41, 0x328}}, {0x105, {0x61, 0x328}}, {0x106, {0x43, 0x301}}, {0x107, {0x63, 0x301}}, {0x108, {0x43, 0x302}}, {0x109, {0x63, 0x302}}, {0x10A, {0x43, 0x307}},
{0x10B, {0x63, 0x307}}, {0x10C, {0x43, 0x30C}}, {0x10D, {0x63, 0x30C}}, {0x10E, {0x44, 0x30C}}, {0x10F, {0x64, 0x30C}}, {0x112, {0x45, 0x304}}, {0x113, {0x65, 0x304}}, {0x114, {0x45, 0x306}},
{0x115, {0x65, 0x306}}, {0x116, {0x45, 0x307}}, {0x117, {0x65, 0x307}}, {0x118, {0x45, 0x328}}, {0x119, {0x65, 0x328}}, {0x11A, {0x45, 0x30C}}, {0x11B, {0x65, 0x30C}}, {0x11C, {0x47, 0x302}},
{0x11D, {0x67, 0x302}}, {0x11E, {0x47, 0x306}}, {0x11F, {0x67, 0x306}}, {0x120, {0x47, 0x307}}, {0x121, {0x67, 0x307}}, {0x122, {0x47, 0x327}}, {0x123, {0x67, 0x327}}, {0x124, {0x48, 0x302}},
{0x125, {0x68, 0x302}}, {0x128, {0x49, 0x303}}, {0x129, {0x69, 0x303}}, {0x12A, {0x49, 0x304}}, {0x12B, {0x69, 0x304}}, {0x12C, {0x49, 0x306}}, {0x12D, {0x69, 0x306}}, {0x12E, {0x49, 0x328}},
{0x12F, {0x69, 0x328}}, {0x130, {0x49, 0x307}}, {0x134, {0x4A, 0x302}}, {0x135, {0x6A, 0x302}}, {0x136, {0x4B, 0x327}}, {0x137, {0x6B, 0x327}}, {0x139, {0x4C, 0x301}}, {0x13A, {0x6C, 0x301}},
{0x13B, {0x4C, 0x327}}, {0x13C, {0x6C, 0x327}}, {0x13D, {0x4C, 0x30C}}, {0x13E, {0x6C, 0x30C}}, {0x143, {0x4E, 0x301}}, {0x144, {0x6E, 0x301}}, {0x145, {0x4E, 0x327}}, {0x146, {0x6E, 0x327}},
{0x147, {0x4E, 0x30C}}, {0x148, {0x6E, 0x30C}}, {0x14C, {0x4F, 0x304}}, {0x14D, {0x6F, 0x304}}, {0x14E, {0x4F, 0x306}}, {0x14F, {0x6F, 0x306}}, {0x150, {0x4F, 0x30B}}, {0x151, {0x6F, 0x30B}},
{0x154, {0x52, 0x301}}, {0x155, {0x72, 0x301}}, {0x156, {0x52, 0x327}}, {0x157, {0x72, 0x327}}, {0x158, {0x52, 0x30C}}, {0x159, {0x72, 0x30C}}, {0x15A, {0x53, 0x301}}, {0x15B, {0x73, 0x301}},
{0x15C, {0x53, 0x302}}, {0x15D, {0x73, 0x302}}, {0x15E, {0x53, 0x327}}, {0x15F, {0x73, 0x327}}, {0x160, {0x53, 0x30C}}, {0x161, {0x73, 0x30C}}, {0x162, {0x54, 0x327}}, {0x163, {0x74, 0x327}},
{0x164, {0x54, 0x30C}}, {0x165, {0x74, 0x30C}}, {0x168, {0x55, 0x303}}, {0x169, {0x75, 0x303}}, {0x16A, {0x55, 0x304}}, {0x16B, {0x75, 0x304}}, {0x16C, {0x55, 0x306}}, {0x16D, {0x75, 0x306}},
{0x16E, {0x55, 0x30A}}, {0x16F, {0x75, 0x30A}}, {0x170, {0x55, 0x30B}}, {0x171, {0x75, 0x30B}}, {0x172, {0x55, 0x328}}, {0x173, {0x75, 0x328}}, {0x174, {0x57, 0x302}}, {0x175, {0x77, 0x302}},
{0x176, {0x59, 0x302}}, {0x177, {0x79, 0x302}}, {0x178, {0x59, 0x308}}, {0x179, {0x5A, 0x301}}, {0x17A, {0x7A, 0x301}}, {0x17B, {0x5A, 0x307}}, {0x17C, {0x7A, 0x307}}, {0x17D, {0x5A, 0x30C}},
{0x17E, {0x7A, 0x30C}}, {0x1A0, {0x4F, 0x31B}}, {0x1A1, {0x6F, 0x31B}}, {0x1AF, {0x55, 0x31B}}, {0x1B0, {0x75, 0x31B}}, {0x1CD, {0x41, 0x30C}}, {0x1CE, {0x61, 0x30C}}, {0x1CF, {0x49, 0x30C}},
{0x1D0, {0x69, 0x30C}}, {0x1D1, {0x4F, 0x30C}}, {0x1D2, {0x6F, 0x30C}}, {0x1D3, {0x55, 0x30C}}, {0x1D4, {0x75, 0x30C}}, {0x1D5, {0x55, 0x308, 0x304}}, {0x1D6, {0x75, 0x308, 0x304}},
{0x1D7, {0x55, 0x308, 0x301}}, {0x1D8, {0x75, 0x308, 0x301}}, {0x1D9, {0x55, 0x308, 0x30C}}, {0x1DA, {0x75, 0x308, 0x30C}}, {0x1DB, {0x55, 0x308, 0x300}}, {0x1DC, {0x75, 0x308, 0x300}},
{0x1DE, {0x41, 0x308, 0x304}}, {0x1DF, {0x61, 0x308, 0x304}}, {0x1E0, {0x41, 0x307, 0x304}}, {0x1E1, {0x61, 0x307, 0x304}}, {0x1E2, {0xC6, 0x304}}, {0x1E3, {0xE6, 0x304}}, {0x1E6, {0x47, 0x30C}},
{0x1E7, {0x67, 0x30C}}, {0x1E8, {0x4B, 0x30C}}, {0x1E9, {0x6B, 0x30C}}, {0x1EA, {0x4F, 0x328}}, {0x1EB, {0x6F, 0x328}}, {0x1EC, {0x4F, 0x328, 0x304}}, {0x1ED, {0x6F, 0x328, 0x304}},
{0x1EE, {0x1B7, 0x30C}}, {0x1EF, {0x292, 0x30C}}, {0x1F0, {0x6A, 0x30C}}, {0x1F4, {0x47, 0x301}}, {0x1F5, {0x67, 0x301}}, {0x1F8, {0x4E, 0x300}}, {0x1F9, {0x6E, 0x300}}, {0x1FA, {0x41, 0x30A, 0x301}},
{0x1FB, {0x61, 0x30A, 0x301}}, {0x1FC, {0xC6, 0x301}}, {0x1FD, {0xE6, 0x301}}, {0x1FE, {0xD8, 0x301}}, {0x1FF, {0xF8, 0x301}}, {0x200, {0x41, 0x30F}}, {0x201, {0x61, 0x30F}}, {0x202, {0x41, 0x311}},
{0x203, {0x61, 0x311}}, {0x204, {0x45, 0x30F}}, {0x205, {0x65, 0x30F}}, {0x206, {0x45, 0x311}}, {0x207, {0x65, 0x311}}, {0x208, {0x49, 0x30F}}, {0x209, {0x69, 0x30F}}, {0x20A, {0x49, 0x311}},
{0x20B, {0x69, 0x311}}, {0x20C, {0x4F, 0x30F}}, {0x20D, {0x6F, 0x30F}}, {0x20E, {0x4F, 0x311}}, {0x20F, {0x6F, 0x311}}, {0x210, {0x52, 0x30F}}, {0x211, {0x72, 0x30F}}, {0x212, {0x52, 0x311}},
{0x213, {0x72, 0x311}}, {0x214, {0x55, 0x30F}}, {0x215, {0x75, 0x30F}}, {0x216, {0x55, 0x311}}, {0x217, {0x75, 0x311}}, {0x218, {0x53, 0x326}}, {0x219, {0x73, 0x326}}, {0x21A, {0x54, 0x326}},
{0x21B, {0x74, 0x326}}, {0x21E, {0x48, 0x30C}}, {0x21F, {0x68, 0x30C}}, {0x226, {0x41, 0x307}}, {0x227, {0x61, 0x307}}, {0x228, {0x45, 0x327}}, {0x229, {0x65, 0x327}}, {0x22A, {0x4F, 0x308, 0x304}},
{0x22B, {0x6F, 0x308, 0x304}}, {0x22C, {0x4F, 0x303, 0x304}}, {0x22D, {0x6F, 0x303, 0x304}}, {0x22E, {0x4F, 0x307}}, {0x22F, {0x6F, 0x307}}, {0x230, {0x4F, 0x307, 0x304}},
{0x231, {0x6F, 0x307, 0x304}}, {0x232, {0x59, 0x304}}, {0x233, {0x79, 0x304}}, {0x340, {0x300}}, {0x341, {0x301}}, {0x343, {0x313}}, {0x344, {0x308, 0x301}}, {0x374, {0x2B9}}, {0x37E, {0x3B}},
{0x385, {0xA8, 0x301}}, {0x386, {0x391, 0x301}}, {0x387, {0xB7}}, {0x388, {0x395, 0x301}}, {0x389, {0x397, 0x301}}, {0x38A, {0x399, 0x301}}, {0x38C, {0x39F, 0x301}}, {0x38E, {0x3A5, 0x301}},
{0x38F, {0x3A9, 0x301}}, {0x390, {0x3B9, 0x308, 0x301}}, {0x3AA, {0x399, 0x308}}, {0x3AB, {0x3A5, 0x308}}, {0x3AC, {0x3B1, 0x301}}, {0x3AD, {0x3B5, 0x301}}, {0x3AE, {0x3B7, 0x301}},
{0x3AF, {0x3B9, 0x301}}, {0x3B0, {0x3C5, 0x308, 0x301}}, {0x3CA, {0x3B9, 0x308}}, {0x3CB, {0x3C5, 0x308}}, {0x3CC, {0x3BF, 0x301}}, {0x3CD, {0x3C5, 0x301}}, {0x3CE, {0x3C9, 0x301}},
{0x3D3, {0x3D2, 0x301}}, {0x3D4, {0x3D2, 0x308}}, {0x400, {0x415, 0x300}}, {0x401, {0x415, 0x308}}, {0x403, {0x413, 0x301}}, {0x407, {0x406, 0x308}}, {0x40C, {0x41A, 0x301}}, {0x40D, {0x418, 0x300}},
{0x40E, {0x423, 0x306}}, {0x419, {0x418, 0x306}}, {0x439, {0x438, 0x306}}, {0x450, {0x435, 0x300}}, {0x451, {0x435, 0x308}}, {0x453, {0x433, 0x301}}, {0x457, {0x456, 0x308}}, {0x45C, {0x43A, 0x301}},
{0x45D, {0x438, 0x300}}, {0x45E, {0x443, 0x306}}, {0x476, {0x474, 0x30F}}, {0x477, {0x475, 0x30F}}, {0x4C1, {0x416, 0x306}}, {0x4C2, {0x436, 0x306}}, {0x4D0, {0x410, 0x306}}, {0x4D1, {0x430, 0x306}},
{0x4D2, {0x410, 0x308}}, {0x4D3, {0x430, 0x308}}, {0x4D6, {0x415, 0x306}}, {0x4D7, {0x435, 0x306}}, {0x4DA, {0x4D8, 0x308}}, {0x4DB, {0x4D9, 0x308}}, {0x4DC, {0x416, 0x308}}, {0x4DD, {0x436, 0x308}},
{0x4DE, {0x417, 0x308}}, {0x4DF, {0x437, 0x308}}, {0x4E2, {0x418, 0x304}}, {0x4E3, {0x438, 0x304}}, {0x4E4, {0x418, 0x308}}, {0x4E5, {0x438, 0x308}}, {0x4E6, {0x41E, 0x308}}, {0x4E7, {0x43E, 0x308}},
{0x4EA, {0x4E8, 0x308}}, {0x4EB, {0x4E9, 0x308}}, {0x4EC, {0x42D, 0x308}}, {0x4ED, {0x44D, 0x308}}, {0x4EE, {0x423, 0x304}}, {0x4EF, {0x443, 0x304}}, {0x4F0, {0x423, 0x308}}, {0x4F1, {0x443, 0x308}},
{0x4F2, {0x423, 0x30B}}, {0x4F3, {0x443, 0x30B}}, {0x4F4, {0x427, 0x308}}, {0x4F5, {0x447, 0x308}}, {0x4F8, {0x42B, 0x308}}, {0x4F9, {0x44B, 0x308}}, {0x622, {0x627, 0x653}}, {0x623, {0x627, 0x654}},
{0x624, {0x648, 0x654}}, {0x625, {0x627, 0x655}}, {0x626, {0x64A, 0x654}}, {0x6C0, {0x6D5, 0x654}}, {0x6C2, {0x6C1, 0x654}}, {0x6D3, {0x6D2, 0x654}}, {0x929, {0x928, 0x93C}}, {0x931, {0x930, 0x93C}},
{0x934, {0x933, 0x93C}}, {0x958, {0x915, 0x93C}}, {0x959, {0x916, 0x93C}}, {0x95A, {0x917, 0x93C}}, {0x95B, {0x91C, 0x93C}}, {0x95C, {0x921, 0x93C}}, {0x95D, {0x922, 0x93C}}, {0x95E, {0x92B, 0x93C}},
{0x95F, {0x92F, 0x93C}}, {0x9CB, {0x9C7, 0x9BE}}, {0x9CC, {0x9C7, 0x9D7}}, {0x9DC, {0x9A1, 0x9BC}}, {0x9DD, {0x9A2, 0x9BC}}, {0x9DF, {0x9AF, 0x9BC}}, {0xA33, {0xA32, 0xA3C}}, {0xA36, {0xA38, 0xA3C}},
{0xA59, {0xA16, 0xA3C}}, {0xA5A, {0xA17, 0xA3C}}, {0xA5B, {0xA1C, 0xA3C}}, {0xA5E, {0xA2B, 0xA3C}}, {0xB48, {0xB47, 0xB56}}, {0xB4B, {0xB47, 0xB3E}}, {0xB4C, {0xB47, 0xB57}}, {0xB5C, {0xB21, 0xB3C}},
{0xB5D, {0xB22, 0xB3C}}, {0xB94, {0xB92, 0xBD7}}, {0xBCA, {0xBC6, 0xBBE}}, {0xBCB, {0xBC7, 0xBBE}}, {0xBCC, {0xBC6, 0xBD7}}, {0xC48, {0xC46, 0xC56}}, {0xCC0, {0xCBF, 0xCD5}}, {0xCC7, {0xCC6, 0xCD5}},
{0xCC8, {0xCC6, 0xCD6}}, {0xCCA, {0xCC6, 0xCC2}}, {0xCCB, {0xCC6, 0xCC2, 0xCD5}}, {0xD4A, {0xD46, 0xD3E}}, {0xD4B, {0xD47, 0xD3E}}, {0xD4C, {0xD46, 0xD57}}, {0xDDA, {0xDD9, 0xDCA}},
{0xDDC, {0xDD9, 0xDCF}}, {0xDDD, {0xDD9, 0xDCF, 0xDCA}}, {0xDDE, {0xDD9, 0xDDF}}, {0xF43, {0xF42, 0xFB7}}, {0xF4D, {0xF4C, 0xFB7}}, {0xF52, {0xF51, 0xFB7}}, {0xF57, {0xF56, 0xFB7}},
{0xF5C, {0xF5B, 0xFB7}}, {0xF69, {0xF40, 0xFB5}}, {0xF73, {0xF71, 0xF72}}, {0xF75, {0xF71, 0xF74}}, {0xF76, {0xFB2, 0xF80}}, {0xF78, {0xFB3, 0xF80}}, {0xF81, {0xF71, 0xF80}}, {0xF93, {0xF92, 0xFB7}},
{0xF9D, {0xF9C, 0xFB7}}, {0xFA2, {0xFA1, 0xFB7}}, {0xFA7, {0xFA6, 0xFB7}}, {0xFAC, {0xFAB, 0xFB7}}, {0xFB9, {0xF90, 0xFB5}}, {0x1026, {0x1025, 0x102E}}, {0x1B06, {0x1B05, 0x1B35}},
{0x1B08, {0x1B07, 0x1B35}}, {0x1B0A, {0x1B09, 0x1B35}}, {0x1B0C, {0x1B0B, 0x1B35}}, {0x1B0E, {0x1B0D, 0x1B35}}, {0x1B12, {0x1B11, 0x1B35}}, {0x1B3B, {0x1B3A, 0x1B35}}, {0x1B3D, {0x1B3C, 0x1B35}},
{0x1B40, {0x1B3E, 0x1B35}}, {0x1B41, {0x1B3F, 0x1B35}}, {0x1B43, {0x1B42, 0x1B35}}, {0x1E00, {0x41, 0x325}}, {0x1E01, {0x61, 0x325}}, {0x1E02, {0x42, 0x307}}, {0x1E03, {0x62, 0x307}},
{0x1E04, {0x42, 0x323}}, {0x1E05, {0x62, 0x323}}, {0x1E06, {0x42, 0x331}}, {0x1E07, {0x62, 0x331}}, {0x1E08, {0x43, 0x327, 0x301}}, {0x1E09, {0x63, 0x327, 0x301}}, {0x1E0A, {0x44, 0x307}},
{0x1E0B, {0x64, 0x307}}, {0x1E0C, {0x44, 0x323}}, {0x1E0D, {0x64, 0x323}}, {0x1E0E, {0x44, 0x331}}, {0x1E0F, {0x64, 0x331}}, {0x1E10, {0x44, 0x327}}, {0x1E11, {0x64, 0x327}}, {0x1E12, {0x44, 0x32D}},
{0x1E13, {0x64, 0x32D}}, {0x1E14, {0x45, 0x304, 0x300}}, {0x1E15, {0x65, 0x304, 0x300}}, {0x1E16, {0x45, 0x304, 0x301}}, {0x1E17, {0x65, 0x304, 0x301}}, {0x1E18, {0x45, 0x32D}},
{0x1E19, {0x65, 0x32D}}, {0x1E1A, {0x45, 0x330}}, {0x1E1B, {0x65, 0x330}}, {0x1E1C, {0x45, 0x327, 0x306}}, {0x1E1D, {0x65, 0x327, 0x306}}, {0x1E1E, {0x46, 0x307}}, {0x1E1F, {0x66, 0x307}},
{0x1E20, {0x47, 0x304}}, {0x1E21, {0x67, 0x304}}, {0x1E22, {0x48, 0x307}}, {0x1E23, {0x68, 0x307}}, {0x1E24, {0x48, 0x323}}, {0x1E25, {0x68, 0x323}}, {0x1E26, {0x48, 0x308}}, {0x1E27, {0x68, 0x308}},
{0x1E28, {0x48, 0x327}}, {0x1E29, {0x68, 0x327}}, {0x1E2A, {0x48, 0x32E}}, {0x1E2B, {0x68, 0x32E}}, {0x1E2C, {0x49, 0x330}}, {0x1E2D, {0x69, 0x330}}, {0x1E2E, {0x49, 0x308, 0x301}},
{0x1E2F, {0x69, 0x308, 0x301}}, {0x1E30, {0x4B, 0x301}}, {0x1E31, {0x6B, 0x301}}, {0x1E32, {0x4B, 0x323}}, {0x1E33, {0x6B, 0x323}}, {0x1E34, {0x4B, 0x331}}, {0x1E35, {0x6B, 0x331}},
{0x1E36, {0x4C, 0x323}}, {0x1E37, {0x6C, 0x323}}, {0x1E38, {0x4C, 0x323, 0x304}}, {0x1E39, {0x6C, 0x323, 0x304}}, {0x1E3A, {0x4C, 0x331}}, {0x1E3B, {0x6C, 0x331}}, {0x1E3C, {0x4C, 0x32D}},
{0x1E3D, {0x6C, 0x32D}}, {0x1E3E, {0x4D, 0x301}}, {0x1E3F, {0x6D, 0x301}}, {0x1E40, {0x4D, 0x307}}, {0x1E41, {0x6D, 0x307}}, {0x1E42, {0x4D, 0x323}}, {0x1E43, {0x6D, 0x323}}, {0x1E44, {0x4E, 0x307}},
{0x1E45, {0x6E, 0x307}}, {0x1E46, {0x4E, 0x323}}, {0x1E47, {0x6E, 0x323}}, {0x1E48, {0x4E, 0x331}}, {0x1E49, {0x6E, 0x331}}, {0x1E4A, {0x4E, 0x32D}}, {0x1E4B, {0x6E, 0x32D}},
{0x1E4C, {0x4F, 0x303, 0x301}}, {0x1E4D, {0x6F, 0x303, 0x301}}, {0x1E4E, {0x4F, 0x303, 0x308}}, {0x1E4F, {0x6F, 0x303, 0x308}}, {0x1E50, {0x4F, 0x304, 0x300}}, {0x1E51, {0x6F, 0x304, 0x300}},
{0x1E52, {0x4F, 0x304, 0x301}}, {0x1E53, {0x6F, 0x304, 0x301}}, {0x1E54, {0x50, 0x301}}, {0x1E55, {0x70, 0x301}}, {0x1E56, {0x50, 0x307}}, {0x1E57, {0x70, 0x307}}, {0x1E58, {0x52, 0x307}},
{0x1E59, {0x72, 0x307}}, {0x1E5A, {0x52, 0x323}}, {0x1E5B, {0x72, 0x323}}, {0x1E5C, {0x52, 0x323, 0x304}}, {0x1E5D, {0x72, 0x323, 0x304}}, {0x1E5E, {0x52, 0x331}}, {0x1E5F, {0x72, 0x331}},
{0x1E60, {0x53, 0x307}}, {0x1E61, {0x73, 0x307}}, {0x1E62, {0x53, 0x323}}, {0x1E63, {0x73, 0x323}}, {0x1E64, {0x53, 0x301, 0x307}}, {0x1E65, {0x73, 0x301, 0x307}}, {0x1E66, {0x53, 0x30C, 0x307}},
{0x1E67, {0x73, 0x30C, 0x307}}, {0x1E68, {0x53, 0x323, 0x307}}, {0x1E69, {0x73, 0x323, 0x307}}, {0x1E6A, {0x54, 0x307}}, {0x1E6B, {0x74, 0x307}}, {0x1E6C, {0x54, 0x323}}, {0x1E6D, {0x74, 0x323}},
{0x1E6E, {0x54, 0x331}}, {0x1E6F, {0x74, 0x331}}, {0x1E70, {0x54, 0x32D}}, {0x1E71, {0x74, 0x32D}}, {0x1E72, {0x55, 0x324}}, {0x1E73, {0x75, 0x324}}, {0x1E74, {0x55, 0x330}}, {0x1E75, {0x75, 0x330}},
{0x1E76, {0x55, 0x32D}}, {0x1E77, {0x75, 0x32D}}, {0x1E78, {0x55, 0x303, 0x301}}, {0x1E79, {0x75, 0x303, 0x301}}, {0x1E7A, {0x55, 0x304, 0x308}}, {0x1E7B, {0x75, 0x304, 0x308}},
{0x1E7C, {0x56, 0x303}}, {0x1E7D, {0x76, 0x303}}, {0x1E7E, {0x56, 0x323}}, {0x1E7F, {0x76, 0x323}}, {0x1E80, {0x57, 0x300}}, {0x1E81, {0x77, 0x300}}, {0x1E82, {0x57, 0x301}}, {0x1E83, {0x77, 0x301}},
{0x1E84, {0x57, 0x308}}, {0x1E85, {0x77, 0x308}}, {0x1E86, {0x57, 0x307}}, {0x1E87, {0x77, 0x307}}, {0x1E88, {0x57, 0x323}}, {0x1E89, {0x77, 0x323}}, {0x1E8A, {0x58, 0x307}}, {0x1E8B, {0x78, 0x307}},
{0x1E8C, {0x58, 0x308}}, {0x1E8D, {0x78, 0x308}}, {0x1E8E, {0x59, 0x307}}, {0x1E8F, {0x79, 0x307}}, {0x1E90, {0x5A, 0x302}}, {0x1E91, {0x7A, 0x302}}, {0x1E92, {0x5A, 0x323}}, {0x1E93, {0x7A, 0x323}},
{0x1E94, {0x5A, 0x331}}, {0x1E95, {0x7A, 0x331}}, {0x1E96, {0x68, 0x331}}, {0x1E97, {0x74, 0x308}}, {0x1E98, {0x77, 0x30A}}, {0x1E99, {0x79, 0x30A}}, {0x1E9B, {0x17F, 0x307}}, {0x1EA0, {0x41, 0x323}},
{0x1EA1, {0x61, 0x323}}, {0x1EA2, {0x41, 0x309}}, {0x1EA3, {0x61, 0x309}}, {0x1EA4, {0x41, 0x302, 0x301}}, {0x1EA5, {0x61, 0x302, 0x301}}, {0x1EA6, {0x41, 0x302, 0x300}},
{0x1EA7, {0x61, 0x302, 0x300}}, {0x1EA8, {0x41, 0x302, 0x309}}, {0x1EA9, {0x61, 0x302, 0x309}}, {0x1EAA, {0x41, 0x302, 0x303}}, {0x1EAB, {0x61, 0x302, 0x303}}, {0x1EAC, {0x41, 0x323, 0x302}},
{0x1EAD, {0x61, 0x323, 0x302}}, {0x1EAE, {0x41, 0x306, 0x301}}, {0x1EAF, {0x61, 0x306, 0x301}}, {0x1EB0, {0x41, 0x306, 0x300}}, {0x1EB1, {0x61, 0x306, 0x300}}, {0x1EB2, {0x41, 0x306, 0x309}},
{0x1EB3, {0x61, 0x306, 0x309}}, {0x1EB4, {0x41, 0x306, 0x303}}, {0x1EB5, {0x61, 0x306, 0x303}}, {0x1EB6, {0x41, 0x323, 0x306}}, {0x1EB7, {0x61, 0x323, 0x306}}, {0x1EB8, {0x45, 0x323}},
{0x1EB9, {0x65, 0x323}}, {0x1EBA, {0x45, 0x309}}, {0x1EBB, {0x65, 0x309}}, {0x1EBC, {0x45, 0x303}}, {0x1EBD, {0x65, 0x303}}, {0x1EBE, {0x45, 0x302, 0x301}}, {0x1EBF, {0x65, 0x302, 0x301}},
{0x1EC0, {0x45, 0x302, 0x300}}, {0x1EC1, {0x65, 0x302, 0x300}}, {0x1EC2, {0x45, 0x302, 0x309}}, {0x1EC3, {0x65, 0x302, 0x309}}, {0x1EC4, {0x45, 0x302, 0x303}}, {0x1EC5, {0x65, 0x302, 0x303}},
{0x1EC6, {0x45, 0x323, 0x302}}, {0x1EC7, {0x65, 0x323, 0x302}}, {0x1EC8, {0x49, 0x309}}, {0x1EC9, {0x69, 0x309}}, {0x1ECA, {0x49, 0x323}}, {0x1ECB, {0x69, 0x323}}, {0x1ECC, {0x4F, 0x323}},
{0x1ECD, {0x6F, 0x323}}, {0x1ECE, {0x4F, 0x309}}, {0x1ECF, {0x6F, 0x309}}, {0x1ED0, {0x4F, 0x302, 0x301}}, {0x1ED1, {0x6F, 0x302, 0x301}}, {0x1ED2, {0x4F, 0x302, 0x300}},
{0x1ED3, {0x6F, 0x302, 0x300}}, {0x1ED4, {0x4F, 0x302, 0x309}}, {0x1ED5, {0x6F, 0x302, 0x309}}, {0x1ED6, {0x4F, 0x302, 0x303}}, {0x1ED7, {0x6F, 0x302, 0x303}}, {0x1ED8, {0x4F, 0x323, 0x302}},
{0x1ED9, {0x6F, 0x323, 0x302}}, {0x1EDA, {0x4F, 0x31B, 0x301}}, {0x1EDB, {0x6F, 0x31B, 0x301}}, {0x1EDC, {0x4F, 0x31B, 0x300}}, {0x1EDD, {0x6F, 0x31B, 0x300}}, {0x1EDE, {0x4F, 0x31B, 0x309}},
{0x1EDF, {0x6F, 0x31B, 0x309}}, {0x1EE0, {0x4F, 0x31B, 0x303}}, {0x1EE1, {0x6F, 0x31B, 0x303}}, {0x1EE2, {0x4F, 0x31B, 0x323}}, {0x1EE3, {0x6F, 0x31B, 0x323}}, {0x1EE4, {0x55, 0x323}},
{0x1EE5, {0x75, 0x323}}, {0x1EE6, {0x55, 0x309}}, {0x1EE7, {0x75, 0x309}}, {0x1EE8, {0x55, 0x31B, 0x301}}, {0x1EE9, {0x75, 0x31B, 0x301}}, {0x1EEA, {0x55, 0x31B, 0x300}},
{0x1EEB, {0x75, 0x31B, 0x300}}, {0x1EEC, {0x55, 0x31B, 0x309}}, {0x1EED, {0x75, 0x31B, 0x309}}, {0x1EEE, {0x55, 0x31B, 0x303}}, {0x1EEF, {0x75, 0x31B, 0x303}}, {0x1EF0, {0x55, 0x31B, 0x323}},
{0x1EF1, {0x75, 0x31B, 0x323}}, {0x1EF2, {0x59, 0x300}}, {0x1EF3, {0x79, 0x300}}, {0x1EF4, {0x59, 0x323}}, {0x1EF5, {0x79, 0x323}}, {0x1EF6, {0x59, 0x309}}, {0x1EF7, {0x79, 0x309}},
{0x1EF8, {0x59, 0x303}}, {0x1EF9, {0x79, 0x303}}, {0x1F00, {0x3B1, 0x313}}, {0x1F01, {0x3B1, 0x314}}, {0x1F02, {0x3B1, 0x313, 0x300}}, {0x1F03, {0x3B1, 0x314, 0x300}}, {0x1F04, {0x3B1, 0x313, 0x301}},
{0x1F05, {0x3B1, 0x314, 0x301}}, {0x1F06, {0x3B1, 0x313, 0x342}}, {0x1F07, {0x3B1, 0x314, 0x342}}, {0x1F08, {0x391, 0x313}}, {0x1F09, {0x391, 0x314}}, {0x1F0A, {0x391, 0x313, 0x300}},
{0x1F0B, {0x391, 0x314, 0x300}}, {0x1F0C, {0x391, 0x313, 0x301}}, {0x1F0D, {0x391, 0x314, 0x301}}, {0x1F0E, {0x391, 0x313, 0x342}}, {0x1F0F, {0x391, 0x314, 0x342}}, {0x1F10, {0x3B5, 0x313}},
{0x1F11, {0x3B5, 0x314}}, {0x1F12, {0x3B5, 0x313, 0x300}}, {0x1F13, {0x3B5, 0x314, 0x300}}, {0x1F14, {0x3B5, 0x313, 0x301}}, {0x1F15, {0x3B5, 0x314, 0x301}}, {0x1F18, {0x395, 0x313}},
{0x1F19, {0x395, 0x314}}, {0x1F1A, {0x395, 0x313, 0x300}}, {0x1F1B, {0x395, 0x314, 0x300}}, {0x1F1C, {0x395, 0x313, 0x301}}, {0x1F1D, {0x395, 0x314, 0x301}}, {0x1F20, {0x3B7, 0x313}},
{0x1F21, {0x3B7, 0x314}}, {0x1F22, {0x3B7, 0x313, 0x300}}, {0x1F23, {0x3B7, 0x314, 0x300}}, {0x1F24, {0x3B7, 0x313, 0x301}}, {0x1F25, {0x3B7, 0x314, 0x301}}, {0x1F26, {0x3B7, 0x313, 0x342}},
{0x1F27, {0x3B7, 0x314, 0x342}}, {0x1F28, {0x397, 0x313}}, {0x1F29, {0x397, 0x314}}, {0x1F2A, {0x397, 0x313, 0x300}}, {0x1F2B, {0x397, 0x314, 0x300}}, {0x1F2C, {0x397, 0x313, 0x301}},
{0x1F2D, {0x397, 0x314, 0x301}}, {0x1F2E, {0x397, 0x313, 0x342}}, {0x1F2F, {0x397, 0x314, 0x342}}, {0x1F30, {0x3B9, 0x313}}, {0x1F31, {0x3B9, 0x314}}, {0x1F32, {0x3B9, 0x313, 0x300}},
{0x1F33, {0x3B9, 0x314, 0x300}}, {0x1F34, {0x3B9, 0x313, 0x301}}, {0x1F35, {0x3B9, 0x314, 0x301}}, {0x1F36, {0x3B9, 0x313, 0x342}}, {0x1F37, {0x3B9, 0x314, 0x342}}, {0x1F38, {0x399, 0x313}},
{0x1F39, {0x399, 0x314}}, {0x1F3A, {0x399, 0x313, 0x300}}, {0x1F3B, {0x399, 0x314, 0x300}}, {0x1F3C, {0x399, 0x313, 0x301}}, {0x1F3D, {0x399, 0x314, 0x301}}, {0x1F3E, {0x399, 0x313, 0x342}},
{0x1F3F, {0x399, 0x314, 0x342}}, {0x1F40, {0x3BF, 0x313}}, {0x1F41, {0x3BF, 0x314}}, {0x1F42, {0x3BF, 0x313, 0x300}}, {0x1F43, {0x3BF, 0x314, 0x300}}, {0x1F44, {0x3BF, 0x313, 0x301}},
{0x1F45, {0x3BF, 0x314, 0x301}}, {0x1F48, {0x39F, 0x313}}, {0x1F49, {0x39F, 0x314}}, {0x1F4A, {0x39F, 0x313, 0x300}}, {0x1F4B, {0x39F, 0x314, 0x300}}, {0x1F4C, {0x39F, 0x313, 0x301}},
{0x1F4D, {0x39F, 0x314, 0x301}}, {0x1F50, {0x3C5, 0x313}}, {0x1F51, {0x3C5, 0x314}}, {0x1F52, {0x3C5, 0x313, 0x300}}, {0x1F53, {0x3C5, 0x314, 0x300}}, {0x1F54, {0x3C5, 0x313, 0x301}},
{0x1F55, {0x3C5, 0x314, 0x301}}, {0x1F56, {0x3C5, 0x313, 0x342}}, {0x1F57, {0x3C5, 0x314, 0x342}}, {0x1F59, {0x3A5, 0x314}}, {0x1F5B, {0x3A5, 0x314, 0x300}}, {0x1F5D, {0x3A5, 0x314, 0x301}},
{0x1F5F, {0x3A5, 0x314, 0x342}}, {0x1F60, {0x3C9, 0x313}}, {0x1F61, {0x3C9, 0x314}}, {0x1F62, {0x3C9, 0x313, 0x300}}, {0x1F63, {0x3C9, 0x314, 0x300}}, {0x1F64, {0x3C9, 0x313, 0x301}},
{0x1F65, {0x3C9, 0x314, 0x301}}, {0x1F66, {0x3C9, 0x313, 0x342}}, {0x1F67, {0x3C9, 0x314, 0x342}}, {0x1F68, {0x3A9, 0x313}}, {0x1F69, {0x3A9, 0x314}}, {0x1F6A, {0x3A9, 0x313, 0x300}},
{0x1F6B, {0x3A9, 0x314, 0x300}}, {0x1F6C, {0x3A9, 0x313, 0x301}}, {0x1F6D, {0x3A9, 0x314, 0x301}}, {0x1F6E, {0x3A9, 0x313, 0x342}}, {0x1F6F, {0x3A9, 0x314, 0x342}}, {0x1F70, {0x3B1, 0x300}},
{0x1F71, {0x3B1, 0x301}}, {0x1F72, {0x3B5, 0x300}}, {0x1F73, {0x3B5, 0x301}}, {0x1F74, {0x3B7, 0x300}}, {0x1F75, {0x3B7, 0x301}}, {0x1F76, {0x3B9, 0x300}}, {0x1F77, {0x3B9, 0x301}},
{0x1F78, {0x3BF, 0x300}}, {0x1F79, {0x3BF, 0x301}}, {0x1F7A, {0x3C5, 0x300}}, {0x1F7B, {0x3C5, 0x301}}, {0x1F7C, {0x3C9, 0x300}}, {0x1F7D, {0x3C9, 0x301}}, {0x1F80, {0x3B1, 0x313, 0x345}},
{0x1F81, {0x3B1, 0x314, 0x345}}, {0x1F82, {0x3B1, 0x313, 0x300, 0x345}}, {0x1F83, {0x3B1, 0x314, 0x300, 0x345}}, {0x1F84, {0x3B1, 0x313, 0x301, 0x345}}, {0x1F85, {0x3B1, 0x314, 0x301, 0x345}},
{0x1F86, {0x3B1, 0x313, 0x342, 0x345}}, {0x1F87, {0x3B1, 0x314, 0x342, 0x345}}, {0x1F88, {0x391, 0x313, 0x345}}, {0x1F89, {0x391, 0x314, 0x345}}, {0x1F8A, {0x391, 0x313, 0x300, 0x345}},
{0x1F8B, {0x391, 0x314, 0x300, 0x345}}, {0x1F8C, {0x391, 0x313, 0x301, 0x345}}, {0x1F8D, {0x391, 0x314, 0x301, 0x345}}, {0x1F8E, {0x391, 0x313, 0x342, 0x345}}, {0x1F8F, {0x391, 0x314, 0x342, 0x345}},
{0x1F90, {0x3B7, 0x313, 0x345}}, {0x1F91, {0x3B7, 0x314, 0x345}}, {0x1F92, {0x3B7, 0x313, 0x300, 0x345}}, {0x1F93, {0x3B7, 0x314, 0x300, 0x345}}, {0x1F94, {0x3B7, 0x313, 0x301, 0x345}},
{0x1F95, {0x3B7, 0x314, 0x301, 0x345}}, {0x1F96, {0x3B7, 0x313, 0x342, 0x345}}, {0x1F97, {0x3B7, 0x314, 0x342, 0x345}}, {0x1F98, {0x397, 0x313, 0x345}}, {0x1F99, {0x397, 0x314, 0x345}},
{0x1F9A, {0x397, 0x313, 0x300, 0x345}}, {0x1F9B, {0x397, 0x314, 0x300, 0x345}}, {0x1F9C, {0x397, 0x313, 0x301, 0x345}}, {0x1F9D, {0x397, 0x314, 0x301, 0x345}}, {0x1F9E, {0x397, 0x313, 0x342, 0x345}},
{0x1F9F, {0x397, 0x314, 0x342, 0x345}}, {0x1FA0, {0x3C9, 0x313, 0x345}}, {0x1FA1, {0x3C9, 0x314, 0x345}}, {0x1FA2, {0x3C9, 0x313, 0x300, 0x345}}, {0x1FA3, {0x3C9, 0x314, 0x300, 0x345}},
{0x1FA4, {0x3C9, 0x313, 0x301, 0x345}}, {0x1FA5, {0x3C9, 0x314, 0x301, 0x345}}, {0x1FA6, {0x3C9, 0x313, 0x342, 0x345}}, {0x1FA7, {0x3C9, 0x314, 0x342, 0x345}}, {0x1FA8, {0x3A9, 0x313, 0x345}},
{0x1FA9, {0x3A9, 0x314, 0x345}}, {0x1FAA, {0x3A9, 0x313, 0x300, 0x345}}, {0x1FAB, {0x3A9, 0x314, 0x300, 0x345}}, {0x1FAC, {0x3A9, 0x313, 0x301, 0x345}}, {0x1FAD, {0x3A9, 0x314, 0x301, 0x345}},
{0x1FAE, {0x3A9, 0x313, 0x342, 0x345}}, {0x1FAF, {0x3A9, 0x314, 0x342, 0x345}}, {0x1FB0, {0x3B1, 0x306}}, {0x1FB1, {0x3B1, 0x304}}, {0x1FB2, {0x3B1, 0x300, 0x345}}, {0x1FB3, {0x3B1, 0x345}},
{0x1FB4, {0x3B1, 0x301, 0x345}}, {0x1FB6, {0x3B1, 0x342}}, {0x1FB7, {0x3B1, 0x342, 0x345}}, {0x1FB8, {0x391, 0x306}}, {0x1FB9, {0x391, 0x304}}, {0x1FBA, {0x391, 0x300}}, {0x1FBB, {0x391, 0x301}},
{0x1FBC, {0x391, 0x345}}, {0x1FBE, {0x3B9}}, {0x1FC1, {0xA8, 0x342}}, {0x1FC2, {0x3B7, 0x300, 0x345}}, {0x1FC3, {0x3B7, 0x345}}, {0x1FC4, {0x3B7, 0x301, 0x345}}, {0x1FC6, {0x3B7, 0x342}},
{0x1FC7, {0x3B7, 0x342, 0x345}}, {0x1FC8, {0x395, 0x300}}, {0x1FC9, {0x395, 0x301}}, {0x1FCA, {0x397, 0x300}}, {0x1FCB, {0x397, 0x301}}, {0x1FCC, {0x397, 0x345}}, {0x1FCD, {0x1FBF, 0x300}},
{0x1FCE, {0x1FBF, 0x301}}, {0x1FCF, {0x1FBF, 0x342}}, {0x1FD0, {0x3B9, 0x306}}, {0x1FD1, {0x3B9, 0x304}}, {0x1FD2, {0x3B9, 0x308, 0x300}}, {0x1FD3, {0x3B9, 0x308, 0x301}}, {0x1FD6, {0x3B9, 0x342}},
{0x1FD7, {0x3B9, 0x308, 0x342}}, {0x1FD8, {0x399, 0x306}}, {0x1FD9, {0x399, 0x304}}, {0x1FDA, {0x399, 0x300}}, {0x1FDB, {0x399, 0x301}}, {0x1FDD, {0x1FFE, 0x300}}, {0x1FDE, {0x1FFE, 0x301}},
{0x1FDF, {0x1FFE, 0x342}}, {0x1FE0, {0x3C5, 0x306}}, {0x1FE1, {0x3C5, 0x304}}, {0x1FE2, {0x3C5, 0x308, 0x300}}, {0x1FE3, {0x3C5, 0x308, 0x301}}, {0x1FE4, {0x3C1, 0x313}}, {0x1FE5, {0x3C1, 0x314}},
{0x1FE6, {0x3C5, 0x342}}, {0x1FE7, {0x3C5, 0x308, 0x342}}, {0x1FE8, {0x3A5, 0x306}}, {0x1FE9, {0x3A5, 0x304}}, {0x1FEA, {0x3A5, 0x300}}, {0x1FEB, {0x3A5, 0x301}}, {0x1FEC, {0x3A1, 0x314}},
{0x1FED, {0xA8, 0x300}}, {0x1FEE, {0xA8, 0x301}}, {0x1FEF, {0x60}}, {0x1FF2, {0x3C9, 0x300, 0x345}}, {0x1FF3, {0x3C9, 0x345}}, {0x1FF4, {0x3C9, 0x301, 0x345}}, {0x1FF6, {0x3C9, 0x342}},
{0x1FF7, {0x3C9, 0x342, 0x345}}, {0x1FF8, {0x39F, 0x300}}, {0x1FF9, {0x39F, 0x301}}, {0x1FFA, {0x3A9, 0x300}}, {0x1FFB, {0x3A9, 0x301}}, {0x1FFC, {0x3A9, 0x345}}, {0x1FFD, {0xB4}}, {0x2000, {0x2002}},
{0x2001, {0x2003}}, {0x2126, {0x3A9}}, {0x212A, {0x4B}}, {0x212B, {0x41, 0x30A}}, {0x219A, {0x2190, 0x338}}, {0x219B, {0x2192, 0x338}}, {0x21AE, {0x2194, 0x338}}, {0x21CD, {0x21D0, 0x338}},
{0x21CE, {0x21D4, 0x338}}, {0x21CF, {0x21D2, 0x338}}, {0x2204, {0x2203, 0x338}}, {0x2209, {0x2208, 0x338}}, {0x220C, {0x220B, 0x338}}, {0x2224, {0x2223, 0x338}}, {0x2226, {0x2225, 0x338}},
{0x2241, {0x223C, 0x338}}, {0x2244, {0x2243, 0x338}}, {0x2247, {0x2245, 0x338}}, {0x2249, {0x2248, 0x338}}, {0x2260, {0x3D, 0x338}}, {0x2262, {0x2261, 0x338}}, {0x226D, {0x224D, 0x338}},
{0x226E, {0x3C, 0x338}}, {0x226F, {0x3E, 0x338}}, {0x2270, {0x2264, 0x338}}, {0x2271, {0x2265, 0x338}}, {0x2274, {0x2272, 0x338}}, {0x2275, {0x2273, 0x338}}, {0x2278, {0x2276, 0x338}},
{0x2279, {0x2277, 0x338}}, {0x2280, {0x227A, 0x338}}, {0x2281, {0x227B, 0x338}}, {0x2284, {0x2282, 0x338}}, {0x2285, {0x2283, 0x338}}, {0x2288, {0x2286, 0x338}}, {0x2289, {0x2287, 0x338}},
{0x22AC, {0x22A2, 0x338}}, {0x22AD, {0x22A8, 0x338}}, {0x22AE, {0x22A9, 0x338}}, {0x22AF, {0x22AB, 0x338}}, {0x22E0, {0x227C, 0x338}}, {0x22E1, {0x227D, 0x338}}, {0x22E2, {0x2291, 0x338}},
{0x22E3, {0x2292, 0x338}}, {0x22EA, {0x22B2, 0x338}}, {0x22EB, {0x22B3, 0x338}}, {0x22EC, {0x22B4, 0x338}}, {0x22ED, {0x22B5, 0x338}}, {0x2329, {0x3008}}, {0x232A, {0x3009}},
{0x2ADC, {0x2ADD, 0x338}}, {0x304C, {0x304B, 0x3099}}, {0x304E, {0x304D, 0x3099}}, {0x3050, {0x304F, 0x3099}}, {0x3052, {0x3051, 0x3099}}, {0x3054, {0x3053, 0x3099}}, {0x3056, {0x3055, 0x3099}},
{0x3058, {0x3057, 0x3099}}, {0x305A, {0x3059, 0x3099}}, {0x305C, {0x305B, 0x3099}}, {0x305E, {0x305D, 0x3099}}, {0x3060, {0x305F, 0x3099}}, {0x3062, {0x3061, 0x3099}}, {0x3065, {0x3064, 0x3099}},
{0x3067, {0x3066, 0x3099}}, {0x3069, {0x3068, 0x3099}}, {0x3070, {0x306F, 0x3099}}, {0x3071, {0x306F, 0x309A}}, {0x3073, {0x3072, 0x3099}}, {0x3074, {0x3072, 0x309A}}, {0x3076, {0x3075, 0x3099}},
{0x3077, {0x3075, 0x309A}}, {0x3079, {0x3078, 0x3099}}, {0x307A, {0x3078, 0x309A}}, {0x307C, {0x307B, 0x3099}}, {0x307D, {0x307B, 0x309A}}, {0x3094, {0x3046, 0x3099}}, {0x309E, {0x309D, 0x3099}},
{0x30AC, {0x30AB, 0x3099}}, {0x30AE, {0x30AD, 0x3099}}, {0x30B0, {0x30AF, 0x3099}}, {0x30B2, {0x30B1, 0x3099}}, {0x30B4, {0x30B3, 0x3099}}, {0x30B6, {0x30B5, 0x3099}}, {0x30B8, {0x30B7, 0x3099}},
{0x30BA, {0x30B9, 0x3099}}, {0x30BC, {0x30BB, 0x3099}}, {0x30BE, {0x30BD, 0x3099}}, {0x30C0, {0x30BF, 0x3099}}, {0x30C2, {0x30C1, 0x3099}}, {0x30C5, {0x30C4, 0x3099}}, {0x30C7, {0x30C6, 0x3099}},
{0x30C9, {0x30C8, 0x3099}}, {0x30D0, {0x30CF, 0x3099}}, {0x30D1, {0x30CF, 0x309A}}, {0x30D3, {0x30D2, 0x3099}}, {0x30D4, {0x30D2, 0x309A}}, {0x30D6, {0x30D5, 0x3099}}, {0x30D7, {0x30D5, 0x309A}},
{0x30D9, {0x30D8, 0x3099}}, {0x30DA, {0x30D8, 0x309A}}, {0x30DC, {0x30DB, 0x3099}}, {0x30DD, {0x30DB, 0x309A}}, {0x30F4, {0x30A6, 0x3099}}, {0x30F7, {0x30EF, 0x3099}}, {0x30F8, {0x30F0, 0x3099}},
{0x30F9, {0x30F1, 0x3099}}, {0x30FA, {0x30F2, 0x3099}}, {0x30FE, {0x30FD, 0x3099}}, {0xF900, {0x8C48}}, {0xF901, {0x66F4}}, {0xF902, {0x8ECA}}, {0xF903, {0x8CC8}}, {0xF904, {0x6ED1}},
{0xF905, {0x4E32}}, {0xF906, {0x53E5}}, {0xF907, {0x9F9C}}, {0xF908, {0x9F9C}}, {0xF909, {0x5951}}, {0xF90A, {0x91D1}}, {0xF90B, {0x5587}}, {0xF90C, {0x5948}}, {0xF90D, {0x61F6}}, {0xF90E, {0x7669}},
{0xF90F, {0x7F85}}, {0xF910, {0x863F}}, {0xF911, {0x87BA}}, {0xF912, {0x88F8}}, {0xF913, {0x908F}}, {0xF914, {0x6A02}}, {0xF915, {0x6D1B}}, {0xF916, {0x70D9}}, {0xF917, {0x73DE}}, {0xF918, {0x843D}},
{0xF919, {0x916A}}, {0xF91A, {0x99F1}}, {0xF91B, {0x4E82}}, {0xF91C, {0x5375}}, {0xF91D, {0x6B04}}, {0xF91E, {0x721B}}, {0xF91F, {0x862D}}, {0xF920, {0x9E1E}}, {0xF921, {0x5D50}}, {0xF922, {0x6FEB}},
{0xF923, {0x85CD}}, {0xF924, {0x8964}}, {0xF925, {0x62C9}}, {0xF926, {0x81D8}}, {0xF927, {0x881F}}, {0xF928, {0x5ECA}}, {0xF929, {0x6717}}, {0xF92A, {0x6D6A}}, {0xF92B, {0x72FC}}, {0xF92C, {0x90CE}},
{0xF92D, {0x4F86}}, {0xF92E, {0x51B7}}, {0xF92F, {0x52DE}}, {0xF930, {0x64C4}}, {0xF931, {0x6AD3}}, {0xF932, {0x7210}}, {0xF933, {0x76E7}}, {0xF934, {0x8001}}, {0xF935, {0x8606}}, {0xF936, {0x865C}},
{0xF937, {0x8DEF}}, {0xF938, {0x9732}}, {0xF939, {0x9B6F}}, {0xF93A, {0x9DFA}}, {0xF93B, {0x788C}}, {0xF93C, {0x797F}}, {0xF93D, {0x7DA0}}, {0xF93E, {0x83C9}}, {0xF93F, {0x9304}}, {0xF940, {0x9E7F}},
{0xF941, {0x8AD6}}, {0xF942, {0x58DF}}, {0xF943, {0x5F04}}, {0xF944, {0x7C60}}, {0xF945, {0x807E}}, {0xF946, {0x7262}}, {0xF947, {0x78CA}}, {0xF948, {0x8CC2}}, {0xF949, {0x96F7}}, {0xF94A, {0x58D8}},
{0xF94B, {0x5C62}}, {0xF94C, {0x6A13}}, {0xF94D, {0x6DDA}}, {0xF94E, {0x6F0F}}, {0xF94F, {0x7D2F}}, {0xF950, {0x7E37}}, {0xF951, {0x964B}}, {0xF952, {0x52D2}}, {0xF953, {0x808B}}, {0xF954, {0x51DC}},
{0xF955, {0x51CC}}, {0xF956, {0x7A1C}}, {0xF957, {0x7DBE}}, {0xF958, {0x83F1}}, {0xF959, {0x9675}}, {0xF95A, {0x8B80}}, {0xF95B, {0x62CF}}, {0xF95C, {0x6A02}}, {0xF95D, {0x8AFE}}, {0xF95E, {0x4E39}},
{0xF95F, {0x5BE7}}, {0xF960, {0x6012}}, {0xF961, {0x7387}}, {0xF962, {0x7570}}, {0xF963, {0x5317}}, {0xF964, {0x78FB}}, {0xF965, {0x4FBF}}, {0xF966, {0x5FA9}}, {0xF967, {0x4E0D}}, {0xF968, {0x6CCC}},
{0xF969, {0x6578}}, {0xF96A, {0x7D22}}, {0xF96B, {0x53C3}}, {0xF96C, {0x585E}}, {0xF96D, {0x7701}}, {0xF96E, {0x8449}}, {0xF96F, {0x8AAA}}, {0xF970, {0x6BBA}}, {0xF971, {0x8FB0}}, {0xF972, {0x6C88}},
{0xF973, {0x62FE}}, {0xF974, {0x82E5}}, {0xF975, {0x63A0}}, {0xF976, {0x7565}}, {0xF977, {0x4EAE}}, {0xF978, {0x5169}}, {0xF979, {0x51C9}}, {0xF97A, {0x6881}}, {0xF97B, {0x7CE7}}, {0xF97C, {0x826F}},
{0xF97D, {0x8AD2}}, {0xF97E, {0x91CF}}, {0xF97F, {0x52F5}}, {0xF980, {0x5442}}, {0xF981, {0x5973}}, {0xF982, {0x5EEC}}, {0xF983, {0x65C5}}, {0xF984, {0x6FFE}}, {0xF985, {0x792A}}, {0xF986, {0x95AD}},
{0xF987, {0x9A6A}}, {0xF988, {0x9E97}}, {0xF989, {0x9ECE}}, {0xF98A, {0x529B}}, {0xF98B, {0x66C6}}, {0xF98C, {0x6B77}}, {0xF98D, {0x8F62}}, {0xF98E, {0x5E74}}, {0xF98F, {0x6190}}, {0xF990, {0x6200}},
{0xF991, {0x649A}}, {0xF992, {0x6F23}}, {0xF993, {0x7149}}, {0xF994, {0x7489}}, {0xF995, {0x79CA}}, {0xF996, {0x7DF4}}, {0xF997, {0x806F}}, {0xF998, {0x8F26}}, {0xF999, {0x84EE}}, {0xF99A, {0x9023}},
{0xF99B, {0x934A}}, {0xF99C, {0x5217}}, {0xF99D, {0x52A3}}, {0xF99E, {0x54BD}}, {0xF99F, {0x70C8}}, {0xF9A0, {0x88C2}}, {0xF9A1, {0x8AAA}}, {0xF9A2, {0x5EC9}}, {0xF9A3, {0x5FF5}}, {0xF9A4, {0x637B}},
{0xF9A5, {0x6BAE}}, {0xF9A6, {0x7C3E}}, {0xF9A7, {0x7375}}, {0xF9A8, {0x4EE4}}, {0xF9A9, {0x56F9}}, {0xF9AA, {0x5BE7}}, {0xF9AB, {0x5DBA}}, {0xF9AC, {0x601C}}, {0xF9AD, {0x73B2}}, {0xF9AE, {0x7469}},
{0xF9AF, {0x7F9A}}, {0xF9B0, {0x8046}}, {0xF9B1, {0x9234}}, {0xF9B2, {0x96F6}}, {0xF9B3, {0x9748}}, {0xF9B4, {0x9818}}, {0xF9B5, {0x4F8B}}, {0xF9B6, {0x79AE}}, {0xF9B7, {0x91B4}}, {0xF9B8, {0x96B8}},
{0xF9B9, {0x60E1}}, {0xF9BA, {0x4E86}}, {0xF9BB, {0x50DA}}, {0xF9BC, {0x5BEE}}, {0xF9BD, {0x5C3F}}, {0xF9BE, {0x6599}}, {0xF9BF, {0x6A02}}, {0xF9C0, {0x71CE}}, {0xF9C1, {0x7642}}, {0xF9C2, {0x84FC}},
{0xF9C3, {0x907C}}, {0xF9C4, {0x9F8D}}, {0xF9C5, {0x6688}}, {0xF9C6, {0x962E}}, {0xF9C7, {0x5289}}, {0xF9C8, {0x677B}}, {0xF9C9, {0x67F3}}, {0xF9CA, {0x6D41}}, {0xF9CB, {0x6E9C}}, {0xF9CC, {0x7409}},
{0xF9CD, {0x7559}}, {0xF9CE, {0x786B}}, {0xF9CF, {0x7D10}}, {0xF9D0, {0x985E}}, {0xF9D1, {0x516D}}, {0xF9D2, {0x622E}}, {0xF9D3, {0x9678}}, {0xF9D4, {0x502B}}, {0xF9D5, {0x5D19}}, {0xF9D6, {0x6DEA}},
{0xF9D7, {0x8F2A}}, {0xF9D8, {0x5F8B}}, {0xF9D9, {0x6144}}, {0xF9DA, {0x6817}}, {0xF9DB, {0x7387}}, {0xF9DC, {0x9686}}, {0xF9DD, {0x5229}}, {0xF9DE, {0x540F}}, {0xF9DF, {0x5C65}}, {0xF9E0, {0x6613}},
{0xF9E1, {0x674E}}, {0xF9E2, {0x68A8}}, {0xF9E3, {0x6CE5}}, {0xF9E4, {0x7406}}, {0xF9E5, {0x75E2}}, {0xF9E6, {0x7F79}}, {0xF9E7, {0x88CF}}, {0xF9E8, {0x88E1}}, {0xF9E9, {0x91CC}}, {0xF9EA, {0x96E2}},
{0xF9EB, {0x533F}}, {0xF9EC, {0x6EBA}}, {0xF9ED, {0x541D}}, {0xF9EE, {0x71D0}}, {0xF9EF, {0x7498}}, {0xF9F0, {0x85FA}}, {0xF9F1, {0x96A3}}, {0xF9F2, {0x9C57}}, {0xF9F3, {0x9E9F}}, {0xF9F4, {0x6797}},
{0xF9F5, {0x6DCB}}, {0xF9F6, {0x81E8}}, {0xF9F7, {0x7ACB}}, {0xF9F8, {0x7B20}}, {0xF9F9, {0x7C92}}, {0xF9FA, {0x72C0}}, {0xF9FB, {0x7099}}, {0xF9FC, {0x8B58}}, {0xF9FD, {0x4EC0}}, {0xF9FE, {0x8336}},
{0xF9FF, {0x523A}}, {0xFA00, {0x5207}}, {0xFA01, {0x5EA6}}, {0xFA02, {0x62D3}}, {0xFA03, {0x7CD6}}, {0xFA04, {0x5B85}}, {0xFA05, {0x6D1E}}, {0xFA06, {0x66B4}}, {0xFA07, {0x8F3B}}, {0xFA08, {0x884C}},
{0xFA09, {0x964D}}, {0xFA0A, {0x898B}}, {0xFA0B, {0x5ED3}}, {0xFA0C, {0x5140}}, {0xFA0D, {0x55C0}}, {0xFA10, {0x585A}}, {0xFA12, {0x6674}}, {0xFA15, {0x51DE}}, {0xFA16, {0x732A}}, {0xFA17, {0x76CA}},
{0xFA18, {0x793C}}, {0xFA19, {0x795E}}, {0xFA1A, {0x7965}}, {0xFA1B, {0x798F}}, {0xFA1C, {0x9756}}, {0xFA1D, {0x7CBE}}, {0xFA1E, {0x7FBD}}, {0xFA20, {0x8612}}, {0xFA22, {0x8AF8}}, {0xFA25, {0x9038}},
{0xFA26, {0x90FD}}, {0xFA2A, {0x98EF}}, {0xFA2B, {0x98FC}}, {0xFA2C, {0x9928}}, {0xFA2D, {0x9DB4}}, {0xFA2E, {0x90DE}}, {0xFA2F, {0x96B7}}, {0xFA30, {0x4FAE}}, {0xFA31, {0x50E7}}, {0xFA32, {0x514D}},
{0xFA33, {0x52C9}}, {0xFA34, {0x52E4}}, {0xFA35, {0x5351}}, {0xFA36, {0x559D}}, {0xFA37, {0x5606}}, {0xFA38, {0x5668}}, {0xFA39, {0x5840}}, {0xFA3A, {0x58A8}}, {0xFA3B, {0x5C64}}, {0xFA3C, {0x5C6E}},
{0xFA3D, {0x6094}}, {0xFA3E, {0x6168}}, {0xFA3F, {0x618E}}, {0xFA40, {0x61F2}}, {0xFA41, {0x654F}}, {0xFA42, {0x65E2}}, {0xFA43, {0x6691}}, {0xFA44, {0x6885}}, {0xFA45, {0x6D77}}, {0xFA46, {0x6E1A}},
{0xFA47, {0x6F22}}, {0xFA48, {0x716E}}, {0xFA49, {0x722B}}, {0xFA4A, {0x7422}}, {0xFA4B, {0x7891}}, {0xFA4C, {0x793E}}, {0xFA4D, {0x7949}}, {0xFA4E, {0x7948}}, {0xFA4F, {0x7950}}, {0xFA50, {0x7956}},
{0xFA51, {0x795D}}, {0xFA52, {0x798D}}, {0xFA53, {0x798E}}, {0xFA54, {0x7A40}}, {0xFA55, {0x7A81}}, {0xFA56, {0x7BC0}}, {0xFA57, {0x7DF4}}, {0xFA58, {0x7E09}}, {0xFA59, {0x7E41}}, {0xFA5A, {0x7F72}},
{0xFA5B, {0x8005}}, {0xFA5C, {0x81ED}}, {0xFA5D, {0x8279}}, {0xFA5E, {0x8279}}, {0xFA5F, {0x8457}}, {0xFA60, {0x8910}}, {0xFA61, {0x8996}}, {0xFA62, {0x8B01}}, {0xFA63, {0x8B39}}, {0xFA64, {0x8CD3}},
{0xFA65, {0x8D08}}, {0xFA66, {0x8FB6}}, {0xFA67, {0x9038}}, {0xFA68, {0x96E3}}, {0xFA69, {0x97FF}}, {0xFA6A, {0x983B}}, {0xFA6B, {0x6075}}, {0xFA6C, {0x242EE}}, {0xFA6D, {0x8218}}, {0xFA70, {0x4E26}},
{0xFA71, {0x51B5}}, {0xFA72, {0x5168}}, {0xFA73, {0x4F80}}, {0xFA74, {0x5145}}, {0xFA75, {0x5180}}, {0xFA76, {0x52C7}}, {0xFA77, {0x52FA}}, {0xFA78, {0x559D}}, {0xFA79, {0x5555}}, {0xFA7A, {0x5599}},
{0xFA7B, {0x55E2}}, {0xFA7C, {0x585A}}, {0xFA7D, {0x58B3}}, {0xFA7E, {0x5944}}, {0xFA7F, {0x5954}}, {0xFA80, {0x5A62}}, {0xFA81, {0x5B28}}, {0xFA82, {0x5ED2}}, {0xFA83, {0x5ED9}}, {0xFA84, {0x5F69}},
{0xFA85, {0x5FAD}}, {0xFA86, {0x60D8}}, {0xFA87, {0x614E}}, {0xFA88, {0x6108}}, {0xFA89, {0x618E}}, {0xFA8A, {0x6160}}, {0xFA8B, {0x61F2}}, {0xFA8C, {0x6234}}, {0xFA8D, {0x63C4}}, {0xFA8E, {0x641C}},
{0xFA8F, {0x6452}}, {0xFA90, {0x6556}}, {0xFA91, {0x6674}}, {0xFA92, {0x6717}}, {0xFA93, {0x671B}}, {0xFA94, {0x6756}}, {0xFA95, {0x6B79}}, {0xFA96, {0x6BBA}}, {0xFA97, {0x6D41}}, {0xFA98, {0x6EDB}},
{0xFA99, {0x6ECB}}, {0xFA9A, {0x6F22}}, {0xFA9B, {0x701E}}, {0xFA9C, {0x716E}}, {0xFA9D, {0x77A7}}, {0xFA9E, {0x7235}}, {0xFA9F, {0x72AF}}, {0xFAA0, {0x732A}}, {0xFAA1, {0x7471}}, {0xFAA2, {0x7506}},
{0xFAA3, {0x753B}}, {0xFAA4, {0x761D}}, {0xFAA5, {0x761F}}, {0xFAA6, {0x76CA}}, {0xFAA7, {0x76DB}}, {0xFAA8, {0x76F4}}, {0xFAA9, {0x774A}}, {0xFAAA, {0x7740}}, {0xFAAB, {0x78CC}}, {0xFAAC, {0x7AB1}},
{0xFAAD, {0x7BC0}}, {0xFAAE, {0x7C7B}}, {0xFAAF, {0x7D5B}}, {0xFAB0, {0x7DF4}}, {0xFAB1, {0x7F3E}}, {0xFAB2, {0x8005}}, {0xFAB3, {0x8352}}, {0xFAB4, {0x83EF}}, {0xFAB5, {0x8779}}, {0xFAB6, {0x8941}},
{0xFAB7, {0x8986}}, {0xFAB8, {0x8996}}, {0xFAB9, {0x8ABF}}, {0xFABA, {0x8AF8}}, {0xFABB, {0x8ACB}}, {0xFABC, {0x8B01}}, {0xFABD, {0x8AFE}}, {0xFABE, {0x8AED}}, {0xFABF, {0x8B39}}, {0xFAC0, {0x8B8A}},
{0xFAC1, {0x8D08}}, {0xFAC2, {0x8F38}}, {0xFAC3, {0x9072}}, {0xFAC4, {0x9199}}, {0xFAC5, {0x9276}}, {0xFAC6, {0x967C}}, {0xFAC7, {0x96E3}}, {0xFAC8, {0x9756}}, {0xFAC9, {0x97DB}}, {0xFACA, {0x97FF}},
{0xFACB, {0x980B}}, {0xFACC, {0x983B}}, {0xFACD, {0x9B12}}, {0xFACE, {0x9F9C}}, {0xFACF, {0x2284A}}, {0xFAD0, {0x22844}}, {0xFAD1, {0x233D5}}, {0xFAD2, {0x3B9D}}, {0xFAD3, {0x4018}},
{0xFAD4, {0x4039}}, {0xFAD5, {0x25249}}, {0xFAD6, {0x25CD0}}, {0xFAD7, {0x27ED3}}, {0xFAD8, {0x9F43}}, {0xFAD9, {0x9F8E}}, {0xFB1D, {0x5D9, 0x5B4}}, {0xFB1F, {0x5F2, 0x5B7}}, {0xFB2A, {0x5E9, 0x5C1}},
{0xFB2B, {0x5E9, 0x5C2}}, {0xFB2C, {0x5E9, 0x5BC, 0x5C1}}, {0xFB2D, {0x5E9, 0x5BC, 0x5C2}}, {0xFB2E, {0x5D0, 0x5B7}}, {0xFB2F, {0x5D0, 0x5B8}}, {0xFB30, {0x5D0, 0x5BC}}, {0xFB31, {0x5D1, 0x5BC}},
{0xFB32, {0x5D2, 0x5BC}}, {0xFB33, {0x5D3, 0x5BC}}, {0xFB34, {0x5D4, 0x5BC}}, {0xFB35, {0x5D5, 0x5BC}}, {0xFB36, {0x5D6, 0x5BC}}, {0xFB38, {0x5D8, 0x5BC}}, {0xFB39, {0x5D9, 0x5BC}},
{0xFB3A, {0x5DA, 0x5BC}}, {0xFB3B, {0x5DB, 0x5BC}}, {0xFB3C, {0x5DC, 0x5BC}}, {0xFB3E, {0x5DE, 0x5BC}}, {0xFB40, {0x5E0, 0x5BC}}, {0xFB41, {0x5E1, 0x5BC}}, {0xFB43, {0x5E3, 0x5BC}},
{0xFB44, {0x5E4, 0x5BC}}, {0xFB46, {0x5E6, 0x5BC}}, {0xFB47, {0x5E7, 0x5BC}}, {0xFB48, {0x5E8, 0x5BC}}, {0xFB49, {0x5E9, 0x5BC}}, {0xFB4A, {0x5EA, 0x5BC}}, {0xFB4B, {0x5D5, 0x5B9}},
{0xFB4C, {0x5D1, 0x5BF}}, {0xFB4D, {0x5DB, 0x5BF}}, {0xFB4E, {0x5E4, 0x5BF}}, {0x1109A, {0x11099, 0x110BA}}, {0x1109C, {0x1109B, 0x110BA}}, {0x110AB, {0x110A5, 0x110BA}},
{0x1112E, {0x11131, 0x11127}}, {0x1112F, {0x11132, 0x11127}}, {0x1134B, {0x11347, 0x1133E}}, {0x1134C, {0x11347, 0x11357}}, {0x114BB, {0x114B9, 0x114BA}}, {0x114BC, {0x114B9, 0x114B0}},
{0x114BE, {0x114B9, 0x114BD}}, {0x115BA, {0x115B8, 0x115AF}}, {0x115BB, {0x115B9, 0x115AF}}, {0x1D15E, {0x1D157, 0x1D165}}, {0x1D15F, {0x1D158, 0x1D165}}, {0x1D160, {0x1D158, 0x1D165, 0x1D16E}},
{0x1D161, {0x1D158, 0x1D165, 0x1D16F}}, {0x1D162, {0x1D158, 0x1D165, 0x1D170}}, {0x1D163, {0x1D158, 0x1D165, 0x1D171}}, {0x1D164, {0x1D158, 0x1D165, 0x1D172}}, {0x1D1BB, {0x1D1B9, 0x1D165}},
{0x1D1BC, {0x1D1BA, 0x1D165}}, {0x1D1BD, {0x1D1B9, 0x1D165, 0x1D16E}}, {0x1D1BE, {0x1D1BA, 0x1D165, 0x1D16E}}, {0x1D1BF, {0x1D1B9, 0x1D165, 0x1D16F}}, {0x1D1C0, {0x1D1BA, 0x1D165, 0x1D16F}},
{0x2F800, {0x4E3D}}, {0x2F801, {0x4E38}}, {0x2F802, {0x4E41}}, {0x2F803, {0x20122}}, {0x2F804, {0x4F60}}, {0x2F805, {0x4FAE}}, {0x2F806, {0x4FBB}}, {0x2F807, {0x5002}}, {0x2F808, {0x507A}},
{0x2F809, {0x5099}}, {0x2F80A, {0x50E7}}, {0x2F80B, {0x50CF}}, {0x2F80C, {0x349E}}, {0x2F80D, {0x2063A}}, {0x2F80E, {0x514D}}, {0x2F80F, {0x5154}}, {0x2F810, {0x5164}}, {0x2F811, {0x5177}},
{0x2F812, {0x2051C}}, {0x2F813, {0x34B9}}, {0x2F814, {0x5167}}, {0x2F815, {0x518D}}, {0x2F816, {0x2054B}}, {0x2F817, {0x5197}}, {0x2F818, {0x51A4}}, {0x2F819, {0x4ECC}}, {0x2F81A, {0x51AC}},
{0x2F81B, {0x51B5}}, {0x2F81C, {0x291DF}}, {0x2F81D, {0x51F5}}, {0x2F81E, {0x5203}}, {0x2F81F, {0x34DF}}, {0x2F820, {0x523B}}, {0x2F821, {0x5246}}, {0x2F822, {0x5272}}, {0x2F823, {0x5277}},
{0x2F824, {0x3515}}, {0x2F825, {0x52C7}}, {0x2F826, {0x52C9}}, {0x2F827, {0x52E4}}, {0x2F828, {0x52FA}}, {0x2F829, {0x5305}}, {0x2F82A, {0x5306}}, {0x2F82B, {0x5317}}, {0x2F82C, {0x5349}},
{0x2F82D, {0x5351}}, {0x2F82E, {0x535A}}, {0x2F82F, {0x5373}}, {0x2F830, {0x537D}}, {0x2F831, {0x537F}}, {0x2F832, {0x537F}}, {0x2F833, {0x537F}}, {0x2F834, {0x20A2C}}, {0x2F835, {0x7070}},
{0x2F836, {0x53CA}}, {0x2F837, {0x53DF}}, {0x2F838, {0x20B63}}, {0x2F839, {0x53EB}}, {0x2F83A, {0x53F1}}, {0x2F83B, {0x5406}}, {0x2F83C, {0x549E}}, {0x2F83D, {0x5438}}, {0x2F83E, {0x5448}},
{0x2F83F, {0x5468}}, {0x2F840, {0x54A2}}, {0x2F841, {0x54F6}}, {0x2F842, {0x5510}}, {0x2F843, {0x5553}}, {0x2F844, {0x5563}}, {0x2F845, {0x5584}}, {0x2F846, {0x5584}}, {0x2F847, {0x5599}},
{0x2F848, {0x55AB}}, {0x2F849, {0x55B3}}, {0x2F84A, {0x55C2}}, {0x2F84B, {0x5716}}, {0x2F84C, {0x5606}}, {0x2F84D, {0x5717}}, {0x2F84E, {0x5651}}, {0x2F84F, {0x5674}}, {0x2F850, {0x5207}},
{0x2F851, {0x58EE}}, {0x2F852, {0x57CE}}, {0x2F853, {0x57F4}}, {0x2F854, {0x580D}}, {0x2F855, {0x578B}}, {0x2F856, {0x5832}}, {0x2F857, {0x5831}}, {0x2F858, {0x58AC}}, {0x2F859, {0x214E4}},
{0x2F85A, {0x58F2}}, {0x2F85B, {0x58F7}}, {0x2F85C, {0x5906}}, {0x2F85D, {0x591A}}, {0x2F85E, {0x5922}}, {0x2F85F, {0x5962}}, {0x2F860, {0x216A8}}, {0x2F861, {0x216EA}}, {0x2F862, {0x59EC}},
{0x2F863, {0x5A1B}}, {0x2F864, {0x5A27}}, {0x2F865, {0x59D8}}, {0x2F866, {0x5A66}}, {0x2F867, {0x36EE}}, {0x2F868, {0x36FC}}, {0x2F869, {0x5B08}}, {0x2F86A, {0x5B3E}}, {0x2F86B, {0x5B3E}},
{0x2F86C, {0x219C8}}, {0x2F86D, {0x5BC3}}, {0x2F86E, {0x5BD8}}, {0x2F86F, {0x5BE7}}, {0x2F870, {0x5BF3}}, {0x2F871, {0x21B18}}, {0x2F872, {0x5BFF}}, {0x2F873, {0x5C06}}, {0x2F874, {0x5F53}},
{0x2F875, {0x5C22}}, {0x2F876, {0x3781}}, {0x2F877, {0x5C60}}, {0x2F878, {0x5C6E}}, {0x2F879, {0x5CC0}}, {0x2F87A, {0x5C8D}}, {0x2F87B, {0x21DE4}}, {0x2F87C, {0x5D43}}, {0x2F87D, {0x21DE6}},
{0x2F87E, {0x5D6E}}, {0x2F87F, {0x5D6B}}, {0x2F880, {0x5D7C}}, {0x2F881, {0x5DE1}}, {0x2F882, {0x5DE2}}, {0x2F883, {0x382F}}, {0x2F884, {0x5DFD}}, {0x2F885, {0x5E28}}, {0x2F886, {0x5E3D}},
{0x2F887, {0x5E69}}, {0x2F888, {0x3862}}, {0x2F889, {0x22183}}, {0x2F88A, {0x387C}}, {0x2F88B, {0x5EB0}}, {0x2F88C, {0x5EB3}}, {0x2F88D, {0x5EB6}}, {0x2F88E, {0x5ECA}}, {0x2F88F, {0x2A392}},
{0x2F890, {0x5EFE}}, {0x2F891, {0x22331}}, {0x2F892, {0x22331}}, {0x2F893, {0x8201}}, {0x2F894, {0x5F22}}, {0x2F895, {0x5F22}}, {0x2F896, {0x38C7}}, {0x2F897, {0x232B8}}, {0x2F898, {0x261DA}},
{0x2F899, {0x5F62}}, {0x2F89A, {0x5F6B}}, {0x2F89B, {0x38E3}}, {0x2F89C, {0x5F9A}}, {0x2F89D, {0x5FCD}}, {0x2F89E, {0x5FD7}}, {0x2F89F, {0x5FF9}}, {0x2F8A0, {0x6081}}, {0x2F8A1, {0x393A}},
{0x2F8A2, {0x391C}}, {0x2F8A3, {0x6094}}, {0x2F8A4, {0x226D4}}, {0x2F8A5, {0x60C7}}, {0x2F8A6, {0x6148}}, {0x2F8A7, {0x614C}}, {0x2F8A8, {0x614E}}, {0x2F8A9, {0x614C}}, {0x2F8AA, {0x617A}},
{0x2F8AB, {0x618E}}, {0x2F8AC, {0x61B2}}, {0x2F8AD, {0x61A4}}, {0x2F8AE, {0x61AF}}, {0x2F8AF, {0x61DE}}, {0x2F8B0, {0x61F2}}, {0x2F8B1, {0x61F6}}, {0x2F8B2, {0x6210}}, {0x2F8B3, {0x621B}},
{0x2F8B4, {0x625D}}, {0x2F8B5, {0x62B1}}, {0x2F8B6, {0x62D4}}, {0x2F8B7, {0x6350}}, {0x2F8B8, {0x22B0C}}, {0x2F8B9, {0x633D}}, {0x2F8BA, {0x62FC}}, {0x2F8BB, {0x6368}}, {0x2F8BC, {0x6383}},
{0x2F8BD, {0x63E4}}, {0x2F8BE, {0x22BF1}}, {0x2F8BF, {0x6422}}, {0x2F8C0, {0x63C5}}, {0x2F8C1, {0x63A9}}, {0x2F8C2, {0x3A2E}}, {0x2F8C3, {0x6469}}, {0x2F8C4, {0x647E}}, {0x2F8C5, {0x649D}},
{0x2F8C6, {0x6477}}, {0x2F8C7, {0x3A6C}}, {0x2F8C8, {0x654F}}, {0x2F8C9, {0x656C}}, {0x2F8CA, {0x2300A}}, {0x2F8CB, {0x65E3}}, {0x2F8CC, {0x66F8}}, {0x2F8CD, {0x6649}}, {0x2F8CE, {0x3B19}},
{0x2F8CF, {0x6691}}, {0x2F8D0, {0x3B08}}, {0x2F8D1, {0x3AE4}}, {0x2F8D2, {0x5192}}, {0x2F8D3, {0x5195}}, {0x2F8D4, {0x6700}}, {0x2F8D5, {0x669C}}, {0x2F8D6, {0x80AD}}, {0x2F8D7, {0x43D9}},
{0x2F8D8, {0x6717}}, {0x2F8D9, {0x671B}}, {0x2F8DA, {0x6721}}, {0x2F8DB, {0x675E}}, {0x2F8DC, {0x6753}}, {0x2F8DD, {0x233C3}}, {0x2F8DE, {0x3B49}}, {0x2F8DF, {0x67FA}}, {0x2F8E0, {0x6785}},
{0x2F8E1, {0x6852}}, {0x2F8E2, {0x6885}}, {0x2F8E3, {0x2346D}}, {0x2F8E4, {0x688E}}, {0x2F8E5, {0x681F}}, {0x2F8E6, {0x6914}}, {0x2F8E7, {0x3B9D}}, {0x2F8E8, {0x6942}}, {0x2F8E9, {0x69A3}},
{0x2F8EA, {0x69EA}}, {0x2F8EB, {0x6AA8}}, {0x2F8EC, {0x236A3}}, {0x2F8ED, {0x6ADB}}, {0x2F8EE, {0x3C18}}, {0x2F8EF, {0x6B21}}, {0x2F8F0, {0x238A7}}, {0x2F8F1, {0x6B54}}, {0x2F8F2, {0x3C4E}},
{0x2F8F3, {0x6B72}}, {0x2F8F4, {0x6B9F}}, {0x2F8F5, {0x6BBA}}, {0x2F8F6, {0x6BBB}}, {0x2F8F7, {0x23A8D}}, {0x2F8F8, {0x21D0B}}, {0x2F8F9, {0x23AFA}}, {0x2F8FA, {0x6C4E}}, {0x2F8FB, {0x23CBC}},
{0x2F8FC, {0x6CBF}}, {0x2F8FD, {0x6CCD}}, {0x2F8FE, {0x6C67}}, {0x2F8FF, {0x6D16}}, {0x2F900, {0x6D3E}}, {0x2F901, {0x6D77}}, {0x2F902, {0x6D41}}, {0x2F903, {0x6D69}}, {0x2F904, {0x6D78}},
{0x2F905, {0x6D85}}, {0x2F906, {0x23D1E}}, {0x2F907, {0x6D34}}, {0x2F908, {0x6E2F}}, {0x2F909, {0x6E6E}}, {0x2F90A, {0x3D33}}, {0x2F90B, {0x6ECB}}, {0x2F90C, {0x6EC7}}, {0x2F90D, {0x23ED1}},
{0x2F90E, {0x6DF9}}, {0x2F90F, {0x6F6E}}, {0x2F910, {0x23F5E}}, {0x2F911, {0x23F8E}}, {0x2F912, {0x6FC6}}, {0x2F913, {0x7039}}, {0x2F914, {0x701E}}, {0x2F915, {0x701B}}, {0x2F916, {0x3D96}},
{0x2F917, {0x704A}}, {0x2F918, {0x707D}}, {0x2F919, {0x7077}}, {0x2F91A, {0x70AD}}, {0x2F91B, {0x20525}}, {0x2F91C, {0x7145}}, {0x2F91D, {0x24263}}, {0x2F91E, {0x719C}}, {0x2F91F, {0x243AB}},
{0x2F920, {0x7228}}, {0x2F921, {0x7235}}, {0x2F922, {0x7250}}, {0x2F923, {0x24608}}, {0x2F924, {0x7280}}, {0x2F925, {0x7295}}, {0x2F926, {0x24735}}, {0x2F927, {0x24814}}, {0x2F928, {0x737A}},
{0x2F929, {0x738B}}, {0x2F92A, {0x3EAC}}, {0x2F92B, {0x73A5}}, {0x2F92C, {0x3EB8}}, {0x2F92D, {0x3EB8}}, {0x2F92E, {0x7447}}, {0x2F92F, {0x745C}}, {0x2F930, {0x7471}}, {0x2F931, {0x7485}},
{0x2F932, {0x74CA}}, {0x2F933, {0x3F1B}}, {0x2F934, {0x7524}}, {0x2F935, {0x24C36}}, {0x2F936, {0x753E}}, {0x2F937, {0x24C92}}, {0x2F938, {0x7570}}, {0x2F939, {0x2219F}}, {0x2F93A, {0x7610}},
{0x2F93B, {0x24FA1}}, {0x2F93C, {0x24FB8}}, {0x2F93D, {0x25044}}, {0x2F93E, {0x3FFC}}, {0x2F93F, {0x4008}}, {0x2F940, {0x76F4}}, {0x2F941, {0x250F3}}, {0x2F942, {0x250F2}}, {0x2F943, {0x25119}},
{0x2F944, {0x25133}}, {0x2F945, {0x771E}}, {0x2F946, {0x771F}}, {0x2F947, {0x771F}}, {0x2F948, {0x774A}}, {0x2F949, {0x4039}}, {0x2F94A, {0x778B}}, {0x2F94B, {0x4046}}, {0x2F94C, {0x4096}},
{0x2F94D, {0x2541D}}, {0x2F94E, {0x784E}}, {0x2F94F, {0x788C}}, {0x2F950, {0x78CC}}, {0x2F951, {0x40E3}}, {0x2F952, {0x25626}}, {0x2F953, {0x7956}}, {0x2F954, {0x2569A}}, {0x2F955, {0x256C5}},
{0x2F956, {0x798F}}, {0x2F957, {0x79EB}}, {0x2F958, {0x412F}}, {0x2F959, {0x7A40}}, {0x2F95A, {0x7A4A}}, {0x2F95B, {0x7A4F}}, {0x2F95C, {0x2597C}}, {0x2F95D, {0x25AA7}}, {0x2F95E, {0x25AA7}},
{0x2F95F, {0x7AEE}}, {0x2F960, {0x4202}}, {0x2F961, {0x25BAB}}, {0x2F962, {0x7BC6}}, {0x2F963, {0x7BC9}}, {0x2F964, {0x4227}}, {0x2F965, {0x25C80}}, {0x2F966, {0x7CD2}}, {0x2F967, {0x42A0}},
{0x2F968, {0x7CE8}}, {0x2F969, {0x7CE3}}, {0x2F96A, {0x7D00}}, {0x2F96B, {0x25F86}}, {0x2F96C, {0x7D63}}, {0x2F96D, {0x4301}}, {0x2F96E, {0x7DC7}}, {0x2F96F, {0x7E02}}, {0x2F970, {0x7E45}},
{0x2F971, {0x4334}}, {0x2F972, {0x26228}}, {0x2F973, {0x26247}}, {0x2F974, {0x4359}}, {0x2F975, {0x262D9}}, {0x2F976, {0x7F7A}}, {0x2F977, {0x2633E}}, {0x2F978, {0x7F95}}, {0x2F979, {0x7FFA}},
{0x2F97A, {0x8005}}, {0x2F97B, {0x264DA}}, {0x2F97C, {0x26523}}, {0x2F97D, {0x8060}}, {0x2F97E, {0x265A8}}, {0x2F97F, {0x8070}}, {0x2F980, {0x2335F}}, {0x2F981, {0x43D5}}, {0x2F982, {0x80B2}},
{0x2F983, {0x8103}}, {0x2F984, {0x440B}}, {0x2F985, {0x813E}}, {0x2F986, {0x5AB5}}, {0x2F987, {0x267A7}}, {0x2F988, {0x267B5}}, {0x2F989, {0x23393}}, {0x2F98A, {0x2339C}}, {0x2F98B, {0x8201}},
{0x2F98C, {0x8204}}, {0x2F98D, {0x8F9E}}, {0x2F98E, {0x446B}}, {0x2F98F, {0x8291}}, {0x2F990, {0x828B}}, {0x2F991, {0x829D}}, {0x2F992, {0x52B3}}, {0x2F993, {0x82B1}}, {0x2F994, {0x82B3}},
{0x2F995, {0x82BD}}, {0x2F996, {0x82E6}}, {0x2F997, {0x26B3C}}, {0x2F998, {0x82E5}}, {0x2F999, {0x831D}}, {0x2F99A, {0x8363}}, {0x2F99B, {0x83AD}}, {0x2F99C, {0x8323}}, {0x2F99D, {0x83BD}},
{0x2F99E, {0x83E7}}, {0x2F99F, {0x8457}}, {0x2F9A0, {0x8353}}, {0x2F9A1, {0x83CA}}, {0x2F9A2, {0x83CC}}, {0x2F9A3, {0x83DC}}, {0x2F9A4, {0x26C36}}, {0x2F9A5, {0x26D6B}}, {0x2F9A6, {0x26CD5}},
{0x2F9A7, {0x452B}}, {0x2F9A8, {0x84F1}}, {0x2F9A9, {0x84F3}}, {0x2F9AA, {0x8516}}, {0x2F9AB, {0x273CA}}, {0x2F9AC, {0x8564}}, {0x2F9AD, {0x26F2C}}, {0x2F9AE, {0x455D}}, {0x2F9AF, {0x4561}},
{0x2F9B0, {0x26FB1}}, {0x2F9B1, {0x270D2}}, {0x2F9B2, {0x456B}}, {0x2F9B3, {0x8650}}, {0x2F9B4, {0x865C}}, {0x2F9B5, {0x8667}}, {0x2F9B6, {0x8669}}, {0x2F9B7, {0x86A9}}, {0x2F9B8, {0x8688}},
{0x2F9B9, {0x870E}}, {0x2F9BA, {0x86E2}}, {0x2F9BB, {0x8779}}, {0x2F9BC, {0x8728}}, {0x2F9BD, {0x876B}}, {0x2F9BE, {0x8786}}, {0x2F9BF, {0x45D7}}, {0x2F9C0, {0x87E1}}, {0x2F9C1, {0x8801}},
{0x2F9C2, {0x45F9}}, {0x2F9C3, {0x8860}}, {0x2F9C4, {0x8863}}, {0x2F9C5, {0x27667}}, {0x2F9C6, {0x88D7}}, {0x2F9C7, {0x88DE}}, {0x2F9C8, {0x4635}}, {0x2F9C9, {0x88FA}}, {0x2F9CA, {0x34BB}},
{0x2F9CB, {0x278AE}}, {0x2F9CC, {0x27966}}, {0x2F9CD, {0x46BE}}, {0x2F9CE, {0x46C7}}, {0x2F9CF, {0x8AA0}}, {0x2F9D0, {0x8AED}}, {0x2F9D1, {0x8B8A}}, {0x2F9D2, {0x8C55}}, {0x2F9D3, {0x27CA8}},
{0x2F9D4, {0x8CAB}}, {0x2F9D5, {0x8CC1}}, {0x2F9D6, {0x8D1B}}, {0x2F9D7, {0x8D77}}, {0x2F9D8, {0x27F2F}}, {0x2F9D9, {0x20804}}, {0x2F9DA, {0x8DCB}}, {0x2F9DB, {0x8DBC}}, {0x2F9DC, {0x8DF0}},
{0x2F9DD, {0x208DE}}, {0x2F9DE, {0x8ED4}}, {0x2F9DF, {0x8F38}}, {0x2F9E0, {0x285D2}}, {0x2F9E1, {0x285ED}}, {0x2F9E2, {0x9094}}, {0x2F9E3, {0x90F1}}, {0x2F9E4, {0x9111}}, {0x2F9E5, {0x2872E}},
{0x2F9E6, {0x911B}}, {0x2F9E7, {0x9238}}, {0x2F9E8, {0x92D7}}, {0x2F9E9, {0x92D8}}, {0x2F9EA, {0x927C}}, {0x2F9EB, {0x93F9}}, {0x2F9EC, {0x9415}}, {0x2F9ED, {0x28BFA}}, {0x2F9EE, {0x958B}},
{0x2F9EF, {0x4995}}, {0x2F9F0, {0x95B7}}, {0x2F9F1, {0x28D77}}, {0x2F9F2, {0x49E6}}, {0x2F9F3, {0x96C3}}, {0x2F9F4, {0x5DB2}}, {0x2F9F5, {0x9723}}, {0x2F9F6, {0x29145}}, {0x2F9F7, {0x2921A}},
{0x2F9F8, {0x4A6E}}, {0x2F9F9, {0x4A76}}, {0x2F9FA, {0x97E0}}, {0x2F9FB, {0x2940A}}, {0x2F9FC, {0x4AB2}}, {0x2F9FD, {0x29496}}, {0x2F9FE, {0x980B}}, {0x2F9FF, {0x980B}}, {0x2FA00, {0x9829}},
{0x2FA01, {0x295B6}}, {0x2FA02, {0x98E2}}, {0x2FA03, {0x4B33}}, {0x2FA04, {0x9929}}, {0x2FA05, {0x99A7}}, {0x2FA06, {0x99C2}}, {0x2FA07, {0x99FE}}, {0x2FA08, {0x4BCE}}, {0x2FA09, {0x29B30}},
{0x2FA0A, {0x9B12}}, {0x2FA0B, {0x9C40}}, {0x2FA0C, {0x9CFD}}, {0x2FA0D, {0x4CCE}}, {0x2FA0E, {0x4CED}}, {0x2FA0F, {0x9D67}}, {0x2FA10, {0x2A0CE}}, {0x2FA11, {0x4CF8}}, {0x2FA12, {0x2A105}},
{0x2FA13, {0x2A20E}}, {0x2FA14, {0x2A291}}, {0x2FA15, {0x9EBB}}, {0x2FA16, {0x4D56}}, {0x2FA17, {0x9EF9}}, {0x2FA18, {0x9EFE}}, {0x2FA19, {0x9F05}}, {0x2FA1A, {0x9F0F}}, {0x2FA1B, {0x9F16}},
{0x2FA1D, {0x2A600}},
static const std::multimap<uint32_t, uint32_t> nfd_map = {
{0xC0, 0x41}, {0xC0, 0x300}, {0xC1, 0x41}, {0xC1, 0x301}, {0xC2, 0x41}, {0xC2, 0x302}, {0xC3, 0x41}, {0xC3, 0x303}, {0xC4, 0x41}, {0xC4, 0x308}, {0xC5, 0x41}, {0xC5, 0x30A}, {0xC7, 0x43},
{0xC7, 0x327}, {0xC8, 0x45}, {0xC8, 0x300}, {0xC9, 0x45}, {0xC9, 0x301}, {0xCA, 0x45}, {0xCA, 0x302}, {0xCB, 0x45}, {0xCB, 0x308}, {0xCC, 0x49}, {0xCC, 0x300}, {0xCD, 0x49}, {0xCD, 0x301},
{0xCE, 0x49}, {0xCE, 0x302}, {0xCF, 0x49}, {0xCF, 0x308}, {0xD1, 0x4E}, {0xD1, 0x303}, {0xD2, 0x4F}, {0xD2, 0x300}, {0xD3, 0x4F}, {0xD3, 0x301}, {0xD4, 0x4F}, {0xD4, 0x302}, {0xD5, 0x4F},
{0xD5, 0x303}, {0xD6, 0x4F}, {0xD6, 0x308}, {0xD9, 0x55}, {0xD9, 0x300}, {0xDA, 0x55}, {0xDA, 0x301}, {0xDB, 0x55}, {0xDB, 0x302}, {0xDC, 0x55}, {0xDC, 0x308}, {0xDD, 0x59}, {0xDD, 0x301},
{0xE0, 0x61}, {0xE0, 0x300}, {0xE1, 0x61}, {0xE1, 0x301}, {0xE2, 0x61}, {0xE2, 0x302}, {0xE3, 0x61}, {0xE3, 0x303}, {0xE4, 0x61}, {0xE4, 0x308}, {0xE5, 0x61}, {0xE5, 0x30A}, {0xE7, 0x63},
{0xE7, 0x327}, {0xE8, 0x65}, {0xE8, 0x300}, {0xE9, 0x65}, {0xE9, 0x301}, {0xEA, 0x65}, {0xEA, 0x302}, {0xEB, 0x65}, {0xEB, 0x308}, {0xEC, 0x69}, {0xEC, 0x300}, {0xED, 0x69}, {0xED, 0x301},
{0xEE, 0x69}, {0xEE, 0x302}, {0xEF, 0x69}, {0xEF, 0x308}, {0xF1, 0x6E}, {0xF1, 0x303}, {0xF2, 0x6F}, {0xF2, 0x300}, {0xF3, 0x6F}, {0xF3, 0x301}, {0xF4, 0x6F}, {0xF4, 0x302}, {0xF5, 0x6F},
{0xF5, 0x303}, {0xF6, 0x6F}, {0xF6, 0x308}, {0xF9, 0x75}, {0xF9, 0x300}, {0xFA, 0x75}, {0xFA, 0x301}, {0xFB, 0x75}, {0xFB, 0x302}, {0xFC, 0x75}, {0xFC, 0x308}, {0xFD, 0x79}, {0xFD, 0x301},
{0xFF, 0x79}, {0xFF, 0x308}, {0x100, 0x41}, {0x100, 0x304}, {0x101, 0x61}, {0x101, 0x304}, {0x102, 0x41}, {0x102, 0x306}, {0x103, 0x61}, {0x103, 0x306}, {0x104, 0x41}, {0x104, 0x328}, {0x105, 0x61},
{0x105, 0x328}, {0x106, 0x43}, {0x106, 0x301}, {0x107, 0x63}, {0x107, 0x301}, {0x108, 0x43}, {0x108, 0x302}, {0x109, 0x63}, {0x109, 0x302}, {0x10A, 0x43}, {0x10A, 0x307}, {0x10B, 0x63},
{0x10B, 0x307}, {0x10C, 0x43}, {0x10C, 0x30C}, {0x10D, 0x63}, {0x10D, 0x30C}, {0x10E, 0x44}, {0x10E, 0x30C}, {0x10F, 0x64}, {0x10F, 0x30C}, {0x112, 0x45}, {0x112, 0x304}, {0x113, 0x65},
{0x113, 0x304}, {0x114, 0x45}, {0x114, 0x306}, {0x115, 0x65}, {0x115, 0x306}, {0x116, 0x45}, {0x116, 0x307}, {0x117, 0x65}, {0x117, 0x307}, {0x118, 0x45}, {0x118, 0x328}, {0x119, 0x65},
{0x119, 0x328}, {0x11A, 0x45}, {0x11A, 0x30C}, {0x11B, 0x65}, {0x11B, 0x30C}, {0x11C, 0x47}, {0x11C, 0x302}, {0x11D, 0x67}, {0x11D, 0x302}, {0x11E, 0x47}, {0x11E, 0x306}, {0x11F, 0x67},
{0x11F, 0x306}, {0x120, 0x47}, {0x120, 0x307}, {0x121, 0x67}, {0x121, 0x307}, {0x122, 0x47}, {0x122, 0x327}, {0x123, 0x67}, {0x123, 0x327}, {0x124, 0x48}, {0x124, 0x302}, {0x125, 0x68},
{0x125, 0x302}, {0x128, 0x49}, {0x128, 0x303}, {0x129, 0x69}, {0x129, 0x303}, {0x12A, 0x49}, {0x12A, 0x304}, {0x12B, 0x69}, {0x12B, 0x304}, {0x12C, 0x49}, {0x12C, 0x306}, {0x12D, 0x69},
{0x12D, 0x306}, {0x12E, 0x49}, {0x12E, 0x328}, {0x12F, 0x69}, {0x12F, 0x328}, {0x130, 0x49}, {0x130, 0x307}, {0x134, 0x4A}, {0x134, 0x302}, {0x135, 0x6A}, {0x135, 0x302}, {0x136, 0x4B},
{0x136, 0x327}, {0x137, 0x6B}, {0x137, 0x327}, {0x139, 0x4C}, {0x139, 0x301}, {0x13A, 0x6C}, {0x13A, 0x301}, {0x13B, 0x4C}, {0x13B, 0x327}, {0x13C, 0x6C}, {0x13C, 0x327}, {0x13D, 0x4C},
{0x13D, 0x30C}, {0x13E, 0x6C}, {0x13E, 0x30C}, {0x143, 0x4E}, {0x143, 0x301}, {0x144, 0x6E}, {0x144, 0x301}, {0x145, 0x4E}, {0x145, 0x327}, {0x146, 0x6E}, {0x146, 0x327}, {0x147, 0x4E},
{0x147, 0x30C}, {0x148, 0x6E}, {0x148, 0x30C}, {0x14C, 0x4F}, {0x14C, 0x304}, {0x14D, 0x6F}, {0x14D, 0x304}, {0x14E, 0x4F}, {0x14E, 0x306}, {0x14F, 0x6F}, {0x14F, 0x306}, {0x150, 0x4F},
{0x150, 0x30B}, {0x151, 0x6F}, {0x151, 0x30B}, {0x154, 0x52}, {0x154, 0x301}, {0x155, 0x72}, {0x155, 0x301}, {0x156, 0x52}, {0x156, 0x327}, {0x157, 0x72}, {0x157, 0x327}, {0x158, 0x52},
{0x158, 0x30C}, {0x159, 0x72}, {0x159, 0x30C}, {0x15A, 0x53}, {0x15A, 0x301}, {0x15B, 0x73}, {0x15B, 0x301}, {0x15C, 0x53}, {0x15C, 0x302}, {0x15D, 0x73}, {0x15D, 0x302}, {0x15E, 0x53},
{0x15E, 0x327}, {0x15F, 0x73}, {0x15F, 0x327}, {0x160, 0x53}, {0x160, 0x30C}, {0x161, 0x73}, {0x161, 0x30C}, {0x162, 0x54}, {0x162, 0x327}, {0x163, 0x74}, {0x163, 0x327}, {0x164, 0x54},
{0x164, 0x30C}, {0x165, 0x74}, {0x165, 0x30C}, {0x168, 0x55}, {0x168, 0x303}, {0x169, 0x75}, {0x169, 0x303}, {0x16A, 0x55}, {0x16A, 0x304}, {0x16B, 0x75}, {0x16B, 0x304}, {0x16C, 0x55},
{0x16C, 0x306}, {0x16D, 0x75}, {0x16D, 0x306}, {0x16E, 0x55}, {0x16E, 0x30A}, {0x16F, 0x75}, {0x16F, 0x30A}, {0x170, 0x55}, {0x170, 0x30B}, {0x171, 0x75}, {0x171, 0x30B}, {0x172, 0x55},
{0x172, 0x328}, {0x173, 0x75}, {0x173, 0x328}, {0x174, 0x57}, {0x174, 0x302}, {0x175, 0x77}, {0x175, 0x302}, {0x176, 0x59}, {0x176, 0x302}, {0x177, 0x79}, {0x177, 0x302}, {0x178, 0x59},
{0x178, 0x308}, {0x179, 0x5A}, {0x179, 0x301}, {0x17A, 0x7A}, {0x17A, 0x301}, {0x17B, 0x5A}, {0x17B, 0x307}, {0x17C, 0x7A}, {0x17C, 0x307}, {0x17D, 0x5A}, {0x17D, 0x30C}, {0x17E, 0x7A},
{0x17E, 0x30C}, {0x1A0, 0x4F}, {0x1A0, 0x31B}, {0x1A1, 0x6F}, {0x1A1, 0x31B}, {0x1AF, 0x55}, {0x1AF, 0x31B}, {0x1B0, 0x75}, {0x1B0, 0x31B}, {0x1CD, 0x41}, {0x1CD, 0x30C}, {0x1CE, 0x61},
{0x1CE, 0x30C}, {0x1CF, 0x49}, {0x1CF, 0x30C}, {0x1D0, 0x69}, {0x1D0, 0x30C}, {0x1D1, 0x4F}, {0x1D1, 0x30C}, {0x1D2, 0x6F}, {0x1D2, 0x30C}, {0x1D3, 0x55}, {0x1D3, 0x30C}, {0x1D4, 0x75},
{0x1D4, 0x30C}, {0x1D5, 0x55}, {0x1D5, 0x308}, {0x1D5, 0x304}, {0x1D6, 0x75}, {0x1D6, 0x308}, {0x1D6, 0x304}, {0x1D7, 0x55}, {0x1D7, 0x308}, {0x1D7, 0x301}, {0x1D8, 0x75}, {0x1D8, 0x308},
{0x1D8, 0x301}, {0x1D9, 0x55}, {0x1D9, 0x308}, {0x1D9, 0x30C}, {0x1DA, 0x75}, {0x1DA, 0x308}, {0x1DA, 0x30C}, {0x1DB, 0x55}, {0x1DB, 0x308}, {0x1DB, 0x300}, {0x1DC, 0x75}, {0x1DC, 0x308},
{0x1DC, 0x300}, {0x1DE, 0x41}, {0x1DE, 0x308}, {0x1DE, 0x304}, {0x1DF, 0x61}, {0x1DF, 0x308}, {0x1DF, 0x304}, {0x1E0, 0x41}, {0x1E0, 0x307}, {0x1E0, 0x304}, {0x1E1, 0x61}, {0x1E1, 0x307},
{0x1E1, 0x304}, {0x1E2, 0xC6}, {0x1E2, 0x304}, {0x1E3, 0xE6}, {0x1E3, 0x304}, {0x1E6, 0x47}, {0x1E6, 0x30C}, {0x1E7, 0x67}, {0x1E7, 0x30C}, {0x1E8, 0x4B}, {0x1E8, 0x30C}, {0x1E9, 0x6B},
{0x1E9, 0x30C}, {0x1EA, 0x4F}, {0x1EA, 0x328}, {0x1EB, 0x6F}, {0x1EB, 0x328}, {0x1EC, 0x4F}, {0x1EC, 0x328}, {0x1EC, 0x304}, {0x1ED, 0x6F}, {0x1ED, 0x328}, {0x1ED, 0x304}, {0x1EE, 0x1B7},
{0x1EE, 0x30C}, {0x1EF, 0x292}, {0x1EF, 0x30C}, {0x1F0, 0x6A}, {0x1F0, 0x30C}, {0x1F4, 0x47}, {0x1F4, 0x301}, {0x1F5, 0x67}, {0x1F5, 0x301}, {0x1F8, 0x4E}, {0x1F8, 0x300}, {0x1F9, 0x6E},
{0x1F9, 0x300}, {0x1FA, 0x41}, {0x1FA, 0x30A}, {0x1FA, 0x301}, {0x1FB, 0x61}, {0x1FB, 0x30A}, {0x1FB, 0x301}, {0x1FC, 0xC6}, {0x1FC, 0x301}, {0x1FD, 0xE6}, {0x1FD, 0x301}, {0x1FE, 0xD8},
{0x1FE, 0x301}, {0x1FF, 0xF8}, {0x1FF, 0x301}, {0x200, 0x41}, {0x200, 0x30F}, {0x201, 0x61}, {0x201, 0x30F}, {0x202, 0x41}, {0x202, 0x311}, {0x203, 0x61}, {0x203, 0x311}, {0x204, 0x45},
{0x204, 0x30F}, {0x205, 0x65}, {0x205, 0x30F}, {0x206, 0x45}, {0x206, 0x311}, {0x207, 0x65}, {0x207, 0x311}, {0x208, 0x49}, {0x208, 0x30F}, {0x209, 0x69}, {0x209, 0x30F}, {0x20A, 0x49},
{0x20A, 0x311}, {0x20B, 0x69}, {0x20B, 0x311}, {0x20C, 0x4F}, {0x20C, 0x30F}, {0x20D, 0x6F}, {0x20D, 0x30F}, {0x20E, 0x4F}, {0x20E, 0x311}, {0x20F, 0x6F}, {0x20F, 0x311}, {0x210, 0x52},
{0x210, 0x30F}, {0x211, 0x72}, {0x211, 0x30F}, {0x212, 0x52}, {0x212, 0x311}, {0x213, 0x72}, {0x213, 0x311}, {0x214, 0x55}, {0x214, 0x30F}, {0x215, 0x75}, {0x215, 0x30F}, {0x216, 0x55},
{0x216, 0x311}, {0x217, 0x75}, {0x217, 0x311}, {0x218, 0x53}, {0x218, 0x326}, {0x219, 0x73}, {0x219, 0x326}, {0x21A, 0x54}, {0x21A, 0x326}, {0x21B, 0x74}, {0x21B, 0x326}, {0x21E, 0x48},
{0x21E, 0x30C}, {0x21F, 0x68}, {0x21F, 0x30C}, {0x226, 0x41}, {0x226, 0x307}, {0x227, 0x61}, {0x227, 0x307}, {0x228, 0x45}, {0x228, 0x327}, {0x229, 0x65}, {0x229, 0x327}, {0x22A, 0x4F},
{0x22A, 0x308}, {0x22A, 0x304}, {0x22B, 0x6F}, {0x22B, 0x308}, {0x22B, 0x304}, {0x22C, 0x4F}, {0x22C, 0x303}, {0x22C, 0x304}, {0x22D, 0x6F}, {0x22D, 0x303}, {0x22D, 0x304}, {0x22E, 0x4F},
{0x22E, 0x307}, {0x22F, 0x6F}, {0x22F, 0x307}, {0x230, 0x4F}, {0x230, 0x307}, {0x230, 0x304}, {0x231, 0x6F}, {0x231, 0x307}, {0x231, 0x304}, {0x232, 0x59}, {0x232, 0x304}, {0x233, 0x79},
{0x233, 0x304}, {0x340, 0x300}, {0x341, 0x301}, {0x343, 0x313}, {0x344, 0x308}, {0x344, 0x301}, {0x374, 0x2B9}, {0x37E, 0x3B}, {0x385, 0xA8}, {0x385, 0x301}, {0x386, 0x391}, {0x386, 0x301},
{0x387, 0xB7}, {0x388, 0x395}, {0x388, 0x301}, {0x389, 0x397}, {0x389, 0x301}, {0x38A, 0x399}, {0x38A, 0x301}, {0x38C, 0x39F}, {0x38C, 0x301}, {0x38E, 0x3A5}, {0x38E, 0x301}, {0x38F, 0x3A9},
{0x38F, 0x301}, {0x390, 0x3B9}, {0x390, 0x308}, {0x390, 0x301}, {0x3AA, 0x399}, {0x3AA, 0x308}, {0x3AB, 0x3A5}, {0x3AB, 0x308}, {0x3AC, 0x3B1}, {0x3AC, 0x301}, {0x3AD, 0x3B5}, {0x3AD, 0x301},
{0x3AE, 0x3B7}, {0x3AE, 0x301}, {0x3AF, 0x3B9}, {0x3AF, 0x301}, {0x3B0, 0x3C5}, {0x3B0, 0x308}, {0x3B0, 0x301}, {0x3CA, 0x3B9}, {0x3CA, 0x308}, {0x3CB, 0x3C5}, {0x3CB, 0x308}, {0x3CC, 0x3BF},
{0x3CC, 0x301}, {0x3CD, 0x3C5}, {0x3CD, 0x301}, {0x3CE, 0x3C9}, {0x3CE, 0x301}, {0x3D3, 0x3D2}, {0x3D3, 0x301}, {0x3D4, 0x3D2}, {0x3D4, 0x308}, {0x400, 0x415}, {0x400, 0x300}, {0x401, 0x415},
{0x401, 0x308}, {0x403, 0x413}, {0x403, 0x301}, {0x407, 0x406}, {0x407, 0x308}, {0x40C, 0x41A}, {0x40C, 0x301}, {0x40D, 0x418}, {0x40D, 0x300}, {0x40E, 0x423}, {0x40E, 0x306}, {0x419, 0x418},
{0x419, 0x306}, {0x439, 0x438}, {0x439, 0x306}, {0x450, 0x435}, {0x450, 0x300}, {0x451, 0x435}, {0x451, 0x308}, {0x453, 0x433}, {0x453, 0x301}, {0x457, 0x456}, {0x457, 0x308}, {0x45C, 0x43A},
{0x45C, 0x301}, {0x45D, 0x438}, {0x45D, 0x300}, {0x45E, 0x443}, {0x45E, 0x306}, {0x476, 0x474}, {0x476, 0x30F}, {0x477, 0x475}, {0x477, 0x30F}, {0x4C1, 0x416}, {0x4C1, 0x306}, {0x4C2, 0x436},
{0x4C2, 0x306}, {0x4D0, 0x410}, {0x4D0, 0x306}, {0x4D1, 0x430}, {0x4D1, 0x306}, {0x4D2, 0x410}, {0x4D2, 0x308}, {0x4D3, 0x430}, {0x4D3, 0x308}, {0x4D6, 0x415}, {0x4D6, 0x306}, {0x4D7, 0x435},
{0x4D7, 0x306}, {0x4DA, 0x4D8}, {0x4DA, 0x308}, {0x4DB, 0x4D9}, {0x4DB, 0x308}, {0x4DC, 0x416}, {0x4DC, 0x308}, {0x4DD, 0x436}, {0x4DD, 0x308}, {0x4DE, 0x417}, {0x4DE, 0x308}, {0x4DF, 0x437},
{0x4DF, 0x308}, {0x4E2, 0x418}, {0x4E2, 0x304}, {0x4E3, 0x438}, {0x4E3, 0x304}, {0x4E4, 0x418}, {0x4E4, 0x308}, {0x4E5, 0x438}, {0x4E5, 0x308}, {0x4E6, 0x41E}, {0x4E6, 0x308}, {0x4E7, 0x43E},
{0x4E7, 0x308}, {0x4EA, 0x4E8}, {0x4EA, 0x308}, {0x4EB, 0x4E9}, {0x4EB, 0x308}, {0x4EC, 0x42D}, {0x4EC, 0x308}, {0x4ED, 0x44D}, {0x4ED, 0x308}, {0x4EE, 0x423}, {0x4EE, 0x304}, {0x4EF, 0x443},
{0x4EF, 0x304}, {0x4F0, 0x423}, {0x4F0, 0x308}, {0x4F1, 0x443}, {0x4F1, 0x308}, {0x4F2, 0x423}, {0x4F2, 0x30B}, {0x4F3, 0x443}, {0x4F3, 0x30B}, {0x4F4, 0x427}, {0x4F4, 0x308}, {0x4F5, 0x447},
{0x4F5, 0x308}, {0x4F8, 0x42B}, {0x4F8, 0x308}, {0x4F9, 0x44B}, {0x4F9, 0x308}, {0x622, 0x627}, {0x622, 0x653}, {0x623, 0x627}, {0x623, 0x654}, {0x624, 0x648}, {0x624, 0x654}, {0x625, 0x627},
{0x625, 0x655}, {0x626, 0x64A}, {0x626, 0x654}, {0x6C0, 0x6D5}, {0x6C0, 0x654}, {0x6C2, 0x6C1}, {0x6C2, 0x654}, {0x6D3, 0x6D2}, {0x6D3, 0x654}, {0x929, 0x928}, {0x929, 0x93C}, {0x931, 0x930},
{0x931, 0x93C}, {0x934, 0x933}, {0x934, 0x93C}, {0x958, 0x915}, {0x958, 0x93C}, {0x959, 0x916}, {0x959, 0x93C}, {0x95A, 0x917}, {0x95A, 0x93C}, {0x95B, 0x91C}, {0x95B, 0x93C}, {0x95C, 0x921},
{0x95C, 0x93C}, {0x95D, 0x922}, {0x95D, 0x93C}, {0x95E, 0x92B}, {0x95E, 0x93C}, {0x95F, 0x92F}, {0x95F, 0x93C}, {0x9CB, 0x9C7}, {0x9CB, 0x9BE}, {0x9CC, 0x9C7}, {0x9CC, 0x9D7}, {0x9DC, 0x9A1},
{0x9DC, 0x9BC}, {0x9DD, 0x9A2}, {0x9DD, 0x9BC}, {0x9DF, 0x9AF}, {0x9DF, 0x9BC}, {0xA33, 0xA32}, {0xA33, 0xA3C}, {0xA36, 0xA38}, {0xA36, 0xA3C}, {0xA59, 0xA16}, {0xA59, 0xA3C}, {0xA5A, 0xA17},
{0xA5A, 0xA3C}, {0xA5B, 0xA1C}, {0xA5B, 0xA3C}, {0xA5E, 0xA2B}, {0xA5E, 0xA3C}, {0xB48, 0xB47}, {0xB48, 0xB56}, {0xB4B, 0xB47}, {0xB4B, 0xB3E}, {0xB4C, 0xB47}, {0xB4C, 0xB57}, {0xB5C, 0xB21},
{0xB5C, 0xB3C}, {0xB5D, 0xB22}, {0xB5D, 0xB3C}, {0xB94, 0xB92}, {0xB94, 0xBD7}, {0xBCA, 0xBC6}, {0xBCA, 0xBBE}, {0xBCB, 0xBC7}, {0xBCB, 0xBBE}, {0xBCC, 0xBC6}, {0xBCC, 0xBD7}, {0xC48, 0xC46},
{0xC48, 0xC56}, {0xCC0, 0xCBF}, {0xCC0, 0xCD5}, {0xCC7, 0xCC6}, {0xCC7, 0xCD5}, {0xCC8, 0xCC6}, {0xCC8, 0xCD6}, {0xCCA, 0xCC6}, {0xCCA, 0xCC2}, {0xCCB, 0xCC6}, {0xCCB, 0xCC2}, {0xCCB, 0xCD5},
{0xD4A, 0xD46}, {0xD4A, 0xD3E}, {0xD4B, 0xD47}, {0xD4B, 0xD3E}, {0xD4C, 0xD46}, {0xD4C, 0xD57}, {0xDDA, 0xDD9}, {0xDDA, 0xDCA}, {0xDDC, 0xDD9}, {0xDDC, 0xDCF}, {0xDDD, 0xDD9}, {0xDDD, 0xDCF},
{0xDDD, 0xDCA}, {0xDDE, 0xDD9}, {0xDDE, 0xDDF}, {0xF43, 0xF42}, {0xF43, 0xFB7}, {0xF4D, 0xF4C}, {0xF4D, 0xFB7}, {0xF52, 0xF51}, {0xF52, 0xFB7}, {0xF57, 0xF56}, {0xF57, 0xFB7}, {0xF5C, 0xF5B},
{0xF5C, 0xFB7}, {0xF69, 0xF40}, {0xF69, 0xFB5}, {0xF73, 0xF71}, {0xF73, 0xF72}, {0xF75, 0xF71}, {0xF75, 0xF74}, {0xF76, 0xFB2}, {0xF76, 0xF80}, {0xF78, 0xFB3}, {0xF78, 0xF80}, {0xF81, 0xF71},
{0xF81, 0xF80}, {0xF93, 0xF92}, {0xF93, 0xFB7}, {0xF9D, 0xF9C}, {0xF9D, 0xFB7}, {0xFA2, 0xFA1}, {0xFA2, 0xFB7}, {0xFA7, 0xFA6}, {0xFA7, 0xFB7}, {0xFAC, 0xFAB}, {0xFAC, 0xFB7}, {0xFB9, 0xF90},
{0xFB9, 0xFB5}, {0x1026, 0x1025}, {0x1026, 0x102E}, {0x1B06, 0x1B05}, {0x1B06, 0x1B35}, {0x1B08, 0x1B07}, {0x1B08, 0x1B35}, {0x1B0A, 0x1B09}, {0x1B0A, 0x1B35}, {0x1B0C, 0x1B0B}, {0x1B0C, 0x1B35},
{0x1B0E, 0x1B0D}, {0x1B0E, 0x1B35}, {0x1B12, 0x1B11}, {0x1B12, 0x1B35}, {0x1B3B, 0x1B3A}, {0x1B3B, 0x1B35}, {0x1B3D, 0x1B3C}, {0x1B3D, 0x1B35}, {0x1B40, 0x1B3E}, {0x1B40, 0x1B35}, {0x1B41, 0x1B3F},
{0x1B41, 0x1B35}, {0x1B43, 0x1B42}, {0x1B43, 0x1B35}, {0x1E00, 0x41}, {0x1E00, 0x325}, {0x1E01, 0x61}, {0x1E01, 0x325}, {0x1E02, 0x42}, {0x1E02, 0x307}, {0x1E03, 0x62}, {0x1E03, 0x307},
{0x1E04, 0x42}, {0x1E04, 0x323}, {0x1E05, 0x62}, {0x1E05, 0x323}, {0x1E06, 0x42}, {0x1E06, 0x331}, {0x1E07, 0x62}, {0x1E07, 0x331}, {0x1E08, 0x43}, {0x1E08, 0x327}, {0x1E08, 0x301}, {0x1E09, 0x63},
{0x1E09, 0x327}, {0x1E09, 0x301}, {0x1E0A, 0x44}, {0x1E0A, 0x307}, {0x1E0B, 0x64}, {0x1E0B, 0x307}, {0x1E0C, 0x44}, {0x1E0C, 0x323}, {0x1E0D, 0x64}, {0x1E0D, 0x323}, {0x1E0E, 0x44}, {0x1E0E, 0x331},
{0x1E0F, 0x64}, {0x1E0F, 0x331}, {0x1E10, 0x44}, {0x1E10, 0x327}, {0x1E11, 0x64}, {0x1E11, 0x327}, {0x1E12, 0x44}, {0x1E12, 0x32D}, {0x1E13, 0x64}, {0x1E13, 0x32D}, {0x1E14, 0x45}, {0x1E14, 0x304},
{0x1E14, 0x300}, {0x1E15, 0x65}, {0x1E15, 0x304}, {0x1E15, 0x300}, {0x1E16, 0x45}, {0x1E16, 0x304}, {0x1E16, 0x301}, {0x1E17, 0x65}, {0x1E17, 0x304}, {0x1E17, 0x301}, {0x1E18, 0x45}, {0x1E18, 0x32D},
{0x1E19, 0x65}, {0x1E19, 0x32D}, {0x1E1A, 0x45}, {0x1E1A, 0x330}, {0x1E1B, 0x65}, {0x1E1B, 0x330}, {0x1E1C, 0x45}, {0x1E1C, 0x327}, {0x1E1C, 0x306}, {0x1E1D, 0x65}, {0x1E1D, 0x327}, {0x1E1D, 0x306},
{0x1E1E, 0x46}, {0x1E1E, 0x307}, {0x1E1F, 0x66}, {0x1E1F, 0x307}, {0x1E20, 0x47}, {0x1E20, 0x304}, {0x1E21, 0x67}, {0x1E21, 0x304}, {0x1E22, 0x48}, {0x1E22, 0x307}, {0x1E23, 0x68}, {0x1E23, 0x307},
{0x1E24, 0x48}, {0x1E24, 0x323}, {0x1E25, 0x68}, {0x1E25, 0x323}, {0x1E26, 0x48}, {0x1E26, 0x308}, {0x1E27, 0x68}, {0x1E27, 0x308}, {0x1E28, 0x48}, {0x1E28, 0x327}, {0x1E29, 0x68}, {0x1E29, 0x327},
{0x1E2A, 0x48}, {0x1E2A, 0x32E}, {0x1E2B, 0x68}, {0x1E2B, 0x32E}, {0x1E2C, 0x49}, {0x1E2C, 0x330}, {0x1E2D, 0x69}, {0x1E2D, 0x330}, {0x1E2E, 0x49}, {0x1E2E, 0x308}, {0x1E2E, 0x301}, {0x1E2F, 0x69},
{0x1E2F, 0x308}, {0x1E2F, 0x301}, {0x1E30, 0x4B}, {0x1E30, 0x301}, {0x1E31, 0x6B}, {0x1E31, 0x301}, {0x1E32, 0x4B}, {0x1E32, 0x323}, {0x1E33, 0x6B}, {0x1E33, 0x323}, {0x1E34, 0x4B}, {0x1E34, 0x331},
{0x1E35, 0x6B}, {0x1E35, 0x331}, {0x1E36, 0x4C}, {0x1E36, 0x323}, {0x1E37, 0x6C}, {0x1E37, 0x323}, {0x1E38, 0x4C}, {0x1E38, 0x323}, {0x1E38, 0x304}, {0x1E39, 0x6C}, {0x1E39, 0x323}, {0x1E39, 0x304},
{0x1E3A, 0x4C}, {0x1E3A, 0x331}, {0x1E3B, 0x6C}, {0x1E3B, 0x331}, {0x1E3C, 0x4C}, {0x1E3C, 0x32D}, {0x1E3D, 0x6C}, {0x1E3D, 0x32D}, {0x1E3E, 0x4D}, {0x1E3E, 0x301}, {0x1E3F, 0x6D}, {0x1E3F, 0x301},
{0x1E40, 0x4D}, {0x1E40, 0x307}, {0x1E41, 0x6D}, {0x1E41, 0x307}, {0x1E42, 0x4D}, {0x1E42, 0x323}, {0x1E43, 0x6D}, {0x1E43, 0x323}, {0x1E44, 0x4E}, {0x1E44, 0x307}, {0x1E45, 0x6E}, {0x1E45, 0x307},
{0x1E46, 0x4E}, {0x1E46, 0x323}, {0x1E47, 0x6E}, {0x1E47, 0x323}, {0x1E48, 0x4E}, {0x1E48, 0x331}, {0x1E49, 0x6E}, {0x1E49, 0x331}, {0x1E4A, 0x4E}, {0x1E4A, 0x32D}, {0x1E4B, 0x6E}, {0x1E4B, 0x32D},
{0x1E4C, 0x4F}, {0x1E4C, 0x303}, {0x1E4C, 0x301}, {0x1E4D, 0x6F}, {0x1E4D, 0x303}, {0x1E4D, 0x301}, {0x1E4E, 0x4F}, {0x1E4E, 0x303}, {0x1E4E, 0x308}, {0x1E4F, 0x6F}, {0x1E4F, 0x303}, {0x1E4F, 0x308},
{0x1E50, 0x4F}, {0x1E50, 0x304}, {0x1E50, 0x300}, {0x1E51, 0x6F}, {0x1E51, 0x304}, {0x1E51, 0x300}, {0x1E52, 0x4F}, {0x1E52, 0x304}, {0x1E52, 0x301}, {0x1E53, 0x6F}, {0x1E53, 0x304}, {0x1E53, 0x301},
{0x1E54, 0x50}, {0x1E54, 0x301}, {0x1E55, 0x70}, {0x1E55, 0x301}, {0x1E56, 0x50}, {0x1E56, 0x307}, {0x1E57, 0x70}, {0x1E57, 0x307}, {0x1E58, 0x52}, {0x1E58, 0x307}, {0x1E59, 0x72}, {0x1E59, 0x307},
{0x1E5A, 0x52}, {0x1E5A, 0x323}, {0x1E5B, 0x72}, {0x1E5B, 0x323}, {0x1E5C, 0x52}, {0x1E5C, 0x323}, {0x1E5C, 0x304}, {0x1E5D, 0x72}, {0x1E5D, 0x323}, {0x1E5D, 0x304}, {0x1E5E, 0x52}, {0x1E5E, 0x331},
{0x1E5F, 0x72}, {0x1E5F, 0x331}, {0x1E60, 0x53}, {0x1E60, 0x307}, {0x1E61, 0x73}, {0x1E61, 0x307}, {0x1E62, 0x53}, {0x1E62, 0x323}, {0x1E63, 0x73}, {0x1E63, 0x323}, {0x1E64, 0x53}, {0x1E64, 0x301},
{0x1E64, 0x307}, {0x1E65, 0x73}, {0x1E65, 0x301}, {0x1E65, 0x307}, {0x1E66, 0x53}, {0x1E66, 0x30C}, {0x1E66, 0x307}, {0x1E67, 0x73}, {0x1E67, 0x30C}, {0x1E67, 0x307}, {0x1E68, 0x53}, {0x1E68, 0x323},
{0x1E68, 0x307}, {0x1E69, 0x73}, {0x1E69, 0x323}, {0x1E69, 0x307}, {0x1E6A, 0x54}, {0x1E6A, 0x307}, {0x1E6B, 0x74}, {0x1E6B, 0x307}, {0x1E6C, 0x54}, {0x1E6C, 0x323}, {0x1E6D, 0x74}, {0x1E6D, 0x323},
{0x1E6E, 0x54}, {0x1E6E, 0x331}, {0x1E6F, 0x74}, {0x1E6F, 0x331}, {0x1E70, 0x54}, {0x1E70, 0x32D}, {0x1E71, 0x74}, {0x1E71, 0x32D}, {0x1E72, 0x55}, {0x1E72, 0x324}, {0x1E73, 0x75}, {0x1E73, 0x324},
{0x1E74, 0x55}, {0x1E74, 0x330}, {0x1E75, 0x75}, {0x1E75, 0x330}, {0x1E76, 0x55}, {0x1E76, 0x32D}, {0x1E77, 0x75}, {0x1E77, 0x32D}, {0x1E78, 0x55}, {0x1E78, 0x303}, {0x1E78, 0x301}, {0x1E79, 0x75},
{0x1E79, 0x303}, {0x1E79, 0x301}, {0x1E7A, 0x55}, {0x1E7A, 0x304}, {0x1E7A, 0x308}, {0x1E7B, 0x75}, {0x1E7B, 0x304}, {0x1E7B, 0x308}, {0x1E7C, 0x56}, {0x1E7C, 0x303}, {0x1E7D, 0x76}, {0x1E7D, 0x303},
{0x1E7E, 0x56}, {0x1E7E, 0x323}, {0x1E7F, 0x76}, {0x1E7F, 0x323}, {0x1E80, 0x57}, {0x1E80, 0x300}, {0x1E81, 0x77}, {0x1E81, 0x300}, {0x1E82, 0x57}, {0x1E82, 0x301}, {0x1E83, 0x77}, {0x1E83, 0x301},
{0x1E84, 0x57}, {0x1E84, 0x308}, {0x1E85, 0x77}, {0x1E85, 0x308}, {0x1E86, 0x57}, {0x1E86, 0x307}, {0x1E87, 0x77}, {0x1E87, 0x307}, {0x1E88, 0x57}, {0x1E88, 0x323}, {0x1E89, 0x77}, {0x1E89, 0x323},
{0x1E8A, 0x58}, {0x1E8A, 0x307}, {0x1E8B, 0x78}, {0x1E8B, 0x307}, {0x1E8C, 0x58}, {0x1E8C, 0x308}, {0x1E8D, 0x78}, {0x1E8D, 0x308}, {0x1E8E, 0x59}, {0x1E8E, 0x307}, {0x1E8F, 0x79}, {0x1E8F, 0x307},
{0x1E90, 0x5A}, {0x1E90, 0x302}, {0x1E91, 0x7A}, {0x1E91, 0x302}, {0x1E92, 0x5A}, {0x1E92, 0x323}, {0x1E93, 0x7A}, {0x1E93, 0x323}, {0x1E94, 0x5A}, {0x1E94, 0x331}, {0x1E95, 0x7A}, {0x1E95, 0x331},
{0x1E96, 0x68}, {0x1E96, 0x331}, {0x1E97, 0x74}, {0x1E97, 0x308}, {0x1E98, 0x77}, {0x1E98, 0x30A}, {0x1E99, 0x79}, {0x1E99, 0x30A}, {0x1E9B, 0x17F}, {0x1E9B, 0x307}, {0x1EA0, 0x41}, {0x1EA0, 0x323},
{0x1EA1, 0x61}, {0x1EA1, 0x323}, {0x1EA2, 0x41}, {0x1EA2, 0x309}, {0x1EA3, 0x61}, {0x1EA3, 0x309}, {0x1EA4, 0x41}, {0x1EA4, 0x302}, {0x1EA4, 0x301}, {0x1EA5, 0x61}, {0x1EA5, 0x302}, {0x1EA5, 0x301},
{0x1EA6, 0x41}, {0x1EA6, 0x302}, {0x1EA6, 0x300}, {0x1EA7, 0x61}, {0x1EA7, 0x302}, {0x1EA7, 0x300}, {0x1EA8, 0x41}, {0x1EA8, 0x302}, {0x1EA8, 0x309}, {0x1EA9, 0x61}, {0x1EA9, 0x302}, {0x1EA9, 0x309},
{0x1EAA, 0x41}, {0x1EAA, 0x302}, {0x1EAA, 0x303}, {0x1EAB, 0x61}, {0x1EAB, 0x302}, {0x1EAB, 0x303}, {0x1EAC, 0x41}, {0x1EAC, 0x323}, {0x1EAC, 0x302}, {0x1EAD, 0x61}, {0x1EAD, 0x323}, {0x1EAD, 0x302},
{0x1EAE, 0x41}, {0x1EAE, 0x306}, {0x1EAE, 0x301}, {0x1EAF, 0x61}, {0x1EAF, 0x306}, {0x1EAF, 0x301}, {0x1EB0, 0x41}, {0x1EB0, 0x306}, {0x1EB0, 0x300}, {0x1EB1, 0x61}, {0x1EB1, 0x306}, {0x1EB1, 0x300},
{0x1EB2, 0x41}, {0x1EB2, 0x306}, {0x1EB2, 0x309}, {0x1EB3, 0x61}, {0x1EB3, 0x306}, {0x1EB3, 0x309}, {0x1EB4, 0x41}, {0x1EB4, 0x306}, {0x1EB4, 0x303}, {0x1EB5, 0x61}, {0x1EB5, 0x306}, {0x1EB5, 0x303},
{0x1EB6, 0x41}, {0x1EB6, 0x323}, {0x1EB6, 0x306}, {0x1EB7, 0x61}, {0x1EB7, 0x323}, {0x1EB7, 0x306}, {0x1EB8, 0x45}, {0x1EB8, 0x323}, {0x1EB9, 0x65}, {0x1EB9, 0x323}, {0x1EBA, 0x45}, {0x1EBA, 0x309},
{0x1EBB, 0x65}, {0x1EBB, 0x309}, {0x1EBC, 0x45}, {0x1EBC, 0x303}, {0x1EBD, 0x65}, {0x1EBD, 0x303}, {0x1EBE, 0x45}, {0x1EBE, 0x302}, {0x1EBE, 0x301}, {0x1EBF, 0x65}, {0x1EBF, 0x302}, {0x1EBF, 0x301},
{0x1EC0, 0x45}, {0x1EC0, 0x302}, {0x1EC0, 0x300}, {0x1EC1, 0x65}, {0x1EC1, 0x302}, {0x1EC1, 0x300}, {0x1EC2, 0x45}, {0x1EC2, 0x302}, {0x1EC2, 0x309}, {0x1EC3, 0x65}, {0x1EC3, 0x302}, {0x1EC3, 0x309},
{0x1EC4, 0x45}, {0x1EC4, 0x302}, {0x1EC4, 0x303}, {0x1EC5, 0x65}, {0x1EC5, 0x302}, {0x1EC5, 0x303}, {0x1EC6, 0x45}, {0x1EC6, 0x323}, {0x1EC6, 0x302}, {0x1EC7, 0x65}, {0x1EC7, 0x323}, {0x1EC7, 0x302},
{0x1EC8, 0x49}, {0x1EC8, 0x309}, {0x1EC9, 0x69}, {0x1EC9, 0x309}, {0x1ECA, 0x49}, {0x1ECA, 0x323}, {0x1ECB, 0x69}, {0x1ECB, 0x323}, {0x1ECC, 0x4F}, {0x1ECC, 0x323}, {0x1ECD, 0x6F}, {0x1ECD, 0x323},
{0x1ECE, 0x4F}, {0x1ECE, 0x309}, {0x1ECF, 0x6F}, {0x1ECF, 0x309}, {0x1ED0, 0x4F}, {0x1ED0, 0x302}, {0x1ED0, 0x301}, {0x1ED1, 0x6F}, {0x1ED1, 0x302}, {0x1ED1, 0x301}, {0x1ED2, 0x4F}, {0x1ED2, 0x302},
{0x1ED2, 0x300}, {0x1ED3, 0x6F}, {0x1ED3, 0x302}, {0x1ED3, 0x300}, {0x1ED4, 0x4F}, {0x1ED4, 0x302}, {0x1ED4, 0x309}, {0x1ED5, 0x6F}, {0x1ED5, 0x302}, {0x1ED5, 0x309}, {0x1ED6, 0x4F}, {0x1ED6, 0x302},
{0x1ED6, 0x303}, {0x1ED7, 0x6F}, {0x1ED7, 0x302}, {0x1ED7, 0x303}, {0x1ED8, 0x4F}, {0x1ED8, 0x323}, {0x1ED8, 0x302}, {0x1ED9, 0x6F}, {0x1ED9, 0x323}, {0x1ED9, 0x302}, {0x1EDA, 0x4F}, {0x1EDA, 0x31B},
{0x1EDA, 0x301}, {0x1EDB, 0x6F}, {0x1EDB, 0x31B}, {0x1EDB, 0x301}, {0x1EDC, 0x4F}, {0x1EDC, 0x31B}, {0x1EDC, 0x300}, {0x1EDD, 0x6F}, {0x1EDD, 0x31B}, {0x1EDD, 0x300}, {0x1EDE, 0x4F}, {0x1EDE, 0x31B},
{0x1EDE, 0x309}, {0x1EDF, 0x6F}, {0x1EDF, 0x31B}, {0x1EDF, 0x309}, {0x1EE0, 0x4F}, {0x1EE0, 0x31B}, {0x1EE0, 0x303}, {0x1EE1, 0x6F}, {0x1EE1, 0x31B}, {0x1EE1, 0x303}, {0x1EE2, 0x4F}, {0x1EE2, 0x31B},
{0x1EE2, 0x323}, {0x1EE3, 0x6F}, {0x1EE3, 0x31B}, {0x1EE3, 0x323}, {0x1EE4, 0x55}, {0x1EE4, 0x323}, {0x1EE5, 0x75}, {0x1EE5, 0x323}, {0x1EE6, 0x55}, {0x1EE6, 0x309}, {0x1EE7, 0x75}, {0x1EE7, 0x309},
{0x1EE8, 0x55}, {0x1EE8, 0x31B}, {0x1EE8, 0x301}, {0x1EE9, 0x75}, {0x1EE9, 0x31B}, {0x1EE9, 0x301}, {0x1EEA, 0x55}, {0x1EEA, 0x31B}, {0x1EEA, 0x300}, {0x1EEB, 0x75}, {0x1EEB, 0x31B}, {0x1EEB, 0x300},
{0x1EEC, 0x55}, {0x1EEC, 0x31B}, {0x1EEC, 0x309}, {0x1EED, 0x75}, {0x1EED, 0x31B}, {0x1EED, 0x309}, {0x1EEE, 0x55}, {0x1EEE, 0x31B}, {0x1EEE, 0x303}, {0x1EEF, 0x75}, {0x1EEF, 0x31B}, {0x1EEF, 0x303},
{0x1EF0, 0x55}, {0x1EF0, 0x31B}, {0x1EF0, 0x323}, {0x1EF1, 0x75}, {0x1EF1, 0x31B}, {0x1EF1, 0x323}, {0x1EF2, 0x59}, {0x1EF2, 0x300}, {0x1EF3, 0x79}, {0x1EF3, 0x300}, {0x1EF4, 0x59}, {0x1EF4, 0x323},
{0x1EF5, 0x79}, {0x1EF5, 0x323}, {0x1EF6, 0x59}, {0x1EF6, 0x309}, {0x1EF7, 0x79}, {0x1EF7, 0x309}, {0x1EF8, 0x59}, {0x1EF8, 0x303}, {0x1EF9, 0x79}, {0x1EF9, 0x303}, {0x1F00, 0x3B1}, {0x1F00, 0x313},
{0x1F01, 0x3B1}, {0x1F01, 0x314}, {0x1F02, 0x3B1}, {0x1F02, 0x313}, {0x1F02, 0x300}, {0x1F03, 0x3B1}, {0x1F03, 0x314}, {0x1F03, 0x300}, {0x1F04, 0x3B1}, {0x1F04, 0x313}, {0x1F04, 0x301},
{0x1F05, 0x3B1}, {0x1F05, 0x314}, {0x1F05, 0x301}, {0x1F06, 0x3B1}, {0x1F06, 0x313}, {0x1F06, 0x342}, {0x1F07, 0x3B1}, {0x1F07, 0x314}, {0x1F07, 0x342}, {0x1F08, 0x391}, {0x1F08, 0x313},
{0x1F09, 0x391}, {0x1F09, 0x314}, {0x1F0A, 0x391}, {0x1F0A, 0x313}, {0x1F0A, 0x300}, {0x1F0B, 0x391}, {0x1F0B, 0x314}, {0x1F0B, 0x300}, {0x1F0C, 0x391}, {0x1F0C, 0x313}, {0x1F0C, 0x301},
{0x1F0D, 0x391}, {0x1F0D, 0x314}, {0x1F0D, 0x301}, {0x1F0E, 0x391}, {0x1F0E, 0x313}, {0x1F0E, 0x342}, {0x1F0F, 0x391}, {0x1F0F, 0x314}, {0x1F0F, 0x342}, {0x1F10, 0x3B5}, {0x1F10, 0x313},
{0x1F11, 0x3B5}, {0x1F11, 0x314}, {0x1F12, 0x3B5}, {0x1F12, 0x313}, {0x1F12, 0x300}, {0x1F13, 0x3B5}, {0x1F13, 0x314}, {0x1F13, 0x300}, {0x1F14, 0x3B5}, {0x1F14, 0x313}, {0x1F14, 0x301},
{0x1F15, 0x3B5}, {0x1F15, 0x314}, {0x1F15, 0x301}, {0x1F18, 0x395}, {0x1F18, 0x313}, {0x1F19, 0x395}, {0x1F19, 0x314}, {0x1F1A, 0x395}, {0x1F1A, 0x313}, {0x1F1A, 0x300}, {0x1F1B, 0x395},
{0x1F1B, 0x314}, {0x1F1B, 0x300}, {0x1F1C, 0x395}, {0x1F1C, 0x313}, {0x1F1C, 0x301}, {0x1F1D, 0x395}, {0x1F1D, 0x314}, {0x1F1D, 0x301}, {0x1F20, 0x3B7}, {0x1F20, 0x313}, {0x1F21, 0x3B7},
{0x1F21, 0x314}, {0x1F22, 0x3B7}, {0x1F22, 0x313}, {0x1F22, 0x300}, {0x1F23, 0x3B7}, {0x1F23, 0x314}, {0x1F23, 0x300}, {0x1F24, 0x3B7}, {0x1F24, 0x313}, {0x1F24, 0x301}, {0x1F25, 0x3B7},
{0x1F25, 0x314}, {0x1F25, 0x301}, {0x1F26, 0x3B7}, {0x1F26, 0x313}, {0x1F26, 0x342}, {0x1F27, 0x3B7}, {0x1F27, 0x314}, {0x1F27, 0x342}, {0x1F28, 0x397}, {0x1F28, 0x313}, {0x1F29, 0x397},
{0x1F29, 0x314}, {0x1F2A, 0x397}, {0x1F2A, 0x313}, {0x1F2A, 0x300}, {0x1F2B, 0x397}, {0x1F2B, 0x314}, {0x1F2B, 0x300}, {0x1F2C, 0x397}, {0x1F2C, 0x313}, {0x1F2C, 0x301}, {0x1F2D, 0x397},
{0x1F2D, 0x314}, {0x1F2D, 0x301}, {0x1F2E, 0x397}, {0x1F2E, 0x313}, {0x1F2E, 0x342}, {0x1F2F, 0x397}, {0x1F2F, 0x314}, {0x1F2F, 0x342}, {0x1F30, 0x3B9}, {0x1F30, 0x313}, {0x1F31, 0x3B9},
{0x1F31, 0x314}, {0x1F32, 0x3B9}, {0x1F32, 0x313}, {0x1F32, 0x300}, {0x1F33, 0x3B9}, {0x1F33, 0x314}, {0x1F33, 0x300}, {0x1F34, 0x3B9}, {0x1F34, 0x313}, {0x1F34, 0x301}, {0x1F35, 0x3B9},
{0x1F35, 0x314}, {0x1F35, 0x301}, {0x1F36, 0x3B9}, {0x1F36, 0x313}, {0x1F36, 0x342}, {0x1F37, 0x3B9}, {0x1F37, 0x314}, {0x1F37, 0x342}, {0x1F38, 0x399}, {0x1F38, 0x313}, {0x1F39, 0x399},
{0x1F39, 0x314}, {0x1F3A, 0x399}, {0x1F3A, 0x313}, {0x1F3A, 0x300}, {0x1F3B, 0x399}, {0x1F3B, 0x314}, {0x1F3B, 0x300}, {0x1F3C, 0x399}, {0x1F3C, 0x313}, {0x1F3C, 0x301}, {0x1F3D, 0x399},
{0x1F3D, 0x314}, {0x1F3D, 0x301}, {0x1F3E, 0x399}, {0x1F3E, 0x313}, {0x1F3E, 0x342}, {0x1F3F, 0x399}, {0x1F3F, 0x314}, {0x1F3F, 0x342}, {0x1F40, 0x3BF}, {0x1F40, 0x313}, {0x1F41, 0x3BF},
{0x1F41, 0x314}, {0x1F42, 0x3BF}, {0x1F42, 0x313}, {0x1F42, 0x300}, {0x1F43, 0x3BF}, {0x1F43, 0x314}, {0x1F43, 0x300}, {0x1F44, 0x3BF}, {0x1F44, 0x313}, {0x1F44, 0x301}, {0x1F45, 0x3BF},
{0x1F45, 0x314}, {0x1F45, 0x301}, {0x1F48, 0x39F}, {0x1F48, 0x313}, {0x1F49, 0x39F}, {0x1F49, 0x314}, {0x1F4A, 0x39F}, {0x1F4A, 0x313}, {0x1F4A, 0x300}, {0x1F4B, 0x39F}, {0x1F4B, 0x314},
{0x1F4B, 0x300}, {0x1F4C, 0x39F}, {0x1F4C, 0x313}, {0x1F4C, 0x301}, {0x1F4D, 0x39F}, {0x1F4D, 0x314}, {0x1F4D, 0x301}, {0x1F50, 0x3C5}, {0x1F50, 0x313}, {0x1F51, 0x3C5}, {0x1F51, 0x314},
{0x1F52, 0x3C5}, {0x1F52, 0x313}, {0x1F52, 0x300}, {0x1F53, 0x3C5}, {0x1F53, 0x314}, {0x1F53, 0x300}, {0x1F54, 0x3C5}, {0x1F54, 0x313}, {0x1F54, 0x301}, {0x1F55, 0x3C5}, {0x1F55, 0x314},
{0x1F55, 0x301}, {0x1F56, 0x3C5}, {0x1F56, 0x313}, {0x1F56, 0x342}, {0x1F57, 0x3C5}, {0x1F57, 0x314}, {0x1F57, 0x342}, {0x1F59, 0x3A5}, {0x1F59, 0x314}, {0x1F5B, 0x3A5}, {0x1F5B, 0x314},
{0x1F5B, 0x300}, {0x1F5D, 0x3A5}, {0x1F5D, 0x314}, {0x1F5D, 0x301}, {0x1F5F, 0x3A5}, {0x1F5F, 0x314}, {0x1F5F, 0x342}, {0x1F60, 0x3C9}, {0x1F60, 0x313}, {0x1F61, 0x3C9}, {0x1F61, 0x314},
{0x1F62, 0x3C9}, {0x1F62, 0x313}, {0x1F62, 0x300}, {0x1F63, 0x3C9}, {0x1F63, 0x314}, {0x1F63, 0x300}, {0x1F64, 0x3C9}, {0x1F64, 0x313}, {0x1F64, 0x301}, {0x1F65, 0x3C9}, {0x1F65, 0x314},
{0x1F65, 0x301}, {0x1F66, 0x3C9}, {0x1F66, 0x313}, {0x1F66, 0x342}, {0x1F67, 0x3C9}, {0x1F67, 0x314}, {0x1F67, 0x342}, {0x1F68, 0x3A9}, {0x1F68, 0x313}, {0x1F69, 0x3A9}, {0x1F69, 0x314},
{0x1F6A, 0x3A9}, {0x1F6A, 0x313}, {0x1F6A, 0x300}, {0x1F6B, 0x3A9}, {0x1F6B, 0x314}, {0x1F6B, 0x300}, {0x1F6C, 0x3A9}, {0x1F6C, 0x313}, {0x1F6C, 0x301}, {0x1F6D, 0x3A9}, {0x1F6D, 0x314},
{0x1F6D, 0x301}, {0x1F6E, 0x3A9}, {0x1F6E, 0x313}, {0x1F6E, 0x342}, {0x1F6F, 0x3A9}, {0x1F6F, 0x314}, {0x1F6F, 0x342}, {0x1F70, 0x3B1}, {0x1F70, 0x300}, {0x1F71, 0x3B1}, {0x1F71, 0x301},
{0x1F72, 0x3B5}, {0x1F72, 0x300}, {0x1F73, 0x3B5}, {0x1F73, 0x301}, {0x1F74, 0x3B7}, {0x1F74, 0x300}, {0x1F75, 0x3B7}, {0x1F75, 0x301}, {0x1F76, 0x3B9}, {0x1F76, 0x300}, {0x1F77, 0x3B9},
{0x1F77, 0x301}, {0x1F78, 0x3BF}, {0x1F78, 0x300}, {0x1F79, 0x3BF}, {0x1F79, 0x301}, {0x1F7A, 0x3C5}, {0x1F7A, 0x300}, {0x1F7B, 0x3C5}, {0x1F7B, 0x301}, {0x1F7C, 0x3C9}, {0x1F7C, 0x300},
{0x1F7D, 0x3C9}, {0x1F7D, 0x301}, {0x1F80, 0x3B1}, {0x1F80, 0x313}, {0x1F80, 0x345}, {0x1F81, 0x3B1}, {0x1F81, 0x314}, {0x1F81, 0x345}, {0x1F82, 0x3B1}, {0x1F82, 0x313}, {0x1F82, 0x300},
{0x1F82, 0x345}, {0x1F83, 0x3B1}, {0x1F83, 0x314}, {0x1F83, 0x300}, {0x1F83, 0x345}, {0x1F84, 0x3B1}, {0x1F84, 0x313}, {0x1F84, 0x301}, {0x1F84, 0x345}, {0x1F85, 0x3B1}, {0x1F85, 0x314},
{0x1F85, 0x301}, {0x1F85, 0x345}, {0x1F86, 0x3B1}, {0x1F86, 0x313}, {0x1F86, 0x342}, {0x1F86, 0x345}, {0x1F87, 0x3B1}, {0x1F87, 0x314}, {0x1F87, 0x342}, {0x1F87, 0x345}, {0x1F88, 0x391},
{0x1F88, 0x313}, {0x1F88, 0x345}, {0x1F89, 0x391}, {0x1F89, 0x314}, {0x1F89, 0x345}, {0x1F8A, 0x391}, {0x1F8A, 0x313}, {0x1F8A, 0x300}, {0x1F8A, 0x345}, {0x1F8B, 0x391}, {0x1F8B, 0x314},
{0x1F8B, 0x300}, {0x1F8B, 0x345}, {0x1F8C, 0x391}, {0x1F8C, 0x313}, {0x1F8C, 0x301}, {0x1F8C, 0x345}, {0x1F8D, 0x391}, {0x1F8D, 0x314}, {0x1F8D, 0x301}, {0x1F8D, 0x345}, {0x1F8E, 0x391},
{0x1F8E, 0x313}, {0x1F8E, 0x342}, {0x1F8E, 0x345}, {0x1F8F, 0x391}, {0x1F8F, 0x314}, {0x1F8F, 0x342}, {0x1F8F, 0x345}, {0x1F90, 0x3B7}, {0x1F90, 0x313}, {0x1F90, 0x345}, {0x1F91, 0x3B7},
{0x1F91, 0x314}, {0x1F91, 0x345}, {0x1F92, 0x3B7}, {0x1F92, 0x313}, {0x1F92, 0x300}, {0x1F92, 0x345}, {0x1F93, 0x3B7}, {0x1F93, 0x314}, {0x1F93, 0x300}, {0x1F93, 0x345}, {0x1F94, 0x3B7},
{0x1F94, 0x313}, {0x1F94, 0x301}, {0x1F94, 0x345}, {0x1F95, 0x3B7}, {0x1F95, 0x314}, {0x1F95, 0x301}, {0x1F95, 0x345}, {0x1F96, 0x3B7}, {0x1F96, 0x313}, {0x1F96, 0x342}, {0x1F96, 0x345},
{0x1F97, 0x3B7}, {0x1F97, 0x314}, {0x1F97, 0x342}, {0x1F97, 0x345}, {0x1F98, 0x397}, {0x1F98, 0x313}, {0x1F98, 0x345}, {0x1F99, 0x397}, {0x1F99, 0x314}, {0x1F99, 0x345}, {0x1F9A, 0x397},
{0x1F9A, 0x313}, {0x1F9A, 0x300}, {0x1F9A, 0x345}, {0x1F9B, 0x397}, {0x1F9B, 0x314}, {0x1F9B, 0x300}, {0x1F9B, 0x345}, {0x1F9C, 0x397}, {0x1F9C, 0x313}, {0x1F9C, 0x301}, {0x1F9C, 0x345},
{0x1F9D, 0x397}, {0x1F9D, 0x314}, {0x1F9D, 0x301}, {0x1F9D, 0x345}, {0x1F9E, 0x397}, {0x1F9E, 0x313}, {0x1F9E, 0x342}, {0x1F9E, 0x345}, {0x1F9F, 0x397}, {0x1F9F, 0x314}, {0x1F9F, 0x342},
{0x1F9F, 0x345}, {0x1FA0, 0x3C9}, {0x1FA0, 0x313}, {0x1FA0, 0x345}, {0x1FA1, 0x3C9}, {0x1FA1, 0x314}, {0x1FA1, 0x345}, {0x1FA2, 0x3C9}, {0x1FA2, 0x313}, {0x1FA2, 0x300}, {0x1FA2, 0x345},
{0x1FA3, 0x3C9}, {0x1FA3, 0x314}, {0x1FA3, 0x300}, {0x1FA3, 0x345}, {0x1FA4, 0x3C9}, {0x1FA4, 0x313}, {0x1FA4, 0x301}, {0x1FA4, 0x345}, {0x1FA5, 0x3C9}, {0x1FA5, 0x314}, {0x1FA5, 0x301},
{0x1FA5, 0x345}, {0x1FA6, 0x3C9}, {0x1FA6, 0x313}, {0x1FA6, 0x342}, {0x1FA6, 0x345}, {0x1FA7, 0x3C9}, {0x1FA7, 0x314}, {0x1FA7, 0x342}, {0x1FA7, 0x345}, {0x1FA8, 0x3A9}, {0x1FA8, 0x313},
{0x1FA8, 0x345}, {0x1FA9, 0x3A9}, {0x1FA9, 0x314}, {0x1FA9, 0x345}, {0x1FAA, 0x3A9}, {0x1FAA, 0x313}, {0x1FAA, 0x300}, {0x1FAA, 0x345}, {0x1FAB, 0x3A9}, {0x1FAB, 0x314}, {0x1FAB, 0x300},
{0x1FAB, 0x345}, {0x1FAC, 0x3A9}, {0x1FAC, 0x313}, {0x1FAC, 0x301}, {0x1FAC, 0x345}, {0x1FAD, 0x3A9}, {0x1FAD, 0x314}, {0x1FAD, 0x301}, {0x1FAD, 0x345}, {0x1FAE, 0x3A9}, {0x1FAE, 0x313},
{0x1FAE, 0x342}, {0x1FAE, 0x345}, {0x1FAF, 0x3A9}, {0x1FAF, 0x314}, {0x1FAF, 0x342}, {0x1FAF, 0x345}, {0x1FB0, 0x3B1}, {0x1FB0, 0x306}, {0x1FB1, 0x3B1}, {0x1FB1, 0x304}, {0x1FB2, 0x3B1},
{0x1FB2, 0x300}, {0x1FB2, 0x345}, {0x1FB3, 0x3B1}, {0x1FB3, 0x345}, {0x1FB4, 0x3B1}, {0x1FB4, 0x301}, {0x1FB4, 0x345}, {0x1FB6, 0x3B1}, {0x1FB6, 0x342}, {0x1FB7, 0x3B1}, {0x1FB7, 0x342},
{0x1FB7, 0x345}, {0x1FB8, 0x391}, {0x1FB8, 0x306}, {0x1FB9, 0x391}, {0x1FB9, 0x304}, {0x1FBA, 0x391}, {0x1FBA, 0x300}, {0x1FBB, 0x391}, {0x1FBB, 0x301}, {0x1FBC, 0x391}, {0x1FBC, 0x345},
{0x1FBE, 0x3B9}, {0x1FC1, 0xA8}, {0x1FC1, 0x342}, {0x1FC2, 0x3B7}, {0x1FC2, 0x300}, {0x1FC2, 0x345}, {0x1FC3, 0x3B7}, {0x1FC3, 0x345}, {0x1FC4, 0x3B7}, {0x1FC4, 0x301}, {0x1FC4, 0x345},
{0x1FC6, 0x3B7}, {0x1FC6, 0x342}, {0x1FC7, 0x3B7}, {0x1FC7, 0x342}, {0x1FC7, 0x345}, {0x1FC8, 0x395}, {0x1FC8, 0x300}, {0x1FC9, 0x395}, {0x1FC9, 0x301}, {0x1FCA, 0x397}, {0x1FCA, 0x300},
{0x1FCB, 0x397}, {0x1FCB, 0x301}, {0x1FCC, 0x397}, {0x1FCC, 0x345}, {0x1FCD, 0x1FBF}, {0x1FCD, 0x300}, {0x1FCE, 0x1FBF}, {0x1FCE, 0x301}, {0x1FCF, 0x1FBF}, {0x1FCF, 0x342}, {0x1FD0, 0x3B9},
{0x1FD0, 0x306}, {0x1FD1, 0x3B9}, {0x1FD1, 0x304}, {0x1FD2, 0x3B9}, {0x1FD2, 0x308}, {0x1FD2, 0x300}, {0x1FD3, 0x3B9}, {0x1FD3, 0x308}, {0x1FD3, 0x301}, {0x1FD6, 0x3B9}, {0x1FD6, 0x342},
{0x1FD7, 0x3B9}, {0x1FD7, 0x308}, {0x1FD7, 0x342}, {0x1FD8, 0x399}, {0x1FD8, 0x306}, {0x1FD9, 0x399}, {0x1FD9, 0x304}, {0x1FDA, 0x399}, {0x1FDA, 0x300}, {0x1FDB, 0x399}, {0x1FDB, 0x301},
{0x1FDD, 0x1FFE}, {0x1FDD, 0x300}, {0x1FDE, 0x1FFE}, {0x1FDE, 0x301}, {0x1FDF, 0x1FFE}, {0x1FDF, 0x342}, {0x1FE0, 0x3C5}, {0x1FE0, 0x306}, {0x1FE1, 0x3C5}, {0x1FE1, 0x304}, {0x1FE2, 0x3C5},
{0x1FE2, 0x308}, {0x1FE2, 0x300}, {0x1FE3, 0x3C5}, {0x1FE3, 0x308}, {0x1FE3, 0x301}, {0x1FE4, 0x3C1}, {0x1FE4, 0x313}, {0x1FE5, 0x3C1}, {0x1FE5, 0x314}, {0x1FE6, 0x3C5}, {0x1FE6, 0x342},
{0x1FE7, 0x3C5}, {0x1FE7, 0x308}, {0x1FE7, 0x342}, {0x1FE8, 0x3A5}, {0x1FE8, 0x306}, {0x1FE9, 0x3A5}, {0x1FE9, 0x304}, {0x1FEA, 0x3A5}, {0x1FEA, 0x300}, {0x1FEB, 0x3A5}, {0x1FEB, 0x301},
{0x1FEC, 0x3A1}, {0x1FEC, 0x314}, {0x1FED, 0xA8}, {0x1FED, 0x300}, {0x1FEE, 0xA8}, {0x1FEE, 0x301}, {0x1FEF, 0x60}, {0x1FF2, 0x3C9}, {0x1FF2, 0x300}, {0x1FF2, 0x345}, {0x1FF3, 0x3C9}, {0x1FF3, 0x345},
{0x1FF4, 0x3C9}, {0x1FF4, 0x301}, {0x1FF4, 0x345}, {0x1FF6, 0x3C9}, {0x1FF6, 0x342}, {0x1FF7, 0x3C9}, {0x1FF7, 0x342}, {0x1FF7, 0x345}, {0x1FF8, 0x39F}, {0x1FF8, 0x300}, {0x1FF9, 0x39F},
{0x1FF9, 0x301}, {0x1FFA, 0x3A9}, {0x1FFA, 0x300}, {0x1FFB, 0x3A9}, {0x1FFB, 0x301}, {0x1FFC, 0x3A9}, {0x1FFC, 0x345}, {0x1FFD, 0xB4}, {0x2000, 0x2002}, {0x2001, 0x2003}, {0x2126, 0x3A9},
{0x212A, 0x4B}, {0x212B, 0x41}, {0x212B, 0x30A}, {0x219A, 0x2190}, {0x219A, 0x338}, {0x219B, 0x2192}, {0x219B, 0x338}, {0x21AE, 0x2194}, {0x21AE, 0x338}, {0x21CD, 0x21D0}, {0x21CD, 0x338},
{0x21CE, 0x21D4}, {0x21CE, 0x338}, {0x21CF, 0x21D2}, {0x21CF, 0x338}, {0x2204, 0x2203}, {0x2204, 0x338}, {0x2209, 0x2208}, {0x2209, 0x338}, {0x220C, 0x220B}, {0x220C, 0x338}, {0x2224, 0x2223},
{0x2224, 0x338}, {0x2226, 0x2225}, {0x2226, 0x338}, {0x2241, 0x223C}, {0x2241, 0x338}, {0x2244, 0x2243}, {0x2244, 0x338}, {0x2247, 0x2245}, {0x2247, 0x338}, {0x2249, 0x2248}, {0x2249, 0x338},
{0x2260, 0x3D}, {0x2260, 0x338}, {0x2262, 0x2261}, {0x2262, 0x338}, {0x226D, 0x224D}, {0x226D, 0x338}, {0x226E, 0x3C}, {0x226E, 0x338}, {0x226F, 0x3E}, {0x226F, 0x338}, {0x2270, 0x2264},
{0x2270, 0x338}, {0x2271, 0x2265}, {0x2271, 0x338}, {0x2274, 0x2272}, {0x2274, 0x338}, {0x2275, 0x2273}, {0x2275, 0x338}, {0x2278, 0x2276}, {0x2278, 0x338}, {0x2279, 0x2277}, {0x2279, 0x338},
{0x2280, 0x227A}, {0x2280, 0x338}, {0x2281, 0x227B}, {0x2281, 0x338}, {0x2284, 0x2282}, {0x2284, 0x338}, {0x2285, 0x2283}, {0x2285, 0x338}, {0x2288, 0x2286}, {0x2288, 0x338}, {0x2289, 0x2287},
{0x2289, 0x338}, {0x22AC, 0x22A2}, {0x22AC, 0x338}, {0x22AD, 0x22A8}, {0x22AD, 0x338}, {0x22AE, 0x22A9}, {0x22AE, 0x338}, {0x22AF, 0x22AB}, {0x22AF, 0x338}, {0x22E0, 0x227C}, {0x22E0, 0x338},
{0x22E1, 0x227D}, {0x22E1, 0x338}, {0x22E2, 0x2291}, {0x22E2, 0x338}, {0x22E3, 0x2292}, {0x22E3, 0x338}, {0x22EA, 0x22B2}, {0x22EA, 0x338}, {0x22EB, 0x22B3}, {0x22EB, 0x338}, {0x22EC, 0x22B4},
{0x22EC, 0x338}, {0x22ED, 0x22B5}, {0x22ED, 0x338}, {0x2329, 0x3008}, {0x232A, 0x3009}, {0x2ADC, 0x2ADD}, {0x2ADC, 0x338}, {0x304C, 0x304B}, {0x304C, 0x3099}, {0x304E, 0x304D}, {0x304E, 0x3099},
{0x3050, 0x304F}, {0x3050, 0x3099}, {0x3052, 0x3051}, {0x3052, 0x3099}, {0x3054, 0x3053}, {0x3054, 0x3099}, {0x3056, 0x3055}, {0x3056, 0x3099}, {0x3058, 0x3057}, {0x3058, 0x3099}, {0x305A, 0x3059},
{0x305A, 0x3099}, {0x305C, 0x305B}, {0x305C, 0x3099}, {0x305E, 0x305D}, {0x305E, 0x3099}, {0x3060, 0x305F}, {0x3060, 0x3099}, {0x3062, 0x3061}, {0x3062, 0x3099}, {0x3065, 0x3064}, {0x3065, 0x3099},
{0x3067, 0x3066}, {0x3067, 0x3099}, {0x3069, 0x3068}, {0x3069, 0x3099}, {0x3070, 0x306F}, {0x3070, 0x3099}, {0x3071, 0x306F}, {0x3071, 0x309A}, {0x3073, 0x3072}, {0x3073, 0x3099}, {0x3074, 0x3072},
{0x3074, 0x309A}, {0x3076, 0x3075}, {0x3076, 0x3099}, {0x3077, 0x3075}, {0x3077, 0x309A}, {0x3079, 0x3078}, {0x3079, 0x3099}, {0x307A, 0x3078}, {0x307A, 0x309A}, {0x307C, 0x307B}, {0x307C, 0x3099},
{0x307D, 0x307B}, {0x307D, 0x309A}, {0x3094, 0x3046}, {0x3094, 0x3099}, {0x309E, 0x309D}, {0x309E, 0x3099}, {0x30AC, 0x30AB}, {0x30AC, 0x3099}, {0x30AE, 0x30AD}, {0x30AE, 0x3099}, {0x30B0, 0x30AF},
{0x30B0, 0x3099}, {0x30B2, 0x30B1}, {0x30B2, 0x3099}, {0x30B4, 0x30B3}, {0x30B4, 0x3099}, {0x30B6, 0x30B5}, {0x30B6, 0x3099}, {0x30B8, 0x30B7}, {0x30B8, 0x3099}, {0x30BA, 0x30B9}, {0x30BA, 0x3099},
{0x30BC, 0x30BB}, {0x30BC, 0x3099}, {0x30BE, 0x30BD}, {0x30BE, 0x3099}, {0x30C0, 0x30BF}, {0x30C0, 0x3099}, {0x30C2, 0x30C1}, {0x30C2, 0x3099}, {0x30C5, 0x30C4}, {0x30C5, 0x3099}, {0x30C7, 0x30C6},
{0x30C7, 0x3099}, {0x30C9, 0x30C8}, {0x30C9, 0x3099}, {0x30D0, 0x30CF}, {0x30D0, 0x3099}, {0x30D1, 0x30CF}, {0x30D1, 0x309A}, {0x30D3, 0x30D2}, {0x30D3, 0x3099}, {0x30D4, 0x30D2}, {0x30D4, 0x309A},
{0x30D6, 0x30D5}, {0x30D6, 0x3099}, {0x30D7, 0x30D5}, {0x30D7, 0x309A}, {0x30D9, 0x30D8}, {0x30D9, 0x3099}, {0x30DA, 0x30D8}, {0x30DA, 0x309A}, {0x30DC, 0x30DB}, {0x30DC, 0x3099}, {0x30DD, 0x30DB},
{0x30DD, 0x309A}, {0x30F4, 0x30A6}, {0x30F4, 0x3099}, {0x30F7, 0x30EF}, {0x30F7, 0x3099}, {0x30F8, 0x30F0}, {0x30F8, 0x3099}, {0x30F9, 0x30F1}, {0x30F9, 0x3099}, {0x30FA, 0x30F2}, {0x30FA, 0x3099},
{0x30FE, 0x30FD}, {0x30FE, 0x3099}, {0xF900, 0x8C48}, {0xF901, 0x66F4}, {0xF902, 0x8ECA}, {0xF903, 0x8CC8}, {0xF904, 0x6ED1}, {0xF905, 0x4E32}, {0xF906, 0x53E5}, {0xF907, 0x9F9C}, {0xF908, 0x9F9C},
{0xF909, 0x5951}, {0xF90A, 0x91D1}, {0xF90B, 0x5587}, {0xF90C, 0x5948}, {0xF90D, 0x61F6}, {0xF90E, 0x7669}, {0xF90F, 0x7F85}, {0xF910, 0x863F}, {0xF911, 0x87BA}, {0xF912, 0x88F8}, {0xF913, 0x908F},
{0xF914, 0x6A02}, {0xF915, 0x6D1B}, {0xF916, 0x70D9}, {0xF917, 0x73DE}, {0xF918, 0x843D}, {0xF919, 0x916A}, {0xF91A, 0x99F1}, {0xF91B, 0x4E82}, {0xF91C, 0x5375}, {0xF91D, 0x6B04}, {0xF91E, 0x721B},
{0xF91F, 0x862D}, {0xF920, 0x9E1E}, {0xF921, 0x5D50}, {0xF922, 0x6FEB}, {0xF923, 0x85CD}, {0xF924, 0x8964}, {0xF925, 0x62C9}, {0xF926, 0x81D8}, {0xF927, 0x881F}, {0xF928, 0x5ECA}, {0xF929, 0x6717},
{0xF92A, 0x6D6A}, {0xF92B, 0x72FC}, {0xF92C, 0x90CE}, {0xF92D, 0x4F86}, {0xF92E, 0x51B7}, {0xF92F, 0x52DE}, {0xF930, 0x64C4}, {0xF931, 0x6AD3}, {0xF932, 0x7210}, {0xF933, 0x76E7}, {0xF934, 0x8001},
{0xF935, 0x8606}, {0xF936, 0x865C}, {0xF937, 0x8DEF}, {0xF938, 0x9732}, {0xF939, 0x9B6F}, {0xF93A, 0x9DFA}, {0xF93B, 0x788C}, {0xF93C, 0x797F}, {0xF93D, 0x7DA0}, {0xF93E, 0x83C9}, {0xF93F, 0x9304},
{0xF940, 0x9E7F}, {0xF941, 0x8AD6}, {0xF942, 0x58DF}, {0xF943, 0x5F04}, {0xF944, 0x7C60}, {0xF945, 0x807E}, {0xF946, 0x7262}, {0xF947, 0x78CA}, {0xF948, 0x8CC2}, {0xF949, 0x96F7}, {0xF94A, 0x58D8},
{0xF94B, 0x5C62}, {0xF94C, 0x6A13}, {0xF94D, 0x6DDA}, {0xF94E, 0x6F0F}, {0xF94F, 0x7D2F}, {0xF950, 0x7E37}, {0xF951, 0x964B}, {0xF952, 0x52D2}, {0xF953, 0x808B}, {0xF954, 0x51DC}, {0xF955, 0x51CC},
{0xF956, 0x7A1C}, {0xF957, 0x7DBE}, {0xF958, 0x83F1}, {0xF959, 0x9675}, {0xF95A, 0x8B80}, {0xF95B, 0x62CF}, {0xF95C, 0x6A02}, {0xF95D, 0x8AFE}, {0xF95E, 0x4E39}, {0xF95F, 0x5BE7}, {0xF960, 0x6012},
{0xF961, 0x7387}, {0xF962, 0x7570}, {0xF963, 0x5317}, {0xF964, 0x78FB}, {0xF965, 0x4FBF}, {0xF966, 0x5FA9}, {0xF967, 0x4E0D}, {0xF968, 0x6CCC}, {0xF969, 0x6578}, {0xF96A, 0x7D22}, {0xF96B, 0x53C3},
{0xF96C, 0x585E}, {0xF96D, 0x7701}, {0xF96E, 0x8449}, {0xF96F, 0x8AAA}, {0xF970, 0x6BBA}, {0xF971, 0x8FB0}, {0xF972, 0x6C88}, {0xF973, 0x62FE}, {0xF974, 0x82E5}, {0xF975, 0x63A0}, {0xF976, 0x7565},
{0xF977, 0x4EAE}, {0xF978, 0x5169}, {0xF979, 0x51C9}, {0xF97A, 0x6881}, {0xF97B, 0x7CE7}, {0xF97C, 0x826F}, {0xF97D, 0x8AD2}, {0xF97E, 0x91CF}, {0xF97F, 0x52F5}, {0xF980, 0x5442}, {0xF981, 0x5973},
{0xF982, 0x5EEC}, {0xF983, 0x65C5}, {0xF984, 0x6FFE}, {0xF985, 0x792A}, {0xF986, 0x95AD}, {0xF987, 0x9A6A}, {0xF988, 0x9E97}, {0xF989, 0x9ECE}, {0xF98A, 0x529B}, {0xF98B, 0x66C6}, {0xF98C, 0x6B77},
{0xF98D, 0x8F62}, {0xF98E, 0x5E74}, {0xF98F, 0x6190}, {0xF990, 0x6200}, {0xF991, 0x649A}, {0xF992, 0x6F23}, {0xF993, 0x7149}, {0xF994, 0x7489}, {0xF995, 0x79CA}, {0xF996, 0x7DF4}, {0xF997, 0x806F},
{0xF998, 0x8F26}, {0xF999, 0x84EE}, {0xF99A, 0x9023}, {0xF99B, 0x934A}, {0xF99C, 0x5217}, {0xF99D, 0x52A3}, {0xF99E, 0x54BD}, {0xF99F, 0x70C8}, {0xF9A0, 0x88C2}, {0xF9A1, 0x8AAA}, {0xF9A2, 0x5EC9},
{0xF9A3, 0x5FF5}, {0xF9A4, 0x637B}, {0xF9A5, 0x6BAE}, {0xF9A6, 0x7C3E}, {0xF9A7, 0x7375}, {0xF9A8, 0x4EE4}, {0xF9A9, 0x56F9}, {0xF9AA, 0x5BE7}, {0xF9AB, 0x5DBA}, {0xF9AC, 0x601C}, {0xF9AD, 0x73B2},
{0xF9AE, 0x7469}, {0xF9AF, 0x7F9A}, {0xF9B0, 0x8046}, {0xF9B1, 0x9234}, {0xF9B2, 0x96F6}, {0xF9B3, 0x9748}, {0xF9B4, 0x9818}, {0xF9B5, 0x4F8B}, {0xF9B6, 0x79AE}, {0xF9B7, 0x91B4}, {0xF9B8, 0x96B8},
{0xF9B9, 0x60E1}, {0xF9BA, 0x4E86}, {0xF9BB, 0x50DA}, {0xF9BC, 0x5BEE}, {0xF9BD, 0x5C3F}, {0xF9BE, 0x6599}, {0xF9BF, 0x6A02}, {0xF9C0, 0x71CE}, {0xF9C1, 0x7642}, {0xF9C2, 0x84FC}, {0xF9C3, 0x907C},
{0xF9C4, 0x9F8D}, {0xF9C5, 0x6688}, {0xF9C6, 0x962E}, {0xF9C7, 0x5289}, {0xF9C8, 0x677B}, {0xF9C9, 0x67F3}, {0xF9CA, 0x6D41}, {0xF9CB, 0x6E9C}, {0xF9CC, 0x7409}, {0xF9CD, 0x7559}, {0xF9CE, 0x786B},
{0xF9CF, 0x7D10}, {0xF9D0, 0x985E}, {0xF9D1, 0x516D}, {0xF9D2, 0x622E}, {0xF9D3, 0x9678}, {0xF9D4, 0x502B}, {0xF9D5, 0x5D19}, {0xF9D6, 0x6DEA}, {0xF9D7, 0x8F2A}, {0xF9D8, 0x5F8B}, {0xF9D9, 0x6144},
{0xF9DA, 0x6817}, {0xF9DB, 0x7387}, {0xF9DC, 0x9686}, {0xF9DD, 0x5229}, {0xF9DE, 0x540F}, {0xF9DF, 0x5C65}, {0xF9E0, 0x6613}, {0xF9E1, 0x674E}, {0xF9E2, 0x68A8}, {0xF9E3, 0x6CE5}, {0xF9E4, 0x7406},
{0xF9E5, 0x75E2}, {0xF9E6, 0x7F79}, {0xF9E7, 0x88CF}, {0xF9E8, 0x88E1}, {0xF9E9, 0x91CC}, {0xF9EA, 0x96E2}, {0xF9EB, 0x533F}, {0xF9EC, 0x6EBA}, {0xF9ED, 0x541D}, {0xF9EE, 0x71D0}, {0xF9EF, 0x7498},
{0xF9F0, 0x85FA}, {0xF9F1, 0x96A3}, {0xF9F2, 0x9C57}, {0xF9F3, 0x9E9F}, {0xF9F4, 0x6797}, {0xF9F5, 0x6DCB}, {0xF9F6, 0x81E8}, {0xF9F7, 0x7ACB}, {0xF9F8, 0x7B20}, {0xF9F9, 0x7C92}, {0xF9FA, 0x72C0},
{0xF9FB, 0x7099}, {0xF9FC, 0x8B58}, {0xF9FD, 0x4EC0}, {0xF9FE, 0x8336}, {0xF9FF, 0x523A}, {0xFA00, 0x5207}, {0xFA01, 0x5EA6}, {0xFA02, 0x62D3}, {0xFA03, 0x7CD6}, {0xFA04, 0x5B85}, {0xFA05, 0x6D1E},
{0xFA06, 0x66B4}, {0xFA07, 0x8F3B}, {0xFA08, 0x884C}, {0xFA09, 0x964D}, {0xFA0A, 0x898B}, {0xFA0B, 0x5ED3}, {0xFA0C, 0x5140}, {0xFA0D, 0x55C0}, {0xFA10, 0x585A}, {0xFA12, 0x6674}, {0xFA15, 0x51DE},
{0xFA16, 0x732A}, {0xFA17, 0x76CA}, {0xFA18, 0x793C}, {0xFA19, 0x795E}, {0xFA1A, 0x7965}, {0xFA1B, 0x798F}, {0xFA1C, 0x9756}, {0xFA1D, 0x7CBE}, {0xFA1E, 0x7FBD}, {0xFA20, 0x8612}, {0xFA22, 0x8AF8},
{0xFA25, 0x9038}, {0xFA26, 0x90FD}, {0xFA2A, 0x98EF}, {0xFA2B, 0x98FC}, {0xFA2C, 0x9928}, {0xFA2D, 0x9DB4}, {0xFA2E, 0x90DE}, {0xFA2F, 0x96B7}, {0xFA30, 0x4FAE}, {0xFA31, 0x50E7}, {0xFA32, 0x514D},
{0xFA33, 0x52C9}, {0xFA34, 0x52E4}, {0xFA35, 0x5351}, {0xFA36, 0x559D}, {0xFA37, 0x5606}, {0xFA38, 0x5668}, {0xFA39, 0x5840}, {0xFA3A, 0x58A8}, {0xFA3B, 0x5C64}, {0xFA3C, 0x5C6E}, {0xFA3D, 0x6094},
{0xFA3E, 0x6168}, {0xFA3F, 0x618E}, {0xFA40, 0x61F2}, {0xFA41, 0x654F}, {0xFA42, 0x65E2}, {0xFA43, 0x6691}, {0xFA44, 0x6885}, {0xFA45, 0x6D77}, {0xFA46, 0x6E1A}, {0xFA47, 0x6F22}, {0xFA48, 0x716E},
{0xFA49, 0x722B}, {0xFA4A, 0x7422}, {0xFA4B, 0x7891}, {0xFA4C, 0x793E}, {0xFA4D, 0x7949}, {0xFA4E, 0x7948}, {0xFA4F, 0x7950}, {0xFA50, 0x7956}, {0xFA51, 0x795D}, {0xFA52, 0x798D}, {0xFA53, 0x798E},
{0xFA54, 0x7A40}, {0xFA55, 0x7A81}, {0xFA56, 0x7BC0}, {0xFA57, 0x7DF4}, {0xFA58, 0x7E09}, {0xFA59, 0x7E41}, {0xFA5A, 0x7F72}, {0xFA5B, 0x8005}, {0xFA5C, 0x81ED}, {0xFA5D, 0x8279}, {0xFA5E, 0x8279},
{0xFA5F, 0x8457}, {0xFA60, 0x8910}, {0xFA61, 0x8996}, {0xFA62, 0x8B01}, {0xFA63, 0x8B39}, {0xFA64, 0x8CD3}, {0xFA65, 0x8D08}, {0xFA66, 0x8FB6}, {0xFA67, 0x9038}, {0xFA68, 0x96E3}, {0xFA69, 0x97FF},
{0xFA6A, 0x983B}, {0xFA6B, 0x6075}, {0xFA6C, 0x242EE}, {0xFA6D, 0x8218}, {0xFA70, 0x4E26}, {0xFA71, 0x51B5}, {0xFA72, 0x5168}, {0xFA73, 0x4F80}, {0xFA74, 0x5145}, {0xFA75, 0x5180}, {0xFA76, 0x52C7},
{0xFA77, 0x52FA}, {0xFA78, 0x559D}, {0xFA79, 0x5555}, {0xFA7A, 0x5599}, {0xFA7B, 0x55E2}, {0xFA7C, 0x585A}, {0xFA7D, 0x58B3}, {0xFA7E, 0x5944}, {0xFA7F, 0x5954}, {0xFA80, 0x5A62}, {0xFA81, 0x5B28},
{0xFA82, 0x5ED2}, {0xFA83, 0x5ED9}, {0xFA84, 0x5F69}, {0xFA85, 0x5FAD}, {0xFA86, 0x60D8}, {0xFA87, 0x614E}, {0xFA88, 0x6108}, {0xFA89, 0x618E}, {0xFA8A, 0x6160}, {0xFA8B, 0x61F2}, {0xFA8C, 0x6234},
{0xFA8D, 0x63C4}, {0xFA8E, 0x641C}, {0xFA8F, 0x6452}, {0xFA90, 0x6556}, {0xFA91, 0x6674}, {0xFA92, 0x6717}, {0xFA93, 0x671B}, {0xFA94, 0x6756}, {0xFA95, 0x6B79}, {0xFA96, 0x6BBA}, {0xFA97, 0x6D41},
{0xFA98, 0x6EDB}, {0xFA99, 0x6ECB}, {0xFA9A, 0x6F22}, {0xFA9B, 0x701E}, {0xFA9C, 0x716E}, {0xFA9D, 0x77A7}, {0xFA9E, 0x7235}, {0xFA9F, 0x72AF}, {0xFAA0, 0x732A}, {0xFAA1, 0x7471}, {0xFAA2, 0x7506},
{0xFAA3, 0x753B}, {0xFAA4, 0x761D}, {0xFAA5, 0x761F}, {0xFAA6, 0x76CA}, {0xFAA7, 0x76DB}, {0xFAA8, 0x76F4}, {0xFAA9, 0x774A}, {0xFAAA, 0x7740}, {0xFAAB, 0x78CC}, {0xFAAC, 0x7AB1}, {0xFAAD, 0x7BC0},
{0xFAAE, 0x7C7B}, {0xFAAF, 0x7D5B}, {0xFAB0, 0x7DF4}, {0xFAB1, 0x7F3E}, {0xFAB2, 0x8005}, {0xFAB3, 0x8352}, {0xFAB4, 0x83EF}, {0xFAB5, 0x8779}, {0xFAB6, 0x8941}, {0xFAB7, 0x8986}, {0xFAB8, 0x8996},
{0xFAB9, 0x8ABF}, {0xFABA, 0x8AF8}, {0xFABB, 0x8ACB}, {0xFABC, 0x8B01}, {0xFABD, 0x8AFE}, {0xFABE, 0x8AED}, {0xFABF, 0x8B39}, {0xFAC0, 0x8B8A}, {0xFAC1, 0x8D08}, {0xFAC2, 0x8F38}, {0xFAC3, 0x9072},
{0xFAC4, 0x9199}, {0xFAC5, 0x9276}, {0xFAC6, 0x967C}, {0xFAC7, 0x96E3}, {0xFAC8, 0x9756}, {0xFAC9, 0x97DB}, {0xFACA, 0x97FF}, {0xFACB, 0x980B}, {0xFACC, 0x983B}, {0xFACD, 0x9B12}, {0xFACE, 0x9F9C},
{0xFACF, 0x2284A}, {0xFAD0, 0x22844}, {0xFAD1, 0x233D5}, {0xFAD2, 0x3B9D}, {0xFAD3, 0x4018}, {0xFAD4, 0x4039}, {0xFAD5, 0x25249}, {0xFAD6, 0x25CD0}, {0xFAD7, 0x27ED3}, {0xFAD8, 0x9F43},
{0xFAD9, 0x9F8E}, {0xFB1D, 0x5D9}, {0xFB1D, 0x5B4}, {0xFB1F, 0x5F2}, {0xFB1F, 0x5B7}, {0xFB2A, 0x5E9}, {0xFB2A, 0x5C1}, {0xFB2B, 0x5E9}, {0xFB2B, 0x5C2}, {0xFB2C, 0x5E9}, {0xFB2C, 0x5BC},
{0xFB2C, 0x5C1}, {0xFB2D, 0x5E9}, {0xFB2D, 0x5BC}, {0xFB2D, 0x5C2}, {0xFB2E, 0x5D0}, {0xFB2E, 0x5B7}, {0xFB2F, 0x5D0}, {0xFB2F, 0x5B8}, {0xFB30, 0x5D0}, {0xFB30, 0x5BC}, {0xFB31, 0x5D1},
{0xFB31, 0x5BC}, {0xFB32, 0x5D2}, {0xFB32, 0x5BC}, {0xFB33, 0x5D3}, {0xFB33, 0x5BC}, {0xFB34, 0x5D4}, {0xFB34, 0x5BC}, {0xFB35, 0x5D5}, {0xFB35, 0x5BC}, {0xFB36, 0x5D6}, {0xFB36, 0x5BC},
{0xFB38, 0x5D8}, {0xFB38, 0x5BC}, {0xFB39, 0x5D9}, {0xFB39, 0x5BC}, {0xFB3A, 0x5DA}, {0xFB3A, 0x5BC}, {0xFB3B, 0x5DB}, {0xFB3B, 0x5BC}, {0xFB3C, 0x5DC}, {0xFB3C, 0x5BC}, {0xFB3E, 0x5DE},
{0xFB3E, 0x5BC}, {0xFB40, 0x5E0}, {0xFB40, 0x5BC}, {0xFB41, 0x5E1}, {0xFB41, 0x5BC}, {0xFB43, 0x5E3}, {0xFB43, 0x5BC}, {0xFB44, 0x5E4}, {0xFB44, 0x5BC}, {0xFB46, 0x5E6}, {0xFB46, 0x5BC},
{0xFB47, 0x5E7}, {0xFB47, 0x5BC}, {0xFB48, 0x5E8}, {0xFB48, 0x5BC}, {0xFB49, 0x5E9}, {0xFB49, 0x5BC}, {0xFB4A, 0x5EA}, {0xFB4A, 0x5BC}, {0xFB4B, 0x5D5}, {0xFB4B, 0x5B9}, {0xFB4C, 0x5D1},
{0xFB4C, 0x5BF}, {0xFB4D, 0x5DB}, {0xFB4D, 0x5BF}, {0xFB4E, 0x5E4}, {0xFB4E, 0x5BF}, {0x1109A, 0x11099}, {0x1109A, 0x110BA}, {0x1109C, 0x1109B}, {0x1109C, 0x110BA}, {0x110AB, 0x110A5},
{0x110AB, 0x110BA}, {0x1112E, 0x11131}, {0x1112E, 0x11127}, {0x1112F, 0x11132}, {0x1112F, 0x11127}, {0x1134B, 0x11347}, {0x1134B, 0x1133E}, {0x1134C, 0x11347}, {0x1134C, 0x11357}, {0x114BB, 0x114B9},
{0x114BB, 0x114BA}, {0x114BC, 0x114B9}, {0x114BC, 0x114B0}, {0x114BE, 0x114B9}, {0x114BE, 0x114BD}, {0x115BA, 0x115B8}, {0x115BA, 0x115AF}, {0x115BB, 0x115B9}, {0x115BB, 0x115AF}, {0x1D15E, 0x1D157},
{0x1D15E, 0x1D165}, {0x1D15F, 0x1D158}, {0x1D15F, 0x1D165}, {0x1D160, 0x1D158}, {0x1D160, 0x1D165}, {0x1D160, 0x1D16E}, {0x1D161, 0x1D158}, {0x1D161, 0x1D165}, {0x1D161, 0x1D16F}, {0x1D162, 0x1D158},
{0x1D162, 0x1D165}, {0x1D162, 0x1D170}, {0x1D163, 0x1D158}, {0x1D163, 0x1D165}, {0x1D163, 0x1D171}, {0x1D164, 0x1D158}, {0x1D164, 0x1D165}, {0x1D164, 0x1D172}, {0x1D1BB, 0x1D1B9}, {0x1D1BB, 0x1D165},
{0x1D1BC, 0x1D1BA}, {0x1D1BC, 0x1D165}, {0x1D1BD, 0x1D1B9}, {0x1D1BD, 0x1D165}, {0x1D1BD, 0x1D16E}, {0x1D1BE, 0x1D1BA}, {0x1D1BE, 0x1D165}, {0x1D1BE, 0x1D16E}, {0x1D1BF, 0x1D1B9}, {0x1D1BF, 0x1D165},
{0x1D1BF, 0x1D16F}, {0x1D1C0, 0x1D1BA}, {0x1D1C0, 0x1D165}, {0x1D1C0, 0x1D16F}, {0x2F800, 0x4E3D}, {0x2F801, 0x4E38}, {0x2F802, 0x4E41}, {0x2F803, 0x20122}, {0x2F804, 0x4F60}, {0x2F805, 0x4FAE},
{0x2F806, 0x4FBB}, {0x2F807, 0x5002}, {0x2F808, 0x507A}, {0x2F809, 0x5099}, {0x2F80A, 0x50E7}, {0x2F80B, 0x50CF}, {0x2F80C, 0x349E}, {0x2F80D, 0x2063A}, {0x2F80E, 0x514D}, {0x2F80F, 0x5154},
{0x2F810, 0x5164}, {0x2F811, 0x5177}, {0x2F812, 0x2051C}, {0x2F813, 0x34B9}, {0x2F814, 0x5167}, {0x2F815, 0x518D}, {0x2F816, 0x2054B}, {0x2F817, 0x5197}, {0x2F818, 0x51A4}, {0x2F819, 0x4ECC},
{0x2F81A, 0x51AC}, {0x2F81B, 0x51B5}, {0x2F81C, 0x291DF}, {0x2F81D, 0x51F5}, {0x2F81E, 0x5203}, {0x2F81F, 0x34DF}, {0x2F820, 0x523B}, {0x2F821, 0x5246}, {0x2F822, 0x5272}, {0x2F823, 0x5277},
{0x2F824, 0x3515}, {0x2F825, 0x52C7}, {0x2F826, 0x52C9}, {0x2F827, 0x52E4}, {0x2F828, 0x52FA}, {0x2F829, 0x5305}, {0x2F82A, 0x5306}, {0x2F82B, 0x5317}, {0x2F82C, 0x5349}, {0x2F82D, 0x5351},
{0x2F82E, 0x535A}, {0x2F82F, 0x5373}, {0x2F830, 0x537D}, {0x2F831, 0x537F}, {0x2F832, 0x537F}, {0x2F833, 0x537F}, {0x2F834, 0x20A2C}, {0x2F835, 0x7070}, {0x2F836, 0x53CA}, {0x2F837, 0x53DF},
{0x2F838, 0x20B63}, {0x2F839, 0x53EB}, {0x2F83A, 0x53F1}, {0x2F83B, 0x5406}, {0x2F83C, 0x549E}, {0x2F83D, 0x5438}, {0x2F83E, 0x5448}, {0x2F83F, 0x5468}, {0x2F840, 0x54A2}, {0x2F841, 0x54F6},
{0x2F842, 0x5510}, {0x2F843, 0x5553}, {0x2F844, 0x5563}, {0x2F845, 0x5584}, {0x2F846, 0x5584}, {0x2F847, 0x5599}, {0x2F848, 0x55AB}, {0x2F849, 0x55B3}, {0x2F84A, 0x55C2}, {0x2F84B, 0x5716},
{0x2F84C, 0x5606}, {0x2F84D, 0x5717}, {0x2F84E, 0x5651}, {0x2F84F, 0x5674}, {0x2F850, 0x5207}, {0x2F851, 0x58EE}, {0x2F852, 0x57CE}, {0x2F853, 0x57F4}, {0x2F854, 0x580D}, {0x2F855, 0x578B},
{0x2F856, 0x5832}, {0x2F857, 0x5831}, {0x2F858, 0x58AC}, {0x2F859, 0x214E4}, {0x2F85A, 0x58F2}, {0x2F85B, 0x58F7}, {0x2F85C, 0x5906}, {0x2F85D, 0x591A}, {0x2F85E, 0x5922}, {0x2F85F, 0x5962},
{0x2F860, 0x216A8}, {0x2F861, 0x216EA}, {0x2F862, 0x59EC}, {0x2F863, 0x5A1B}, {0x2F864, 0x5A27}, {0x2F865, 0x59D8}, {0x2F866, 0x5A66}, {0x2F867, 0x36EE}, {0x2F868, 0x36FC}, {0x2F869, 0x5B08},
{0x2F86A, 0x5B3E}, {0x2F86B, 0x5B3E}, {0x2F86C, 0x219C8}, {0x2F86D, 0x5BC3}, {0x2F86E, 0x5BD8}, {0x2F86F, 0x5BE7}, {0x2F870, 0x5BF3}, {0x2F871, 0x21B18}, {0x2F872, 0x5BFF}, {0x2F873, 0x5C06},
{0x2F874, 0x5F53}, {0x2F875, 0x5C22}, {0x2F876, 0x3781}, {0x2F877, 0x5C60}, {0x2F878, 0x5C6E}, {0x2F879, 0x5CC0}, {0x2F87A, 0x5C8D}, {0x2F87B, 0x21DE4}, {0x2F87C, 0x5D43}, {0x2F87D, 0x21DE6},
{0x2F87E, 0x5D6E}, {0x2F87F, 0x5D6B}, {0x2F880, 0x5D7C}, {0x2F881, 0x5DE1}, {0x2F882, 0x5DE2}, {0x2F883, 0x382F}, {0x2F884, 0x5DFD}, {0x2F885, 0x5E28}, {0x2F886, 0x5E3D}, {0x2F887, 0x5E69},
{0x2F888, 0x3862}, {0x2F889, 0x22183}, {0x2F88A, 0x387C}, {0x2F88B, 0x5EB0}, {0x2F88C, 0x5EB3}, {0x2F88D, 0x5EB6}, {0x2F88E, 0x5ECA}, {0x2F88F, 0x2A392}, {0x2F890, 0x5EFE}, {0x2F891, 0x22331},
{0x2F892, 0x22331}, {0x2F893, 0x8201}, {0x2F894, 0x5F22}, {0x2F895, 0x5F22}, {0x2F896, 0x38C7}, {0x2F897, 0x232B8}, {0x2F898, 0x261DA}, {0x2F899, 0x5F62}, {0x2F89A, 0x5F6B}, {0x2F89B, 0x38E3},
{0x2F89C, 0x5F9A}, {0x2F89D, 0x5FCD}, {0x2F89E, 0x5FD7}, {0x2F89F, 0x5FF9}, {0x2F8A0, 0x6081}, {0x2F8A1, 0x393A}, {0x2F8A2, 0x391C}, {0x2F8A3, 0x6094}, {0x2F8A4, 0x226D4}, {0x2F8A5, 0x60C7},
{0x2F8A6, 0x6148}, {0x2F8A7, 0x614C}, {0x2F8A8, 0x614E}, {0x2F8A9, 0x614C}, {0x2F8AA, 0x617A}, {0x2F8AB, 0x618E}, {0x2F8AC, 0x61B2}, {0x2F8AD, 0x61A4}, {0x2F8AE, 0x61AF}, {0x2F8AF, 0x61DE},
{0x2F8B0, 0x61F2}, {0x2F8B1, 0x61F6}, {0x2F8B2, 0x6210}, {0x2F8B3, 0x621B}, {0x2F8B4, 0x625D}, {0x2F8B5, 0x62B1}, {0x2F8B6, 0x62D4}, {0x2F8B7, 0x6350}, {0x2F8B8, 0x22B0C}, {0x2F8B9, 0x633D},
{0x2F8BA, 0x62FC}, {0x2F8BB, 0x6368}, {0x2F8BC, 0x6383}, {0x2F8BD, 0x63E4}, {0x2F8BE, 0x22BF1}, {0x2F8BF, 0x6422}, {0x2F8C0, 0x63C5}, {0x2F8C1, 0x63A9}, {0x2F8C2, 0x3A2E}, {0x2F8C3, 0x6469},
{0x2F8C4, 0x647E}, {0x2F8C5, 0x649D}, {0x2F8C6, 0x6477}, {0x2F8C7, 0x3A6C}, {0x2F8C8, 0x654F}, {0x2F8C9, 0x656C}, {0x2F8CA, 0x2300A}, {0x2F8CB, 0x65E3}, {0x2F8CC, 0x66F8}, {0x2F8CD, 0x6649},
{0x2F8CE, 0x3B19}, {0x2F8CF, 0x6691}, {0x2F8D0, 0x3B08}, {0x2F8D1, 0x3AE4}, {0x2F8D2, 0x5192}, {0x2F8D3, 0x5195}, {0x2F8D4, 0x6700}, {0x2F8D5, 0x669C}, {0x2F8D6, 0x80AD}, {0x2F8D7, 0x43D9},
{0x2F8D8, 0x6717}, {0x2F8D9, 0x671B}, {0x2F8DA, 0x6721}, {0x2F8DB, 0x675E}, {0x2F8DC, 0x6753}, {0x2F8DD, 0x233C3}, {0x2F8DE, 0x3B49}, {0x2F8DF, 0x67FA}, {0x2F8E0, 0x6785}, {0x2F8E1, 0x6852},
{0x2F8E2, 0x6885}, {0x2F8E3, 0x2346D}, {0x2F8E4, 0x688E}, {0x2F8E5, 0x681F}, {0x2F8E6, 0x6914}, {0x2F8E7, 0x3B9D}, {0x2F8E8, 0x6942}, {0x2F8E9, 0x69A3}, {0x2F8EA, 0x69EA}, {0x2F8EB, 0x6AA8},
{0x2F8EC, 0x236A3}, {0x2F8ED, 0x6ADB}, {0x2F8EE, 0x3C18}, {0x2F8EF, 0x6B21}, {0x2F8F0, 0x238A7}, {0x2F8F1, 0x6B54}, {0x2F8F2, 0x3C4E}, {0x2F8F3, 0x6B72}, {0x2F8F4, 0x6B9F}, {0x2F8F5, 0x6BBA},
{0x2F8F6, 0x6BBB}, {0x2F8F7, 0x23A8D}, {0x2F8F8, 0x21D0B}, {0x2F8F9, 0x23AFA}, {0x2F8FA, 0x6C4E}, {0x2F8FB, 0x23CBC}, {0x2F8FC, 0x6CBF}, {0x2F8FD, 0x6CCD}, {0x2F8FE, 0x6C67}, {0x2F8FF, 0x6D16},
{0x2F900, 0x6D3E}, {0x2F901, 0x6D77}, {0x2F902, 0x6D41}, {0x2F903, 0x6D69}, {0x2F904, 0x6D78}, {0x2F905, 0x6D85}, {0x2F906, 0x23D1E}, {0x2F907, 0x6D34}, {0x2F908, 0x6E2F}, {0x2F909, 0x6E6E},
{0x2F90A, 0x3D33}, {0x2F90B, 0x6ECB}, {0x2F90C, 0x6EC7}, {0x2F90D, 0x23ED1}, {0x2F90E, 0x6DF9}, {0x2F90F, 0x6F6E}, {0x2F910, 0x23F5E}, {0x2F911, 0x23F8E}, {0x2F912, 0x6FC6}, {0x2F913, 0x7039},
{0x2F914, 0x701E}, {0x2F915, 0x701B}, {0x2F916, 0x3D96}, {0x2F917, 0x704A}, {0x2F918, 0x707D}, {0x2F919, 0x7077}, {0x2F91A, 0x70AD}, {0x2F91B, 0x20525}, {0x2F91C, 0x7145}, {0x2F91D, 0x24263},
{0x2F91E, 0x719C}, {0x2F91F, 0x243AB}, {0x2F920, 0x7228}, {0x2F921, 0x7235}, {0x2F922, 0x7250}, {0x2F923, 0x24608}, {0x2F924, 0x7280}, {0x2F925, 0x7295}, {0x2F926, 0x24735}, {0x2F927, 0x24814},
{0x2F928, 0x737A}, {0x2F929, 0x738B}, {0x2F92A, 0x3EAC}, {0x2F92B, 0x73A5}, {0x2F92C, 0x3EB8}, {0x2F92D, 0x3EB8}, {0x2F92E, 0x7447}, {0x2F92F, 0x745C}, {0x2F930, 0x7471}, {0x2F931, 0x7485},
{0x2F932, 0x74CA}, {0x2F933, 0x3F1B}, {0x2F934, 0x7524}, {0x2F935, 0x24C36}, {0x2F936, 0x753E}, {0x2F937, 0x24C92}, {0x2F938, 0x7570}, {0x2F939, 0x2219F}, {0x2F93A, 0x7610}, {0x2F93B, 0x24FA1},
{0x2F93C, 0x24FB8}, {0x2F93D, 0x25044}, {0x2F93E, 0x3FFC}, {0x2F93F, 0x4008}, {0x2F940, 0x76F4}, {0x2F941, 0x250F3}, {0x2F942, 0x250F2}, {0x2F943, 0x25119}, {0x2F944, 0x25133}, {0x2F945, 0x771E},
{0x2F946, 0x771F}, {0x2F947, 0x771F}, {0x2F948, 0x774A}, {0x2F949, 0x4039}, {0x2F94A, 0x778B}, {0x2F94B, 0x4046}, {0x2F94C, 0x4096}, {0x2F94D, 0x2541D}, {0x2F94E, 0x784E}, {0x2F94F, 0x788C},
{0x2F950, 0x78CC}, {0x2F951, 0x40E3}, {0x2F952, 0x25626}, {0x2F953, 0x7956}, {0x2F954, 0x2569A}, {0x2F955, 0x256C5}, {0x2F956, 0x798F}, {0x2F957, 0x79EB}, {0x2F958, 0x412F}, {0x2F959, 0x7A40},
{0x2F95A, 0x7A4A}, {0x2F95B, 0x7A4F}, {0x2F95C, 0x2597C}, {0x2F95D, 0x25AA7}, {0x2F95E, 0x25AA7}, {0x2F95F, 0x7AEE}, {0x2F960, 0x4202}, {0x2F961, 0x25BAB}, {0x2F962, 0x7BC6}, {0x2F963, 0x7BC9},
{0x2F964, 0x4227}, {0x2F965, 0x25C80}, {0x2F966, 0x7CD2}, {0x2F967, 0x42A0}, {0x2F968, 0x7CE8}, {0x2F969, 0x7CE3}, {0x2F96A, 0x7D00}, {0x2F96B, 0x25F86}, {0x2F96C, 0x7D63}, {0x2F96D, 0x4301},
{0x2F96E, 0x7DC7}, {0x2F96F, 0x7E02}, {0x2F970, 0x7E45}, {0x2F971, 0x4334}, {0x2F972, 0x26228}, {0x2F973, 0x26247}, {0x2F974, 0x4359}, {0x2F975, 0x262D9}, {0x2F976, 0x7F7A}, {0x2F977, 0x2633E},
{0x2F978, 0x7F95}, {0x2F979, 0x7FFA}, {0x2F97A, 0x8005}, {0x2F97B, 0x264DA}, {0x2F97C, 0x26523}, {0x2F97D, 0x8060}, {0x2F97E, 0x265A8}, {0x2F97F, 0x8070}, {0x2F980, 0x2335F}, {0x2F981, 0x43D5},
{0x2F982, 0x80B2}, {0x2F983, 0x8103}, {0x2F984, 0x440B}, {0x2F985, 0x813E}, {0x2F986, 0x5AB5}, {0x2F987, 0x267A7}, {0x2F988, 0x267B5}, {0x2F989, 0x23393}, {0x2F98A, 0x2339C}, {0x2F98B, 0x8201},
{0x2F98C, 0x8204}, {0x2F98D, 0x8F9E}, {0x2F98E, 0x446B}, {0x2F98F, 0x8291}, {0x2F990, 0x828B}, {0x2F991, 0x829D}, {0x2F992, 0x52B3}, {0x2F993, 0x82B1}, {0x2F994, 0x82B3}, {0x2F995, 0x82BD},
{0x2F996, 0x82E6}, {0x2F997, 0x26B3C}, {0x2F998, 0x82E5}, {0x2F999, 0x831D}, {0x2F99A, 0x8363}, {0x2F99B, 0x83AD}, {0x2F99C, 0x8323}, {0x2F99D, 0x83BD}, {0x2F99E, 0x83E7}, {0x2F99F, 0x8457},
{0x2F9A0, 0x8353}, {0x2F9A1, 0x83CA}, {0x2F9A2, 0x83CC}, {0x2F9A3, 0x83DC}, {0x2F9A4, 0x26C36}, {0x2F9A5, 0x26D6B}, {0x2F9A6, 0x26CD5}, {0x2F9A7, 0x452B}, {0x2F9A8, 0x84F1}, {0x2F9A9, 0x84F3},
{0x2F9AA, 0x8516}, {0x2F9AB, 0x273CA}, {0x2F9AC, 0x8564}, {0x2F9AD, 0x26F2C}, {0x2F9AE, 0x455D}, {0x2F9AF, 0x4561}, {0x2F9B0, 0x26FB1}, {0x2F9B1, 0x270D2}, {0x2F9B2, 0x456B}, {0x2F9B3, 0x8650},
{0x2F9B4, 0x865C}, {0x2F9B5, 0x8667}, {0x2F9B6, 0x8669}, {0x2F9B7, 0x86A9}, {0x2F9B8, 0x8688}, {0x2F9B9, 0x870E}, {0x2F9BA, 0x86E2}, {0x2F9BB, 0x8779}, {0x2F9BC, 0x8728}, {0x2F9BD, 0x876B},
{0x2F9BE, 0x8786}, {0x2F9BF, 0x45D7}, {0x2F9C0, 0x87E1}, {0x2F9C1, 0x8801}, {0x2F9C2, 0x45F9}, {0x2F9C3, 0x8860}, {0x2F9C4, 0x8863}, {0x2F9C5, 0x27667}, {0x2F9C6, 0x88D7}, {0x2F9C7, 0x88DE},
{0x2F9C8, 0x4635}, {0x2F9C9, 0x88FA}, {0x2F9CA, 0x34BB}, {0x2F9CB, 0x278AE}, {0x2F9CC, 0x27966}, {0x2F9CD, 0x46BE}, {0x2F9CE, 0x46C7}, {0x2F9CF, 0x8AA0}, {0x2F9D0, 0x8AED}, {0x2F9D1, 0x8B8A},
{0x2F9D2, 0x8C55}, {0x2F9D3, 0x27CA8}, {0x2F9D4, 0x8CAB}, {0x2F9D5, 0x8CC1}, {0x2F9D6, 0x8D1B}, {0x2F9D7, 0x8D77}, {0x2F9D8, 0x27F2F}, {0x2F9D9, 0x20804}, {0x2F9DA, 0x8DCB}, {0x2F9DB, 0x8DBC},
{0x2F9DC, 0x8DF0}, {0x2F9DD, 0x208DE}, {0x2F9DE, 0x8ED4}, {0x2F9DF, 0x8F38}, {0x2F9E0, 0x285D2}, {0x2F9E1, 0x285ED}, {0x2F9E2, 0x9094}, {0x2F9E3, 0x90F1}, {0x2F9E4, 0x9111}, {0x2F9E5, 0x2872E},
{0x2F9E6, 0x911B}, {0x2F9E7, 0x9238}, {0x2F9E8, 0x92D7}, {0x2F9E9, 0x92D8}, {0x2F9EA, 0x927C}, {0x2F9EB, 0x93F9}, {0x2F9EC, 0x9415}, {0x2F9ED, 0x28BFA}, {0x2F9EE, 0x958B}, {0x2F9EF, 0x4995},
{0x2F9F0, 0x95B7}, {0x2F9F1, 0x28D77}, {0x2F9F2, 0x49E6}, {0x2F9F3, 0x96C3}, {0x2F9F4, 0x5DB2}, {0x2F9F5, 0x9723}, {0x2F9F6, 0x29145}, {0x2F9F7, 0x2921A}, {0x2F9F8, 0x4A6E}, {0x2F9F9, 0x4A76},
{0x2F9FA, 0x97E0}, {0x2F9FB, 0x2940A}, {0x2F9FC, 0x4AB2}, {0x2F9FD, 0x29496}, {0x2F9FE, 0x980B}, {0x2F9FF, 0x980B}, {0x2FA00, 0x9829}, {0x2FA01, 0x295B6}, {0x2FA02, 0x98E2}, {0x2FA03, 0x4B33},
{0x2FA04, 0x9929}, {0x2FA05, 0x99A7}, {0x2FA06, 0x99C2}, {0x2FA07, 0x99FE}, {0x2FA08, 0x4BCE}, {0x2FA09, 0x29B30}, {0x2FA0A, 0x9B12}, {0x2FA0B, 0x9C40}, {0x2FA0C, 0x9CFD}, {0x2FA0D, 0x4CCE},
{0x2FA0E, 0x4CED}, {0x2FA0F, 0x9D67}, {0x2FA10, 0x2A0CE}, {0x2FA11, 0x4CF8}, {0x2FA12, 0x2A105}, {0x2FA13, 0x2A20E}, {0x2FA14, 0x2A291}, {0x2FA15, 0x9EBB}, {0x2FA16, 0x4D56}, {0x2FA17, 0x9EF9},
{0x2FA18, 0x9EFE}, {0x2FA19, 0x9F05}, {0x2FA1A, 0x9F0F}, {0x2FA1B, 0x9F16}, {0x2FA1D, 0x2A600},
};
static std::string codepoint_to_utf8(uint32_t cp) {