vbatts/llama.cpp
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convert-hf-to-gguf.py: print() to logger conversion

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brian khuu 2024-04-15 11:39:26 +10:00
parent dd8b9774eb
commit 44b058d131
1 changed files with 4 additions and 4 deletions
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convert-hf-to-gguf.py
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@ -1649,7 +1649,7 @@ class DbrxModel(Model):
self.gguf_writer.add_layer_norm_eps(1e-5) self.gguf_writer.add_layer_norm_eps(1e-5)
self.gguf_writer.add_file_type(self.ftype) self.gguf_writer.add_file_type(self.ftype)
print(f"gguf: file type = {self.ftype}") logger.info(f"gguf: file type = {self.ftype}")
def write_tensors(self): def write_tensors(self):
block_count = self.hparams.get("n_layers") block_count = self.hparams.get("n_layers")
@ -1692,7 +1692,7 @@ class DbrxModel(Model):
# https://huggingface.co/databricks/dbrx-instruct/blob/main/model.safetensors.index.json#L15 # https://huggingface.co/databricks/dbrx-instruct/blob/main/model.safetensors.index.json#L15
new_name = tensor_map.get_name(name if not experts else name + ".weight", try_suffixes=(".weight",)) new_name = tensor_map.get_name(name if not experts else name + ".weight", try_suffixes=(".weight",))
if new_name is None: if new_name is None:
print(f"Can not map tensor {name!r}") logger.error(f"Can not map tensor {name!r}")
sys.exit() sys.exit()
n_dims = len(data.shape) n_dims = len(data.shape)
@ -1701,7 +1701,7 @@ class DbrxModel(Model):
# Most of the codebase that takes in 1D tensors only handles F32 tensors # Most of the codebase that takes in 1D tensors only handles F32 tensors
# and most of the outputs tensors are F32. # and most of the outputs tensors are F32.
if data_dtype != np.float32 and n_dims == 1: if data_dtype != np.float32 and n_dims == 1:
print(f"Can not map tensor {name!r}: all 1D tensors must be F32") logger.error(f"Can not map tensor {name!r}: all 1D tensors must be F32")
sys.exit() sys.exit()
# if f32 desired, convert any float16 to float32 # if f32 desired, convert any float16 to float32
@ -1712,7 +1712,7 @@ class DbrxModel(Model):
if self.ftype == 1 and data_dtype == np.float32 and n_dims > 1: if self.ftype == 1 and data_dtype == np.float32 and n_dims > 1:
data = data.astype(np.float16) data = data.astype(np.float16)
print(f"{new_name}, n_dims = {n_dims}, shape = {data.shape}, {old_dtype} --> {data.dtype}") logger.debug(f"{new_name}, n_dims = {n_dims}, shape = {data.shape}, {old_dtype} --> {data.dtype}")
self.gguf_writer.add_tensor(new_name, data) self.gguf_writer.add_tensor(new_name, data)