Merge branch 'master' into finetune-lora
This commit is contained in:
commit
281245a48f
13 changed files with 80 additions and 65 deletions
|
@ -301,7 +301,7 @@ if (LLAMA_METAL)
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set(GGML_SOURCES_METAL ggml-metal.m ggml-metal.h)
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add_compile_definitions(GGML_USE_METAL)
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add_compile_definitions(GGML_METAL_NDEBUG)
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#add_compile_definitions(GGML_METAL_NDEBUG)
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# get full path to the file
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#add_compile_definitions(GGML_METAL_DIR_KERNELS="${CMAKE_CURRENT_SOURCE_DIR}/")
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|
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51
Makefile
51
Makefile
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@ -1,5 +1,5 @@
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# Define the default target now so that it is always the first target
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BUILD_TARGETS = main quantize quantize-stats perplexity embedding vdot train-text-from-scratch convert-llama2c-to-ggml simple server embd-input-test gguf llama-bench
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BUILD_TARGETS = main quantize quantize-stats perplexity embedding vdot train-text-from-scratch convert-llama2c-to-ggml simple save-load-state server embd-input-test gguf llama-bench baby-llama beam_search
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# Binaries only useful for tests
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TEST_TARGETS = tests/test-llama-grammar tests/test-grammar-parser tests/test-double-float tests/test-grad0 tests/test-opt tests/test-quantize-fns tests/test-quantize-perf tests/test-sampling tests/test-tokenizer-0-llama tests/test-tokenizer-0-falcon tests/test-tokenizer-1
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@ -305,7 +305,7 @@ ggml-cuda.o: ggml-cuda.cu ggml-cuda.h
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endif # LLAMA_HIPBLAS
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ifdef LLAMA_METAL
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CFLAGS += -DGGML_USE_METAL -DGGML_METAL_NDEBUG
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CFLAGS += -DGGML_USE_METAL #-DGGML_METAL_NDEBUG
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CXXFLAGS += -DGGML_USE_METAL
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LDFLAGS += -framework Foundation -framework Metal -framework MetalKit
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OBJS += ggml-metal.o
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@ -356,7 +356,7 @@ OBJS += ggml-alloc.o
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llama.o: llama.cpp ggml.h ggml-alloc.h ggml-cuda.h ggml-metal.h llama.h
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$(CXX) $(CXXFLAGS) -c $< -o $@
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common.o: common/common.cpp common/common.h
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common.o: common/common.cpp common/common.h build-info.h
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$(CXX) $(CXXFLAGS) -c $< -o $@
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console.o: common/console.cpp common/console.h
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@ -369,7 +369,7 @@ libllama.so: llama.o ggml.o $(OBJS)
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$(CXX) $(CXXFLAGS) -shared -fPIC -o $@ $^ $(LDFLAGS)
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clean:
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rm -vf *.o *.so *.dll main quantize quantize-stats perplexity embedding benchmark-matmult save-load-state server simple vdot train-text-from-scratch convert-llama2c-to-ggml embd-input-test gguf llama-bench build-info.h $(TEST_TARGETS)
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rm -vf *.o *.so *.dll benchmark-matmult build-info.h $(BUILD_TARGETS) $(TEST_TARGETS)
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#
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# Examples
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@ -409,18 +409,33 @@ $(LIB_PRE)embdinput$(DSO_EXT): examples/embd-input/embd-input.h examples/embd-in
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embd-input-test: $(LIB_PRE)embdinput$(DSO_EXT) examples/embd-input/embd-input-test.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %$(DSO_EXT),$(filter-out %.h,$(filter-out %.hpp,$^))) -o $@ $(LDFLAGS) -L. -lembdinput
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gguf: examples/gguf/gguf.cpp build-info.h ggml.o llama.o $(OBJS)
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gguf: examples/gguf/gguf.cpp ggml.o llama.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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train-text-from-scratch: examples/train-text-from-scratch/train-text-from-scratch.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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train-text-from-scratch: examples/train-text-from-scratch/train-text-from-scratch.cpp ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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convert-llama2c-to-ggml: examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp build-info.h ggml.o llama.o $(OBJS)
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convert-llama2c-to-ggml: examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp ggml.o llama.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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llama-bench: examples/llama-bench/llama-bench.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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baby-llama: examples/baby-llama/baby-llama.cpp ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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beam_search: examples/beam_search/beam_search.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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|
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ifneq '' '$(or $(filter clean,$(MAKECMDGOALS)),$(LLAMA_METAL))'
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BUILD_TARGETS += metal
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endif
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|
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ifdef LLAMA_METAL
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metal: examples/metal/metal.cpp ggml.o $(OBJS)
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$(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS)
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endif
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build-info.h: $(wildcard .git/index) scripts/build-info.sh
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@sh scripts/build-info.sh > $@.tmp
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@if ! cmp -s $@.tmp $@; then \
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|
@ -443,34 +458,34 @@ vdot: pocs/vdot/vdot.cpp ggml.o $(OBJS)
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$(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS)
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|
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tests/test-llama-grammar: tests/test-llama-grammar.cpp build-info.h ggml.o common.o grammar-parser.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.txt,$^) -o $@ $(LDFLAGS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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|
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tests/test-grammar-parser: tests/test-grammar-parser.cpp build-info.h ggml.o llama.o common.o grammar-parser.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.txt,$^) -o $@ $(LDFLAGS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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tests/test-double-float: tests/test-double-float.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.txt,$^) -o $@ $(LDFLAGS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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|
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tests/test-grad0: tests/test-grad0.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.txt,$^) -o $@ $(LDFLAGS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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|
||||
tests/test-opt: tests/test-opt.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.txt,$^) -o $@ $(LDFLAGS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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tests/test-quantize-fns: tests/test-quantize-fns.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.txt,$^) -o $@ $(LDFLAGS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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|
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tests/test-quantize-perf: tests/test-quantize-perf.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.txt,$^) -o $@ $(LDFLAGS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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||||
|
||||
tests/test-sampling: tests/test-sampling.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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||||
$(CXX) $(CXXFLAGS) $(filter-out %.txt,$^) -o $@ $(LDFLAGS)
|
||||
$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
|
||||
|
||||
tests/test-tokenizer-0-falcon: tests/test-tokenizer-0-falcon.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.txt,$^) -o $@ $(LDFLAGS)
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||||
$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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||||
|
||||
tests/test-tokenizer-0-llama: tests/test-tokenizer-0-llama.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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||||
$(CXX) $(CXXFLAGS) $(filter-out %.txt,$^) -o $@ $(LDFLAGS)
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||||
$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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||||
|
||||
tests/test-tokenizer-1: tests/test-tokenizer-1.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.txt,$^) -o $@ $(LDFLAGS)
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||||
$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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||||
|
|
|
@ -113,6 +113,7 @@ as the main playground for developing new features for the [ggml](https://github
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- C#/.NET: [SciSharp/LLamaSharp](https://github.com/SciSharp/LLamaSharp)
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||||
- Scala 3: [donderom/llm4s](https://github.com/donderom/llm4s)
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||||
- Clojure: [phronmophobic/llama.clj](https://github.com/phronmophobic/llama.clj)
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||||
- React Native: [mybigday/llama.rn](https://github.com/mybigday/llama.rn)
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||||
|
||||
**UI:**
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||||
|
||||
|
|
|
@ -48,7 +48,7 @@ def count_model_parts(dir_model: str) -> int:
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if len(sys.argv) < 3:
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print("Usage: convert-h5-to-ggml.py dir-model ftype\n")
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print(f"Usage: python {sys.argv[0]} dir-model ftype\n")
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print(" ftype == 0 -> float32")
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print(" ftype == 1 -> float16")
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sys.exit(1)
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|
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@ -50,7 +50,7 @@ def count_model_parts(dir_model: str) -> int:
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if len(sys.argv) < 3:
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print("Usage: convert-h5-to-ggml.py dir-model ftype\n")
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print(f"Usage: python {sys.argv[0]} dir-model ftype\n")
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print(" ftype == 0 -> float32")
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print(" ftype == 1 -> float16")
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sys.exit(1)
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|
|
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@ -32,7 +32,7 @@ def count_model_parts(dir_model: str) -> int:
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|||
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if len(sys.argv) < 3:
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print("Usage: convert-h5-to-ggml.py dir-model ftype\n")
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print(f"Usage: python {sys.argv[0]} dir-model ftype\n")
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print(" ftype == 0 -> float32")
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print(" ftype == 1 -> float16")
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|
|
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@ -44,7 +44,7 @@ def count_model_parts(dir_model: str) -> int:
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|||
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||||
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||||
if len(sys.argv) < 3:
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||||
print("Usage: convert-h5-to-ggml.py dir-model ftype\n")
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||||
print(f"Usage: python {sys.argv[0]} dir-model ftype\n")
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||||
print(" ftype == 0 -> float32")
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print(" ftype == 1 -> float16")
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||||
|
|
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@ -469,7 +469,7 @@ class UnquantizedTensor(Tensor):
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def permute_part(self, n_part: int, n_head: int) -> 'UnquantizedTensor':
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r = self.ndarray.shape[0] // 3
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return UnquantizedTensor(permute(self.ndarray[r * n_part : r * n_part + r, ...], n_head))
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return UnquantizedTensor(permute(self.ndarray[r * n_part : r * n_part + r, ...], n_head, n_head))
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def part(self, n_part: int) -> 'UnquantizedTensor':
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r = self.ndarray.shape[0] // 3
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|
@ -952,9 +952,10 @@ def convert_model_names(model: LazyModel, params: Params) -> LazyModel:
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#tmp[f"model.layers.{i}.self_attn.v_proj.weight"] = model[f"model.layers.{i}.self_attn.v_proj.weight"]
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||||
elif f"model.layers.{i}.self_attn.W_pack.weight" in model:
|
||||
print(f"Unpacking and permuting layer {i}")
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tmp[f"model.layers.{i}.self_attn.q_proj.weight"] = permute_part_lazy(model[f"model.layers.{i}.self_attn.W_pack.weight"], 0, params.n_head, params.n_head)
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tmp[f"model.layers.{i}.self_attn.k_proj.weight"] = permute_part_lazy(model[f"model.layers.{i}.self_attn.W_pack.weight"], 1, params.n_head, params.n_head_kv)
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tmp[f"model.layers.{i}.self_attn.q_proj.weight"] = permute_part_lazy(model[f"model.layers.{i}.self_attn.W_pack.weight"], 0, params.n_head)
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tmp[f"model.layers.{i}.self_attn.k_proj.weight"] = permute_part_lazy(model[f"model.layers.{i}.self_attn.W_pack.weight"], 1, params.n_head)
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tmp[f"model.layers.{i}.self_attn.v_proj.weight"] = part_lazy (model[f"model.layers.{i}.self_attn.W_pack.weight"], 2)
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del tmp[f"model.layers.{i}.self_attn.W_pack.weight"]
|
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else:
|
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break
|
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|
||||
|
|
71
ggml-metal.m
71
ggml-metal.m
|
@ -11,6 +11,7 @@
|
|||
#define MIN(a, b) ((a) < (b) ? (a) : (b))
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#define MAX(a, b) ((a) > (b) ? (a) : (b))
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|
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// TODO: temporary - reuse llama.cpp logging
|
||||
#ifdef GGML_METAL_NDEBUG
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#define metal_printf(...)
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#else
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|
@ -113,7 +114,7 @@ static NSString * const msl_library_source = @"see metal.metal";
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@end
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struct ggml_metal_context * ggml_metal_init(int n_cb) {
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fprintf(stderr, "%s: allocating\n", __func__);
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metal_printf("%s: allocating\n", __func__);
|
||||
|
||||
struct ggml_metal_context * ctx = malloc(sizeof(struct ggml_metal_context));
|
||||
|
||||
|
@ -132,7 +133,7 @@ struct ggml_metal_context * ggml_metal_init(int n_cb) {
|
|||
|
||||
ctx->library = [ctx->device newLibraryWithSource:msl_library_source options:nil error:&error];
|
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if (error) {
|
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fprintf(stderr, "%s: error: %s\n", __func__, [[error description] UTF8String]);
|
||||
metal_printf("%s: error: %s\n", __func__, [[error description] UTF8String]);
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return NULL;
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||||
}
|
||||
}
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|
@ -146,11 +147,11 @@ struct ggml_metal_context * ggml_metal_init(int n_cb) {
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|||
//NSString * path = [[NSBundle mainBundle] pathForResource:@"../../examples/metal/metal" ofType:@"metal"];
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NSBundle * bundle = [NSBundle bundleForClass:[GGMLMetalClass class]];
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NSString * path = [bundle pathForResource:@"ggml-metal" ofType:@"metal"];
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fprintf(stderr, "%s: loading '%s'\n", __func__, [path UTF8String]);
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metal_printf("%s: loading '%s'\n", __func__, [path UTF8String]);
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|
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NSString * src = [NSString stringWithContentsOfFile:path encoding:NSUTF8StringEncoding error:&error];
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if (error) {
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fprintf(stderr, "%s: error: %s\n", __func__, [[error description] UTF8String]);
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metal_printf("%s: error: %s\n", __func__, [[error description] UTF8String]);
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return NULL;
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||||
}
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|
||||
|
@ -162,7 +163,7 @@ struct ggml_metal_context * ggml_metal_init(int n_cb) {
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|||
ctx->library = [ctx->device newLibraryWithSource:src options:nil error:&error];
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#endif
|
||||
if (error) {
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fprintf(stderr, "%s: error: %s\n", __func__, [[error description] UTF8String]);
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metal_printf("%s: error: %s\n", __func__, [[error description] UTF8String]);
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||||
return NULL;
|
||||
}
|
||||
}
|
||||
|
@ -174,11 +175,11 @@ struct ggml_metal_context * ggml_metal_init(int n_cb) {
|
|||
#define GGML_METAL_ADD_KERNEL(name) \
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ctx->function_##name = [ctx->library newFunctionWithName:@"kernel_"#name]; \
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ctx->pipeline_##name = [ctx->device newComputePipelineStateWithFunction:ctx->function_##name error:&error]; \
|
||||
fprintf(stderr, "%s: loaded %-32s %16p | th_max = %4d | th_width = %4d\n", __func__, "kernel_"#name, (void *) ctx->pipeline_##name, \
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metal_printf("%s: loaded %-32s %16p | th_max = %4d | th_width = %4d\n", __func__, "kernel_"#name, (void *) ctx->pipeline_##name, \
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(int) ctx->pipeline_##name.maxTotalThreadsPerThreadgroup, \
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||||
(int) ctx->pipeline_##name.threadExecutionWidth); \
|
||||
if (error) { \
|
||||
fprintf(stderr, "%s: load pipeline error: %s\n", __func__, [[error description] UTF8String]); \
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||||
metal_printf("%s: load pipeline error: %s\n", __func__, [[error description] UTF8String]); \
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||||
return NULL; \
|
||||
}
|
||||
|
||||
|
@ -230,19 +231,19 @@ struct ggml_metal_context * ggml_metal_init(int n_cb) {
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|||
#undef GGML_METAL_ADD_KERNEL
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||||
}
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||||
|
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fprintf(stderr, "%s: recommendedMaxWorkingSetSize = %8.2f MB\n", __func__, ctx->device.recommendedMaxWorkingSetSize / 1024.0 / 1024.0);
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||||
fprintf(stderr, "%s: hasUnifiedMemory = %s\n", __func__, ctx->device.hasUnifiedMemory ? "true" : "false");
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||||
metal_printf("%s: recommendedMaxWorkingSetSize = %8.2f MB\n", __func__, ctx->device.recommendedMaxWorkingSetSize / 1024.0 / 1024.0);
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||||
metal_printf("%s: hasUnifiedMemory = %s\n", __func__, ctx->device.hasUnifiedMemory ? "true" : "false");
|
||||
if (ctx->device.maxTransferRate != 0) {
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||||
fprintf(stderr, "%s: maxTransferRate = %8.2f MB/s\n", __func__, ctx->device.maxTransferRate / 1024.0 / 1024.0);
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||||
metal_printf("%s: maxTransferRate = %8.2f MB/s\n", __func__, ctx->device.maxTransferRate / 1024.0 / 1024.0);
|
||||
} else {
|
||||
fprintf(stderr, "%s: maxTransferRate = built-in GPU\n", __func__);
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||||
metal_printf("%s: maxTransferRate = built-in GPU\n", __func__);
|
||||
}
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||||
|
||||
return ctx;
|
||||
}
|
||||
|
||||
void ggml_metal_free(struct ggml_metal_context * ctx) {
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||||
fprintf(stderr, "%s: deallocating\n", __func__);
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||||
metal_printf("%s: deallocating\n", __func__);
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||||
#define GGML_METAL_DEL_KERNEL(name) \
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||||
[ctx->function_##name release]; \
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||||
[ctx->pipeline_##name release];
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||||
|
@ -311,7 +312,7 @@ void * ggml_metal_host_malloc(size_t n) {
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|||
void * data = NULL;
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||||
const int result = posix_memalign((void **) &data, getpagesize(), n);
|
||||
if (result != 0) {
|
||||
fprintf(stderr, "%s: error: posix_memalign failed\n", __func__);
|
||||
metal_printf("%s: error: posix_memalign failed\n", __func__);
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||||
return NULL;
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||||
}
|
||||
|
||||
|
@ -339,7 +340,7 @@ int * ggml_metal_get_concur_list(struct ggml_metal_context * ctx) {
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|||
// Metal buffer based on the host memory pointer
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||||
//
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||||
static id<MTLBuffer> ggml_metal_get_buffer(struct ggml_metal_context * ctx, struct ggml_tensor * t, size_t * offs) {
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||||
//fprintf(stderr, "%s: data tensor '%16s', offs_data = %8ld, offs_eval = %8ld, offs_cach = %8ld\n", __func__, t->name, offs_data, offs_eval, offs_cach);
|
||||
//metal_printf("%s: data tensor '%16s', offs_data = %8ld, offs_eval = %8ld, offs_cach = %8ld\n", __func__, t->name, offs_data, offs_eval, offs_cach);
|
||||
|
||||
const int64_t tsize = ggml_nbytes(t);
|
||||
|
||||
|
@ -350,13 +351,13 @@ static id<MTLBuffer> ggml_metal_get_buffer(struct ggml_metal_context * ctx, stru
|
|||
if (ioffs >= 0 && ioffs + tsize <= (int64_t) ctx->buffers[i].size) {
|
||||
*offs = (size_t) ioffs;
|
||||
|
||||
//fprintf(stderr, "%s: '%s' tensor '%16s', offs = %8ld\n", __func__, ctx->buffers[i].name, t->name, *offs);
|
||||
//metal_printf("%s: '%s' tensor '%16s', offs = %8ld\n", __func__, ctx->buffers[i].name, t->name, *offs);
|
||||
|
||||
return ctx->buffers[i].metal;
|
||||
}
|
||||
}
|
||||
|
||||
fprintf(stderr, "%s: error: buffer is nil\n", __func__);
|
||||
metal_printf("%s: error: buffer is nil\n", __func__);
|
||||
|
||||
return nil;
|
||||
}
|
||||
|
@ -368,7 +369,7 @@ bool ggml_metal_add_buffer(
|
|||
size_t size,
|
||||
size_t max_size) {
|
||||
if (ctx->n_buffers >= GGML_METAL_MAX_BUFFERS) {
|
||||
fprintf(stderr, "%s: too many buffers\n", __func__);
|
||||
metal_printf("%s: too many buffers\n", __func__);
|
||||
return false;
|
||||
}
|
||||
|
||||
|
@ -378,7 +379,7 @@ bool ggml_metal_add_buffer(
|
|||
const int64_t ioffs = (int64_t) data - (int64_t) ctx->buffers[i].data;
|
||||
|
||||
if (ioffs >= 0 && ioffs < (int64_t) ctx->buffers[i].size) {
|
||||
fprintf(stderr, "%s: error: buffer '%s' overlaps with '%s'\n", __func__, name, ctx->buffers[i].name);
|
||||
metal_printf("%s: error: buffer '%s' overlaps with '%s'\n", __func__, name, ctx->buffers[i].name);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
@ -399,11 +400,11 @@ bool ggml_metal_add_buffer(
|
|||
ctx->buffers[ctx->n_buffers].metal = [ctx->device newBufferWithBytesNoCopy:data length:size_aligned options:MTLResourceStorageModeShared deallocator:nil];
|
||||
|
||||
if (ctx->buffers[ctx->n_buffers].metal == nil) {
|
||||
fprintf(stderr, "%s: failed to allocate '%-16s' buffer, size = %8.2f MB\n", __func__, name, size_aligned / 1024.0 / 1024.0);
|
||||
metal_printf("%s: failed to allocate '%-16s' buffer, size = %8.2f MB\n", __func__, name, size_aligned / 1024.0 / 1024.0);
|
||||
return false;
|
||||
}
|
||||
|
||||
fprintf(stderr, "%s: allocated '%-16s' buffer, size = %8.2f MB", __func__, name, size_aligned / 1024.0 / 1024.0);
|
||||
metal_printf("%s: allocated '%-16s' buffer, size = %8.2f MB", __func__, name, size_aligned / 1024.0 / 1024.0);
|
||||
|
||||
++ctx->n_buffers;
|
||||
} else {
|
||||
|
@ -423,27 +424,27 @@ bool ggml_metal_add_buffer(
|
|||
ctx->buffers[ctx->n_buffers].metal = [ctx->device newBufferWithBytesNoCopy:(void *) ((uint8_t *) data + i) length:size_step_aligned options:MTLResourceStorageModeShared deallocator:nil];
|
||||
|
||||
if (ctx->buffers[ctx->n_buffers].metal == nil) {
|
||||
fprintf(stderr, "%s: failed to allocate '%-16s' buffer, size = %8.2f MB\n", __func__, name, size_step_aligned / 1024.0 / 1024.0);
|
||||
metal_printf("%s: failed to allocate '%-16s' buffer, size = %8.2f MB\n", __func__, name, size_step_aligned / 1024.0 / 1024.0);
|
||||
return false;
|
||||
}
|
||||
|
||||
fprintf(stderr, "%s: allocated '%-16s' buffer, size = %8.2f MB, offs = %12ld", __func__, name, size_step_aligned / 1024.0 / 1024.0, i);
|
||||
metal_printf("%s: allocated '%-16s' buffer, size = %8.2f MB, offs = %12ld", __func__, name, size_step_aligned / 1024.0 / 1024.0, i);
|
||||
if (i + size_step < size) {
|
||||
fprintf(stderr, "\n");
|
||||
metal_printf("\n");
|
||||
}
|
||||
|
||||
++ctx->n_buffers;
|
||||
}
|
||||
}
|
||||
|
||||
fprintf(stderr, ", (%8.2f / %8.2f)",
|
||||
metal_printf(", (%8.2f / %8.2f)",
|
||||
ctx->device.currentAllocatedSize / 1024.0 / 1024.0,
|
||||
ctx->device.recommendedMaxWorkingSetSize / 1024.0 / 1024.0);
|
||||
|
||||
if (ctx->device.currentAllocatedSize > ctx->device.recommendedMaxWorkingSetSize) {
|
||||
fprintf(stderr, ", warning: current allocated size is greater than the recommended max working set size\n");
|
||||
metal_printf(", warning: current allocated size is greater than the recommended max working set size\n");
|
||||
} else {
|
||||
fprintf(stderr, "\n");
|
||||
metal_printf("\n");
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -453,8 +454,6 @@ bool ggml_metal_add_buffer(
|
|||
void ggml_metal_set_tensor(
|
||||
struct ggml_metal_context * ctx,
|
||||
struct ggml_tensor * t) {
|
||||
metal_printf("%s: set input for tensor '%s'\n", __func__, t->name);
|
||||
|
||||
size_t offs;
|
||||
id<MTLBuffer> id_dst = ggml_metal_get_buffer(ctx, t, &offs);
|
||||
|
||||
|
@ -464,8 +463,6 @@ void ggml_metal_set_tensor(
|
|||
void ggml_metal_get_tensor(
|
||||
struct ggml_metal_context * ctx,
|
||||
struct ggml_tensor * t) {
|
||||
metal_printf("%s: extract results for tensor '%s'\n", __func__, t->name);
|
||||
|
||||
size_t offs;
|
||||
id<MTLBuffer> id_src = ggml_metal_get_buffer(ctx, t, &offs);
|
||||
|
||||
|
@ -560,15 +557,13 @@ void ggml_metal_graph_find_concurrency(
|
|||
}
|
||||
|
||||
if (ctx->concur_list_len > GGML_MAX_CONCUR) {
|
||||
fprintf(stderr, "%s: too many elements for metal ctx->concur_list!\n", __func__);
|
||||
metal_printf("%s: too many elements for metal ctx->concur_list!\n", __func__);
|
||||
}
|
||||
}
|
||||
|
||||
void ggml_metal_graph_compute(
|
||||
struct ggml_metal_context * ctx,
|
||||
struct ggml_cgraph * gf) {
|
||||
metal_printf("%s: evaluating graph\n", __func__);
|
||||
|
||||
@autoreleasepool {
|
||||
|
||||
// if there is ctx->concur_list, dispatch concurrently
|
||||
|
@ -616,7 +611,7 @@ void ggml_metal_graph_compute(
|
|||
continue;
|
||||
}
|
||||
|
||||
metal_printf("%s: encoding node %3d, op = %8s\n", __func__, i, ggml_op_name(gf->nodes[i]->op));
|
||||
//metal_printf("%s: encoding node %3d, op = %8s\n", __func__, i, ggml_op_name(gf->nodes[i]->op));
|
||||
|
||||
struct ggml_tensor * src0 = gf->nodes[i]->src[0];
|
||||
struct ggml_tensor * src1 = gf->nodes[i]->src[1];
|
||||
|
@ -764,7 +759,7 @@ void ggml_metal_graph_compute(
|
|||
} break;
|
||||
default:
|
||||
{
|
||||
fprintf(stderr, "%s: node %3d, op = %8s not implemented\n", __func__, i, ggml_op_name(dst->op));
|
||||
metal_printf("%s: node %3d, op = %8s not implemented\n", __func__, i, ggml_op_name(dst->op));
|
||||
GGML_ASSERT(false);
|
||||
}
|
||||
} break;
|
||||
|
@ -923,7 +918,7 @@ void ggml_metal_graph_compute(
|
|||
} break;
|
||||
default:
|
||||
{
|
||||
fprintf(stderr, "Asserting on type %d\n",(int)src0t);
|
||||
metal_printf("Asserting on type %d\n",(int)src0t);
|
||||
GGML_ASSERT(false && "not implemented");
|
||||
}
|
||||
};
|
||||
|
@ -1161,7 +1156,7 @@ void ggml_metal_graph_compute(
|
|||
} break;
|
||||
default:
|
||||
{
|
||||
fprintf(stderr, "%s: node %3d, op = %8s not implemented\n", __func__, i, ggml_op_name(dst->op));
|
||||
metal_printf("%s: node %3d, op = %8s not implemented\n", __func__, i, ggml_op_name(dst->op));
|
||||
GGML_ASSERT(false);
|
||||
}
|
||||
}
|
||||
|
@ -1186,7 +1181,7 @@ void ggml_metal_graph_compute(
|
|||
|
||||
MTLCommandBufferStatus status = (MTLCommandBufferStatus) [ctx->command_buffers[i] status];
|
||||
if (status != MTLCommandBufferStatusCompleted) {
|
||||
fprintf(stderr, "%s: command buffer %d failed with status %lu\n", __func__, i, status);
|
||||
metal_printf("%s: command buffer %d failed with status %lu\n", __func__, i, status);
|
||||
GGML_ASSERT(false);
|
||||
}
|
||||
}
|
||||
|
|
2
llama.h
2
llama.h
|
@ -534,7 +534,7 @@ extern "C" {
|
|||
// If this is not called, or NULL is supplied, everything is output on stderr.
|
||||
LLAMA_API void llama_log_set(llama_log_callback log_callback, void * user_data);
|
||||
|
||||
LLAMA_API void llama_dump_timing_info_yaml(FILE * stream, const llama_context * ctx);
|
||||
LLAMA_API void llama_dump_timing_info_yaml(FILE * stream, const struct llama_context * ctx);
|
||||
|
||||
#ifdef __cplusplus
|
||||
}
|
||||
|
|
|
@ -20,6 +20,7 @@ fi
|
|||
model="$1"
|
||||
out="../tmp/results-${model}"
|
||||
|
||||
set -o pipefail
|
||||
set -e
|
||||
|
||||
mkdir -p ${out}
|
||||
|
|
|
@ -20,6 +20,7 @@ fi
|
|||
model="$1"
|
||||
out="../tmp/results-${model}"
|
||||
|
||||
set -o pipefail
|
||||
set -e
|
||||
|
||||
mkdir -p ${out}
|
||||
|
|
|
@ -17,6 +17,7 @@ if [ ! -z "$3" ]; then
|
|||
args="$3"
|
||||
fi
|
||||
|
||||
set -o pipefail
|
||||
set -e
|
||||
|
||||
model="$1"
|
||||
|
|
Loading…
Add table
Add a link
Reference in a new issue