mirror of
https://github.com/ggerganov/llama.cpp.git
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tests : Fix compilation warnings (Linux/GCC) (#2451)
* fix hellaswag print format, cast away warning in test-double-float * c++11 cannot use designated initializers * add static to test-grad0.c internal functions * use memcpy in test-double-float.c * port c tests to c++ * use initializer list for ggml_init_params
This commit is contained in:
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a312193e18
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6
Makefile
6
Makefile
@ -411,13 +411,13 @@ benchmark-matmult: examples/benchmark/benchmark-matmult.cpp build-info.h ggml.o
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vdot: pocs/vdot/vdot.cpp ggml.o $(OBJS)
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vdot: pocs/vdot/vdot.cpp ggml.o $(OBJS)
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$(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS)
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$(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS)
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tests/test-double-float: tests/test-double-float.c build-info.h ggml.o llama.o common.o $(OBJS)
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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) $(filter-out %.txt,$^) -o $@ $(LDFLAGS)
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tests/test-grad0: tests/test-grad0.c build-info.h ggml.o llama.o common.o $(OBJS)
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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) $(filter-out %.txt,$^) -o $@ $(LDFLAGS)
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tests/test-opt: tests/test-opt.c build-info.h ggml.o llama.o common.o $(OBJS)
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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) $(filter-out %.txt,$^) -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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tests/test-quantize-fns: tests/test-quantize-fns.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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@ -572,7 +572,7 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
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fprintf(stdout, " --temp N temperature (default: %.1f)\n", (double)params.temp);
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fprintf(stdout, " --temp N temperature (default: %.1f)\n", (double)params.temp);
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fprintf(stdout, " --perplexity compute perplexity over each ctx window of the prompt\n");
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fprintf(stdout, " --perplexity compute perplexity over each ctx window of the prompt\n");
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fprintf(stdout, " --hellaswag compute HellaSwag score over random tasks from datafile supplied with -f\n");
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fprintf(stdout, " --hellaswag compute HellaSwag score over random tasks from datafile supplied with -f\n");
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fprintf(stdout, " --hellaswag-tasks N number of tasks to use when computing the HellaSwag score (default: %d)\n", params.hellaswag_tasks);
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fprintf(stdout, " --hellaswag-tasks N number of tasks to use when computing the HellaSwag score (default: %zu)\n", params.hellaswag_tasks);
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fprintf(stdout, " --keep N number of tokens to keep from the initial prompt (default: %d, -1 = all)\n", params.n_keep);
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fprintf(stdout, " --keep N number of tokens to keep from the initial prompt (default: %d, -1 = all)\n", params.n_keep);
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fprintf(stdout, " --chunks N max number of chunks to process (default: %d, -1 = all)\n", params.n_chunks);
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fprintf(stdout, " --chunks N max number of chunks to process (default: %d, -1 = all)\n", params.n_chunks);
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if (llama_mlock_supported()) {
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if (llama_mlock_supported()) {
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@ -10,5 +10,5 @@ cp -rpv ../ggml/src/ggml-metal.m ./ggml-metal.m
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cp -rpv ../ggml/src/ggml-metal.metal ./ggml-metal.metal
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cp -rpv ../ggml/src/ggml-metal.metal ./ggml-metal.metal
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cp -rpv ../ggml/include/ggml/ggml.h ./ggml.h
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cp -rpv ../ggml/include/ggml/ggml.h ./ggml.h
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cp -rpv ../ggml/tests/test-opt.c ./tests/test-opt.c
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cp -rpv ../ggml/tests/test-opt.cpp ./tests/test-opt.cpp
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cp -rpv ../ggml/tests/test-grad0.c ./tests/test-grad0.c
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cp -rpv ../ggml/tests/test-grad0.cpp ./tests/test-grad0.cpp
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@ -6,10 +6,10 @@ function(llama_add_test source)
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add_test(NAME ${TEST_TARGET} COMMAND $<TARGET_FILE:${TEST_TARGET}> ${ARGN})
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add_test(NAME ${TEST_TARGET} COMMAND $<TARGET_FILE:${TEST_TARGET}> ${ARGN})
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endfunction()
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endfunction()
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# llama_add_test(test-double-float.c) # SLOW
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# llama_add_test(test-double-float.cpp) # SLOW
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llama_add_test(test-quantize-fns.cpp)
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llama_add_test(test-quantize-fns.cpp)
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llama_add_test(test-quantize-perf.cpp)
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llama_add_test(test-quantize-perf.cpp)
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llama_add_test(test-sampling.cpp)
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llama_add_test(test-sampling.cpp)
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llama_add_test(test-tokenizer-0.cpp ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab.bin)
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llama_add_test(test-tokenizer-0.cpp ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab.bin)
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llama_add_test(test-grad0.c) # SLOW
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llama_add_test(test-grad0.cpp) # SLOW
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# llama_add_test(test-opt.c) # SLOW
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# llama_add_test(test-opt.cpp) # SLOW
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@ -3,10 +3,11 @@
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// This is done by checking all finite (non-NaN, non-infinite) floats.
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// This is done by checking all finite (non-NaN, non-infinite) floats.
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#undef NDEBUG
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#undef NDEBUG
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#include <assert.h>
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#include <cassert>
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#include <immintrin.h>
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#include <immintrin.h>
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#include <math.h>
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#include <cmath>
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#include <stdint.h>
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#include <cstdint>
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#include <cstring>
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#pragma GCC diagnostic push
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#pragma GCC diagnostic push
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#pragma GCC diagnostic ignored "-Wdouble-promotion"
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#pragma GCC diagnostic ignored "-Wdouble-promotion"
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@ -32,8 +33,9 @@ inline static float silu_float(float x) {
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int main(void) {
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int main(void) {
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uint32_t x = UINT32_MAX;
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uint32_t x = UINT32_MAX;
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do {
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do {
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float f = *(float *)&x;
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float f;
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assert(!isfinite(f) || (round_orig(f) == round_float(f)));
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memcpy(&f, &x, sizeof(x));
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assert(!std::isfinite(f) || (round_orig(f) == round_float(f)));
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} while (x--);
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} while (x--);
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#ifdef __F16C__
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#ifdef __F16C__
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@ -1,10 +1,10 @@
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#define _CRT_SECURE_NO_DEPRECATE // Disables ridiculous "unsafe" warnigns on Windows
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#define _CRT_SECURE_NO_DEPRECATE // Disables ridiculous "unsafe" warnigns on Windows
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#include "ggml.h"
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#include "ggml.h"
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#include <math.h>
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#include <cmath>
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#include <stdio.h>
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#include <cstdio>
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#include <stdlib.h>
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#include <cstdlib>
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#include <assert.h>
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#include <cassert>
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#if defined(_MSC_VER)
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#if defined(_MSC_VER)
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#pragma warning(disable: 4244 4267) // possible loss of data
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#pragma warning(disable: 4244 4267) // possible loss of data
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@ -47,16 +47,16 @@
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#define GGML_PRINT(...) printf(__VA_ARGS__)
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#define GGML_PRINT(...) printf(__VA_ARGS__)
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float frand(void) {
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static float frand(void) {
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return (float)rand()/(float)RAND_MAX;
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return (float)rand()/(float)RAND_MAX;
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}
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}
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int irand(int n) {
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static int irand(int n) {
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if (n == 0) return 0;
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if (n == 0) return 0;
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return rand()%n;
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return rand()%n;
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}
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}
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void get_random_dims(int64_t * dims, int ndims) {
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static void get_random_dims(int64_t * dims, int ndims) {
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dims[0] = dims[1] = dims[2] = dims[3] = 1;
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dims[0] = dims[1] = dims[2] = dims[3] = 1;
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for (int i = 0; i < ndims; i++) {
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for (int i = 0; i < ndims; i++) {
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@ -64,7 +64,7 @@ void get_random_dims(int64_t * dims, int ndims) {
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}
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}
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}
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}
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struct ggml_tensor * get_random_tensor_f32(
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static struct ggml_tensor * get_random_tensor_f32(
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struct ggml_context * ctx0,
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struct ggml_context * ctx0,
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int ndims,
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int ndims,
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int64_t ne[],
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int64_t ne[],
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@ -112,7 +112,7 @@ struct ggml_tensor * get_random_tensor_f32(
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return result;
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return result;
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}
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}
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struct ggml_tensor * get_random_tensor_f16(
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static struct ggml_tensor * get_random_tensor_f16(
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struct ggml_context * ctx0,
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struct ggml_context * ctx0,
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int ndims,
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int ndims,
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int64_t ne[],
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int64_t ne[],
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@ -160,7 +160,7 @@ struct ggml_tensor * get_random_tensor_f16(
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return result;
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return result;
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}
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}
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struct ggml_tensor * get_random_tensor_i32(
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static struct ggml_tensor * get_random_tensor_i32(
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struct ggml_context * ctx0,
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struct ggml_context * ctx0,
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int ndims,
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int ndims,
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int64_t ne[],
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int64_t ne[],
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@ -208,7 +208,7 @@ struct ggml_tensor * get_random_tensor_i32(
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return result;
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return result;
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}
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}
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void print_elements(const char* label, const struct ggml_tensor * t) {
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static void print_elements(const char* label, const struct ggml_tensor * t) {
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if (!t) {
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if (!t) {
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printf("%s: %s = null\n", __func__, label);
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printf("%s: %s = null\n", __func__, label);
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return;
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return;
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@ -228,7 +228,7 @@ void print_elements(const char* label, const struct ggml_tensor * t) {
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}
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}
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bool check_gradient(
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static bool check_gradient(
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const char * op_name,
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const char * op_name,
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struct ggml_context * ctx0,
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struct ggml_context * ctx0,
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struct ggml_tensor * x[],
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struct ggml_tensor * x[],
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@ -310,7 +310,7 @@ bool check_gradient(
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}
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}
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// TODO: clean-up this ..
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// TODO: clean-up this ..
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bool check_mat_mul(
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static bool check_mat_mul(
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const struct ggml_tensor * y,
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const struct ggml_tensor * y,
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const struct ggml_tensor * x0,
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const struct ggml_tensor * x0,
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const struct ggml_tensor * x1) {
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const struct ggml_tensor * x1) {
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@ -373,9 +373,9 @@ bool check_mat_mul(
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int main(int argc, const char ** argv) {
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int main(int argc, const char ** argv) {
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struct ggml_init_params params = {
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struct ggml_init_params params = {
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.mem_size = 128*1024*1024,
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/* .mem_size = */ 128*1024*1024,
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.mem_buffer = NULL,
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/* .mem_buffer = */ NULL,
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.no_alloc = false,
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/* .no_alloc = */ false,
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};
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};
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int64_t ne[4];
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int64_t ne[4];
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@ -1,9 +1,9 @@
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#include "ggml.h"
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#include "ggml.h"
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#include <math.h>
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#include <cmath>
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#include <stdio.h>
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#include <cstdio>
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#include <stdlib.h>
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#include <cstdlib>
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#include <assert.h>
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#include <cassert>
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#define MAX_NARGS 2
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#define MAX_NARGS 2
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@ -119,10 +119,11 @@ void set_element(struct ggml_tensor * t, int idx, float value) {
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int main(void) {
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int main(void) {
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struct ggml_init_params params = {
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struct ggml_init_params params = {
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.mem_size = 1024*1024*1024,
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/* .mem_size = */ 1024*1024*1024,
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.mem_buffer = NULL,
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/* .mem_buffer = */ NULL,
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.no_alloc = false,
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/* .no_alloc = */ false,
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};
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};
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struct ggml_context * ctx = ggml_init(params);
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struct ggml_context * ctx = ggml_init(params);
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int64_t ne1[4] = {4, 128, 1, 1};
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int64_t ne1[4] = {4, 128, 1, 1};
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