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Merge branch 'master' into concedo_experimental
# Conflicts: # Makefile # README.md # docs/token_generation_performance_tips.md # grammars/README.md # scripts/sync-ggml.sh # tests/CMakeLists.txt # tests/test-grad0.cpp # tests/test-opt.cpp
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commit
35a97e14b2
49 changed files with 4972 additions and 3131 deletions
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@ -172,7 +172,8 @@ int main(int argc, char ** argv) {
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struct ggml_tensor * m11xm2 = ggml_mul_mat(ctx, m11, m2);
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// printf("Creating compute graph\n");
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struct ggml_cgraph gf = ggml_build_forward(m11xm2);
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struct ggml_cgraph * gf = ggml_new_graph(ctx);
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ggml_build_forward_expand(gf, m11xm2);
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printf("n_threads=%i\n", benchmark_params.n_threads);
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@ -181,9 +182,9 @@ int main(int argc, char ** argv) {
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std::vector<uint8_t> work_buffer;
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ggml_graph_compute_helper(work_buffer, &gf, benchmark_params.n_threads);
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ggml_graph_compute_helper(work_buffer, gf, benchmark_params.n_threads);
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TENSOR_DUMP(gf.nodes[0]);
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TENSOR_DUMP(gf->nodes[0]);
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printf("\n------ Test 2 - Matrix Mult via %s code\n", ggml_type_name(qtype));
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@ -201,7 +202,8 @@ int main(int argc, char ** argv) {
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struct ggml_tensor * q31 = ggml_mul_mat(ctx, q11, m2);
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// printf("Creating compute graph\n");
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struct ggml_cgraph gf31 = ggml_build_forward(q31);
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struct ggml_cgraph * gf31 = ggml_new_graph(ctx);
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ggml_build_forward_expand(gf31, q31);
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// Set up a second graph computation to make sure we override the CPU cache lines
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// printf("Creating new tensor q12 & Running quantize\n");
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@ -212,7 +214,8 @@ int main(int argc, char ** argv) {
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struct ggml_tensor * q32 = ggml_mul_mat(ctx, q12, m2);
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//printf("Creating compute graph\n");
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struct ggml_cgraph gf32 = ggml_build_forward(q32);
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struct ggml_cgraph * gf32 = ggml_new_graph(ctx);
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ggml_build_forward_expand(gf32, q32);
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printf("n_threads=%i\n", benchmark_params.n_threads);
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const int dimx = sizex;
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@ -224,7 +227,7 @@ int main(int argc, char ** argv) {
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// Let's use the F32 result from above as a reference for the quantized multiplication
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float sum_of_F32_reference = tensor_sum_elements(gf.nodes[0]);
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float sum_of_F32_reference = tensor_sum_elements(gf->nodes[0]);
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printf("Iteration;NThreads; SizeX; SizeY; SizeZ; Required_FLOPS; Elapsed_u_Seconds; gigaFLOPS\n");
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printf("=====================================================================================\n");
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@ -234,7 +237,7 @@ int main(int argc, char ** argv) {
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long long int start = ggml_time_us();
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//printf("Running ggml_graph_compute\n");
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ggml_graph_compute_helper(work_buffer, &gf31, benchmark_params.n_threads);
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ggml_graph_compute_helper(work_buffer, gf31, benchmark_params.n_threads);
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long long int stop = ggml_time_us();
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long long int usec = stop-start;
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@ -252,7 +255,7 @@ int main(int argc, char ** argv) {
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// Check that the matrix multiplication result is in the right ballpark
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// We cannot use the exact value from the F32 multiplication because the quantizuation will be slightly different
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float sum_of_Q4_result = tensor_sum_elements(gf31.nodes[0]);
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float sum_of_Q4_result = tensor_sum_elements(gf31->nodes[0]);
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float delta = std::abs(sum_of_Q4_result - sum_of_F32_reference);
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float allowed_delta = (sum_of_F32_reference) / 1000 / 1000; // Let's accept an epsilon of 10^-6
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@ -267,7 +270,7 @@ int main(int argc, char ** argv) {
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}
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// Running a different graph computation to make sure we override the CPU cache lines
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ggml_graph_compute_helper(work_buffer, &gf32, benchmark_params.n_threads);
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ggml_graph_compute_helper(work_buffer, gf32, benchmark_params.n_threads);
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}
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printf("\n");
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printf("Average%78.2f\n",gflops_sum/((double)benchmark_params.n_iterations));
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