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Diffstat (limited to 'tests/test-opt.c')
| -rw-r--r-- | tests/test-opt.c | 205 |
1 files changed, 205 insertions, 0 deletions
diff --git a/tests/test-opt.c b/tests/test-opt.c new file mode 100644 index 0000000..d001615 --- /dev/null +++ b/tests/test-opt.c @@ -0,0 +1,205 @@ +#include "ggml.h" + +#include <math.h> +#include <stdio.h> +#include <stdlib.h> +#include <assert.h> + +#define MAX_NARGS 2 + + +// +// logging +// +#define GGML_DEBUG 0 +#if (GGML_DEBUG >= 1) +#define GGML_PRINT_DEBUG(...) printf(__VA_ARGS__) +#else +#define GGML_PRINT_DEBUG(...) +#endif + +#if (GGML_DEBUG >= 5) +#define GGML_PRINT_DEBUG_5(...) printf(__VA_ARGS__) +#else +#define GGML_PRINT_DEBUG_5(...) +#endif + +#if (GGML_DEBUG >= 10) +#define GGML_PRINT_DEBUG_10(...) printf(__VA_ARGS__) +#else +#define GGML_PRINT_DEBUG_10(...) +#endif + +#define GGML_PRINT(...) printf(__VA_ARGS__) + + +float frand() { + return (float)rand()/(float)RAND_MAX; +} + +int irand(int n) { + return rand()%n; +} + +void get_random_dims(int64_t * dims, int ndims) { + dims[0] = dims[1] = dims[2] = dims[3] = 1; + + for (int i = 0; i < ndims; i++) { + dims[i] = 1 + irand(4); + } +} + +void get_random_dims_minmax(int64_t * dims, int ndims, int min, int max) { + dims[0] = dims[1] = dims[2] = dims[3] = 1; + + for (int i = 0; i < ndims; i++) { + dims[i] = min + irand(max-min); + } +} + + +struct ggml_tensor * get_random_tensor( + struct ggml_context * ctx0, + int ndims, + int64_t ne[], + float fmin, + float fmax) { + struct ggml_tensor * result = ggml_new_tensor(ctx0, GGML_TYPE_F32, ndims, ne); + + switch (ndims) { + case 1: + for (int i0 = 0; i0 < ne[0]; i0++) { + ((float *)result->data)[i0] = frand()*(fmax - fmin) + fmin; + } + break; + case 2: + for (int i1 = 0; i1 < ne[1]; i1++) { + for (int i0 = 0; i0 < ne[0]; i0++) { + ((float *)result->data)[i1*ne[0] + i0] = frand()*(fmax - fmin) + fmin; + } + } + break; + case 3: + for (int i2 = 0; i2 < ne[2]; i2++) { + for (int i1 = 0; i1 < ne[1]; i1++) { + for (int i0 = 0; i0 < ne[0]; i0++) { + ((float *)result->data)[i2*ne[1]*ne[0] + i1*ne[0] + i0] = frand()*(fmax - fmin) + fmin; + } + } + } + break; + case 4: + for (int i3 = 0; i3 < ne[3]; i3++) { + for (int i2 = 0; i2 < ne[2]; i2++) { + for (int i1 = 0; i1 < ne[1]; i1++) { + for (int i0 = 0; i0 < ne[0]; i0++) { + ((float *)result->data)[i3*ne[2]*ne[1]*ne[0] + i2*ne[1]*ne[0] + i1*ne[0] + i0] = frand()*(fmax - fmin) + fmin; + } + } + } + } + break; + default: + assert(false); + }; + + return result; +} + +float get_element(const struct ggml_tensor * t, int idx) { + return ((float *)t->data)[idx]; +} + +void set_element(struct ggml_tensor * t, int idx, float value) { + ((float *)t->data)[idx] = value; +} + +int main(int argc, const char ** argv) { + struct ggml_init_params params = { + .mem_size = 1024*1024*1024, + .mem_buffer = NULL, + .no_alloc = false, + }; + struct ggml_context * ctx = ggml_init(params); + + int64_t ne1[4] = {4, 1024, 1, 1}; + int64_t ne2[4] = {4, 2048, 1, 1};; + int64_t ne3[4] = {1024, 2048, 1, 1}; + + struct ggml_tensor * a = get_random_tensor(ctx, 2, ne1, -1, +1); + struct ggml_tensor * b = get_random_tensor(ctx, 2, ne2, -1, +1); + ggml_set_param(ctx, a); + ggml_set_param(ctx, b); + + struct ggml_tensor * c = get_random_tensor(ctx, 2, ne3, -1, +1); + + struct ggml_tensor * ab = ggml_mul_mat(ctx, a, b); + struct ggml_tensor * d = ggml_sub(ctx, c, ab); + struct ggml_tensor * e = ggml_sum(ctx, ggml_sqr(ctx, d)); + + + struct ggml_cgraph ge = ggml_build_forward(e); + ggml_graph_reset (&ge); + ggml_graph_compute(ctx, &ge); + const float fe = ggml_get_f32_1d(e, 0); + printf("%s: e = %.4f\n", __func__, fe); + + struct ggml_opt_params opt_params = ggml_opt_default_params(GGML_OPT_ADAM); + + ggml_opt(ctx, opt_params, e); + + ggml_graph_reset (&ge); + ggml_graph_compute(ctx, &ge); + const float fe_opt = ggml_get_f32_1d(e, 0); + printf("%s: original e = %.4f\n", __func__, fe); + printf("%s: optimized e = %.4f\n", __func__, fe_opt); + + const bool success = (fe_opt <= fe); + assert(success); + + ggml_free(ctx); + return success ? 0 : -1; +} +// int64_t ne1[4] = {4, 128, 1, 1}; +// int64_t ne2[4] = {4, 256, 1, 1};; +// int64_t ne3[4] = {128, 256, 1, 1}; +// main: original e = 25890.9375 +// main: optimized e = 10094.7031 + +// int64_t ne1[4] = {8, 128, 1, 1}; +// int64_t ne2[4] = {8, 256, 1, 1};; +// int64_t ne3[4] = {128, 256, 1, 1}; +// main: original e = 39429.5078 +// main: optimized e = 9275.8936 + +// int64_t ne1[4] = {16, 128, 1, 1}; +// int64_t ne2[4] = {16, 256, 1, 1};; +// int64_t ne3[4] = {128, 256, 1, 1}; +// main: original e = 68371.1328 +// main: optimized e = 7854.4502 + + +// int64_t ne1[4] = {32, 128, 1, 1}; +// int64_t ne2[4] = {32, 256, 1, 1};; +// int64_t ne3[4] = {128, 256, 1, 1}; +// main: original e = 126061.1953 +// main: optimized e = 5451.0166 + +// int64_t ne1[4] = {4, 1024, 1, 1}; +// int64_t ne2[4] = {4, 2048, 1, 1};; +// int64_t ne3[4] = {1024, 2048, 1, 1}; +// main: original e = 1620817.8750 +// main: optimized e = 698387.6875 + +// another run on M1 +// int64_t ne1[4] = {4, 1024, 1, 1}; +// int64_t ne2[4] = {4, 2048, 1, 1};; +// int64_t ne3[4] = {1024, 2048, 1, 1}; +// main: original e = 1629595.6250 +// main: optimized e = 698169.1250 + +// int64_t ne1[4] = {32, 1024, 1, 1}; +// int64_t ne2[4] = {32, 2048, 1, 1};; +// int64_t ne3[4] = {1024, 2048, 1, 1}; +// main: original e = 8146770.5000 +// main: optimized e = 651119.1250 |