#include "ggml/ggml.h" #include #include #include struct ggml_context* make_ctx(void) { struct ggml_init_params params = { .mem_size = 2 * 1024 * 1024, }; return ggml_init(params); } int main(int argc, const char** argv) { float buf_f32[1024]; for (int i = 0; i < 1024; ++i) { buf_f32[i] = (float)(i + 1); } // avg pool 1d { struct ggml_context * ctx = make_ctx(); struct ggml_tensor * t = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 10, 2); memcpy(t->data, buf_f32, ggml_nbytes(t)); struct ggml_tensor * t_pooled = ggml_pool_1d(ctx, t, GGML_OP_POOL_AVG, 3, 3, 0); GGML_ASSERT(t_pooled->ne[0] == 3); GGML_ASSERT(t_pooled->ne[1] == 2); GGML_ASSERT(t_pooled->ne[2] == 1); struct ggml_cgraph graph = ggml_build_forward(t_pooled); ggml_graph_compute_with_ctx(ctx, &graph, 4); const float * output = ggml_get_data_f32(t_pooled); GGML_ASSERT(output[0] == 2); GGML_ASSERT(output[1] == 5); GGML_ASSERT(output[2] == 8); GGML_ASSERT(output[3] == 12); GGML_ASSERT(output[4] == 15); GGML_ASSERT(output[5] == 18); ggml_free(ctx); } // max pool 1d { struct ggml_context * ctx = make_ctx(); struct ggml_tensor * t = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 10, 2); memcpy(t->data, buf_f32, ggml_nbytes(t)); struct ggml_tensor * t_pooled = ggml_pool_1d(ctx, t, GGML_OP_POOL_MAX, 3, 3, 0); GGML_ASSERT(t_pooled->ne[0] == 3); GGML_ASSERT(t_pooled->ne[1] == 2); GGML_ASSERT(t_pooled->ne[2] == 1); struct ggml_cgraph graph = ggml_build_forward(t_pooled); ggml_graph_compute_with_ctx(ctx, &graph, 4); const float * output = ggml_get_data_f32(t_pooled); GGML_ASSERT(output[0] == 3); GGML_ASSERT(output[1] == 6); GGML_ASSERT(output[2] == 9); GGML_ASSERT(output[3] == 13); GGML_ASSERT(output[4] == 16); GGML_ASSERT(output[5] == 19); ggml_free(ctx); } // avg pool 2d { struct ggml_context * ctx = make_ctx(); struct ggml_tensor * t = ggml_new_tensor_3d(ctx, GGML_TYPE_F32, 10, 10, 2); memcpy(t->data, buf_f32, ggml_nbytes(t)); struct ggml_tensor * t_pooled = ggml_pool_2d(ctx, t, GGML_OP_POOL_AVG, 3, 4, 3, 4, 0, 0); GGML_ASSERT(t_pooled->ne[0] == 3); GGML_ASSERT(t_pooled->ne[1] == 2); GGML_ASSERT(t_pooled->ne[2] == 2); GGML_ASSERT(t_pooled->ne[3] == 1); struct ggml_cgraph graph = ggml_build_forward(t_pooled); ggml_graph_compute_with_ctx(ctx, &graph, 4); const float * output = ggml_get_data_f32(t_pooled); GGML_ASSERT(output[0] == 17); GGML_ASSERT(output[1] == 20); GGML_ASSERT(output[2] == 23); GGML_ASSERT(output[3] == 57); GGML_ASSERT(output[4] == 60); GGML_ASSERT(output[5] == 63); GGML_ASSERT(output[6] == 117); GGML_ASSERT(output[7] == 120); GGML_ASSERT(output[8] == 123); GGML_ASSERT(output[9] == 157); GGML_ASSERT(output[10] == 160); GGML_ASSERT(output[11] == 163); ggml_free(ctx); } // max pool 2d { struct ggml_context * ctx = make_ctx(); struct ggml_tensor * t = ggml_new_tensor_3d(ctx, GGML_TYPE_F32, 10, 10, 2); memcpy(t->data, buf_f32, ggml_nbytes(t)); struct ggml_tensor * t_pooled = ggml_pool_2d(ctx, t, GGML_OP_POOL_MAX, 3, 4, 3, 4, 0, 0); GGML_ASSERT(t_pooled->ne[0] == 3); GGML_ASSERT(t_pooled->ne[1] == 2); GGML_ASSERT(t_pooled->ne[2] == 2); GGML_ASSERT(t_pooled->ne[3] == 1); struct ggml_cgraph graph = ggml_build_forward(t_pooled); ggml_graph_compute_with_ctx(ctx, &graph, 4); const float * output = ggml_get_data_f32(t_pooled); GGML_ASSERT(output[0] == 33); GGML_ASSERT(output[1] == 36); GGML_ASSERT(output[2] == 39); GGML_ASSERT(output[3] == 73); GGML_ASSERT(output[4] == 76); GGML_ASSERT(output[5] == 79); GGML_ASSERT(output[6] == 133); GGML_ASSERT(output[7] == 136); GGML_ASSERT(output[8] == 139); GGML_ASSERT(output[9] == 173); GGML_ASSERT(output[10] == 176); GGML_ASSERT(output[11] == 179); ggml_free(ctx); } return 0; }