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initial release

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civ
2026-07-05 18:11:23 +07:00
commit 8fb29dac70
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ggml/tests/test-pool.c
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#include "ggml.h"
#include "ggml-cpu.h"
#include <string.h>
#include <stdio.h>
#include <stdlib.h>
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];
ggml_fp16_t buf_f16[1024];
for (int i = 0; i < 1024; ++i) {
buf_f32[i] = (float)(i + 1);
buf_f16[i] = ggml_fp32_to_fp16(buf_f32[i]);
}
// avg pool 1d - Float 32
{
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_new_graph(ctx);
ggml_build_forward_expand(graph, 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);
}
// avg pool 1d - Float 16
{
struct ggml_context * ctx = make_ctx();
struct ggml_tensor * t = ggml_new_tensor_2d(ctx, GGML_TYPE_F16, 10, 2);
memcpy(t->data, buf_f16, 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_new_graph(ctx);
ggml_build_forward_expand(graph, 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 - Float 32
{
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_new_graph(ctx);
ggml_build_forward_expand(graph, 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);
}
// max pool 1d - Float 16
{
struct ggml_context * ctx = make_ctx();
struct ggml_tensor * t = ggml_new_tensor_2d(ctx, GGML_TYPE_F16, 10, 2);
memcpy(t->data, buf_f16, 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_new_graph(ctx);
ggml_build_forward_expand(graph, 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 - Float 32
{
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_new_graph(ctx);
ggml_build_forward_expand(graph, 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);
}
// avg pool 2d - Float 16
{
struct ggml_context * ctx = make_ctx();
struct ggml_tensor * t = ggml_new_tensor_3d(ctx, GGML_TYPE_F16, 10, 10, 2);
memcpy(t->data, buf_f16, 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_new_graph(ctx);
ggml_build_forward_expand(graph, 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 - Float 32
{
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_new_graph(ctx);
ggml_build_forward_expand(graph, 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);
}
// max pool 2d - Float 16
{
struct ggml_context * ctx = make_ctx();
struct ggml_tensor * t = ggml_new_tensor_3d(ctx, GGML_TYPE_F16, 10, 10, 2);
memcpy(t->data, buf_f16, 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_new_graph(ctx);
ggml_build_forward_expand(graph, 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;
}