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