restored test-conv-transpose.c

tests/CMakeLists.txt

@@ -333,10 +333,18 @@ set_property(TEST ${TEST_TARGET} PROPERTY ENVIRONMENT "LLVM_PROFILE_FILE=${TEST_
 # test-conv-transpose
 
 set(TEST_TARGET test-conv-transpose)
+add_executable(${TEST_TARGET} ${TEST_TARGET}.c)
+target_link_libraries(${TEST_TARGET} PRIVATE ggml)
+add_test(NAME ${TEST_TARGET} COMMAND $<TARGET_FILE:${TEST_TARGET}>)
+
+# test-conv-transpose-1d
+
+set(TEST_TARGET test-conv-transpose-1d)
 add_executable(${TEST_TARGET} ${TEST_TARGET}.cpp)
 target_link_libraries(${TEST_TARGET} PRIVATE ggml)
 add_test(NAME ${TEST_TARGET} COMMAND $<TARGET_FILE:${TEST_TARGET}>)
 
+
 #
 # test-dup
 

tests/test-conv-transpose.cpp → tests/test-conv-transpose-1d.cpp

@@ -2,6 +2,7 @@
 #include "ggml/ggml-alloc.h"
 #include "ggml/ggml-backend.h"
 
+
 #ifdef GGML_USE_CUBLAS
 #include "ggml-cuda.h"
 #endif

tests/test-conv-transpose.c

@@ -0,0 +1,247 @@
+#include "ggml/ggml.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);
+}
+
+void printf_tensor(struct ggml_tensor * t) {
+ if (t->type == GGML_TYPE_F32) {
+ const float * t_d = ggml_get_data_f32(t);
+ for (int i = 0; i < t->ne[2]; ++i) {
+ for (int j = 0; j < t->ne[1]; ++j) {
+ for (int k = 0; k < t->ne[0]; ++k) {
+ printf("%.1f ", t_d[i * t->ne[1] * t->ne[0] + j * t->ne[0] + k]);
+ }
+ printf("\n");
+ }
+ printf("---\n");
+ }
+ }
+ else if (t->type == GGML_TYPE_F16) {
+ const ggml_fp16_t * t_d = ggml_get_data(t);
+ for (int i = 0; i < t->ne[2]; ++i) {
+ for (int j = 0; j < t->ne[1]; ++j) {
+ for (int k = 0; k < t->ne[0]; ++k) {
+ printf("%.1f ", ggml_fp16_to_fp32(t_d[i * t->ne[1] * t->ne[0] + j * t->ne[0] + k]));
+ }
+ printf("\n");
+ }
+ printf("---\n");
+ }
+ }
+ else {
+ printf("unknown type\n");
+ }
+}
+
+void check_tensor(struct ggml_tensor * t, float * expected_t_d, int ne0, int ne1, int ne2) {
+ GGML_ASSERT(t->type == GGML_TYPE_F32);
+ GGML_ASSERT(t->ne[0] == ne0);
+ GGML_ASSERT(t->ne[1] == ne1);
+ GGML_ASSERT(t->ne[2] == ne2);
+ for (int i2 = 0; i2 < ne2; ++i2) {
+ for (int i1 = 0; i1 < ne1; ++i1) {
+ for (int i0 = 0; i0 < ne0; ++i0) {
+ float expected = *(expected_t_d + i2 * ne1 * ne0 + i1 * ne0 + i0);
+ float actual = ggml_get_data_f32(t)[i2 * ne1 * ne0 + i1 * ne0 + i0];
+ if (expected != actual) {
+ printf("expected %.1f, got %.1f\n", expected, actual);
+ }
+ GGML_ASSERT(expected == actual);
+ }
+ }
+ }
+}
+
+void test_conv_transpose_1d(void) {
+
+ float buf_f32[1024];
+ for (int i = 0; i < 1024; ++i) {
+ buf_f32[i] = (float)i;
+ }
+
+ ggml_fp16_t buf_f16[1024];
+ for (int i = 0; i < 1024; ++i) {
+ buf_f16[i] = ggml_fp32_to_fp16((float)i);
+ }
+
+ float expected_out_1[3][4] = {
+ {18.0, 45.0, 59.0, 37.0},
+ {24.0, 61.0, 83.0, 51.0},
+ {30.0, 77.0, 107.0, 65.0},
+ };
+ float expected_out_2[3][6] = {
+ {18.0, 21.0, 24.0, 29.0, 30.0, 37.0},
+ {24.0, 27.0, 34.0, 39.0, 44.0, 51.0},
+ {30.0, 33.0, 44.0, 49.0, 58.0, 65.0},
+ };
+ float expected_out_3[3][8] = {
+ {18.0, 21.0, 0.0, 24.0, 29.0, 0.0, 30.0, 37.0},
+ {24.0, 27.0, 0.0, 34.0, 39.0, 0.0, 44.0, 51.0},
+ {30.0, 33.0, 0.0, 44.0, 49.0, 0.0, 58.0, 65.0},
+ };
+
+ // conv transpose 1d with stride 1, 2 & 3
+ {
+ struct ggml_context * ctx = make_ctx();
+
+ struct ggml_tensor * t = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 3, 2); // l x cin
+ memcpy(t->data, buf_f32, ggml_nbytes(t));
+
+ struct ggml_tensor * k = ggml_new_tensor_3d(ctx, GGML_TYPE_F16, 2, 3, 2); // k x cout x cin
+ memcpy(k->data, buf_f16, ggml_nbytes(k));
+
+ struct ggml_tensor * out_1 = ggml_conv_transpose_1d(ctx, k, t, 1 /* s0 */, 0 /* p0 */, 1 /* d0 */);
+ struct ggml_tensor * out_2 = ggml_conv_transpose_1d(ctx, k, t, 2 /* s0 */, 0 /* p0 */, 1 /* d0 */);
+ struct ggml_tensor * out_3 = ggml_conv_transpose_1d(ctx, k, t, 3 /* s0 */, 0 /* p0 */, 1 /* d0 */);
+
+ struct ggml_cgraph * gf_1 = ggml_new_graph(ctx);
+ struct ggml_cgraph * gf_2 = ggml_new_graph(ctx);
+ struct ggml_cgraph * gf_3 = ggml_new_graph(ctx);
+
+ ggml_build_forward_expand(gf_1, out_1);
+ ggml_build_forward_expand(gf_2, out_2);
+ ggml_build_forward_expand(gf_3, out_3);
+
+ ggml_graph_compute_with_ctx(ctx, gf_1, 1);
+ ggml_graph_compute_with_ctx(ctx, gf_2, 1);
+ ggml_graph_compute_with_ctx(ctx, gf_3, 1);
+
+ check_tensor(out_1, (float*)expected_out_1, 4, 3, 1);
+ check_tensor(out_2, (float*)expected_out_2, 6, 3, 1);
+ check_tensor(out_3, (float*)expected_out_3, 8, 3, 1);
+ }
+}
+
+void test_conv_transpose_2d(void) {
+
+ float buf_f32[1024];
+ for (int i = 0; i < 1024; ++i) {
+ buf_f32[i] = (float)i;
+ }
+
+ ggml_fp16_t buf_f16[1024];
+ for (int i = 0; i < 1024; ++i) {
+ buf_f16[i] = ggml_fp32_to_fp16((float)i);
+ }
+
+ float expected_out_1[3][3][4] = {
+ {
+ {72.0, 162.0, 188.0, 106.0},
+ {192.0, 430.0, 490.0, 274.0},
+ {132.0, 292.0, 326.0, 180.0},
+ },
+ {
+ {96.0, 218.0, 260.0, 146.0},
+ {264.0, 590.0, 682.0, 378.0},
+ {180.0, 396.0, 446.0, 244.0},
+ },
+ {
+ {120.0, 274.0, 332.0, 186.0},
+ {336.0, 750.0, 874.0, 482.0},
+ {228.0, 500.0, 566.0, 308.0},
+ },
+ };
+
+ float expected_out_2[3][4][6] = {
+ {
+ {72.0, 78.0, 84.0, 92.0, 96.0, 106.0},
+ {84.0, 90.0, 100.0, 108.0, 116.0, 126.0},
+ {108.0, 120.0, 120.0, 134.0, 132.0, 148.0},
+ {132.0, 144.0, 148.0, 162.0, 164.0, 180.0},
+ },
+ {
+ {96.0, 102.0, 116.0, 124.0, 136.0, 146.0},
+ {108.0, 114.0, 132.0, 140.0, 156.0, 166.0},
+ {156.0, 168.0, 176.0, 190.0, 196.0, 212.0},
+ {180.0, 192.0, 204.0, 218.0, 228.0, 244.0},
+ },
+ {
+ {120.0, 126.0, 148.0, 156.0, 176.0, 186.0},
+ {132.0, 138.0, 164.0, 172.0, 196.0, 206.0},
+ {204.0, 216.0, 232.0, 246.0, 260.0, 276.0},
+ {228.0, 240.0, 260.0, 274.0, 292.0, 308.0},
+ },
+ };
+
+ float expected_out_3[3][5][8] = {
+ {
+ {72.0, 78.0, 0.0, 84.0, 92.0, 0.0, 96.0, 106.0},
+ {84.0, 90.0, 0.0, 100.0, 108.0, 0.0, 116.0, 126.0},
+ {0.0, 0.0, 0.0, 0.0, 0.0, 0.0},
+ {108.0, 120.0, 0.0, 120.0, 134.0, 0.0, 132.0, 148.0},
+ {132.0, 144.0, 0.0, 148.0, 162.0, 0.0, 164.0, 180.0},
+ },
+ {
+ {96.0, 102.0, 0.0, 116.0, 124.0, 0.0, 136.0, 146.0},
+ {108.0, 114.0, 0.0, 132.0, 140.0, 0.0, 156.0, 166.0},
+ {0.0, 0.0, 0.0, 0.0, 0.0, 0.0},
+ {156.0, 168.0, 0.0, 176.0, 190.0, 0.0, 196.0, 212.0},
+ {180.0, 192.0, 0.0, 204.0, 218.0, 0.0, 228.0, 244.0},
+ },
+ {
+ {120.0, 126.0, 0.0, 148.0, 156.0, 0.0, 176.0, 186.0},
+ {132.0, 138.0, 0.0, 164.0, 172.0, 0.0, 196.0, 206.0},
+ {0.0, 0.0, 0.0, 0.0, 0.0, 0.0},
+ {204.0, 216.0, 0.0, 232.0, 246.0, 0.0, 260.0, 276.0},
+ {228.0, 240.0, 0.0, 260.0, 274.0, 0.0, 292.0, 308.0},
+ },
+ };
+
+ // conv transpose 2d with stride 1, 2 & 3
+ {
+ struct ggml_context * ctx = make_ctx();
+
+ struct ggml_tensor * t = ggml_new_tensor_4d(ctx, GGML_TYPE_F32, 3, 2, 2, 1); // w x h x cin
+ memcpy(t->data, buf_f32, ggml_nbytes(t));
+
+ struct ggml_tensor * k = ggml_new_tensor_4d(ctx, GGML_TYPE_F16, 2, 2, 3, 2); // w x h cin x cout
+ memcpy(k->data, buf_f16, ggml_nbytes(k));
+
+ struct ggml_tensor * out_1 = ggml_conv_transpose_2d_p0(ctx, k, t, 1);
+ struct ggml_tensor * out_2 = ggml_conv_transpose_2d_p0(ctx, k, t, 2);
+ struct ggml_tensor * out_3 = ggml_conv_transpose_2d_p0(ctx, k, t, 3);
+
+ struct ggml_cgraph * gf_1 = ggml_new_graph(ctx);
+ struct ggml_cgraph * gf_2 = ggml_new_graph(ctx);
+ struct ggml_cgraph * gf_3 = ggml_new_graph(ctx);
+
+ ggml_build_forward_expand(gf_1, out_1);
+ ggml_build_forward_expand(gf_2, out_2);
+ ggml_build_forward_expand(gf_3, out_3);
+
+ ggml_graph_compute_with_ctx(ctx, gf_1, 1);
+ ggml_graph_compute_with_ctx(ctx, gf_2, 1);
+ ggml_graph_compute_with_ctx(ctx, gf_3, 1);
+
+ // printf("in\n");
+ // printf_tensor(t);
+ // printf("\n\nkernel\n");
+ // printf_tensor(k);
+ // printf("\n\nout\n");
+ // printf_tensor(out);
+ // printf("\n\nout_2\n");
+ // printf_tensor(out_2);
+ // printf("\n\nout_3\n");
+ // printf_tensor(out_3);
+
+ check_tensor(out_1, (float*)expected_out_1, 4, 3, 3);
+ check_tensor(out_2, (float*)expected_out_2, 6, 4, 3);
+ check_tensor(out_3, (float*)expected_out_3, 8, 5, 3);
+
+ }
+}
+
+int main(int argc, const char * argv[]) {
+ test_conv_transpose_1d();
+ test_conv_transpose_2d();
+ return 0;
+}