add test-pad-reflect-1d test case

tests/CMakeLists.txt

@@ -295,6 +295,13 @@ endif()
 add_test(NAME ${TEST_TARGET} COMMAND $<TARGET_FILE:${TEST_TARGET}>)
 set_property(TEST ${TEST_TARGET} PROPERTY ENVIRONMENT "LLVM_PROFILE_FILE=${TEST_TARGET}.profraw")
 
+#
+# test-pad-reflect-1d
+
+set(TEST_TARGET test-pad-reflect-1d)
+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

tests/test-pad-reflect-1d.c

@@ -0,0 +1,109 @@
+#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);
+}
+
+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 at (%d,%d,%d)\n", expected, actual, i0, i1, i2);
+                }
+                GGML_ASSERT(expected == actual);
+            }
+        }
+    }
+}
+
+void test_pad_reflect_1d(void) {
+    // Test cases for different padding configurations
+    {
+        struct ggml_context * ctx = make_ctx();
+
+        // Create a simple 1D input tensor [1, 2, 3, 4]
+        struct ggml_tensor * t = ggml_new_tensor_1d(ctx, GGML_TYPE_F32, 4);
+        float input_data[] = {1.0f, 2.0f, 3.0f, 4.0f};
+        memcpy(t->data, input_data, ggml_nbytes(t));
+
+        // Test case 1: pad left=1, right=1
+        // Expected: [2, 1, 2, 3, 4, 3]
+        float expected_1[] = {2.0f, 1.0f, 2.0f, 3.0f, 4.0f, 3.0f};
+        struct ggml_tensor * out_1 = ggml_pad_reflect_1d(ctx, t, 1, 1);
+
+        // Test case 2: pad left=2, right=1
+        // Expected: [3, 2, 1, 2, 3, 4, 3]
+        float expected_2[] = {3.0f, 2.0f, 1.0f, 2.0f, 3.0f, 4.0f, 3.0f};
+        struct ggml_tensor * out_2 = ggml_pad_reflect_1d(ctx, t, 2, 1);
+
+        // Test case 3: pad left=1, right=2
+        // Expected: [2, 1, 2, 3, 4, 3, 2]
+        float expected_3[] = {2.0f, 1.0f, 2.0f, 3.0f, 4.0f, 3.0f, 2.0f};
+        struct ggml_tensor * out_3 = ggml_pad_reflect_1d(ctx, t, 1, 2);
+
+        struct ggml_cgraph * gf = ggml_new_graph(ctx);
+        ggml_build_forward_expand(gf, out_1);
+        ggml_build_forward_expand(gf, out_2);
+        ggml_build_forward_expand(gf, out_3);
+
+        ggml_graph_compute_with_ctx(ctx, gf, 1);
+
+        check_tensor(out_1, expected_1, 6, 1, 1);
+        check_tensor(out_2, expected_2, 7, 1, 1);
+        check_tensor(out_3, expected_3, 7, 1, 1);
+
+        ggml_free(ctx);
+    }
+
+    {
+        struct ggml_context * ctx = make_ctx();
+
+        // Create a 2D input tensor (5 columns × 4 rows)
+        struct ggml_tensor * t = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 5, 4);
+        float input_data[] = {
+            1.0f, 2.0f, 3.0f, 4.0f, 5.0f,  // row 1
+            6.0f, 7.0f, 8.0f, 9.0f, 10.0f, // row 2
+            11.0f, 12.0f, 13.0f, 14.0f, 15.0f, // row 3
+            16.0f, 17.0f, 18.0f, 19.0f, 20.0f  // row 4
+        };
+        memcpy(t->data, input_data, ggml_nbytes(t));
+
+        // Test case 4: pad left=3, right=2 on a 2D tensor
+        // Each row should be padded independently
+        float expected_4[] = {
+            4.0f, 3.0f, 2.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 4.0f, 3.0f,  // row 1
+            9.0f, 8.0f, 7.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 9.0f, 8.0f, // row 2
+            14.0f, 13.0f, 12.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 14.0f, 13.0f, // row 3
+            19.0f, 18.0f, 17.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 19.0f, 18.0f  // row 4
+        };
+        struct ggml_tensor * out_4 = ggml_pad_reflect_1d(ctx, t, 3, 2);
+
+        struct ggml_cgraph * gf = ggml_new_graph(ctx);
+        ggml_build_forward_expand(gf, out_4);
+        ggml_graph_compute_with_ctx(ctx, gf, 1);
+
+        check_tensor(out_4, expected_4, 10, 4, 1);
+
+        ggml_free(ctx);
+    }
+}
+
+int main(int argc, const char * argv[]) {
+    test_pad_reflect_1d();
+    return 0;
+}