Test support for alternative conv layout (#25617)

* add  bool cwhn = true to conv_2d test cases

* add layout check at graph building time

* extend layout checks for conv2d.cu kernel

* in CPU back-end kernel needs to be stored contiguously to prevent test failures with cwhn=1

* trim white space

* do op support check in vulkan backend

* fix CI failure and vulkan run-time assert failure by introducing new graph build-time check in ggml_backend_vk_device_supports_op

* add additional check in support_op function for Vulkan to fix run-time assert failure

diff --git a/ggml/src/ggml-cpu/ggml-cpu.cpp b/ggml/src/ggml-cpu/ggml-cpu.cpp
index 74631c2857ba7c1f072538ce966dc20c6c6d8eac..16cc5116c5451787c6a1dd1988e38b761f20ef12 100644 (file)
--- a/ggml/src/ggml-cpu/ggml-cpu.cpp
+++ b/ggml/src/ggml-cpu/ggml-cpu.cpp
@@ -469,6 +469,8 @@ static bool ggml_backend_cpu_device_supports_op(ggml_backend_dev_t dev, const st
             return (src0->type == GGML_TYPE_F32 ||
                     ((src0->type == GGML_TYPE_F16 || ggml_is_quantized(src0->type)) && src0->ne[2] == src1->ne[2] && src0->ne[3] == src1->ne[3])) &&
                 src1->type == GGML_TYPE_F32 && op->type == GGML_TYPE_F32;
+        case GGML_OP_CONV_2D:
+            return ggml_is_contiguous(op->src[0]);
         default:
             return true;
     }

diff --git a/ggml/src/ggml-cuda/conv2d.cu b/ggml/src/ggml-cuda/conv2d.cu
index 142dd66903aaaa4b595c5ee20e748e85f1559ddd..14774d4a5e736d2c7ff1013bad30cb535cfa72e1 100644 (file)
--- a/ggml/src/ggml-cuda/conv2d.cu
+++ b/ggml/src/ggml-cuda/conv2d.cu
@@ -126,6 +126,7 @@ void ggml_cuda_op_conv2d(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
     const float *       X_D    = (const float *) input->data;
     float *             Y_D    = (float *) dst->data;
 
+    GGML_ASSERT(ggml_is_contiguous(input));
     GGML_ASSERT(ggml_is_contiguous(kernel));
     GGML_ASSERT(kernel->type == GGML_TYPE_F16 || kernel->type == GGML_TYPE_F32);
 

diff --git a/ggml/src/ggml-cuda/ggml-cuda.cu b/ggml/src/ggml-cuda/ggml-cuda.cu
index 3e2c622951b5d32b25da4ae461f31cb778ee0e96..561ab7ac599f9e285d2a0296caee0ab0a14ea5c8 100644 (file)
--- a/ggml/src/ggml-cuda/ggml-cuda.cu
+++ b/ggml/src/ggml-cuda/ggml-cuda.cu
@@ -5105,7 +5105,7 @@ static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const g
         case GGML_OP_IM2COL:
         case GGML_OP_IM2COL_3D:
         case GGML_OP_CONV_2D:
-            return true;
+            return (ggml_is_contiguous(op->src[0]) && ggml_is_contiguous(op->src[1]));
         case GGML_OP_CONV_2D_DW:
             return op->src[0]->type == GGML_TYPE_F32;
         case GGML_OP_CONV_TRANSPOSE_2D:

diff --git a/ggml/src/ggml-vulkan/ggml-vulkan.cpp b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
index 49fd6e0b42f68767249d7eb2298b83e7e9b64b6c..8a1bff65a5f8c2773f540aedc70ee27fa6626a85 100644 (file)
--- a/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+++ b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
@@ -18016,10 +18016,17 @@ static bool ggml_backend_vk_device_supports_op(ggml_backend_dev_t dev, const ggm
         case GGML_OP_CONV_2D:
         case GGML_OP_CONV_TRANSPOSE_2D:
             {
+                const bool transpose = op->op == GGML_OP_CONV_TRANSPOSE_2D;
+                const int64_t cout = !transpose ? op->src[0]->ne[3] : op->src[0]->ne[2];
+                const int64_t cin  = !transpose ? op->src[0]->ne[2] : op->src[0]->ne[3];
+
                 // Channel-contiguous format is not supported yet.
                 return ((op->src[0]->type == GGML_TYPE_F32 || op->src[0]->type == GGML_TYPE_F16) &&
+                    (op->src[0]->nb[0] == sizeof(float) || op->src[0]->nb[0] == sizeof(ggml_fp16_t) ) &&
                     op->src[1]->type == GGML_TYPE_F32 &&
                     op->type == GGML_TYPE_F32 &&
+                    cout == op->ne[2] &&
+                    cin == op->src[1]->ne[2] &&
                     ggml_is_contiguous(op->src[0]) &&
                     ggml_is_contiguous(op->src[1]) &&
                     ggml_is_contiguous(op));

diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp
index e8d0e00d5b8bb5e17c9f4c19dcebe21c44fb83f0..162bfc98c8b31e7896e003c11a86c4729526fcc6 100644 (file)
--- a/tests/test-backend-ops.cpp
+++ b/tests/test-backend-ops.cpp
@@ -8329,7 +8329,11 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
             test_cases.emplace_back(new test_conv_2d(
                 { act_case[iwh_idx], act_case[iwh_idx], act_case[Cin_idx], act_case[B_idx] },
                 { act_case[kwh_idx], act_case[kwh_idx], act_case[Cin_idx], act_case[Cout_idx] },
-                kernel_type, 1, 1, 0, 0, 1, 1, false));
+                kernel_type, 1, 1, 0, 0, 1, 1, false));  // bool cwhn = false
+            test_cases.emplace_back(new test_conv_2d(
+                { act_case[iwh_idx], act_case[iwh_idx], act_case[Cin_idx], act_case[B_idx] },
+                { act_case[kwh_idx], act_case[kwh_idx], act_case[Cin_idx], act_case[Cout_idx] },
+                kernel_type, 1, 1, 0, 0, 1, 1, true));  // bool cwhn = true
         }
     }
 #endif
@@ -8358,7 +8362,9 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
                                         calc_conv_output_size(H, KH, s1, p1, d1) > 0) {
                                         for (auto kernel_type : {GGML_TYPE_F32, GGML_TYPE_F16}) {
                                             test_cases.emplace_back(new test_conv_2d(
-                                                { W, H, Cin, 2 }, { KW, KH, Cin, Cout }, kernel_type, s0, s1, p0, p1, d0, d1, false));
+                                                { W, H, Cin, 2 }, { KW, KH, Cin, Cout }, kernel_type, s0, s1, p0, p1, d0, d1, false)); // bool cwhn = false
+                                            test_cases.emplace_back(new test_conv_2d(
+                                                { W, H, Cin, 2 }, { KW, KH, Cin, Cout }, kernel_type, s0, s1, p0, p1, d0, d1, true));  // bool cwhn = true
                                         }
                                     }
                                 }
@@ -8370,7 +8376,8 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
         }
     }
     for (auto kernel_type : {GGML_TYPE_F32, GGML_TYPE_F16}) {
-        test_cases.emplace_back(new test_conv_2d({ 256, 256, 192, 1 }, { 3, 3, 192, 96 }, kernel_type, 1, 1, 1, 1, 1, 1, false));
+        test_cases.emplace_back(new test_conv_2d({ 256, 256, 192, 1 }, { 3, 3, 192, 96 }, kernel_type, 1, 1, 1, 1, 1, 1, false)); // bool cwhn = false
+        test_cases.emplace_back(new test_conv_2d({ 256, 256, 192, 1 }, { 3, 3, 192, 96 }, kernel_type, 1, 1, 1, 1, 1, 1, true));  // bool cwhn = true
     }
 
     // sycl backend will limit task global_range < MAX_INT
@@ -9757,7 +9764,11 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_perf() {
             test_cases.emplace_back(new test_conv_2d(
                 { act_case[iwh_idx], act_case[iwh_idx], act_case[Cin_idx], act_case[B_idx] },
                 { act_case[kwh_idx], act_case[kwh_idx], act_case[Cin_idx], act_case[Cout_idx] },
-                kernel_type, 1, 1, 0, 0, 1, 1, false));
+                kernel_type, 1, 1, 0, 0, 1, 1, false));   // bool cwhn = false
+            test_cases.emplace_back(new test_conv_2d(
+                { act_case[iwh_idx], act_case[iwh_idx], act_case[Cin_idx], act_case[B_idx] },
+                { act_case[kwh_idx], act_case[kwh_idx], act_case[Cin_idx], act_case[Cout_idx] },
+                kernel_type, 1, 1, 0, 0, 1, 1, true));    // bool cwhn = true
         }
     }