Introduce multiABD api and deprecate multiD

include/ck/tensor_operation/gpu/device/device_grouped_conv_fwd_multiple_abd.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <array>
+
+#include "ck/tensor_operation/gpu/device/device_base.hpp"
+#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_utils.hpp"
+#include "ck/utility/is_detected.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+
+template <typename T>
+using is_tuple = decltype(std::declval<T&>().IsTuple());
+
+/**
+ * \brief Grouped Convolution Forward
+ *
+ * \details
+ * input : input image A[G, N, C, Hi, Wi], A1[G, N, C, Hi, Wi]...
+ * input : weight B[G, K, C, Y, X], B1[G, K, C, Y, X]...
+ * input : D0[G, N, K, Ho, Wo], D1[G, N, K, Ho, Wo], ...
+ * output : output image E[G, N, K, Ho, Wo]
+ *
+ * C = a_op(A, A1...) * b_op(B, B1...)
+ * E = cde_op(C, D0, D1, ...)
+ *
+ * \tparam NDimSpatial Number of spatial dimensions.
+ * \tparam ALayout Input layout (also for a1, a2...).
+ * \tparam BLayout Weight layout (also for b1, b2...).
+ * \tparam DsLayout Ds layouts.
+ * \tparam ELayout Output layout.
+ * \tparam ADataType Input data type. Pass tuple if there is multiple A.
+ * \tparam BDataType Weight data type. Pass tuple if there is multiple B.
+ * \tparam DsDataType D data types.
+ * \tparam EDataType Output data type.
+ * \tparam AElementwiseOperation A elementwise operation.
+ * \tparam BElementwiseOperation B elementwise operation.
+ * \tparam CDEElementwiseOperation CDE elementwise operation.
+ * \tparam ComputeType Compute data type (default: ADataType, first if tuple passed).
+ */
+template <index_t NDimSpatial,
+          typename ALayout,
+          typename BLayout,
+          typename DsLayout,
+          typename ELayout,
+          typename ADataType,
+          typename BDataType,
+          typename DsDataType,
+          typename EDataType,
+          typename AElementwiseOperation,
+          typename BElementwiseOperation,
+          typename CDEElementwiseOperation,
+          typename ComputeType =
+              decltype(UnpackDataType<is_detected<is_tuple, ADataType>::value,
+                                      Number<0>,
+                                      ADataType>())> // ComputeType is InputType by default (first
+                                                     // in tuple for MultiAB), unpack if tuple was
+                                                     // passed
+struct DeviceGroupedConvFwdMultipleABD : public BaseOperator
+{
+    static constexpr bool isMultiA = is_detected<is_tuple, ADataType>::value;
+    static constexpr bool isMultiB = is_detected<is_tuple, BDataType>::value;
+
+    static constexpr index_t NumATensor = GetNumABTensors<isMultiA, ADataType>();
+    static constexpr index_t NumBTensor = GetNumABTensors<isMultiB, BDataType>();
+    static constexpr index_t NumDTensor = DsDataType::Size();
+
+    static_assert(NumDTensor == DsLayout::Size(), "wrong! Inconsistent NumDTensor");
+
+    // If DataType is tuple, user has to pass std::array with pointers.
+    using APointers =
+        std::conditional_t<isMultiA, std::array<const void*, NumATensor>&, const void*>;
+    using BPointers =
+        std::conditional_t<isMultiB, std::array<const void*, NumBTensor>&, const void*>;
+
+    /**
+     * \brief Make argument pointer for grouped conv fwd.
+     *
+     * \param p_a A pointer to the input (std::array<const void*, NumA> with
+                  pointers for multiple A).
+     * \param p_b A pointer to the weight (std::array<const void*, NumA> with
+                  pointers for multiple B).
+     * \param p_ds A pointers to the Ds.
+     * \param p_e A pointers to the output.
+     * \param a_g_n_c_wis_lengths Input lengths [G, N, C, Spatial...] (for 3d).
+     * \param a_g_n_c_wis_strides Input strides [G, N, C, Spatial...] (for 3d).
+     * \param b_g_k_c_xs_lengths Weight lengths [G, K, C, Spatial...] (for 3d).
+     * \param b_g_k_c_xs_strides Weight strides [G, K, C, Spatial...] (for 3d).
+     * \param ds_g_n_k_wos_lengths Ds lengths [G, N, K, Spatial...] (for 3d).
+     * \param ds_g_n_k_wos_strides Ds strides [G, N, K, Spatial...] (for 3d).
+     * \param e_g_n_k_wos_lengths Output lengths [G, N, K, Spatial...] (for 3d).
+     * \param e_g_n_k_wos_strides Output strides [G, N, K, Spatial...] (for 3d).
+     * \param conv_filter_strides Convolution filter strides.
+     * \param conv_filter_dilations Convolution filter dilations.
+     * \param input_left_pads Input left paddings.
+     * \param input_right_pads Input right paddings.
+     * \param a_element_op A elementwise operation object.
+     * \param b_element_op B elementwise operation object.
+     * \param cde_element_op CDE elementwise operation object.
+     * \return Pointer to the argument.
+     */
+    virtual std::unique_ptr<BaseArgument> MakeArgumentPointer(
+        APointers p_a,
+        BPointers p_b,
+        const std::array<const void*, NumDTensor>& p_ds,
+        void* p_e,
+        const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_lengths,
+        const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_strides,
+        const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_lengths,
+        const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_strides,
+        const std::array<std::array<index_t, NDimSpatial + 3>, NumDTensor>& ds_g_n_k_wos_lengths,
+        const std::array<std::array<index_t, NDimSpatial + 3>, NumDTensor>& ds_g_n_k_wos_strides,
+        const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_lengths,
+        const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_strides,
+        const std::array<index_t, NDimSpatial>& conv_filter_strides,
+        const std::array<index_t, NDimSpatial>& conv_filter_dilations,
+        const std::array<index_t, NDimSpatial>& input_left_pads,
+        const std::array<index_t, NDimSpatial>& input_right_pads,
+        const AElementwiseOperation& a_element_op,
+        const BElementwiseOperation& b_element_op,
+        const CDEElementwiseOperation& cde_element_op) = 0;
+
+    virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
+};
+
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

include/ck/tensor_operation/gpu/device/device_grouped_conv_fwd_multiple_d.hpp

@@ -3,30 +3,18 @@
 
 #pragma once
 
-#include <array>
-
-#include "ck/tensor_operation/gpu/device/device_base.hpp"
+#include "ck/tensor_operation/gpu/device/device_grouped_conv_fwd_multiple_abd.hpp"
 #include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_utils.hpp"
-#include "ck/utility/is_detected.hpp"
 
 namespace ck {
 namespace tensor_operation {
 namespace device {
 
-template <typename T>
-using is_tuple = decltype(std::declval<T&>().IsTuple());
-
 /**
  * \brief Grouped Convolution Forward
  *
- * \details
- * input : input image A[G, N, C, Hi, Wi], A1[G, N, C, Hi, Wi]...
- * input : weight B[G, K, C, Y, X], B1[G, K, C, Y, X]...
- * input : D0[G, N, K, Ho, Wo], D1[G, N, K, Ho, Wo], ...
- * output : output image E[G, N, K, Ho, Wo]
- *
- * C = a_op(A, A1...) * b_op(B, B1...)
- * E = cde_op(C, D0, D1, ...)
+ * \deprecated This structure is deprecated (left for backwards compatibility). Please use
+ *             DeviceGroupedConvFwdMultipleABD.
  *
  * \tparam NDimSpatial Number of spatial dimensions.
  * \tparam ALayout Input layout (also for a1, a2...).
@@ -60,72 +48,19 @@ template <index_t NDimSpatial,
                                       ADataType>())> // ComputeType is InputType by default (first
                                                      // in tuple for MultiAB), unpack if tuple was
                                                      // passed
-struct DeviceGroupedConvFwdMultipleD : public BaseOperator
-{
-    static constexpr bool isMultiA = is_detected<is_tuple, ADataType>::value;
-    static constexpr bool isMultiB = is_detected<is_tuple, BDataType>::value;
-
-    static constexpr index_t NumATensor = GetNumABTensors<isMultiA, ADataType>();
-    static constexpr index_t NumBTensor = GetNumABTensors<isMultiB, BDataType>();
-    static constexpr index_t NumDTensor = DsDataType::Size();
-
-    static_assert(NumDTensor == DsLayout::Size(), "wrong! Inconsistent NumDTensor");
-
-    // If DataType is tuple, user has to pass std::array with pointers.
-    using APointers =
-        std::conditional_t<isMultiA, std::array<const void*, NumATensor>&, const void*>;
-    using BPointers =
-        std::conditional_t<isMultiB, std::array<const void*, NumBTensor>&, const void*>;
-
-    /**
-     * \brief Make argument pointer for grouped conv fwd.
-     *
-     * \param p_a A pointer to the input (std::array<const void*, NumA> with
-                  pointers for multiple A).
-     * \param p_b A pointer to the weight (std::array<const void*, NumA> with
-                  pointers for multiple B).
-     * \param p_ds A pointers to the Ds.
-     * \param p_e A pointers to the output.
-     * \param a_g_n_c_wis_lengths Input lengths [G, N, C, Spatial...] (for 3d).
-     * \param a_g_n_c_wis_strides Input strides [G, N, C, Spatial...] (for 3d).
-     * \param b_g_k_c_xs_lengths Weight lengths [G, K, C, Spatial...] (for 3d).
-     * \param b_g_k_c_xs_strides Weight strides [G, K, C, Spatial...] (for 3d).
-     * \param ds_g_n_k_wos_lengths Ds lengths [G, N, K, Spatial...] (for 3d).
-     * \param ds_g_n_k_wos_strides Ds strides [G, N, K, Spatial...] (for 3d).
-     * \param e_g_n_k_wos_lengths Output lengths [G, N, K, Spatial...] (for 3d).
-     * \param e_g_n_k_wos_strides Output strides [G, N, K, Spatial...] (for 3d).
-     * \param conv_filter_strides Convolution filter strides.
-     * \param conv_filter_dilations Convolution filter dilations.
-     * \param input_left_pads Input left paddings.
-     * \param input_right_pads Input right paddings.
-     * \param a_element_op A elementwise operation object.
-     * \param b_element_op B elementwise operation object.
-     * \param cde_element_op CDE elementwise operation object.
-     * \return Pointer to the argument.
-     */
-    virtual std::unique_ptr<BaseArgument> MakeArgumentPointer(
-        APointers p_a,
-        BPointers p_b,
-        const std::array<const void*, NumDTensor>& p_ds,
-        void* p_e,
-        const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_lengths,
-        const std::array<index_t, NDimSpatial + 3>& a_g_n_c_wis_strides,
-        const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_lengths,
-        const std::array<index_t, NDimSpatial + 3>& b_g_k_c_xs_strides,
-        const std::array<std::array<index_t, NDimSpatial + 3>, NumDTensor>& ds_g_n_k_wos_lengths,
-        const std::array<std::array<index_t, NDimSpatial + 3>, NumDTensor>& ds_g_n_k_wos_strides,
-        const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_lengths,
-        const std::array<index_t, NDimSpatial + 3>& e_g_n_k_wos_strides,
-        const std::array<index_t, NDimSpatial>& conv_filter_strides,
-        const std::array<index_t, NDimSpatial>& conv_filter_dilations,
-        const std::array<index_t, NDimSpatial>& input_left_pads,
-        const std::array<index_t, NDimSpatial>& input_right_pads,
-        const AElementwiseOperation& a_element_op,
-        const BElementwiseOperation& b_element_op,
-        const CDEElementwiseOperation& cde_element_op) = 0;
-
-    virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
-};
+using DeviceGroupedConvFwdMultipleD = DeviceGroupedConvFwdMultipleABD<NDimSpatial,
+                                                                      ALayout,
+                                                                      BLayout,
+                                                                      DsLayout,
+                                                                      ELayout,
+                                                                      ADataType,
+                                                                      BDataType,
+                                                                      DsDataType,
+                                                                      EDataType,
+                                                                      AElementwiseOperation,
+                                                                      BElementwiseOperation,
+                                                                      CDEElementwiseOperation,
+                                                                      ComputeType>;
 
 } // namespace device
 } // namespace tensor_operation

test/grouped_convnd_fwd/CMakeLists.txt

@@ -3,3 +3,6 @@ target_link_libraries(test_grouped_convnd_fwd PRIVATE utility device_grouped_con
 
 add_gtest_executable(test_grouped_convnd_fwd_multi_ab_interface test_grouped_convnd_fwd_multi_ab_interface.cpp)
 target_link_libraries(test_grouped_convnd_fwd_multi_ab_interface PRIVATE utility)
+
+add_gtest_executable(test_grouped_convnd_fwd_multi_d_interface_compatibility test_grouped_convnd_fwd_multi_d_interface_compatibility.cpp)
+target_link_libraries(test_grouped_convnd_fwd_multi_d_interface_compatibility PRIVATE utility device_grouped_conv3d_fwd_instance)

test/grouped_convnd_fwd/test_grouped_convnd_fwd_multi_d_interface_compatibility.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <cstdlib>
+#include <iostream>
+#include <initializer_list>
+#include <tuple>
+#include <vector>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/tensor_operation/gpu/device/device_grouped_conv_fwd_multiple_d.hpp"
+
+#include <gtest/gtest.h>
+
+template <ck::index_t... Is>
+using S = ck::Sequence<Is...>;
+
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+
+template <typename DataType,
+          typename InDataTypes,
+          typename WeiDataTypes,
+          typename InElementOp,
+          typename WeiElementOp>
+class TestGroupedConvndFwdMultiDInterfaceCompatibility : public ::testing::Test
+{
+    protected:
+    static constexpr ck::index_t NDimSpatial = 3;
+
+    using InDataType  = float;
+    using WeiDataType = float;
+    using OutDataType = float;
+    using InLayout    = ck::tensor_layout::convolution::GNDHWC;
+    using WeiLayout   = ck::tensor_layout::convolution::GKZYXC;
+    using OutLayout   = ck::tensor_layout::convolution::GNDHWK;
+
+    using DeviceOp = ck::tensor_operation::device::DeviceGroupedConvFwdMultipleD<NDimSpatial,
+                                                                                 InLayout,
+                                                                                 WeiLayout,
+                                                                                 ck::Tuple<>,
+                                                                                 OutLayout,
+                                                                                 InDataType,
+                                                                                 WeiDataType,
+                                                                                 ck::Tuple<>,
+                                                                                 OutDataType,
+                                                                                 PassThrough,
+                                                                                 PassThrough,
+                                                                                 PassThrough>;
+
+    bool Run()
+    {
+        const auto op_ptrs = ck::tensor_operation::device::instance::DeviceOperationInstanceFactory<
+            DeviceOp>::GetInstances();
+        return op_ptrs.size() != 0;
+    }
+};
+
+TEST_F(TestGroupedConvndFwdMultiDInterfaceCompatibility, CompatibilityTest)
+{
+    EXPECT_TRUE(this->template Run());
+}