Several fixes of image to column

example/52_image_to_column/image_to_column_f32.cpp

@@ -107,11 +107,9 @@ bool RunImageToColumn(const ExecutionConfig& config, const ck::utils::conv::Conv
     }
 
     float ave_time = invoker.Run(argument, StreamConfig{nullptr, config.time_kernel});
-
-    std::size_t num_btype = NDoHoWo * CZYX * sizeof(InDataType);
-
+    std::size_t num_btype =
+        NDoHoWo * CZYX * sizeof(OutDataType) + conv_params.GetInputByte<InputDataType>();
     float gb_per_sec = num_btype / 1.E6 / ave_time;
-
     std::cout << "Perf: " << ave_time << " ms, " << gb_per_sec << " GB/s" << std::endl;
 
     if(config.do_verification)
@@ -159,7 +157,7 @@ int RunImageToColumnExample(int argc, char* argv[])
 
     if(conv_params.num_dim_spatial_ != NDimSpatial)
     {
-        std::cerr << "unsupported # of spatials dimensions" << std::endl;
+        std::cerr << "unsupported # of spatial dimensions" << std::endl;
         return EXIT_FAILURE;
     }
 

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

@@ -11,18 +11,45 @@ namespace ck {
 namespace tensor_operation {
 namespace device {
 
-// Image to column:
-//   input : input image [N, Di, Hi, Wi, C],
-//   output : output image [N * Do * Ho * Wo, Z *  Y * X * C]
+/**
+ * \brief Image to column.
+ *
+ * This Device operator converts image ([G, N, Di, Hi, Wi, C]) to the gemm
+ * problem([N * Do * Ho * Wo, Z *  Y * X * C]). G must be equal to 1.
+ *
+ * \tparam NDimSpatial Number of spatial dimensions.
+ * \tparam InputLayout Input Layout.
+ * \tparam InputDataType Input Data Type.
+ * \tparam OutputDataType Output Data Type.
+ */
 template <index_t NDimSpatial,
           typename InputLayout,
           typename InputDataType,
           typename OutputDataType>
 struct DeviceImageToColumn : public BaseOperator
 {
+
+    /**
+     * \brief Make argument pointer for image to column.
+     *
+     * \param p_in A pointer to the device memory of the input image.
+     * \param p_out A pointer to the device memory of the output.
+     * \param N Convolution batch size.
+     * \param C Convolution number of channels.
+     * \param input_spatial_lengths Input spatial lengths.
+     * \param filter_spatial_lengths Filter spatial lengths.
+     * \param output_spatial_lengths Output spatial lengths.
+     * \param input_g_n_c_wis_strides Input strides in order [G, N, C, D, H, W].
+     * \param output_m_k_strides Output strides.
+     * \param conv_filter_strides Convolution filter strides.
+     * \param conv_filter_dilations Convolution filter dilations.
+     * \param input_left_pads Convolution left pads.
+     * \param input_right_pads Convolution right pads.
+     * \return Pointer to the argument.
+     */
     virtual std::unique_ptr<BaseArgument>
-    MakeArgumentPointer(const void* p_in, // input image
-                        void* p_out,      // output image
+    MakeArgumentPointer(const void* p_in,
+                        void* p_out,
                         const ck::index_t N,
                         const ck::index_t C,
                         const std::array<index_t, NDimSpatial>& input_spatial_lengths,

include/ck/tensor_operation/gpu/device/impl/device_image_to_column_impl.hpp

@@ -7,9 +7,7 @@
 #include "ck/tensor_description/tensor_descriptor_helper.hpp"
 #include "ck/tensor_operation/gpu/device/device_image_to_column.hpp"
 #include "ck/tensor_operation/gpu/grid/gridwise_image_to_column.hpp"
-#include "ck/host_utility/device_prop.hpp"
 #include "ck/host_utility/kernel_launch.hpp"
-#include "ck/host_utility/stream_utility.hpp"
 #include "ck/tensor_operation/gpu/grid/block_to_ctile_map.hpp"
 #include "ck/tensor_operation/operator_transform/transform_conv_fwd_to_gemm.hpp"
 #include "ck/tensor_operation/gpu/device/convolution_forward_specialization.hpp"
@@ -284,24 +282,28 @@ struct DeviceImageToColumnImpl
             return false;
         }
 
-        const auto x_pad_left  = arg.input_left_pads_[NDimSpatial - I1];
-        const auto x_pad_right = arg.input_right_pads_[NDimSpatial - I1];
+        const auto w_pad_left  = arg.input_left_pads_[NDimSpatial - I1];
+        const auto w_pad_right = arg.input_right_pads_[NDimSpatial - I1];
         const auto dilation_x  = arg.conv_filter_dilations_[NDimSpatial - I1];
         const auto stride_x    = arg.conv_filter_strides_[NDimSpatial - I1];
-        bool is_c_packed       = arg.input_g_n_c_wis_strides_[NDimSpatial + I2] == arg.C_;
+        bool is_x_packed       = arg.input_g_n_c_wis_strides_[NDimSpatial + I2] == arg.C_;
+        bool is_c_packed       = arg.input_g_n_c_wis_strides_[I2] == 1;
 
+        // check vector acces with c not packed
+        if(!is_c_packed && ScalarPerVector != 1)
+            return false;
         // check vector access of filter window row (only C if C is not packed)
-        if(!is_c_packed && arg.C_ % ScalarPerVector != 0)
+        if(!is_x_packed && arg.C_ % ScalarPerVector != 0)
             return false;
         // check vector access of filter window row (X * C)
         if(arg.X_ * arg.C_ % ScalarPerVector != 0)
             return false;
-        // check vector access of pads (x_pad_left/x_pad_right * C)
-        if(x_pad_left * arg.C_ % ScalarPerVector != 0 ||
-           x_pad_right * arg.C_ % ScalarPerVector != 0)
+        // check vector access of pads (w_pad_left/w_pad_right * C)
+        if(w_pad_left * arg.C_ % ScalarPerVector != 0 ||
+           w_pad_right * arg.C_ % ScalarPerVector != 0)
             return false;
         // check vector access of with stride and pad
-        if((x_pad_left != 0 || x_pad_right != 0) && stride_x > 1 && arg.C_ % ScalarPerVector != 0)
+        if((w_pad_left != 0 || w_pad_right != 0) && stride_x > 1 && arg.C_ % ScalarPerVector != 0)
             return false;
         // check vector access of with dilation
         if(dilation_x > 1 && arg.C_ % ScalarPerVector != 0)

include/ck/tensor_operation/gpu/grid/gridwise_image_to_column.hpp

@@ -10,7 +10,6 @@
 #include "ck/tensor_operation/gpu/grid/block_to_ctile_map.hpp"
 #include "ck/tensor_operation/gpu/grid/gridwise_gemm_pipeline_selector.hpp"
 #include "ck/tensor_operation/gpu/block/blockwise_gemm_xdlops.hpp"
-#include "ck/tensor_operation/gpu/block/thread_group_tensor_slice_transfer_v4r1.hpp"
 #include "ck/tensor_operation/gpu/block/thread_group_tensor_slice_transfer_v7.hpp"
 #include "ck/tensor_operation/gpu/thread/threadwise_tensor_slice_transfer.hpp"
 #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"

library/include/ck/library/reference_tensor_operation/cpu/reference_image_to_column.hpp

@@ -15,19 +15,17 @@ namespace ck {
 namespace tensor_operation {
 namespace host {
 
-//
-// @brief      Reference implementation for image to column.
-//
-// @paragraph
-//             Tensor descriptor in NCHW dimensional order
-//
-// @tparam     InDataType               Input tensor data type.
-// @tparam     OutDataType              Output tensor data type.
-// @tparam     NDimSpatial  Number of spatial dimensions.
-//
-// input descriptor in [N, C, Di, Hi, Wi] order
-// output descriptor in [N * Do * Ho * Wo, C * Z * Y * X] order
-// phyiscal layout is [N, Di, Hi, Wi, C]
+/**
+ * \brief Reference implementation for image to column.
+ *
+ * Tensor descriptor has [G, N, C, Di, Hi, Wi] data layout.
+ * G must be equal to 1. Memory layout is [G, N, Di, Hi, Wi, C].
+ *
+ * \tparam NDimSpatial Number of spatial dimensions.
+ * \tparam InputLayout Input Layout.
+ * \tparam InDataType Input Data Type.
+ * \tparam OutDataType Output Data Type.
+ */
 template <ck::index_t NDimSpatial,
           typename InputLayout,
           typename InDataType,
@@ -242,12 +240,12 @@ struct ReferenceImageToColumn : public device::BaseOperator
     {
         using namespace tensor_layout::convolution;
 
-        if(!(std::is_same_v<InputLayout, GNWC> || std::is_same_v<InputLayout, GNHWC> ||
-             std::is_same_v<InputLayout, GNDHWC>))
+        if constexpr(!(std::is_same_v<InputLayout, GNWC> || std::is_same_v<InputLayout, GNHWC> ||
+                       std::is_same_v<InputLayout, GNDHWC>))
         {
             return false;
         }
-        if(!(NDimSpatial >= 1 && NDimSpatial <= 3))
+        if constexpr(!(NDimSpatial >= 1 && NDimSpatial <= 3))
         {
             return false;
         }