COMPMID-809: Add NHWC data format on CLGEMMConvolutionLayer.
Change-Id: I50e4f5e7d47e21c300f754bee2c216863075b5cf
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/136191
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp
index 97e9e10..712a117 100644
--- a/src/core/CL/CLKernelLibrary.cpp
+++ b/src/core/CL/CLKernelLibrary.cpp
@@ -329,7 +329,8 @@
{ "remap_nearest_neighbour", "remap.cl" },
{ "remap_bilinear", "remap.cl" },
{ "reshape_layer", "reshape_layer.cl" },
- { "reshape_to_columns", "convolution_layer.cl" },
+ { "reshape_to_columns_nchw", "convolution_layer.cl" },
+ { "reshape_to_columns_nhwc", "convolution_layer.cl" },
{ "RGB888_to_IYUV_bt709", "color_convert.cl" },
{ "RGB888_to_NV12_bt709", "color_convert.cl" },
{ "RGB888_to_RGBA8888_bt709", "color_convert.cl" },
diff --git a/src/core/CL/cl_kernels/col2im.cl b/src/core/CL/cl_kernels/col2im.cl
index 9b5a7b5..6e491f3 100644
--- a/src/core/CL/cl_kernels/col2im.cl
+++ b/src/core/CL/cl_kernels/col2im.cl
@@ -52,8 +52,6 @@
* @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes)
* @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes)
- * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes)
* @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
* @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr
* @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes)
@@ -66,11 +64,11 @@
* @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes)
*/
__kernel void col2im(
- TENSOR3D_DECLARATION(src),
+ IMAGE_DECLARATION(src),
TENSOR3D_DECLARATION(dst),
uint dst_stride_w)
{
- Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src);
+ Image src = CONVERT_TO_IMAGE_STRUCT(src);
VEC_DATA_TYPE(DATA_TYPE, 8)
data = vload8(0, (__global DATA_TYPE *)src.ptr);
@@ -113,8 +111,6 @@
* @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes)
* @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes)
- * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes)
* @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
* @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr
* @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes)
@@ -127,11 +123,11 @@
* @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes)
*/
__kernel void col2im(
- TENSOR3D_DECLARATION(src),
+ IMAGE_DECLARATION(src),
TENSOR3D_DECLARATION(dst),
uint dst_stride_w)
{
- Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src);
+ Image src = CONVERT_TO_IMAGE_STRUCT(src);
Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(dst);
// Compute output offset
diff --git a/src/core/CL/cl_kernels/convolution_layer.cl b/src/core/CL/cl_kernels/convolution_layer.cl
index f8e0c27..6a70b00 100644
--- a/src/core/CL/cl_kernels/convolution_layer.cl
+++ b/src/core/CL/cl_kernels/convolution_layer.cl
@@ -55,7 +55,7 @@
* @param[in] depth The depth of the input tensor
* @param[in] total_filters Total number of filters. 4th dimension of the weights matrix
*/
-__kernel void reshape_to_columns(
+__kernel void reshape_to_columns_nchw(
TENSOR3D_DECLARATION(src),
IMAGE_DECLARATION(dst),
#ifdef HAS_BIAS
@@ -97,4 +97,74 @@
}
}
}
+
+/** This kernel reshapes the tensor's low three dimensions to single column
+ *
+ * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
+ *
+ * @param[in] src_ptr Pointer to the source tensor. Supported data types: F16/F32
+ * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes)
+ * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes)
+ * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes)
+ * @param[in] src_step_z src_stride_z * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
+ * @param[out] dst_ptr Pointer to the destination tensor. Same as @p src_ptr
+ * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes)
+ * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes)
+ * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor
+ * @param[in] bias_ptr Pointer to the bias tensor. Same as @p src_ptr
+ * @param[in] bias_stride_x Stride of the bias tensor in X dimension (in bytes)
+ * @param[in] bias_step_x bias_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] bias_offset_first_element_in_bytes The offset of the first element in the source tensor
+ * @param[in] depth The depth of the input tensor
+ * @param[in] width The width of the input tensor
+ * @param[in] height The height of the input tensor
+ * @param[in] total_filters Total number of filters. 4th dimension of the weights matrix
+ */
+__kernel void reshape_to_columns_nhwc(
+ TENSOR3D_DECLARATION(src),
+ IMAGE_DECLARATION(dst),
+#ifdef HAS_BIAS
+ VECTOR_DECLARATION(bias),
+#endif /* HAS_BIAS */
+ uint depth, uint width, uint height, uint total_filters)
+{
+ Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src);
+ bool is_last_thread = (get_global_id(0) == (get_global_size(0) - 1) && get_global_id(1) == (get_global_size(1) - 1) && get_global_id(2) == (get_global_size(2) - 1));
+
+ __global uchar *tmp_src_ptr = src.ptr;
+ __global uchar *tmp_dst_ptr = dst_ptr + dst_offset_first_element_in_bytes + get_global_id(1) * dst_stride_y + get_global_id(2) * width * dst_stride_y + get_global_id(
+ 0) * width * height * dst_stride_y;
+#ifdef HAS_BIAS
+ __global uchar *tmp_bias_ptr = bias_ptr + bias_offset_first_element_in_bytes;
+#endif /* HAS_BIAS */
+
+ if(is_last_thread)
+ {
+ for(uint i = 0; i < total_filters; ++i)
+ {
+ *((__global DATA_TYPE *)tmp_dst_ptr) = *((__global DATA_TYPE *)tmp_src_ptr);
+
+#ifdef HAS_BIAS
+ *((__global DATA_TYPE *)(tmp_dst_ptr + dst_stride_y)) = *((__global DATA_TYPE *)(tmp_bias_ptr));
+ tmp_bias_ptr += bias_stride_x;
+#endif /* HAS_BIAS */
+ tmp_src_ptr += height * src_stride_z;
+ tmp_dst_ptr += dst_stride_x;
+ }
+ }
+ else
+ {
+ for(uint i = 0; i < total_filters; ++i)
+ {
+ *((__global DATA_TYPE *)tmp_dst_ptr) = *((__global DATA_TYPE *)tmp_src_ptr);
+ tmp_src_ptr += height * src_stride_z;
+ tmp_dst_ptr += dst_stride_x;
+ }
+ }
+}
#endif // defined(DATA_TYPE)
\ No newline at end of file
diff --git a/src/core/CL/cl_kernels/im2col.cl b/src/core/CL/cl_kernels/im2col.cl
index c60c9a9..6f25ad4 100644
--- a/src/core/CL/cl_kernels/im2col.cl
+++ b/src/core/CL/cl_kernels/im2col.cl
@@ -136,6 +136,7 @@
* @note The pad_left, pad_right, pad_top and pad_bottom must be passed at compile time using -DPAD_LEFT, -DPAD_RIGHT, -DPAD_TOP and -DPAD_BOTTOM: e.g. -DPAD_LEFT=1, -DPAD_RIGHT=2, -DPAD_TOP=3 and -DPAD_BOTTOM=2
* @note The zero value to store in case we load values out-of-bounds must be passed at compile time using -DPAD_VALUE: e.g. -DPAD_VALUE=0.0
* @note The stride along the X and Y directions must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1 and -DSTRIDE_Y=1
+ * @note The dilation_x and dilation_y must be passed at compile time using -DDILATION_X and -DDILATION_Y: e.g. -DDILATION_X=1, -DDILATION_Y=1
* @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row.
*
* @param[in] src_ptr Pointer to the source tensor. Supported data types: QS8/QASYMM8/QS16/F16/F32
@@ -182,16 +183,18 @@
for(int yk = 0; yk < KERNEL_HEIGHT; ++yk)
{
- const int y0 = yi + yk;
+ const int dilated_offset_y = yk * DILATION_Y;
+ const int y0 = yi + dilated_offset_y;
if(y0 >= 0 && y0 < SRC_HEIGHT)
{
int xk;
for(xk = 0; xk < KERNEL_WIDTH; xk++)
{
- const int x0 = xi + xk;
+ const int dilated_offset_x = xk * DILATION_X;
+ const int x0 = xi + dilated_offset_x;
if(x0 >= 0 && x0 < SRC_WIDTH)
{
- *((__global DATA_TYPE *)output_ptr) = PTR_TO_VALUE(input_ptr + xk * src_stride_y + yk * src_stride_z, DATA_TYPE);
+ *((__global DATA_TYPE *)output_ptr) = PTR_TO_VALUE(input_ptr + dilated_offset_x * src_stride_y + dilated_offset_y * src_stride_z, DATA_TYPE);
}
else
{
diff --git a/src/core/CL/kernels/CLCol2ImKernel.cpp b/src/core/CL/kernels/CLCol2ImKernel.cpp
index 4e44420..64e6a0b 100644
--- a/src/core/CL/kernels/CLCol2ImKernel.cpp
+++ b/src/core/CL/kernels/CLCol2ImKernel.cpp
@@ -140,23 +140,25 @@
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(ICLKernel::window(), window);
- // The collapse method rely on the assumption that the third dimension of input buffer is 1
- ARM_COMPUTE_ERROR_ON(window.z().end() != 1);
+
+ Window out_window;
+ out_window.use_tensor_dimensions(_output->info()->tensor_shape());
Window collapsed_window = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);
- Window slice = collapsed_window.first_slice_window_3D();
+ Window slice = collapsed_window.first_slice_window_2D();
+ Window slice_out = out_window.first_slice_window_3D();
// Set static kernel arguments
- unsigned int idx = 2 * num_arguments_per_3D_tensor();
+ unsigned int idx = num_arguments_per_2D_tensor() + num_arguments_per_3D_tensor();
_kernel.setArg<cl_uint>(idx++, _output->info()->strides_in_bytes()[3]);
do
{
// Set inputs
unsigned int idx = 0;
- add_3D_tensor_argument(idx, _input, slice);
- add_3D_tensor_argument(idx, _output, slice);
+ add_2D_tensor_argument(idx, _input, slice);
+ add_3D_tensor_argument(idx, _output, slice_out);
enqueue(queue, *this, slice, _lws_hint);
}
- while(collapsed_window.slide_window_slice_3D(slice));
+ while(collapsed_window.slide_window_slice_2D(slice) && out_window.slide_window_slice_3D(slice_out));
}
diff --git a/src/core/CL/kernels/CLIm2ColKernel.cpp b/src/core/CL/kernels/CLIm2ColKernel.cpp
index 328b396..21deb92 100644
--- a/src/core/CL/kernels/CLIm2ColKernel.cpp
+++ b/src/core/CL/kernels/CLIm2ColKernel.cpp
@@ -143,7 +143,7 @@
{
case 1:
// Optimized im2col1x1 if stride_x = 1 and conv_info.has_padding() = false
- if(conv_info.stride().first == 1 && !conv_info.has_padding())
+ if(conv_info.stride().first == 1 && !conv_info.has_padding() && data_layout == DataLayout::NCHW)
{
// Set hint for LWS
_lws_hint = cl::NDRange(1, 1, 8);
@@ -350,11 +350,14 @@
// Change the Z dimension's step back to 1
window_collapsed.set_dimension_step(Window::DimZ, 1);
+ Window window_output;
+ window_output.use_tensor_dimensions(_output->info()->tensor_shape());
+
const Window first_slice_3d = window_collapsed.first_slice_window_3D();
Window slice = first_slice_3d;
Window slice_in = first_slice_3d;
- Window slice_out = first_slice_3d;
+ Window slice_out = window_output.first_slice_window_2D();
const bool out_dim_not_same_input_dim = _convolved_dims.first != _input->info()->dimension(width_idx) || _convolved_dims.second != _input->info()->dimension(height_idx);
@@ -386,21 +389,16 @@
slice_in.set(Window::DimY, Window::Dimension(0, 0, 0));
slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
- // Setup output slice
- slice_out.set(Window::DimX, Window::Dimension(0, _output->info()->dimension(0), _kernel_dims.area()));
- slice_out.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1), _output->info()->dimension(1)));
- slice_out.set(Window::DimZ, Window::Dimension(0, 1, 1));
-
do
{
unsigned int idx = 0;
add_3D_tensor_argument(idx, _input, slice_in);
add_2D_tensor_argument(idx, _output, slice_out);
_kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input->info()->strides_in_bytes()[3]));
- _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[3]));
+ _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[2]));
enqueue(queue, *this, slice, _lws_hint);
}
- while(window_collapsed.slide_window_slice_3D(slice) && window_collapsed.slide_window_slice_3D(slice_out) && window_collapsed.slide_window_slice_3D(slice_in));
+ while(window_collapsed.slide_window_slice_3D(slice) && window_output.slide_window_slice_2D(slice_out) && window_collapsed.slide_window_slice_3D(slice_in));
}
void CLIm2ColKernel::run_reduced(const Window &window, cl::CommandQueue &queue)
diff --git a/src/core/CL/kernels/CLWeightsReshapeKernel.cpp b/src/core/CL/kernels/CLWeightsReshapeKernel.cpp
index c0a4517..b012d58 100644
--- a/src/core/CL/kernels/CLWeightsReshapeKernel.cpp
+++ b/src/core/CL/kernels/CLWeightsReshapeKernel.cpp
@@ -85,7 +85,8 @@
(biases != nullptr) ? biases->info() : nullptr,
output->info()));
- const DataType data_type = input->info()->data_type();
+ const DataType data_type = input->info()->data_type();
+ const DataLayout data_layout = input->info()->data_layout();
_biases = biases;
_output = output;
@@ -98,7 +99,8 @@
build_opts.add_option_if(is_data_type_fixed_point(data_type), "-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position()));
// Create kernel
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("reshape_to_columns", build_opts.options()));
+ std::string kernel_name = std::string("reshape_to_columns_") + lower_string(string_from_data_layout(data_layout));
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
// Set static arguments
unsigned int idx = num_arguments_per_3D_tensor() + num_arguments_per_2D_tensor();