COMPMID-2047: Add support for dilation in CLDepthwiseConvolution.
Change-Id: I3106aa34bd168985a56791613d95072756be6e9b
Signed-off-by: Usama Arif <usama.arif@arm.com>
Reviewed-on: https://review.mlplatform.org/c/958
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez <pablo.tello@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp
index 83fac16..ec27e41 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp
@@ -43,7 +43,7 @@
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier,
- const ActivationLayerInfo &act_info)
+ const ActivationLayerInfo &act_info, const Size2D dilation)
{
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
@@ -56,6 +56,8 @@
ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(0) != 3 || weights->dimension(1) != 3);
ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().first < 1 || conv_info.stride().first > 3);
+ ARM_COMPUTE_RETURN_ERROR_ON((dilation.x() < 1) || (dilation.y() < 1));
+
const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type());
if(biases != nullptr)
@@ -74,7 +76,7 @@
if(output->total_size() != 0)
{
- const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier);
+ const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape);
}
@@ -82,10 +84,10 @@
}
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier,
- GPUTarget gpu_target, std::string &kernel_name)
+ GPUTarget gpu_target, std::string &kernel_name, const Size2D dilation)
{
// Output auto inizialitation if not yet initialized
- const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier);
+ const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation);
auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape));
const unsigned int conv_stride_x = conv_info.stride().first;
@@ -176,10 +178,12 @@
kernel_name += (is_qasymm ? "_nchw" : "");
num_elems_written_per_iteration_x = 8 / data_size_from_type(input->data_type());
- num_elems_written_per_iteration_y = (is_qasymm && conv_stride_y == 1) ? 2 : 1;
+ num_elems_written_per_iteration_y = (is_qasymm && conv_stride_y == 1 && dilation.y() == 1) ? 2 : 1;
num_elems_read_per_iteration_x = 3 + (num_elems_written_per_iteration_x - 1) * conv_stride_x;
num_elems_read_per_iteration_y = num_elems_written_per_iteration_y + 2;
}
+ num_elems_read_per_iteration_x += (num_elems_read_per_iteration_x - 1) * (dilation.x() - 1);
+ num_elems_read_per_iteration_y += (num_elems_read_per_iteration_y - 1) * (dilation.y() - 1);
// Create window and update padding
Window win = calculate_max_window(*output, Steps(num_elems_written_per_iteration_x, num_elems_written_per_iteration_y));
@@ -210,10 +214,10 @@
}
void CLDepthwiseConvolutionLayer3x3NCHWKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
- unsigned int depth_multiplier, ActivationLayerInfo act_info)
+ unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, act_info));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, act_info, dilation));
bool is_qasymm = is_data_type_quantized_asymmetric(input->info()->data_type());
@@ -231,7 +235,7 @@
std::string kernel_name;
const GPUTarget gpu_target = get_target();
- auto win_config = validate_and_configure_window(input->info(), weights->info(), output->info(), conv_info, depth_multiplier, gpu_target, kernel_name);
+ auto win_config = validate_and_configure_window(input->info(), weights->info(), output->info(), conv_info, depth_multiplier, gpu_target, kernel_name, dilation);
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure_internal(win_config.second);
@@ -240,6 +244,8 @@
build_opts.add_option("-DDST_CHANNELS=" + support::cpp11::to_string(_output->info()->tensor_shape().z()));
build_opts.add_option("-DDEPTH_MULTIPLIER=" + support::cpp11::to_string(depth_multiplier));
build_opts.add_option("-DCONV_STRIDE_X=" + support::cpp11::to_string(_conv_stride_x));
+ build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x()));
+ build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y()));
build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS");
if(is_qasymm)
@@ -292,12 +298,11 @@
}
Status CLDepthwiseConvolutionLayer3x3NCHWKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
- unsigned int depth_multiplier,
- ActivationLayerInfo act_info, GPUTarget gpu_target)
+ unsigned int depth_multiplier, ActivationLayerInfo act_info, GPUTarget gpu_target, const Size2D &dilation)
{
std::string kernel_name;
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info));
- ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), output->clone().get(), conv_info, depth_multiplier, gpu_target, kernel_name).first);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), output->clone().get(), conv_info, depth_multiplier, gpu_target, kernel_name, dilation).first);
return Status{};
}
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
index 431039c..86d186b 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
@@ -42,7 +42,7 @@
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier,
- const ActivationLayerInfo &act_info)
+ const ActivationLayerInfo &act_info, const Size2D &dilation)
{
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32, DataType::QASYMM8);
@@ -57,6 +57,8 @@
ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().first < 1);
ARM_COMPUTE_RETURN_ERROR_ON(std::max(conv_info.pad_top(), conv_info.pad_bottom()) > 1);
+ ARM_COMPUTE_RETURN_ERROR_ON((dilation.x() < 1) || (dilation.y() < 1));
+
const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type());
const size_t weights_width = 3;
const size_t weights_height = 3;
@@ -89,7 +91,8 @@
if(output->total_size() != 0)
{
- const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*input, weights_width, weights_height, conv_info, depth_multiplier);
+ const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(
+ *input, TensorInfo(TensorShape(weights_width, weights_height), 1, weights->data_type()).set_data_layout(DataLayout::NCHW), conv_info, depth_multiplier, dilation);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape);
}
@@ -97,13 +100,14 @@
}
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *output,
- const PadStrideInfo &conv_info, unsigned int depth_multiplier)
+ const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation)
{
const size_t weights_width = 3;
const size_t weights_height = 3;
// Get convolved dimensions
- const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*input, weights_width, weights_height, conv_info, depth_multiplier);
+ const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(
+ *input, TensorInfo(TensorShape(weights_width, weights_height), 1, weights->data_type()).set_data_layout(DataLayout::NCHW), conv_info, depth_multiplier, dilation);
// Output auto inizialitation if not yet initialized
auto_init_if_empty(*output,
@@ -112,10 +116,10 @@
input->data_type(),
input->quantization_info());
- const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type());
- const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1));
+ const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type());
+ const bool is_stride_1_dilation_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1) && dilation.x() == 1 && dilation.y() == 1);
- const unsigned int num_rows_processed_per_iteration = is_stride_1 ? 2 : 1;
+ const unsigned int num_rows_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1;
const unsigned int num_elems_accessed_per_iteration = is_qasymm ? 4 : (8 / input->element_size());
const unsigned int num_rows_read_per_iteration = num_rows_processed_per_iteration + 2;
const unsigned int num_rows_written_per_iteration = std::ceil(num_rows_processed_per_iteration / static_cast<float>(conv_info.stride().first));
@@ -166,15 +170,17 @@
}
void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
- unsigned int depth_multiplier, ActivationLayerInfo act_info)
+ unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, act_info));
- auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, act_info, dilation));
+ auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, dilation);
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
- const bool is_qasymm = is_data_type_quantized_asymmetric(input->info()->data_type());
- const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1));
+ const bool is_qasymm = is_data_type_quantized_asymmetric(input->info()->data_type());
+ const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1));
+ const bool is_stride_1_dilation_1 = (is_stride_1 && dilation.x() == 1 && dilation.y() == 1);
+
const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device());
_input = input;
@@ -182,8 +188,8 @@
_weights = weights;
_biases = biases;
_conv_stride_y = conv_info.stride().second;
- _num_rows_processed_per_iteration = is_stride_1 ? 2 : 1;
- _num_planes_processed_per_iteration = is_stride_1 ? 2 : 1;
+ _num_rows_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1;
+ _num_planes_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1;
// If QASYMM8 and the 8 bit dot product is available, force _num_planes_processed_per_iteration to 1
if(is_dot8_supported && is_qasymm)
@@ -201,6 +207,8 @@
build_opts.add_option("-DSRC_DIM_2=" + support::cpp11::to_string(_input->info()->dimension(2)));
build_opts.add_option("-DCONV_PAD_TOP=" + support::cpp11::to_string(conv_info.pad_top()));
build_opts.add_option("-DCONV_PAD_LEFT=" + support::cpp11::to_string(conv_info.pad_left()));
+ build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x()));
+ build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y()));
if(is_qasymm)
{
@@ -238,7 +246,7 @@
build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(_input->info()->data_type()));
}
- if(is_stride_1)
+ if(is_stride_1_dilation_1)
{
build_opts.add_option("-DNUM_ROWS_PROCESSED=" + support::cpp11::to_string(_num_rows_processed_per_iteration));
build_opts.add_option("-DNUM_PLANES_PROCESSED=" + support::cpp11::to_string(_num_planes_processed_per_iteration));
@@ -257,14 +265,14 @@
if(is_qasymm)
{
kernel_name = std::string("dwc_3x3_reshaped_qasymm8");
- kernel_name += (is_dot8_supported && is_stride_1 ? "_dot8" : "");
- kernel_name += (is_stride_1 ? "_stride1" : "");
+ kernel_name += (is_dot8_supported && is_stride_1_dilation_1 ? "_dot8" : "");
+ kernel_name += (is_stride_1_dilation_1 ? "_stride1" : "");
kernel_name += "_nhwc";
}
else
{
kernel_name = std::string("depthwise_convolution_3x3_nhwc");
- kernel_name += (is_stride_1 ? "_stride1" : "");
+ kernel_name += (is_stride_1_dilation_1 ? "_stride1" : "");
}
ICLKernel::configure_internal(win_config.second);
@@ -287,13 +295,12 @@
}
Status CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
- unsigned int depth_multiplier,
- ActivationLayerInfo act_info)
+ unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation)
{
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation));
ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(),
biases != nullptr ? biases->clone().get() : nullptr,
- output->clone().get(), conv_info, depth_multiplier)
+ output->clone().get(), conv_info, depth_multiplier, dilation)
.first);
return Status{};
diff --git a/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp b/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp
index beff7ae..28d4ff2 100644
--- a/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp
@@ -44,7 +44,8 @@
namespace
{
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier)
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier,
+ const Size2D &dilation)
{
const size_t idx_c = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL);
@@ -55,16 +56,18 @@
ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_asymmetric(input->data_type()) && has_bias);
ARM_COMPUTE_RETURN_ERROR_ON((input->dimension(idx_c) * depth_multiplier) != output->dimension(2));
ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(0) != (kernel_dims.width * kernel_dims.height + ((has_bias) ? 1 : 0)));
+ ARM_COMPUTE_RETURN_ERROR_ON((dilation.x() < 1) || dilation.y() < 1);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
return Status{};
}
} // namespace
-void CLDepthwiseIm2ColKernel::configure(const ICLTensor *input, ICLTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier)
+void CLDepthwiseIm2ColKernel::configure(const ICLTensor *input, ICLTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier,
+ const Size2D &dilation)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), kernel_dims, conv_info, has_bias, depth_multiplier));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), kernel_dims, conv_info, has_bias, depth_multiplier, dilation));
_input = input;
_output = output;
@@ -88,6 +91,8 @@
build_opts.add_option("-DKERNEL_WIDTH=" + support::cpp11::to_string(kernel_dims.width));
build_opts.add_option("-DKERNEL_HEIGHT=" + support::cpp11::to_string(kernel_dims.height));
build_opts.add_option("-DDEPTH_MULTIPLIER=" + support::cpp11::to_string(depth_multiplier));
+ build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x()));
+ build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y()));
build_opts.add_option("-D" + string_from_data_layout(input->info()->data_layout()));
build_opts.add_option_if(has_bias, "-DHAS_BIAS");
build_opts.add_option_if_else(is_data_type_quantized_asymmetric(input->info()->data_type()),
@@ -104,9 +109,10 @@
ICLKernel::configure_internal(win);
}
-Status CLDepthwiseIm2ColKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier)
+Status CLDepthwiseIm2ColKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier,
+ const Size2D &dilation)
{
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, kernel_dims, conv_info, has_bias, depth_multiplier));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, kernel_dims, conv_info, has_bias, depth_multiplier, dilation));
return Status{};
}