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/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{};