aboutsummaryrefslogtreecommitdiff
path: root/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp
diff options
context:
space:
mode:
Diffstat (limited to 'src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp')
-rw-r--r--src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp8
1 files changed, 5 insertions, 3 deletions
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp
index c34018a000..fcfa7f878d 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2019-2020 Arm Limited.
+ * Copyright (c) 2019-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -58,7 +58,8 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights,
ARM_COMPUTE_UNUSED(idx_c);
ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_c) != (input->dimension(idx_c) * depth_multiplier));
- const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation);
+ const ConvolutionInfo info{ conv_info, depth_multiplier, ActivationLayerInfo(), dilation };
+ const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*input, *weights, info);
const bool is_quantized = is_data_type_quantized(input->data_type());
@@ -156,7 +157,8 @@ void CLDepthwiseConvolutionLayerNativeKernel::configure(const CLCompileContext &
auto padding_info = get_padding_info({ input, output });
- const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*(input->info()), *(weights->info()), conv_info, depth_multiplier, dilation);
+ const ConvolutionInfo info{ conv_info, depth_multiplier, ActivationLayerInfo(), dilation };
+ const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*(input->info()), *(weights->info()), info);
auto_init_if_empty(*(output->info()), input->info()->clone()->set_tensor_shape(output_shape).set_quantization_info(output->info()->quantization_info()));
_input = input;