diff options
Diffstat (limited to 'arm_compute/core/utils/misc/ShapeCalculator.h')
| -rw-r--r-- | arm_compute/core/utils/misc/ShapeCalculator.h | 42 |
1 files changed, 8 insertions, 34 deletions
diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h index 26b337d5c5..b46b1b2535 100644 --- a/arm_compute/core/utils/misc/ShapeCalculator.h +++ b/arm_compute/core/utils/misc/ShapeCalculator.h @@ -402,10 +402,12 @@ inline TensorShape compute_transposed_shape(const ITensorInfo &input) * @param[in] weights Weights tensor info * @param[in] conv_info Padding and stride information to use for the convolution. * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth. + * @param[in] dilation Dilation, in elements, across x and y. Defaults to (1, 1). * * @return the calculated shape */ -inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input, const ITensorInfo &weights, PadStrideInfo conv_info, unsigned int depth_multiplier) +inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input, const ITensorInfo &weights, PadStrideInfo conv_info, unsigned int depth_multiplier, const Size2D &dilation = Size2D(1U, + 1U)) { const TensorShape input_shape{ input.tensor_shape() }; const TensorShape weights_shape{ weights.tensor_shape() }; @@ -415,43 +417,15 @@ inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input, const int height_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); const int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL); - unsigned int output_width = 0; - unsigned int output_height = 0; - std::tie(output_width, output_height) = scaled_dimensions(input_shape[width_idx], input_shape[height_idx], - weights_shape[width_idx], weights_shape[height_idx], - conv_info); - - TensorShape output_shape{ input_shape }; - output_shape.set(width_idx, output_width); - output_shape.set(height_idx, output_height); - output_shape.set(channel_idx, input_shape[channel_idx] * depth_multiplier); - - return output_shape; -} - -/** Calculate the depthwise convolution output shape of a tensor - * - * @param[in] input Input tensor info - * @param[in] weights_width Weights width - * @param[in] weights_height Weights height - * @param[in] conv_info Padding and stride information to use for the convolution. - * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth. - * - * @return the calculated shape - */ -inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input, int weights_width, int weights_height, PadStrideInfo conv_info, unsigned int depth_multiplier) -{ - const TensorShape input_shape{ input.tensor_shape() }; - - const DataLayout data_layout = input.data_layout(); - const int width_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); - const int height_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); - const int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL); + const DataLayout weights_data_layout = weights.data_layout(); + const int weights_width_idx = get_data_layout_dimension_index(weights_data_layout, DataLayoutDimension::WIDTH); + const int weights_height_idx = get_data_layout_dimension_index(weights_data_layout, DataLayoutDimension::HEIGHT); unsigned int output_width = 0; unsigned int output_height = 0; std::tie(output_width, output_height) = scaled_dimensions(input_shape[width_idx], input_shape[height_idx], - weights_width, weights_width, conv_info); + weights_shape[weights_width_idx], weights_shape[weights_height_idx], + conv_info, dilation); TensorShape output_shape{ input_shape }; output_shape.set(width_idx, output_width); |