diff options
Diffstat (limited to 'arm_compute')
-rw-r--r-- | arm_compute/core/NEON/kernels/NEIm2ColKernel.h | 2 | ||||
-rw-r--r-- | arm_compute/core/utils/misc/ShapeCalculator.h | 42 | ||||
-rw-r--r-- | arm_compute/runtime/NEON/functions/NEIm2Col.h | 22 |
3 files changed, 52 insertions, 14 deletions
diff --git a/arm_compute/core/NEON/kernels/NEIm2ColKernel.h b/arm_compute/core/NEON/kernels/NEIm2ColKernel.h index ecfce2436d..5aa803f4fd 100644 --- a/arm_compute/core/NEON/kernels/NEIm2ColKernel.h +++ b/arm_compute/core/NEON/kernels/NEIm2ColKernel.h @@ -111,7 +111,7 @@ public: void run(const Window &window, const ThreadInfo &info) override; private: - /** Template function to run the im2col optimised for the fully connected layer case + /** Template function to run the im2col optimised for the fully connected and flatten layers case * * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()). */ diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h index c3d5b64a92..e174227302 100644 --- a/arm_compute/core/utils/misc/ShapeCalculator.h +++ b/arm_compute/core/utils/misc/ShapeCalculator.h @@ -107,13 +107,6 @@ inline TensorShape compute_reductionB_shape(const ITensorInfo &a) return shape_vector_sum_row; } -inline TensorShape compute_im2col_shape(const ITensorInfo &input) -{ - TensorShape shape_im2col{ input.tensor_shape() }; - shape_im2col.collapse(3); - - return shape_im2col; -} inline TensorShape compute_col2im_shape(const ITensorInfo &input, std::pair<unsigned int, unsigned int> convolved_dims) { TensorShape col2im_shape{ input.tensor_shape() }; @@ -159,7 +152,25 @@ inline TensorShape compute_deconvolution_shape(const ITensorInfo &input, unsigne return scale_out_shape; } -inline TensorShape compute_im2col_shape(const ITensorInfo *input, const int num_input_dimensions = 3) +inline TensorShape compute_im2col_conv_shape(const ITensorInfo *input, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation) +{ + // The output shape will be the 2D shape used as input for GEMM [ out_channels * kernel_area, num_elems_per_out_channel ] + + TensorShape output_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); + + std::pair<unsigned int, unsigned int> out_dims = scaled_dimensions(output_shape[width_idx], output_shape[height_idx], kernel_dims.width, kernel_dims.height, conv_info, dilation); + output_shape.set(width_idx, (output_shape[channel_idx] * kernel_dims.area() + (has_bias ? 1 : 0))); + output_shape.set(height_idx, (out_dims.first * out_dims.second)); + output_shape.set(channel_idx, 1); + + return output_shape; +} +inline TensorShape compute_im2col_fc_shape(const ITensorInfo *input, const int num_input_dimensions = 3) { TensorShape output_shape{ input->tensor_shape() }; @@ -167,6 +178,21 @@ inline TensorShape compute_im2col_shape(const ITensorInfo *input, const int num_ return output_shape; } +inline TensorShape compute_im2col_flatten_shape(const ITensorInfo *input) +{ + // The output shape will be the flatten version of the input (i.e. [ width * height * channels, 1, 1, ... ] ). Used for FlattenLayer. + + ARM_COMPUTE_ERROR_ON(input->num_dimensions() < 3); + + TensorShape output_shape{ input->tensor_shape() }; + + const size_t flatten_shape = input->dimension(0) * input->dimension(1) * input->dimension(2); + output_shape.set(0, flatten_shape); + output_shape.remove_dimension(1); + output_shape.remove_dimension(1); + + return output_shape; +} inline TensorShape compute_interleave_custom_shape(const TensorShape &input, const int x_interleave, const int y_interleave) { TensorShape output_shape{ input }; diff --git a/arm_compute/runtime/NEON/functions/NEIm2Col.h b/arm_compute/runtime/NEON/functions/NEIm2Col.h index cf4999b5af..caa8a011f6 100644 --- a/arm_compute/runtime/NEON/functions/NEIm2Col.h +++ b/arm_compute/runtime/NEON/functions/NEIm2Col.h @@ -26,6 +26,7 @@ #include "arm_compute/runtime/NEON/INESimpleFunction.h" +#include "arm_compute/core/NEON/kernels/NEIm2ColKernel.h" #include "arm_compute/core/Size2D.h" #include "arm_compute/core/Types.h" @@ -34,9 +35,11 @@ namespace arm_compute class ITensor; /** Basic function to run @ref NEIm2ColKernel */ -class NEIm2Col : public INESimpleFunction +class NEIm2Col : public IFunction { public: + /** Default constructor */ + NEIm2Col(); /** Configure the im2col NEON kernel * * @param[in] input The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM], @@ -46,9 +49,10 @@ public: * @param[in] kernel_dims The kernel dimensions (width and height). * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. * @param[in] has_bias In case biases are provided expands the matrix with 1. - * @param[in] is_fully_connected Determines whether this kernel will be called by @ref NEFullyConnectedLayer in order to validate the arguments + * @param[in] is_fully_connected (Optional) Determines whether this function will be called by @ref NEFullyConnectedLayer in order to validate the arguments + * @param[in] is_flatten (Optional) Determines whether this function will be called by @ref NEFlattenLayer in order to validate the arguments */ - void configure(const ITensor *input, ITensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, bool is_fully_connected = false); + void configure(const ITensor *input, ITensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, bool is_fully_connected = false, bool is_flatten = false); /** Static function to check if given info will lead to a valid configuration of @ref NEIm2Col * * @param[in] input The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM], @@ -58,11 +62,19 @@ public: * @param[in] kernel_dims The kernel dimensions (width and height). * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. * @param[in] has_bias In case biases are provided expands the matrix with 1. - * @param[in] is_fully_connected Determines whether this kernel will be called by @ref NEFullyConnectedLayer in order to validate the arguments + * @param[in] is_fully_connected Determines whether this function will be called by @ref NEFullyConnectedLayer in order to validate the arguments + * @param[in] is_flatten Determines whether this function will be called by @ref NEFlattenLayer in order to validate the arguments * * @return a status */ - static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, bool is_fully_connected); + static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, bool is_fully_connected, bool is_flatten); + + // Inherited methods overridden: + void run() override; + +private: + NEIm2ColKernel _kernel; + unsigned int _y_dim; }; } #endif /* __ARM_COMPUTE_NEIM2COL_H__ */ |