| /* |
| * Copyright (c) 2016-2022 Arm Limited. |
| * |
| * SPDX-License-Identifier: MIT |
| * |
| * Permission is hereby granted, free of charge, to any person obtaining a copy |
| * of this software and associated documentation files (the "Software"), to |
| * deal in the Software without restriction, including without limitation the |
| * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| * sell copies of the Software, and to permit persons to whom the Software is |
| * furnished to do so, subject to the following conditions: |
| * |
| * The above copyright notice and this permission notice shall be included in all |
| * copies or substantial portions of the Software. |
| * |
| * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| * SOFTWARE. |
| */ |
| #ifndef ARM_COMPUTE_TENSORINFO_H |
| #define ARM_COMPUTE_TENSORINFO_H |
| |
| #include "arm_compute/core/ITensorInfo.h" |
| |
| #include "ITensorInfo.h" |
| #include "arm_compute/core/Coordinates.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/Strides.h" |
| #include "arm_compute/core/TensorShape.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/Utils.h" |
| |
| #include <cstddef> |
| #include <memory> |
| |
| namespace arm_compute |
| { |
| /** Store the tensor's metadata */ |
| class TensorInfo final : public ITensorInfo |
| { |
| public: |
| /** Default constructor */ |
| TensorInfo(); |
| /** Default destructor */ |
| ~TensorInfo() = default; |
| /** Allow instances of this class to be copy constructed */ |
| TensorInfo(const ITensorInfo &info); |
| /** Allow instances of this class to be copy constructed */ |
| TensorInfo(const TensorInfo &) = default; |
| /** Allow instances of this class to be copied */ |
| TensorInfo &operator=(const TensorInfo &) = default; |
| /** Allow instances of this class to be move constructed */ |
| TensorInfo(TensorInfo &&) = default; |
| /** Allow instances of this class to be moved */ |
| TensorInfo &operator=(TensorInfo &&) = default; |
| |
| /** Construct a tensor info with a format. |
| * |
| * Can be used for automatic derivation of the shape by the function. |
| * |
| * @param[in] format Format of the tensor. |
| */ |
| TensorInfo(Format format); |
| |
| /** 2D tensor constructor |
| * |
| * @param[in] width Width of the 2D tensor |
| * @param[in] height Height of the 2D tensor |
| * @param[in] format Single plane format of the tensor. |
| */ |
| TensorInfo(unsigned int width, unsigned int height, Format format); |
| /** Constructor |
| * |
| * @param[in] tensor_shape It specifies the size for each dimension of the tensor in number of elements. |
| * @param[in] format Single plane format of the tensor. |
| */ |
| TensorInfo(const TensorShape &tensor_shape, Format format); |
| |
| /** Construct a tensor info with a data type and number of channels. |
| * |
| * Can be used for automatic derivation of the shape by the function. |
| * |
| * @param[in] num_channels It indicates the number of channels for each tensor element |
| * @param[in] data_type Data type to use for each tensor element |
| */ |
| TensorInfo(size_t num_channels, DataType data_type); |
| |
| /** Constructor |
| * |
| * @param[in] tensor_shape It specifies the size for each dimension of the tensor in number of elements. |
| * @param[in] num_channels It indicates the number of channels for each tensor element |
| * @param[in] data_type Data type to use for each tensor element |
| */ |
| TensorInfo(const TensorShape &tensor_shape, size_t num_channels, DataType data_type); |
| |
| /** Constructor |
| * |
| * @param[in] tensor_shape It specifies the size for each dimension of the tensor in number of elements. |
| * @param[in] num_channels It indicates the number of channels for each tensor element |
| * @param[in] data_type Data type to use for each tensor element |
| * @param[in] data_layout The data layout setting for the tensor data. |
| */ |
| TensorInfo(const TensorShape &tensor_shape, size_t num_channels, DataType data_type, DataLayout data_layout); |
| |
| /** Constructor |
| * |
| * @param[in] tensor_shape It specifies the size for each dimension of the tensor in number of elements. |
| * @param[in] num_channels It indicates the number of channels for each tensor element |
| * @param[in] data_type Data type to use for each tensor element |
| * @param[in] quantization_info The quantization settings for the tensor data. |
| */ |
| TensorInfo(const TensorShape &tensor_shape, size_t num_channels, DataType data_type, QuantizationInfo quantization_info); |
| |
| /** Initialize the tensor info with just a format. |
| * |
| * Can be used for automatic derivation of the shape by the function. |
| * |
| * @param[in] format Single plane format of the tensor. |
| */ |
| void init(Format format); |
| |
| /** Initialize the metadata structure with the given parameters |
| * |
| * @param[in] tensor_shape Size for each dimension of the tensor in number of elements. |
| * @param[in] format Single plane format of the tensor. |
| */ |
| void init(const TensorShape &tensor_shape, Format format); |
| /** Initialize the metadata structure with the given parameters |
| * |
| * @param[in] tensor_shape Size for each dimension of the tensor in number of elements. |
| * @param[in] format Single plane format of the tensor. |
| * @param[in] strides_in_bytes Stride in bytes for accessing each dimension of the tensor. |
| * @param[in] offset_first_element_in_bytes Offset in bytes from the beginning of memory allocation to access the first element. |
| * @param[in] total_size_in_bytes Size in bytes of the memory allocation (including the offset to the first element). |
| */ |
| void init(const TensorShape &tensor_shape, Format format, const Strides &strides_in_bytes, size_t offset_first_element_in_bytes, size_t total_size_in_bytes); |
| |
| /** Initialize the tensor info with just a format. |
| * |
| * Can be used for automatic derivation of the shape by the function. |
| * |
| * @param[in] num_channels Desired number of channels for each tensor element. |
| * @param[in] data_type Data type to use for each tensor element. |
| */ |
| void init(size_t num_channels, DataType data_type); |
| |
| /** Initialize the metadata structure with the given parameters |
| * |
| * @param[in] tensor_shape Size for each dimension of the tensor in number of elements. |
| * @param[in] num_channels Desired number of channels for each tensor element. |
| * @param[in] data_type Data type to use for each tensor element. |
| */ |
| void init(const TensorShape &tensor_shape, size_t num_channels, DataType data_type); |
| |
| /** Initialize the metadata structure with the given parameters |
| * |
| * @param[in] tensor_shape Size for each dimension of the tensor in number of elements. |
| * @param[in] num_channels Desired number of channels for each tensor element. |
| * @param[in] data_type Data type to use for each tensor element. |
| * @param[in] strides_in_bytes Stride in bytes for accessing each dimension of the tensor. |
| * @param[in] offset_first_element_in_bytes Offset in bytes from the beginning of memory allocation to access the first element. |
| * @param[in] total_size_in_bytes Size in bytes of the memory allocation (including the offset to the first element). |
| */ |
| void init(const TensorShape &tensor_shape, size_t num_channels, DataType data_type, const Strides &strides_in_bytes, size_t offset_first_element_in_bytes, |
| size_t total_size_in_bytes); |
| /** Initialize the metadata structure for the given tensor shape and single-plane format, (Padding is automatically calculated) |
| * |
| * @note The padding used by this method is really conservative so that the tensor can be used for most functions. |
| * |
| * @param[in] tensor_shape It specifies the size for each dimension of the tensor in number of elements |
| * @param[in] format Single plane format of the image. |
| * |
| * @return Total allocation size including padding in bytes. |
| */ |
| size_t init_auto_padding(const TensorShape &tensor_shape, Format format); |
| /** Initialize the metadata structure for the given tensor shape, number of channels and |
| * data type. (Padding is automatically calculated) |
| * |
| * @note The padding used by this method is really conservative so that the tensor can be used for most functions. |
| * |
| * @param[in] tensor_shape It specifies the size for each dimension of the tensor in number of elements |
| * @param[in] num_channels It indicates the number of channels for each tensor element |
| * @param[in] data_type Data type to use for each tensor element |
| * |
| * @return Total allocation size including padding in bytes. |
| */ |
| size_t init_auto_padding(const TensorShape &tensor_shape, size_t num_channels, DataType data_type); |
| |
| // Inherited methods overridden: |
| std::unique_ptr<ITensorInfo> clone() const override; |
| ITensorInfo &set_data_type(DataType data_type) override; |
| ITensorInfo &set_num_channels(int num_channels) override; |
| ITensorInfo &set_format(Format format) override; |
| ITensorInfo &set_tensor_shape(const TensorShape &shape) override; |
| ITensorInfo &set_tensor_dims_state(const TensorDimsState &state) override; |
| ITensorInfo &set_quantization_info(const QuantizationInfo &quantization_info) override; |
| ITensorInfo &set_data_layout(const DataLayout &data_layout) override; |
| ITensorInfo &reset_padding() override; |
| bool auto_padding() override; |
| bool extend_padding(const PaddingSize &padding) override; |
| size_t dimension(size_t index) const override |
| { |
| return _tensor_shape[index]; |
| } |
| size_t dimension(DataLayoutDimension dimension) const override |
| { |
| return get_data_layout_dimension_index(_data_layout, dimension); |
| } |
| const Strides &strides_in_bytes() const override |
| { |
| return _strides_in_bytes; |
| } |
| size_t offset_first_element_in_bytes() const override |
| { |
| return _offset_first_element_in_bytes; |
| } |
| int32_t offset_element_in_bytes(const Coordinates &pos) const override; |
| size_t element_size() const override |
| { |
| return data_size_from_type(_data_type) * _num_channels; |
| } |
| size_t num_dimensions() const override |
| { |
| return _tensor_shape.num_dimensions(); |
| } |
| size_t num_channels() const override |
| { |
| return _num_channels; |
| } |
| const TensorShape &tensor_shape() const override |
| { |
| return _tensor_shape; |
| } |
| const TensorDimsState &tensor_dims_state() const override |
| { |
| return _dims_state; |
| } |
| DataType data_type() const override |
| { |
| return _data_type; |
| } |
| Format format() const override |
| { |
| return _format; |
| } |
| size_t total_size() const override |
| { |
| return _total_size; |
| } |
| PaddingSize padding() const override |
| { |
| return _padding; |
| } |
| bool has_padding() const override |
| { |
| return !_padding.empty(); |
| } |
| bool is_resizable() const override |
| { |
| return _is_resizable; |
| } |
| bool is_dynamic() const override |
| { |
| return std::find(std::cbegin(_dims_state), std::cend(_dims_state), get_dynamic_state_value()) != std::cend(_dims_state); |
| } |
| bool are_values_constant() const override |
| { |
| return _are_values_constant; |
| } |
| ITensorInfo &set_is_resizable(bool is_resizable) override |
| { |
| _is_resizable = is_resizable; |
| return *this; |
| } |
| ValidRegion valid_region() const override |
| { |
| return _valid_region; |
| } |
| void set_valid_region(const ValidRegion &valid_region) override |
| { |
| _valid_region = valid_region; |
| } |
| QuantizationInfo quantization_info() const override |
| { |
| return _quantization_info; |
| } |
| DataLayout data_layout() const override |
| { |
| return _data_layout; |
| } |
| ITensorInfo &set_are_values_constant(bool are_values_constant) override |
| { |
| _are_values_constant = are_values_constant; |
| return *this; |
| } |
| inline friend bool operator==(const TensorInfo &lhs, const TensorInfo &rhs); |
| |
| private: |
| /** Calculates strides, offset and total size resulting from the specified padding around the XY plane. |
| * |
| * @param[in] padding Padding around the XY plane in elements. |
| */ |
| std::tuple<Strides, size_t, size_t> calculate_padding_requirements(const PaddingSize &padding); |
| |
| size_t _total_size; |
| size_t _offset_first_element_in_bytes; |
| Strides _strides_in_bytes; |
| size_t _num_channels; |
| TensorShape _tensor_shape; |
| TensorDimsState _dims_state; |
| DataType _data_type; |
| Format _format; |
| bool _is_resizable; |
| ValidRegion _valid_region; |
| PaddingSize _padding; |
| QuantizationInfo _quantization_info; |
| DataLayout _data_layout; |
| bool _are_values_constant; |
| }; |
| |
| /** Check whether two tensor info are equal. |
| * |
| * @param[in] lhs LHS tensor info. |
| * @param[in] rhs RHS tensor info. |
| * |
| * @return True if the given tensor infos are the same. |
| */ |
| inline bool operator==(const TensorInfo &lhs, const TensorInfo &rhs) |
| { |
| return (lhs._total_size == rhs._total_size) && (lhs._offset_first_element_in_bytes == rhs._offset_first_element_in_bytes) && (lhs._strides_in_bytes == rhs._strides_in_bytes) |
| && (lhs._num_channels == rhs._num_channels) && (lhs._tensor_shape == rhs._tensor_shape) && (lhs._dims_state == rhs._dims_state) && (lhs._data_type == rhs._data_type) && (lhs._format == rhs._format) |
| && (lhs._is_resizable == rhs._is_resizable) && (lhs._valid_region == rhs._valid_region) && (lhs._padding == rhs._padding) && (lhs._quantization_info == rhs._quantization_info) |
| && (lhs._data_layout == rhs._data_layout) && (lhs._are_values_constant == rhs._are_values_constant); |
| } |
| } // namespace arm_compute |
| #endif /*ARM_COMPUTE_TENSORINFO_H */ |