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diff --git a/tests/validation/Reference.h b/tests/validation/Reference.h new file mode 100644 index 0000000000..4e5b462f9e --- /dev/null +++ b/tests/validation/Reference.h @@ -0,0 +1,303 @@ +/* + * Copyright (c) 2017 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_TEST_REFERENCE_REFERENCE_H__ +#define __ARM_COMPUTE_TEST_REFERENCE_REFERENCE_H__ + +#include "RawTensor.h" +#include "Types.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +/** Interface for reference implementations. */ +class Reference +{ +public: + /** Compute reference integral image. + * + * @param[in] shape Shape of the input and output tensors. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_integral_image(const TensorShape &shape); + /** Compute reference absolute difference. + * + * @param[in] shape Shape of the input and output tensors. + * @param[in] dt_in0 Data type of first input tensor. + * @param[in] dt_in1 Data type of second input tensor. + * @param[in] dt_out Data type of the output tensor. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_absolute_difference(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out); + /** Compute reference accumulate. + * + * @param[in] shape Shape of the input and output tensors. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_accumulate(const TensorShape &shape); + /** Compute reference accumulate. + * + * @param[in] shape Shape of the input and output tensors. + * @param[in] shift A uint32_t value within the range of [0, 15] + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_accumulate_squared(const TensorShape &shape, uint32_t shift); + /** Compute reference accumulate. + * + * @param[in] shape Shape of the input and output tensors. + * @param[in] alpha A float value within the range of [0, 1] + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_accumulate_weighted(const TensorShape &shape, float alpha); + /** Compute reference arithmetic addition. + * + * @param[in] shape Shape of the input and output tensors. + * @param[in] dt_in0 Data type of first input tensor. + * @param[in] dt_in1 Data type of second input tensor. + * @param[in] dt_out Data type of the output tensor. + * @param[in] convert_policy Overflow policy of the operation. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_arithmetic_addition(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, ConvertPolicy convert_policy); + /** Compute reference arithmetic subtraction. + * + * @param[in] shape Shape of the input and output tensors. + * @param[in] dt_in0 Data type of first input tensor. + * @param[in] dt_in1 Data type of second input tensor. + * @param[in] dt_out Data type of the output tensor. + * @param[in] convert_policy Overflow policy of the operation. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_arithmetic_subtraction(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, ConvertPolicy convert_policy); + /** Compute reference bitwise and. + * + * @param[in] shape Shape of the input and output tensors. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_bitwise_and(const TensorShape &shape); + /** Compute reference bitwise or. + * + * @param[in] shape Shape of the input and output tensors. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_bitwise_or(const TensorShape &shape); + /** Compute reference bitwise xor. + * + * @param[in] shape Shape of the input and output tensors. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_bitwise_xor(const TensorShape &shape); + /** Compute reference bitwise not. + * + * @param[in] shape Shape of the input and output tensors. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_bitwise_not(const TensorShape &shape); + /** Compute reference 3-by-3 box filter. + * + * @param[in] shape Shape of the input and output tensors. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_box3x3(const TensorShape &shape); + /** Compute reference depth convert. + * + * @param[in] shape Shape of the input and output tensors. + * @param[in] dt_in Data type of input tensor. + * @param[in] dt_out Data type of the output tensor. + * @param[in] policy Overflow policy of the operation. + * @param[in] shift Value for down/up conversions. Must be 0 <= shift < 8. + * @param[in] fixed_point_position Fixed point position. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_depth_convert(const TensorShape &shape, DataType dt_in, DataType dt_out, ConvertPolicy policy, uint32_t shift, uint32_t fixed_point_position); + /** Compute matrix multiply function. + * + * @param[in] src_shape1 First input tensor shape + * @param[in] src_shape2 Second input tensor shape + * @param[in] src_shape3 Third input tensor shape + * @param[out] dst_shape Output tensor. + * @param[in] alpha Weight of the matrix product + * @param[in] beta Weight of the third matrix + * @param[in] dt Tensor's data type + * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers + * + * @return Computed output tensor. + */ + static RawTensor compute_reference_gemm(const TensorShape &src_shape1, const TensorShape &src_shape2, const TensorShape &src_shape3, + const TensorShape &dst_shape, float alpha, float beta, DataType dt, int fixed_point_position = 0); + /** Compute reference pixel-wise multiplication + * + * @param[in] shape Shape of the input and output tensors. + * @param[in] dt_in0 Data type of first input tensor. + * @param[in] dt_in1 Data type of second input tensor. + * @param[in] dt_out Data type of the output tensor. + * @param[in] scale Non-negative scale. + * @param[in] convert_policy Overflow policy of the operation. + * @param[in] rounding_policy Rounding policy of the operation. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_pixel_wise_multiplication(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, float scale, ConvertPolicy convert_policy, + RoundingPolicy rounding_policy); + /** Compute reference pixel-wise multiplication. + * + * @param[in] shape Shape of the input and output tensors. + * @param[in] dt_in0 Data type of first input tensor. + * @param[in] dt_in1 Data type of second input tensor. + * @param[in] dt_out Data type of the output tensor. + * @param[in] scale Scale to apply after multiplication. Must be positive. + * @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number. + * @param[in] convert_policy Overflow policy of the operation. + * @param[in] rounding_policy Rounding policy of the operation. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_fixed_point_pixel_wise_multiplication(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, float scale, int fixed_point_position, + ConvertPolicy convert_policy, RoundingPolicy rounding_policy); + /** Compute reference threshold. + * + * @param[in] shape Shape of the input and output tensors. + * @param[in] threshold Threshold. When the threshold type is RANGE, this is used as the lower threshold. + * @param[in] false_value value to set when the condition is not respected. + * @param[in] true_value value to set when the condition is respected. + * @param[in] type Thresholding type. Either RANGE or BINARY. + * @param[in] upper Upper threshold. Only used when the thresholding type is RANGE. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_threshold(const TensorShape &shape, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper); + /** Compute reference activation layer. + * + * @param[in] shape Shape of the input and output tensors. + * @param[in] dt Data type of the tensors. + * @param[in] act_info Activation layer information. + * @param[in] fixed_point_position (Optional)Number of bits for the fractional part of fixed point numbers. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_activation_layer(const TensorShape &shape, DataType dt, ActivationLayerInfo act_info, int fixed_point_position = 0); + /** Compute reference batch normalization layer. + * + * @param[in] shape0 Shape of the input and output tensors. + * @param[in] shape1 Shape of the vector tensors. + * @param[in] dt Data type of all input and output tensors. + * @param[in] epsilon Small value to avoid division with zero. + * @param[in] fixed_point_position Fixed point position. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_batch_normalization_layer(const TensorShape &shape0, const TensorShape &shape1, DataType dt, float epsilon, int fixed_point_position = 0); + /** Compute reference pixel-wise multiplication + * + * @param[in] input_shape Shape for the input tensor + * @param[in] weights_shape Shape for the weights tensor + * @param[in] bias_shape Shape for the bias tensor + * @param[in] output_shape Shape for the output tensor + * @param[in] dt Data type to use + * @param[in] conv_info Pads and strides information for the convolution layer + * @param[in] fixed_point_position Number of bits for the fractional part of the fixed point numbers + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_convolution_layer(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, DataType dt, + const PadStrideInfo &conv_info, int fixed_point_position); + /** Compute reference for fully connected layer function + * + * @param[in] input_shape Shape for the input tensor + * @param[in] weights_shape Shape for the weights tensor + * @param[in] bias_shape Shape for the bias tensor + * @param[in] output_shape Shape for the output tensor + * @param[in] dt Data type to use + * @param[in] transpose_weights Transpose the weights if true + * @param[in] fixed_point_position Number of bits for the fractional part of the fixed point numbers + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_fully_connected_layer(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, DataType dt, + bool transpose_weights, int fixed_point_position); + /** Compute reference normalization layer. + * + * @param[in] shape Shape of the input and output tensors. + * @param[in] dt Data type of input and output tensors. + * @param[in] norm_info Normalization Layer information. + * @param[in] fixed_point_position (Optional) Fixed point position that expresses the number of bits for the fractional part of the number when the tensor's data type is QS8 or QS16 (default = 0). + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_normalization_layer(const TensorShape &shape, DataType dt, NormalizationLayerInfo norm_info, int fixed_point_position = 0); + /** Compute reference pooling layer. + * + * @param[in] shape_in Shape of the input tensor. + * @param[in] shape_out Shape of the output tensor. + * @param[in] dt Data type of input and output tensors. + * @param[in] pool_info Pooling Layer information. + * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers. + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_pooling_layer(const TensorShape &shape_in, const TensorShape &shape_out, DataType dt, PoolingLayerInfo pool_info, int fixed_point_position = 0); + /** Compute reference softmax layer. + * + * @param[in] shape Shape of the input and output tensors. + * @param[in] dt Data type of input and output tensors. + * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_softmax_layer(const TensorShape &shape, DataType dt, int fixed_point_position = 0); + /** Compute reference fixed point operation. + * + * @param[in] shape Shape of the input and output tensors. + * @param[in] dt_in Data type of the input tensor. + * @param[in] dt_out Data type of the output tensor. + * @param[in] op Fixed point operation to perform. + * @param[in] fixed_point_position Number of bits for the fractional part of the fixed point numbers + * + * @return Computed raw tensor. + */ + static RawTensor compute_reference_fixed_point_operation(const TensorShape &shape, DataType dt_in, DataType dt_out, FixedPointOp op, int fixed_point_position); + +protected: + Reference() = default; + ~Reference() = default; +}; +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif |