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/*
* 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
|
