From cbf39c63a6eb89a2c80b2338afc374081803d79d Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Mon, 10 Sep 2018 15:07:45 +0100 Subject: COMPMID-1566: Add broadcast to CLArithmeticSubtraction Change-Id: I05d21f9a92013ecfd1128d12cf1561cfd6e5c5e9 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/147983 Tested-by: bsgcomp Reviewed-by: Anthony Barbier --- .../core/CL/kernels/CLArithmeticAdditionKernel.h | 2 +- .../CL/kernels/CLArithmeticSubtractionKernel.h | 15 +- .../NEON/kernels/NEArithmeticSubtractionKernel.h | 1 + .../runtime/CL/functions/CLArithmeticSubtraction.h | 6 +- .../NEON/functions/NEArithmeticSubtraction.h | 12 +- src/core/CL/CLKernelLibrary.cpp | 1 + src/core/CL/cl_kernels/arithmetic_op_quantized.cl | 74 +++++++- src/core/CL/kernels/CLArithmeticAdditionKernel.cpp | 2 +- .../CL/kernels/CLArithmeticSubtractionKernel.cpp | 176 ++++++++++++------ .../NEON/kernels/NEArithmeticAdditionKernel.cpp | 2 +- .../NEON/kernels/NEArithmeticSubtractionKernel.cpp | 171 +++++++++-------- .../CL/functions/CLArithmeticSubtraction.cpp | 15 +- .../NEON/functions/NEArithmeticAddition.cpp | 5 +- .../NEON/functions/NEArithmeticSubtraction.cpp | 21 ++- tests/validation/CL/ArithmeticAddition.cpp | 2 +- tests/validation/CL/ArithmeticSubtraction.cpp | 204 ++++++++++----------- .../validation/GLES_COMPUTE/ArithmeticAddition.cpp | 4 +- tests/validation/NEON/ArithmeticAddition.cpp | 2 +- tests/validation/NEON/ArithmeticSubtraction.cpp | 172 ++++++----------- .../fixtures/ArithmeticAdditionFixture.h | 157 ---------------- .../fixtures/ArithmeticOperationsFixture.h | 201 ++++++++++++++++++++ .../fixtures/ArithmeticSubtractionFixture.h | 114 ------------ tests/validation/fixtures/LSTMLayerFixture.h | 21 +-- tests/validation/fixtures/RNNLayerFixture.h | 4 +- tests/validation/reference/ArithmeticAddition.cpp | 147 --------------- tests/validation/reference/ArithmeticAddition.h | 48 ----- .../validation/reference/ArithmeticOperations.cpp | 149 +++++++++++++++ tests/validation/reference/ArithmeticOperations.h | 54 ++++++ .../validation/reference/ArithmeticSubtraction.cpp | 63 ------- tests/validation/reference/ArithmeticSubtraction.h | 44 ----- tests/validation/reference/LaplacianPyramid.cpp | 7 +- .../validation/reference/LaplacianReconstruct.cpp | 6 +- 32 files changed, 940 insertions(+), 962 deletions(-) delete mode 100644 tests/validation/fixtures/ArithmeticAdditionFixture.h create mode 100644 tests/validation/fixtures/ArithmeticOperationsFixture.h delete mode 100644 tests/validation/fixtures/ArithmeticSubtractionFixture.h delete mode 100644 tests/validation/reference/ArithmeticAddition.cpp delete mode 100644 tests/validation/reference/ArithmeticAddition.h create mode 100644 tests/validation/reference/ArithmeticOperations.cpp create mode 100644 tests/validation/reference/ArithmeticOperations.h delete mode 100644 tests/validation/reference/ArithmeticSubtraction.cpp delete mode 100644 tests/validation/reference/ArithmeticSubtraction.h diff --git a/arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h b/arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h index f4275f4153..48e72f3c13 100644 --- a/arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h +++ b/arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h @@ -51,7 +51,7 @@ public: CLArithmeticAdditionKernel &operator=(CLArithmeticAdditionKernel &&) = default; /** Default destructor */ ~CLArithmeticAdditionKernel() = default; - /** Initialise the kernel's inputs, output and convertion policy. + /** Initialise the kernel's inputs, output and conversion policy. * * @param[in] input1 First tensor input. Data types supported: U8/QASYMM8/S16/F16/F32. * @param[in] input2 Second tensor input. Data types supported: U8, QASYMM8 (only if @p input1 is QASYMM8), S16/F16/F32. diff --git a/arm_compute/core/CL/kernels/CLArithmeticSubtractionKernel.h b/arm_compute/core/CL/kernels/CLArithmeticSubtractionKernel.h index 35b918fe4b..9875ac7a31 100644 --- a/arm_compute/core/CL/kernels/CLArithmeticSubtractionKernel.h +++ b/arm_compute/core/CL/kernels/CLArithmeticSubtractionKernel.h @@ -53,19 +53,19 @@ public: /** Default destructor */ ~CLArithmeticSubtractionKernel() = default; - /** Initialise the kernel's inputs, output and convertion policy. + /** Initialise the kernel's inputs, output and conversion policy. * - * @param[in] input1 First tensor input. Data types supported: U8/S16/F16/F32. - * @param[in] input2 Second tensor input. Data types supported: U8/S16/F16/F32. - * @param[out] output Output tensor. Data types supported: U8 (Only if both inputs are U8), S16/F16/F32. + * @param[in] input1 First tensor input. Data types supported: U8/QASYMM8/S16/F16/F32. + * @param[in] input2 Second tensor input. Data types supported: U8/QASYMM8/S16/F16/F32. + * @param[out] output Output tensor. Data types supported: U8 (Only if both inputs are U8), QASYMM8/S16/F16/F32. * @param[in] policy Policy to use to handle overflow. */ void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ConvertPolicy policy); /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticSubtractionKernel * - * @param[in] input1 First tensor input info. Data types supported: U8/S16/F16/F32. - * @param[in] input2 Second tensor input info. Data types supported: U8/S16/F16/F32. - * @param[in] output Output tensor info. Data types supported: U8 (Only if both inputs are U8), S16/F16/F32. + * @param[in] input1 First tensor input info. Data types supported: U8/QASYMM8/S16/F16/F32. + * @param[in] input2 Second tensor input info. Data types supported: U8/QASYMM8/S16/F16/F32. + * @param[in] output Output tensor info. Data types supported: U8 (Only if both inputs are U8), QASYMM8/S16/F16/F32. * @param[in] policy Policy to use to handle overflow. * * @return a status @@ -74,6 +74,7 @@ public: // Inherited methods overridden: void run(const Window &window, cl::CommandQueue &queue) override; + BorderSize border_size() const override; private: const ICLTensor *_input1; /**< Source tensor 1 */ diff --git a/arm_compute/core/NEON/kernels/NEArithmeticSubtractionKernel.h b/arm_compute/core/NEON/kernels/NEArithmeticSubtractionKernel.h index 3e93922b65..64ad6e072d 100644 --- a/arm_compute/core/NEON/kernels/NEArithmeticSubtractionKernel.h +++ b/arm_compute/core/NEON/kernels/NEArithmeticSubtractionKernel.h @@ -83,6 +83,7 @@ public: // Inherited methods overridden: void run(const Window &window, const ThreadInfo &info) override; + BorderSize border_size() const override; private: /** Common signature for all the specialised sub functions diff --git a/arm_compute/runtime/CL/functions/CLArithmeticSubtraction.h b/arm_compute/runtime/CL/functions/CLArithmeticSubtraction.h index b9690806d7..2940044ed9 100644 --- a/arm_compute/runtime/CL/functions/CLArithmeticSubtraction.h +++ b/arm_compute/runtime/CL/functions/CLArithmeticSubtraction.h @@ -36,6 +36,10 @@ class ICLTensor; * * @note The tensor data type for the inputs must be U8/S16/F16/F32. * @note The function performs an arithmetic subtraction between two tensors. + * + * This function calls the following kernels: + * -# @ref CLFillBorderKernel (In case of broadcasting, in the input being broadcasted) + * -# @ref CLArithmeticSubtractionKernel */ class CLArithmeticSubtraction : public ICLSimpleFunction { @@ -47,7 +51,7 @@ public: * @param[out] output Output tensor. Data types supported: U8 (Only if both inputs are U8), S16/F16/F32. * @param[in] policy Policy to use to handle overflow. */ - void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ConvertPolicy policy); + void configure(ICLTensor *input1, ICLTensor *input2, ICLTensor *output, ConvertPolicy policy); /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticSubtraction * * @param[in] input1 First tensor input info. Data types supported: U8/S16/F16/F32. diff --git a/arm_compute/runtime/NEON/functions/NEArithmeticSubtraction.h b/arm_compute/runtime/NEON/functions/NEArithmeticSubtraction.h index 9b460c1031..541756cd2c 100644 --- a/arm_compute/runtime/NEON/functions/NEArithmeticSubtraction.h +++ b/arm_compute/runtime/NEON/functions/NEArithmeticSubtraction.h @@ -31,7 +31,15 @@ namespace arm_compute { class ITensor; -/** Basic function to run @ref NEArithmeticSubtractionKernel */ +/** Basic function to run @ref NEArithmeticSubtractionKernel + * + * @note The tensor data type for the inputs must be U8/S16/F16/F32. + * @note The function performs an arithmetic subtraction between two tensors. + * + * This function calls the following kernels: + * -# @ref NEFillBorderKernel (In case of broadcasting, in the input being broadcasted) + * -# @ref NEArithmeticSubtractionKernel + */ class NEArithmeticSubtraction : public INESimpleFunction { public: @@ -42,7 +50,7 @@ public: * @param[out] output Output tensor. Data types supported: U8/S16/F16/F32 * @param[in] policy Policy to use to handle overflow. */ - void configure(const ITensor *input1, const ITensor *input2, ITensor *output, ConvertPolicy policy); + void configure(ITensor *input1, ITensor *input2, ITensor *output, ConvertPolicy policy); /** Static function to check if given info will lead to a valid configuration of @ref NEArithmeticSubtraction * * @param[in] input1 First tensor input. Data types supported: U8/S16/F16/F32 diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index dfc41da09f..8a309ec757 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -152,6 +152,7 @@ const std::map CLKernelLibrary::_kernel_program_map = { "arithmetic_add_quantized", "arithmetic_op_quantized.cl" }, { "arithmetic_add", "arithmetic_op.cl" }, { "arithmetic_sub", "arithmetic_op.cl" }, + { "arithmetic_sub_quantized", "arithmetic_op_quantized.cl" }, { "arithmetic_div", "arithmetic_op.cl" }, { "batch_to_space_nchw", "batch_to_space.cl" }, { "batch_to_space_static_nchw", "batch_to_space.cl" }, diff --git a/src/core/CL/cl_kernels/arithmetic_op_quantized.cl b/src/core/CL/cl_kernels/arithmetic_op_quantized.cl index 082317ba11..5f31c56250 100644 --- a/src/core/CL/cl_kernels/arithmetic_op_quantized.cl +++ b/src/core/CL/cl_kernels/arithmetic_op_quantized.cl @@ -31,12 +31,16 @@ #define SUB(x, y) (x) - (y) #endif /* SATURATE */ -#if defined(OFFSET_IN1) - +#if defined(OFFSET_IN1) && defined(OFFSET_IN2) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_IN2) && defined(SCALE_OUT) /** This function adds two tensors. * - * @attention The quantization offset must be passed at compile time using -DOFFSET_IN1, i.e. -DOFFSET_IN1=10 - * @attention To perform saturating operation -DSATURATE has to be passed to the compiler otherwise wrapping policy will be used. + * @note The quantization offset of the first operand must be passed at compile time using -DOFFSET_IN1, i.e. -DOFFSET_IN1=10 + * @note The quantization offset of the second operand must be passed at compile time using -DOFFSET_IN2, i.e. -DOFFSET_IN2=10 + * @note The quantization offset of the output must be passed at compile time using -DOFFSET_OUT, i.e. -DOFFSET_OUT=10 + * @note The quantization scale of the first operand must be passed at compile time using -DSCALE_IN1, i.e. -DSCALE_IN1=10 + * @note The quantization scale of the second operand must be passed at compile time using -DSCALE_IN2, i.e. -DSCALE_IN2=10 + * @note The quantization scale of the output must be passed at compile time using -DSCALE_OUT, i.e. -DSCALE_OUT=10 + * @note To perform saturating operation -DSATURATE has to be passed to the compiler otherwise wrapping policy will be used. * * @param[in] in1_ptr Pointer to the source tensor. Supported data types: QASYMM8 * @param[in] in1_stride_x Stride of the source tensor in X dimension (in bytes) @@ -87,4 +91,64 @@ __kernel void arithmetic_add_quantized( // Store result vstore16(res, 0, (__global uchar *)out.ptr); } -#endif /* defined(OFFSET) */ + +/** This function subtracts two tensors. + * + * @note The quantization offset of the first operand must be passed at compile time using -DOFFSET_IN1, i.e. -DOFFSET_IN1=10 + * @note The quantization offset of the second operand must be passed at compile time using -DOFFSET_IN2, i.e. -DOFFSET_IN2=10 + * @note The quantization offset of the output must be passed at compile time using -DOFFSET_OUT, i.e. -DOFFSET_OUT=10 + * @note The quantization scale of the first operand must be passed at compile time using -DSCALE_IN1, i.e. -DSCALE_IN1=10 + * @note The quantization scale of the second operand must be passed at compile time using -DSCALE_IN2, i.e. -DSCALE_IN2=10 + * @note The quantization scale of the output must be passed at compile time using -DSCALE_OUT, i.e. -DSCALE_OUT=10 + * @note To perform saturating operation -DSATURATE has to be passed to the compiler otherwise wrapping policy will be used. + * + * @param[in] in1_ptr Pointer to the source tensor. Supported data types: QASYMM8 + * @param[in] in1_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] in1_step_x in1_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] in1_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] in1_step_y in1_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] in1_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] in1_step_z in1_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] in1_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] in2_ptr Pointer to the source tensor. Supported data types: same as @p in1_ptr + * @param[in] in2_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] in2_step_x in2_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] in2_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] in2_step_y in2_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] in2_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] in2_step_z in2_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] in2_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[out] out_ptr Pointer to the destination tensor. Supported data types: same as @p in1_ptr + * @param[in] out_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] out_step_x out_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] out_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] out_step_y out_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] out_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] out_step_z out_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] out_offset_first_element_in_bytes The offset of the first element in the destination tensor + */ +__kernel void arithmetic_sub_quantized( + TENSOR3D_DECLARATION(in1), + TENSOR3D_DECLARATION(in2), + TENSOR3D_DECLARATION(out)) +{ + // Get pixels pointer + Tensor3D in1 = CONVERT_TO_TENSOR3D_STRUCT(in1); + Tensor3D in2 = CONVERT_TO_TENSOR3D_STRUCT(in2); + Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(out); + + int16 in_a = CONVERT(vload16(0, (__global uchar *)in1.ptr), int16); + int16 in_b = CONVERT(vload16(0, (__global uchar *)in2.ptr), int16); + + in_a = SUB(in_a, (int16)((int)OFFSET_IN1)); + in_b = SUB(in_b, (int16)((int)OFFSET_IN2)); + + const float16 in1f32 = convert_float16(in_a) * (float16)((float)SCALE_IN1); + const float16 in2f32 = convert_float16(in_b) * (float16)((float)SCALE_IN2); + const float16 qresf32 = (in1f32 - in2f32) / ((float16)(float)SCALE_OUT) + ((float16)((float16)OFFSET_OUT)); + const uchar16 res = convert_uchar16_sat(convert_int16_rte(qresf32)); + + // Store result + vstore16(res, 0, (__global uchar *)out.ptr); +} +#endif /* defined(OFFSET_IN1) && defined(OFFSET_IN2) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_IN2) && defined(SCALE_OUT) */ \ No newline at end of file diff --git a/src/core/CL/kernels/CLArithmeticAdditionKernel.cpp b/src/core/CL/kernels/CLArithmeticAdditionKernel.cpp index 2372d458cf..de14f00856 100644 --- a/src/core/CL/kernels/CLArithmeticAdditionKernel.cpp +++ b/src/core/CL/kernels/CLArithmeticAdditionKernel.cpp @@ -159,7 +159,7 @@ void CLArithmeticAdditionKernel::configure(const ICLTensor *input1, const ICLTen Status CLArithmeticAdditionKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy) { - ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output); ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*input1, *input2, *output, policy)); ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(*input1->clone(), *input2->clone(), *output->clone()).first); diff --git a/src/core/CL/kernels/CLArithmeticSubtractionKernel.cpp b/src/core/CL/kernels/CLArithmeticSubtractionKernel.cpp index 299ac553e9..95d201104d 100644 --- a/src/core/CL/kernels/CLArithmeticSubtractionKernel.cpp +++ b/src/core/CL/kernels/CLArithmeticSubtractionKernel.cpp @@ -36,45 +36,82 @@ #include #include -using namespace arm_compute; - +namespace arm_compute +{ namespace { -Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy) +constexpr unsigned int num_elems_processed_per_iteration = 16; + +Status validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output, ConvertPolicy policy) { ARM_COMPUTE_UNUSED(policy); - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input1); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input2); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, input2); + ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&input1); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input1, 1, DataType::U8, DataType::QASYMM8, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&input2); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input2, 1, DataType::U8, DataType::QASYMM8, DataType::S16, DataType::F16, DataType::F32); + const bool is_qasymm = is_data_type_quantized_asymmetric(input1.data_type()) || is_data_type_quantized_asymmetric(input2.data_type()); + if(is_qasymm) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input1, &input2); + } + + const TensorShape out_shape = TensorShape::broadcast_shape(input1.tensor_shape(), input2.tensor_shape()); + + ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible"); // Validate in case of configured output - if((output != nullptr) && (output->total_size() != 0)) + if(output.total_size() > 0) { - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(output); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::U8 && (input1->data_type() != DataType::U8 || input2->data_type() != DataType::U8), + ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&output); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&output, 1, DataType::U8, DataType::QASYMM8, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MSG((output.data_type() == DataType::U8) && ((input1.data_type() != DataType::U8) || (input2.data_type() != DataType::U8)), "Output can only be U8 if both inputs are U8"); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, output); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output.tensor_shape(), 0), + "Wrong shape for output"); + if(is_qasymm) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input1, &output); + } } return Status{}; } -std::pair validate_and_configure_window(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output) +std::pair validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output) { - constexpr unsigned int num_elems_processed_per_iteration = 16; + const std::pair broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(input1, input2); + const TensorShape &out_shape = broadcast_pair.first; + const ValidRegion &valid_region = broadcast_pair.second; - Window win = calculate_max_window(*input1, Steps(num_elems_processed_per_iteration)); - AccessWindowHorizontal input1_access(input1, 0, num_elems_processed_per_iteration); - AccessWindowHorizontal input2_access(input2, 0, num_elems_processed_per_iteration); - AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); + // Auto initialize output if not initialized + { + set_shape_if_empty(output, out_shape); - bool window_changed = update_window_and_padding(win, input1_access, input2_access, output_access); + if(input1.data_type() == DataType::S16 || input2.data_type() == DataType::S16) + { + set_format_if_unknown(output, Format::S16); + } + else if(input1.data_type() == DataType::F16 && input2.data_type() == DataType::F16) + { + set_format_if_unknown(output, Format::F16); + } + else if(input1.data_type() == DataType::F32 || input2.data_type() == DataType::F32) + { + set_format_if_unknown(output, Format::F32); + } + } + + Window win = calculate_max_window(valid_region, Steps(num_elems_processed_per_iteration)); + Window win_input1 = win.broadcast_if_dimension_le_one(input1); + Window win_input2 = win.broadcast_if_dimension_le_one(input2); - ValidRegion valid_region = intersect_valid_regions(input1->valid_region(), - input2->valid_region()); + AccessWindowHorizontal input1_access(&input1, 0, num_elems_processed_per_iteration); + AccessWindowHorizontal input2_access(&input2, 0, num_elems_processed_per_iteration); + AccessWindowHorizontal output_access(&output, 0, num_elems_processed_per_iteration); + + bool window_changed = update_window_and_padding(win_input1, input1_access) + || update_window_and_padding(win_input2, input2_access) + || update_window_and_padding(win, output_access); output_access.set_valid_region(win, valid_region); @@ -91,22 +128,11 @@ CLArithmeticSubtractionKernel::CLArithmeticSubtractionKernel() void CLArithmeticSubtractionKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ConvertPolicy policy) { ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input1->info(), *input2->info(), *output->info(), policy)); - // Auto initialize output if not initialized - { - set_shape_if_empty(*output->info(), input1->info()->tensor_shape()); - - if(input1->info()->data_type() == DataType::S16 || input2->info()->data_type() == DataType::S16) - { - set_format_if_unknown(*output->info(), Format::S16); - } - else if(input1->info()->data_type() == DataType::F32 || input2->info()->data_type() == DataType::F32) - { - set_format_if_unknown(*output->info(), Format::F32); - } - } - - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1->info(), input2->info(), output->info(), policy)); + // Configure kernel window + auto win_config = validate_and_configure_window(*input1->info(), *input2->info(), *output->info()); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); _input1 = input1; _input2 = input2; @@ -114,26 +140,39 @@ void CLArithmeticSubtractionKernel::configure(const ICLTensor *input1, const ICL bool has_float_out = is_data_type_float(output->info()->data_type()); + // Setup kernel + std::string kernel_name = "arithmetic_sub"; + // Set kernel build options - std::set build_opts; - build_opts.emplace((policy == ConvertPolicy::WRAP || has_float_out) ? "-DWRAP" : "-DSATURATE"); - build_opts.emplace("-DDATA_TYPE_IN1=" + get_cl_type_from_data_type(input1->info()->data_type())); - build_opts.emplace("-DDATA_TYPE_IN2=" + get_cl_type_from_data_type(input2->info()->data_type())); - build_opts.emplace("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(output->info()->data_type())); + CLBuildOptions build_opts; + build_opts.add_option_if_else(policy == ConvertPolicy::WRAP || has_float_out, "-DWRAP", "-DSATURATE"); + build_opts.add_option("-DDATA_TYPE_IN1=" + get_cl_type_from_data_type(input1->info()->data_type())); + build_opts.add_option("-DDATA_TYPE_IN2=" + get_cl_type_from_data_type(input2->info()->data_type())); + build_opts.add_option("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(output->info()->data_type())); + if(is_data_type_quantized_asymmetric(input1->info()->data_type())) + { + build_opts.add_option("-DOFFSET_IN1=" + support::cpp11::to_string(input1->info()->quantization_info().offset)); + build_opts.add_option("-DOFFSET_IN2=" + support::cpp11::to_string(input2->info()->quantization_info().offset)); + build_opts.add_option("-DOFFSET_OUT=" + support::cpp11::to_string(output->info()->quantization_info().offset)); + build_opts.add_option("-DSCALE_IN1=" + support::cpp11::to_string(input1->info()->quantization_info().scale)); + build_opts.add_option("-DSCALE_IN2=" + support::cpp11::to_string(input2->info()->quantization_info().scale)); + build_opts.add_option("-DSCALE_OUT=" + support::cpp11::to_string(output->info()->quantization_info().scale)); + kernel_name += "_quantized"; + } // Create kernel - _kernel = static_cast(CLKernelLibrary::get().create_kernel("arithmetic_sub", build_opts)); + _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); // Configure kernel window - auto win_config = validate_and_configure_window(input1->info(), input2->info(), output->info()); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); ICLKernel::configure_internal(win_config.second); } Status CLArithmeticSubtractionKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy) { - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input1, input2, output, policy)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input1->clone().get(), input2->clone().get(), output->clone().get()).first); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output); + + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*input1, *input2, *output, policy)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(*input1->clone(), *input2->clone(), *output->clone()).first); return Status{}; } @@ -143,16 +182,51 @@ void CLArithmeticSubtractionKernel::run(const Window &window, cl::CommandQueue & ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); - Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); - Window slice = collapsed.first_slice_window_3D(); + const TensorShape &in_shape1 = _input1->info()->tensor_shape(); + const TensorShape &in_shape2 = _input2->info()->tensor_shape(); + const TensorShape &out_shape = _output->info()->tensor_shape(); + + // Collapse only if broadcast dimensions is less than 2, or in case of no broadcasting + bool can_collapse = true; + if(std::min(in_shape1.total_size(), in_shape2.total_size()) > 1) + { + can_collapse = (std::min(in_shape1.num_dimensions(), in_shape2.num_dimensions()) > Window::DimZ); + for(size_t d = Window::DimZ; can_collapse && (d < out_shape.num_dimensions()); d++) + { + can_collapse = (in_shape1[d] == in_shape2[d]); + } + } + + bool has_collapsed = false; + Window collapsed = can_collapse ? window.collapse_if_possible(ICLKernel::window(), Window::DimZ, &has_collapsed) : window; + + const TensorShape &in_shape1_collapsed = has_collapsed ? in_shape1.collapsed_from(Window::DimZ) : in_shape1; + const TensorShape &in_shape2_collapsed = has_collapsed ? in_shape2.collapsed_from(Window::DimZ) : in_shape2; + + Window slice = collapsed.first_slice_window_3D(); + Window slice_input1 = slice.broadcast_if_dimension_le_one(in_shape1_collapsed); + Window slice_input2 = slice.broadcast_if_dimension_le_one(in_shape2_collapsed); do { unsigned int idx = 0; - add_3D_tensor_argument(idx, _input1, slice); - add_3D_tensor_argument(idx, _input2, slice); + + add_3D_tensor_argument(idx, _input1, slice_input1); + add_3D_tensor_argument(idx, _input2, slice_input2); add_3D_tensor_argument(idx, _output, slice); + enqueue(queue, *this, slice); + + collapsed.slide_window_slice_3D(slice_input1); + collapsed.slide_window_slice_3D(slice_input2); } while(collapsed.slide_window_slice_3D(slice)); } + +BorderSize CLArithmeticSubtractionKernel::border_size() const +{ + const unsigned int replicateSize = _output->info()->dimension(0) - std::min(_input1->info()->dimension(0), _input2->info()->dimension(0)); + const unsigned int border = std::min(num_elems_processed_per_iteration - 1U, replicateSize); + return BorderSize(0, border, 0, 0); +} +} // namespace arm_compute \ No newline at end of file diff --git a/src/core/NEON/kernels/NEArithmeticAdditionKernel.cpp b/src/core/NEON/kernels/NEArithmeticAdditionKernel.cpp index a6102b159f..169554f87a 100644 --- a/src/core/NEON/kernels/NEArithmeticAdditionKernel.cpp +++ b/src/core/NEON/kernels/NEArithmeticAdditionKernel.cpp @@ -456,7 +456,7 @@ void NEArithmeticAdditionKernel::configure(const ITensor *input1, const ITensor Status NEArithmeticAdditionKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy) { - ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output); ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*input1, *input2, *output, policy)); ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(*input1->clone(), *input2->clone(), *output->clone()).first); diff --git a/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp b/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp index 3c76548b0a..ff8fb84958 100644 --- a/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp +++ b/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp @@ -46,10 +46,12 @@ class Coordinates; namespace { +constexpr unsigned int num_elems_processed_per_iteration = 16; + void sub_wrap_U8_U8_U8(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) { - Iterator input1(in1, window); - Iterator input2(in2, window); + Iterator input1(in1, window.broadcast_if_dimension_le_one(in1->info()->tensor_shape())); + Iterator input2(in2, window.broadcast_if_dimension_le_one(in2->info()->tensor_shape())); Iterator output(out, window); execute_window_loop(window, [&](const Coordinates & id) @@ -64,8 +66,8 @@ void sub_wrap_U8_U8_U8(const ITensor *in1, const ITensor *in2, ITensor *out, con void sub_saturate_U8_U8_U8(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) { - Iterator input1(in1, window); - Iterator input2(in2, window); + Iterator input1(in1, window.broadcast_if_dimension_le_one(in1->info()->tensor_shape())); + Iterator input2(in2, window.broadcast_if_dimension_le_one(in2->info()->tensor_shape())); Iterator output(out, window); execute_window_loop(window, [&](const Coordinates & id) @@ -80,8 +82,8 @@ void sub_saturate_U8_U8_U8(const ITensor *in1, const ITensor *in2, ITensor *out, void sub_wrap_S16_S16_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) { - Iterator input1(in1, window); - Iterator input2(in2, window); + Iterator input1(in1, window.broadcast_if_dimension_le_one(in1->info()->tensor_shape())); + Iterator input2(in2, window.broadcast_if_dimension_le_one(in2->info()->tensor_shape())); Iterator output(out, window); execute_window_loop(window, [&](const Coordinates & id) @@ -104,8 +106,8 @@ void sub_wrap_S16_S16_S16(const ITensor *in1, const ITensor *in2, ITensor *out, void sub_saturate_S16_S16_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) { - Iterator input1(in1, window); - Iterator input2(in2, window); + Iterator input1(in1, window.broadcast_if_dimension_le_one(in1->info()->tensor_shape())); + Iterator input2(in2, window.broadcast_if_dimension_le_one(in2->info()->tensor_shape())); Iterator output(out, window); execute_window_loop(window, [&](const Coordinates & id) @@ -144,8 +146,8 @@ inline float16x8x2_t vsub2q_f16(const float16x8x2_t &a, const float16x8x2_t &b) void sub_F16_F16_F16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) { #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC - Iterator input1(in1, window); - Iterator input2(in2, window); + Iterator input1(in1, window.broadcast_if_dimension_le_one(in1->info()->tensor_shape())); + Iterator input2(in2, window.broadcast_if_dimension_le_one(in2->info()->tensor_shape())); Iterator output(out, window); execute_window_loop(window, [&](const Coordinates & id) @@ -167,8 +169,8 @@ void sub_F16_F16_F16(const ITensor *in1, const ITensor *in2, ITensor *out, const void sub_F32_F32_F32(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) { - Iterator input1(in1, window); - Iterator input2(in2, window); + Iterator input1(in1, window.broadcast_if_dimension_le_one(in1->info()->tensor_shape())); + Iterator input2(in2, window.broadcast_if_dimension_le_one(in2->info()->tensor_shape())); Iterator output(out, window); execute_window_loop(window, [&](const Coordinates & id) @@ -192,8 +194,8 @@ void sub_F32_F32_F32(const ITensor *in1, const ITensor *in2, ITensor *out, const } void sub_wrap_S16_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) { - Iterator input1(in1, window); - Iterator input2(in2, window); + Iterator input1(in1, window.broadcast_if_dimension_le_one(in1->info()->tensor_shape())); + Iterator input2(in2, window.broadcast_if_dimension_le_one(in2->info()->tensor_shape())); Iterator output(out, window); execute_window_loop(window, [&](const Coordinates & id) @@ -213,8 +215,8 @@ void sub_wrap_S16_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, c void sub_saturate_S16_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) { - Iterator input1(in1, window); - Iterator input2(in2, window); + Iterator input1(in1, window.broadcast_if_dimension_le_one(in1->info()->tensor_shape())); + Iterator input2(in2, window.broadcast_if_dimension_le_one(in2->info()->tensor_shape())); Iterator output(out, window); execute_window_loop(window, [&](const Coordinates & id) @@ -234,8 +236,8 @@ void sub_saturate_S16_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *ou void sub_wrap_U8_S16_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) { - Iterator input1(in1, window); - Iterator input2(in2, window); + Iterator input1(in1, window.broadcast_if_dimension_le_one(in1->info()->tensor_shape())); + Iterator input2(in2, window.broadcast_if_dimension_le_one(in2->info()->tensor_shape())); Iterator output(out, window); execute_window_loop(window, [&](const Coordinates & id) @@ -255,8 +257,8 @@ void sub_wrap_U8_S16_S16(const ITensor *in1, const ITensor *in2, ITensor *out, c void sub_saturate_U8_S16_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) { - Iterator input1(in1, window); - Iterator input2(in2, window); + Iterator input1(in1, window.broadcast_if_dimension_le_one(in1->info()->tensor_shape())); + Iterator input2(in2, window.broadcast_if_dimension_le_one(in2->info()->tensor_shape())); Iterator output(out, window); execute_window_loop(window, [&](const Coordinates & id) @@ -276,8 +278,8 @@ void sub_saturate_U8_S16_S16(const ITensor *in1, const ITensor *in2, ITensor *ou void sub_wrap_U8_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) { - Iterator input1(in1, window); - Iterator input2(in2, window); + Iterator input1(in1, window.broadcast_if_dimension_le_one(in1->info()->tensor_shape())); + Iterator input2(in2, window.broadcast_if_dimension_le_one(in2->info()->tensor_shape())); Iterator output(out, window); execute_window_loop(window, [&](const Coordinates & id) @@ -298,8 +300,8 @@ void sub_wrap_U8_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, co void sub_saturate_U8_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) { - Iterator input1(in1, window); - Iterator input2(in2, window); + Iterator input1(in1, window.broadcast_if_dimension_le_one(in1->info()->tensor_shape())); + Iterator input2(in2, window.broadcast_if_dimension_le_one(in2->info()->tensor_shape())); Iterator output(out, window); execute_window_loop(window, [&](const Coordinates & id) @@ -318,43 +320,71 @@ void sub_saturate_U8_U8_S16(const ITensor *in1, const ITensor *in2, ITensor *out input1, input2, output); } -inline Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy) +inline Status validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output, ConvertPolicy policy) { ARM_COMPUTE_UNUSED(policy); - ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input1); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, input2, output); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::S16, DataType::F16, DataType::F32); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG( - !(input1->data_type() == DataType::U8 && input2->data_type() == DataType::U8 && output->data_type() == DataType::U8) - && !(input1->data_type() == DataType::U8 && input2->data_type() == DataType::U8 && output->data_type() == DataType::S16) - && !(input1->data_type() == DataType::U8 && input2->data_type() == DataType::S16 && output->data_type() == DataType::S16) - && !(input1->data_type() == DataType::S16 && input2->data_type() == DataType::U8 && output->data_type() == DataType::S16) - && !(input1->data_type() == DataType::S16 && input2->data_type() == DataType::S16 && output->data_type() == DataType::S16) - && !(input1->data_type() == DataType::F32 && input2->data_type() == DataType::F32 && output->data_type() == DataType::F32) - && !(input1->data_type() == DataType::F16 && input2->data_type() == DataType::F16 && output->data_type() == DataType::F16), - "You called subtract with the wrong image formats"); + ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(&input1); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input1, 1, DataType::U8, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input2, 1, DataType::U8, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&output, 1, DataType::U8, DataType::S16, DataType::F16, DataType::F32); + + const TensorShape out_shape = TensorShape::broadcast_shape(input1.tensor_shape(), input2.tensor_shape()); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible"); + // Validate in case of configured output + if(output.total_size() > 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG( + !(input1.data_type() == DataType::U8 && input2.data_type() == DataType::U8 && output.data_type() == DataType::U8) + && !(input1.data_type() == DataType::U8 && input2.data_type() == DataType::U8 && output.data_type() == DataType::S16) + && !(input1.data_type() == DataType::U8 && input2.data_type() == DataType::S16 && output.data_type() == DataType::S16) + && !(input1.data_type() == DataType::S16 && input2.data_type() == DataType::U8 && output.data_type() == DataType::S16) + && !(input1.data_type() == DataType::S16 && input2.data_type() == DataType::S16 && output.data_type() == DataType::S16) + && !(input1.data_type() == DataType::F32 && input2.data_type() == DataType::F32 && output.data_type() == DataType::F32) + && !(input1.data_type() == DataType::F16 && input2.data_type() == DataType::F16 && output.data_type() == DataType::F16), + "You called subtract with the wrong image formats"); + + ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output.tensor_shape(), 0), + "Wrong shape for output"); + } return Status{}; } -inline std::pair validate_and_configure_window(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output) +inline std::pair validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output) { - constexpr unsigned int num_elems_processed_per_iteration = 16; + const std::pair broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(input1, input2); + const TensorShape &out_shape = broadcast_pair.first; + const ValidRegion &valid_region = broadcast_pair.second; - // Configure kernel window - Window win = calculate_max_window(*input1, Steps(num_elems_processed_per_iteration)); - AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); + // Auto initialize output if not initialized + { + set_shape_if_empty(output, out_shape); - bool window_changed = update_window_and_padding(win, - AccessWindowHorizontal(input1, 0, num_elems_processed_per_iteration), - AccessWindowHorizontal(input2, 0, num_elems_processed_per_iteration), - output_access); + if(input1.data_type() == DataType::S16 || input2.data_type() == DataType::S16) + { + set_format_if_unknown(output, Format::S16); + } + else if(input1.data_type() == DataType::F16 && input2.data_type() == DataType::F16) + { + set_format_if_unknown(output, Format::F16); + } + else if(input1.data_type() == DataType::F32 || input2.data_type() == DataType::F32) + { + set_format_if_unknown(output, Format::F32); + } + } + + Window win = calculate_max_window(valid_region, Steps(num_elems_processed_per_iteration)); + Window win_input1 = win.broadcast_if_dimension_le_one(input1); + Window win_input2 = win.broadcast_if_dimension_le_one(input2); - ValidRegion valid_region = intersect_valid_regions(input1->valid_region(), - input2->valid_region()); + AccessWindowHorizontal input1_access(&input1, 0, num_elems_processed_per_iteration); + AccessWindowHorizontal input2_access(&input2, 0, num_elems_processed_per_iteration); + AccessWindowHorizontal output_access(&output, 0, num_elems_processed_per_iteration); + + bool window_changed = update_window_and_padding(win_input1, input1_access) + || update_window_and_padding(win_input2, input2_access) + || update_window_and_padding(win, output_access); output_access.set_valid_region(win, valid_region); @@ -371,26 +401,11 @@ NEArithmeticSubtractionKernel::NEArithmeticSubtractionKernel() void NEArithmeticSubtractionKernel::configure(const ITensor *input1, const ITensor *input2, ITensor *output, ConvertPolicy policy) { ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input1->info(), *input2->info(), *output->info(), policy)); - // Auto initialize output if not initialized - { - set_shape_if_empty(*output->info(), input1->info()->tensor_shape()); - - if(input1->info()->data_type() == DataType::S16 || input2->info()->data_type() == DataType::S16) - { - set_format_if_unknown(*output->info(), Format::S16); - } - else if(input1->info()->data_type() == DataType::F16 || input2->info()->data_type() == DataType::F16) - { - set_format_if_unknown(*output->info(), Format::F16); - } - else if(input1->info()->data_type() == DataType::F32 || input2->info()->data_type() == DataType::F32) - { - set_format_if_unknown(*output->info(), Format::F32); - } - } - - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1->info(), input2->info(), output->info(), policy)); + // Configure kernel window + auto win_config = validate_and_configure_window(*input1->info(), *input2->info(), *output->info()); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); static std::map map_function = { @@ -427,16 +442,15 @@ void NEArithmeticSubtractionKernel::configure(const ITensor *input1, const ITens _func = it->second; } - // Configure kernel window - auto win_config = validate_and_configure_window(input1->info(), input2->info(), output->info()); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); INEKernel::configure(win_config.second); } Status NEArithmeticSubtractionKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy) { - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input1, input2, output, policy)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input1->clone().get(), input2->clone().get(), output->clone().get()).first); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output); + + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*input1, *input2, *output, policy)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(*input1->clone(), *input2->clone(), *output->clone()).first); return Status{}; } @@ -450,3 +464,10 @@ void NEArithmeticSubtractionKernel::run(const Window &window, const ThreadInfo & (*_func)(_input1, _input2, _output, window); } + +BorderSize NEArithmeticSubtractionKernel::border_size() const +{ + const unsigned int replicateSize = _output->info()->dimension(0) - std::min(_input1->info()->dimension(0), _input2->info()->dimension(0)); + const unsigned int border = std::min(num_elems_processed_per_iteration - 1U, replicateSize); + return BorderSize(0, border, 0, 0); +} \ No newline at end of file diff --git a/src/runtime/CL/functions/CLArithmeticSubtraction.cpp b/src/runtime/CL/functions/CLArithmeticSubtraction.cpp index 5fca30c4f9..e661f6adc1 100644 --- a/src/runtime/CL/functions/CLArithmeticSubtraction.cpp +++ b/src/runtime/CL/functions/CLArithmeticSubtraction.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016, 2017 ARM Limited. + * Copyright (c) 2016-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -23,6 +23,7 @@ */ #include "arm_compute/runtime/CL/functions/CLArithmeticSubtraction.h" +#include "arm_compute/core/CL/ICLTensor.h" #include "arm_compute/core/CL/kernels/CLArithmeticSubtractionKernel.h" #include "support/ToolchainSupport.h" @@ -30,11 +31,21 @@ using namespace arm_compute; -void CLArithmeticSubtraction::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ConvertPolicy policy) +void CLArithmeticSubtraction::configure(ICLTensor *input1, ICLTensor *input2, ICLTensor *output, ConvertPolicy policy) { auto k = arm_compute::support::cpp14::make_unique(); k->configure(input1, input2, output, policy); _kernel = std::move(k); + + if(output->info()->dimension(0) > 1) + { + ICLTensor *broadcasted_info = (input1->info()->dimension(0) == 1) ? input1 : input2; + + if(broadcasted_info->info()->dimension(0) == 1) + { + _border_handler.configure(broadcasted_info, _kernel->border_size(), BorderMode::REPLICATE); + } + } } Status CLArithmeticSubtraction::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy) diff --git a/src/runtime/NEON/functions/NEArithmeticAddition.cpp b/src/runtime/NEON/functions/NEArithmeticAddition.cpp index 7d8e3cff1c..677e9f676f 100644 --- a/src/runtime/NEON/functions/NEArithmeticAddition.cpp +++ b/src/runtime/NEON/functions/NEArithmeticAddition.cpp @@ -29,8 +29,8 @@ #include -using namespace arm_compute; - +namespace arm_compute +{ void NEArithmeticAddition::configure(ITensor *input1, ITensor *input2, ITensor *output, ConvertPolicy policy) { auto k = arm_compute::support::cpp14::make_unique(); @@ -51,3 +51,4 @@ Status NEArithmeticAddition::validate(const ITensorInfo *input1, const ITensorIn { return NEArithmeticAdditionKernel::validate(input1, input2, output, policy); } +} // namespace arm_compute diff --git a/src/runtime/NEON/functions/NEArithmeticSubtraction.cpp b/src/runtime/NEON/functions/NEArithmeticSubtraction.cpp index 5c0491ec6f..ceb4b496bc 100644 --- a/src/runtime/NEON/functions/NEArithmeticSubtraction.cpp +++ b/src/runtime/NEON/functions/NEArithmeticSubtraction.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -23,20 +23,33 @@ */ #include "arm_compute/runtime/NEON/functions/NEArithmeticSubtraction.h" +#include "arm_compute/core/ITensor.h" #include "arm_compute/core/NEON/kernels/NEArithmeticSubtractionKernel.h" #include "support/ToolchainSupport.h" #include -using namespace arm_compute; - -void NEArithmeticSubtraction::configure(const ITensor *input1, const ITensor *input2, ITensor *output, ConvertPolicy policy) +namespace arm_compute +{ +void NEArithmeticSubtraction::configure(ITensor *input1, ITensor *input2, ITensor *output, ConvertPolicy policy) { auto k = arm_compute::support::cpp14::make_unique(); k->configure(input1, input2, output, policy); _kernel = std::move(k); + + if(output->info()->dimension(0) > 1) + { + ITensor *broadcasted_info = (input1->info()->dimension(0) == 1) ? input1 : input2; + + if(broadcasted_info->info()->dimension(0) == 1) + { + _border_handler.configure(broadcasted_info, _kernel->border_size(), BorderMode::REPLICATE); + } + } } + Status NEArithmeticSubtraction::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy) { return NEArithmeticSubtractionKernel::validate(input1, input2, output, policy); } +} // namespace arm_compute diff --git a/tests/validation/CL/ArithmeticAddition.cpp b/tests/validation/CL/ArithmeticAddition.cpp index bd27bc4043..e327769397 100644 --- a/tests/validation/CL/ArithmeticAddition.cpp +++ b/tests/validation/CL/ArithmeticAddition.cpp @@ -33,7 +33,7 @@ #include "tests/framework/Macros.h" #include "tests/framework/datasets/Datasets.h" #include "tests/validation/Validation.h" -#include "tests/validation/fixtures/ArithmeticAdditionFixture.h" +#include "tests/validation/fixtures/ArithmeticOperationsFixture.h" namespace arm_compute { diff --git a/tests/validation/CL/ArithmeticSubtraction.cpp b/tests/validation/CL/ArithmeticSubtraction.cpp index b19d963515..cd13f42ec4 100644 --- a/tests/validation/CL/ArithmeticSubtraction.cpp +++ b/tests/validation/CL/ArithmeticSubtraction.cpp @@ -18,7 +18,7 @@ * 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 CONCLCTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ #include "arm_compute/core/Types.h" @@ -33,7 +33,7 @@ #include "tests/framework/Macros.h" #include "tests/framework/datasets/Datasets.h" #include "tests/validation/Validation.h" -#include "tests/validation/fixtures/ArithmeticSubtractionFixture.h" +#include "tests/validation/fixtures/ArithmeticOperationsFixture.h" namespace arm_compute { @@ -47,14 +47,11 @@ namespace const auto ArithmeticSubtractionU8Dataset = combine(combine(framework::dataset::make("DataType", DataType::U8), framework::dataset::make("DataType", DataType::U8)), framework::dataset::make("DataType", DataType::U8)); -const auto ArithmeticSubtractionS16Dataset = combine(combine(framework::dataset::make("DataType", DataType::S16), framework::dataset::make("DataType", DataType::S16)), +const auto ArithmeticSubtractionQASYMM8Dataset = combine(combine(framework::dataset::make("DataType", DataType::QASYMM8), framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("DataType", + DataType::QASYMM8)); +const auto ArithmeticSubtractionS16Dataset = combine(combine(framework::dataset::make("DataType", { DataType::U8, DataType::S16 }), framework::dataset::make("DataType", DataType::S16)), framework::dataset::make("DataType", DataType::S16)); -const auto ArithmeticSubtractionU8U8S16Dataset = combine(combine(framework::dataset::make("DataType", DataType::U8), framework::dataset::make("DataType", DataType::U8)), - framework::dataset::make("DataType", DataType::S16)); -const auto ArithmeticSubtractionS16U8S16Dataset = combine(combine(framework::dataset::make("DataType", DataType::S16), framework::dataset::make("DataType", DataType::U8)), - framework::dataset::make("DataType", DataType::S16)); -const auto ArithmeticSubtractionU8S16S16Dataset = combine(combine(framework::dataset::make("DataType", DataType::U8), framework::dataset::make("DataType", DataType::S16)), - framework::dataset::make("DataType", DataType::S16)); const auto ArithmeticSubtractionFP16Dataset = combine(combine(framework::dataset::make("DataType", DataType::F16), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("DataType", DataType::F16)); const auto ArithmeticSubtractionFP32Dataset = combine(combine(framework::dataset::make("DataType", DataType::F32), framework::dataset::make("DataType", DataType::F32)), @@ -67,34 +64,34 @@ TEST_SUITE(ArithmeticSubtraction) // *INDENT-OFF* // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( - framework::dataset::make("Input1Info", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), // Window shrink - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), // Invalid data type combination - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching shapes - }), - framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), - TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), - })), - framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), - })), - framework::dataset::make("Expected", { true, true, false, false, false, false, true })), - input1_info, input2_info, output_info, expected) + framework::dataset::make("Input1Info", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), // Window shrink + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), // Invalid data type combination + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching shapes + }), + framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("Expected", { true, true, false, false, false})), + input1_info, input2_info, output_info, expected) { ARM_COMPUTE_EXPECT(bool(CLArithmeticSubtraction::validate(&input1_info.clone()->set_is_resizable(false), &input2_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), ConvertPolicy::WRAP)) == expected, framework::LogLevel::ERRORS); } // clang-format on // *INDENT-ON* -template -using CLArithmeticSubtractionFixture = ArithmeticSubtractionValidationFixture; +template +using CLArithmeticSubtractionFixture = ArithmeticSubtractionValidationFixture; TEST_SUITE(U8) DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })), @@ -120,33 +117,30 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::da validate(dst.info()->padding(), padding); } -FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticSubtractionFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), - ArithmeticSubtractionU8Dataset), +FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticSubtractionFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), ArithmeticSubtractionU8Dataset), framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) { // Validate output validate(CLAccessor(_target), _reference); } -TEST_SUITE_END() +TEST_SUITE_END() // U8 -template -using CLArithmeticSubtractionToS16Fixture = CLArithmeticSubtractionFixture; +template +using CLArithmeticSubtractionQuantizedFixture = ArithmeticSubtractionValidationQuantizedFixture; -TEST_SUITE(S16) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), - framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), - framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })), - shape, data_type1, data_type2, policy) +TEST_SUITE(Quantized) +TEST_SUITE(QASYMM8) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })), + shape, policy) { // Create tensors - CLTensor ref_src1 = create_tensor(shape, data_type1); - CLTensor ref_src2 = create_tensor(shape, data_type2); - CLTensor dst = create_tensor(shape, DataType::S16); + CLTensor ref_src1 = create_tensor(shape, DataType::QASYMM8); + CLTensor ref_src2 = create_tensor(shape, DataType::QASYMM8); + CLTensor dst = create_tensor(shape, DataType::QASYMM8); // Create and Configure function - CLArithmeticSubtraction sub; - sub.configure(&ref_src1, &ref_src2, &dst, policy); + CLArithmeticSubtraction add; + add.configure(&ref_src1, &ref_src2, &dst, policy); // Validate valid region const ValidRegion valid_region = shape_to_valid_region(shape); @@ -158,78 +152,61 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combi validate(ref_src2.info()->padding(), padding); validate(dst.info()->padding(), padding); } -TEST_SUITE(S16_S16_S16) -FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticSubtractionToS16Fixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), ArithmeticSubtractionS16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) -{ - // Validate output - validate(CLAccessor(_target), _reference); -} -FIXTURE_DATA_TEST_CASE(RunLarge, CLArithmeticSubtractionToS16Fixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), ArithmeticSubtractionS16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) -{ - // Validate output - validate(CLAccessor(_target), _reference); -} -TEST_SUITE_END() +FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticSubtractionQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(datasets::SmallShapes(), + ArithmeticSubtractionQASYMM8Dataset), + framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255.f, 5) })) -TEST_SUITE(U8_U8_S16) -FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticSubtractionToS16Fixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), - ArithmeticSubtractionU8U8S16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) + ) { // Validate output validate(CLAccessor(_target), _reference); } +TEST_SUITE_END() // QASYMM8 +TEST_SUITE_END() // Quantized -FIXTURE_DATA_TEST_CASE(RunLarge, CLArithmeticSubtractionToS16Fixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), - ArithmeticSubtractionU8U8S16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) +TEST_SUITE(S16) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), + framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })), + shape, data_type, policy) { - // Validate output - validate(CLAccessor(_target), _reference); -} -TEST_SUITE_END() + // Create tensors + CLTensor ref_src1 = create_tensor(shape, data_type); + CLTensor ref_src2 = create_tensor(shape, DataType::S16); + CLTensor dst = create_tensor(shape, DataType::S16); -TEST_SUITE(S16_U8_S16) -using CLAriSubS16U8ToS16Fixture = CLArithmeticSubtractionToS16Fixture; -FIXTURE_DATA_TEST_CASE(RunSmall, CLAriSubS16U8ToS16Fixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), - ArithmeticSubtractionS16U8S16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) -{ - // Validate output - validate(CLAccessor(_target), _reference); -} + // Create and Configure function + CLArithmeticSubtraction sub; + sub.configure(&ref_src1, &ref_src2, &dst, policy); -FIXTURE_DATA_TEST_CASE(RunLarge, CLAriSubS16U8ToS16Fixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), - ArithmeticSubtractionS16U8S16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) -{ - // Validate output - validate(CLAccessor(_target), _reference); + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), 16).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); } -TEST_SUITE_END() -TEST_SUITE(U8_S16_S16) -using CLAriSubU8S16ToS16Fixture = CLArithmeticSubtractionToS16Fixture; -FIXTURE_DATA_TEST_CASE(RunSmall, CLAriSubU8S16ToS16Fixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), - ArithmeticSubtractionU8S16S16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) +FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticSubtractionFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), ArithmeticSubtractionS16Dataset), + framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) { // Validate output validate(CLAccessor(_target), _reference); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLAriSubU8S16ToS16Fixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), - ArithmeticSubtractionU8S16S16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) +FIXTURE_DATA_TEST_CASE(RunLarge, CLArithmeticSubtractionFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), ArithmeticSubtractionS16Dataset), + framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) { // Validate output validate(CLAccessor(_target), _reference); } -TEST_SUITE_END() -TEST_SUITE_END() +TEST_SUITE_END() // S16 TEST_SUITE(Float) TEST_SUITE(FP16) @@ -239,7 +216,7 @@ FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticSubtractionFixture, framework // Validate output validate(CLAccessor(_target), _reference); } -TEST_SUITE_END() +TEST_SUITE_END() // FP16 TEST_SUITE(FP32) DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })), @@ -278,11 +255,30 @@ FIXTURE_DATA_TEST_CASE(RunLarge, CLArithmeticSubtractionFixture, framewor // Validate output validate(CLAccessor(_target), _reference); } -TEST_SUITE_END() -TEST_SUITE_END() -TEST_SUITE_END() -TEST_SUITE_END() +template +using CLArithmeticSubtractionBroadcastFixture = ArithmeticSubtractionBroadcastValidationFixture; + +FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, CLArithmeticSubtractionBroadcastFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapesBroadcast(), + ArithmeticSubtractionFP32Dataset), + framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLargeBroadcast, CLArithmeticSubtractionBroadcastFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapesBroadcast(), + ArithmeticSubtractionFP32Dataset), + framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() // FP32 +TEST_SUITE_END() // Float + +TEST_SUITE_END() // ArithmeticSubtraction +TEST_SUITE_END() // CL } // namespace validation } // namespace test -} // namespace arm_compute +} // namespace arm_compute \ No newline at end of file diff --git a/tests/validation/GLES_COMPUTE/ArithmeticAddition.cpp b/tests/validation/GLES_COMPUTE/ArithmeticAddition.cpp index b16503e079..82946fa209 100755 --- a/tests/validation/GLES_COMPUTE/ArithmeticAddition.cpp +++ b/tests/validation/GLES_COMPUTE/ArithmeticAddition.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -33,7 +33,7 @@ #include "tests/framework/Macros.h" #include "tests/framework/datasets/Datasets.h" #include "tests/validation/Validation.h" -#include "tests/validation/fixtures/ArithmeticAdditionFixture.h" +#include "tests/validation/fixtures/ArithmeticOperationsFixture.h" namespace arm_compute { diff --git a/tests/validation/NEON/ArithmeticAddition.cpp b/tests/validation/NEON/ArithmeticAddition.cpp index 3632c3c207..4dc56dce54 100644 --- a/tests/validation/NEON/ArithmeticAddition.cpp +++ b/tests/validation/NEON/ArithmeticAddition.cpp @@ -33,7 +33,7 @@ #include "tests/framework/Macros.h" #include "tests/framework/datasets/Datasets.h" #include "tests/validation/Validation.h" -#include "tests/validation/fixtures/ArithmeticAdditionFixture.h" +#include "tests/validation/fixtures/ArithmeticOperationsFixture.h" namespace arm_compute { diff --git a/tests/validation/NEON/ArithmeticSubtraction.cpp b/tests/validation/NEON/ArithmeticSubtraction.cpp index 210ed4578f..2e21c14ebc 100644 --- a/tests/validation/NEON/ArithmeticSubtraction.cpp +++ b/tests/validation/NEON/ArithmeticSubtraction.cpp @@ -33,7 +33,7 @@ #include "tests/framework/Macros.h" #include "tests/framework/datasets/Datasets.h" #include "tests/validation/Validation.h" -#include "tests/validation/fixtures/ArithmeticSubtractionFixture.h" +#include "tests/validation/fixtures/ArithmeticOperationsFixture.h" namespace arm_compute { @@ -49,12 +49,6 @@ const auto ArithmeticSubtractionU8Dataset = combine(combine(framework::dataset:: DataType::U8)); const auto ArithmeticSubtractionS16Dataset = combine(combine(framework::dataset::make("DataType", { DataType::U8, DataType::S16 }), framework::dataset::make("DataType", DataType::S16)), framework::dataset::make("DataType", DataType::S16)); -const auto ArithmeticSubtractionU8U8S16Dataset = combine(combine(framework::dataset::make("DataType", DataType::U8), framework::dataset::make("DataType", DataType::U8)), - framework::dataset::make("DataType", DataType::S16)); -const auto ArithmeticSubtractionS16U8S16Dataset = combine(combine(framework::dataset::make("DataType", DataType::S16), framework::dataset::make("DataType", DataType::U8)), - framework::dataset::make("DataType", DataType::S16)); -const auto ArithmeticSubtractionU8S16S16Dataset = combine(combine(framework::dataset::make("DataType", DataType::U8), framework::dataset::make("DataType", DataType::S16)), - framework::dataset::make("DataType", DataType::S16)); #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC const auto ArithmeticSubtractionFP16Dataset = combine(combine(framework::dataset::make("DataType", DataType::F16), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("DataType", DataType::F16)); @@ -66,38 +60,38 @@ const auto ArithmeticSubtractionFP32Dataset = combine(combine(framework::dataset TEST_SUITE(NEON) TEST_SUITE(ArithmeticSubtraction) +template +using NEArithmeticSubtractionFixture = ArithmeticSubtractionValidationFixture; + // *INDENT-OFF* // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( - framework::dataset::make("Input1Info", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), // Window shrink - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), // Invalid data type combination - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching shapes - }), - framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), - TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), - })), - framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), - })), - framework::dataset::make("Expected", { true, true, false, false, false})), - input1_info, input2_info, output_info, expected) + framework::dataset::make("Input1Info", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), // Window shrink + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), // Invalid data type combination + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching shapes + }), + framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("Expected", { true, true, false, false, false})), + input1_info, input2_info, output_info, expected) { ARM_COMPUTE_EXPECT(bool(NEArithmeticSubtraction::validate(&input1_info.clone()->set_is_resizable(false), &input2_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), ConvertPolicy::WRAP)) == expected, framework::LogLevel::ERRORS); } // clang-format on // *INDENT-ON* -template -using NEArithmeticSubtractionFixture = ArithmeticSubtractionValidationFixture; - TEST_SUITE(U8) DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })), shape, policy) @@ -128,21 +122,16 @@ FIXTURE_DATA_TEST_CASE(RunSmall, NEArithmeticSubtractionFixture, framew // Validate output validate(Accessor(_target), _reference); } -TEST_SUITE_END() - -template -using NEArithmeticSubtractionToS16Fixture = NEArithmeticSubtractionFixture; +TEST_SUITE_END() // U8 TEST_SUITE(S16) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), - framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), - framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })), - shape, data_type1, data_type2, policy) + shape, data_type, policy) { // Create tensors - Tensor ref_src1 = create_tensor(shape, data_type1); - Tensor ref_src2 = create_tensor(shape, data_type2); + Tensor ref_src1 = create_tensor(shape, data_type); + Tensor ref_src2 = create_tensor(shape, DataType::S16); Tensor dst = create_tensor(shape, DataType::S16); // Create and Configure function @@ -160,92 +149,34 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combi validate(dst.info()->padding(), padding); } -TEST_SUITE(S16_S16_S16) -FIXTURE_DATA_TEST_CASE(RunSmall, NEArithmeticSubtractionToS16Fixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), ArithmeticSubtractionS16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) -{ - // Validate output - validate(Accessor(_target), _reference); -} - -FIXTURE_DATA_TEST_CASE(RunLarge, NEArithmeticSubtractionToS16Fixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), ArithmeticSubtractionS16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) -{ - // Validate output - validate(Accessor(_target), _reference); -} -TEST_SUITE_END() - -TEST_SUITE(U8_U8_S16) -FIXTURE_DATA_TEST_CASE(RunSmall, NEArithmeticSubtractionToS16Fixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), - ArithmeticSubtractionU8U8S16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) -{ - // Validate output - validate(Accessor(_target), _reference); -} - -FIXTURE_DATA_TEST_CASE(RunLarge, NEArithmeticSubtractionToS16Fixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), - ArithmeticSubtractionU8U8S16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) -{ - // Validate output - validate(Accessor(_target), _reference); -} -TEST_SUITE_END() - -TEST_SUITE(S16_U8_S16) -using NEAriSubS16U8ToS16Fixture = NEArithmeticSubtractionToS16Fixture; -FIXTURE_DATA_TEST_CASE(RunSmall, NEAriSubS16U8ToS16Fixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), - ArithmeticSubtractionS16U8S16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) -{ - // Validate output - validate(Accessor(_target), _reference); -} - -FIXTURE_DATA_TEST_CASE(RunLarge, NEAriSubS16U8ToS16Fixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), - ArithmeticSubtractionS16U8S16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) -{ - // Validate output - validate(Accessor(_target), _reference); -} -TEST_SUITE_END() - -TEST_SUITE(U8_S16_S16) -using NEAriSubU8S16ToS16Fixture = NEArithmeticSubtractionToS16Fixture; -FIXTURE_DATA_TEST_CASE(RunSmall, NEAriSubU8S16ToS16Fixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), - ArithmeticSubtractionU8S16S16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) +FIXTURE_DATA_TEST_CASE(RunSmall, NEArithmeticSubtractionFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), ArithmeticSubtractionS16Dataset), + framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) { // Validate output validate(Accessor(_target), _reference); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEAriSubU8S16ToS16Fixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), - ArithmeticSubtractionU8S16S16Dataset), - framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) +FIXTURE_DATA_TEST_CASE(RunLarge, NEArithmeticSubtractionFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), ArithmeticSubtractionS16Dataset), + framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) { // Validate output validate(Accessor(_target), _reference); } -TEST_SUITE_END() -TEST_SUITE_END() +TEST_SUITE_END() // S16 TEST_SUITE(Float) #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC -TEST_SUITE(FP16) +TEST_SUITE(F16) FIXTURE_DATA_TEST_CASE(RunSmall, NEArithmeticSubtractionFixture, framework::DatasetMode::ALL, combine(combine(datasets::SmallShapes(), ArithmeticSubtractionFP16Dataset), framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) { // Validate output validate(Accessor(_target), _reference); } -TEST_SUITE_END() -#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ +TEST_SUITE_END() // F16 +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ -TEST_SUITE(FP32) +TEST_SUITE(F32) DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })), shape, policy) { @@ -282,11 +213,30 @@ FIXTURE_DATA_TEST_CASE(RunLarge, NEArithmeticSubtractionFixture, framewor // Validate output validate(Accessor(_target), _reference); } -TEST_SUITE_END() -TEST_SUITE_END() -TEST_SUITE_END() -TEST_SUITE_END() +template +using NEArithmeticSubtractionBroadcastFixture = ArithmeticSubtractionBroadcastValidationFixture; + +FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, NEArithmeticSubtractionBroadcastFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapesBroadcast(), + ArithmeticSubtractionFP32Dataset), + framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLargeBroadcast, NEArithmeticSubtractionBroadcastFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapesBroadcast(), + ArithmeticSubtractionFP32Dataset), + framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // F32 +TEST_SUITE_END() // Float + +TEST_SUITE_END() // ArithmeticSubtraction +TEST_SUITE_END() // NEON } // namespace validation } // namespace test } // namespace arm_compute diff --git a/tests/validation/fixtures/ArithmeticAdditionFixture.h b/tests/validation/fixtures/ArithmeticAdditionFixture.h deleted file mode 100644 index 66875934de..0000000000 --- a/tests/validation/fixtures/ArithmeticAdditionFixture.h +++ /dev/null @@ -1,157 +0,0 @@ -/* - * Copyright (c) 2017-2018 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_ARITHMETIC_ADDITION_FIXTURE -#define ARM_COMPUTE_TEST_ARITHMETIC_ADDITION_FIXTURE - -#include "arm_compute/core/TensorShape.h" -#include "arm_compute/core/Types.h" -#include "tests/AssetsLibrary.h" -#include "tests/Globals.h" -#include "tests/IAccessor.h" -#include "tests/framework/Asserts.h" -#include "tests/framework/Fixture.h" -#include "tests/validation/Helpers.h" -#include "tests/validation/reference/ArithmeticAddition.h" - -namespace arm_compute -{ -namespace test -{ -namespace validation -{ -template -class ArithmeticAdditionGenericFixture : public framework::Fixture -{ -public: - template - void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, - QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) - { - _target = compute_target(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, qinfo0, qinfo1, qinfo_out); - _reference = compute_reference(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, qinfo0, qinfo1, qinfo_out); - } - -protected: - template - void fill(U &&tensor, int i) - { - library->fill_tensor_uniform(tensor, i); - } - - TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, - QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) - { - // Create tensors - TensorType ref_src1 = create_tensor(shape0, data_type0, 1, qinfo0); - TensorType ref_src2 = create_tensor(shape1, data_type1, 1, qinfo1); - TensorType dst = create_tensor(TensorShape::broadcast_shape(shape0, shape1), output_data_type, 1, qinfo_out); - - // Create and configure function - FunctionType add; - add.configure(&ref_src1, &ref_src2, &dst, convert_policy); - - ARM_COMPUTE_EXPECT(ref_src1.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(ref_src2.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Allocate tensors - ref_src1.allocator()->allocate(); - ref_src2.allocator()->allocate(); - dst.allocator()->allocate(); - - ARM_COMPUTE_EXPECT(!ref_src1.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!ref_src2.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Fill tensors - fill(AccessorType(ref_src1), 0); - fill(AccessorType(ref_src2), 1); - - // Compute function - add.run(); - - return dst; - } - - SimpleTensor compute_reference(const TensorShape &shape0, const TensorShape &shape1, - DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, - QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) - { - // Create reference - SimpleTensor ref_src1{ shape0, data_type0, 1, qinfo0 }; - SimpleTensor ref_src2{ shape1, data_type1, 1, qinfo1 }; - SimpleTensor ref_dst{ TensorShape::broadcast_shape(shape0, shape1), output_data_type, 1, qinfo_out }; - - // Fill reference - fill(ref_src1, 0); - fill(ref_src2, 1); - - return reference::arithmetic_addition(ref_src1, ref_src2, ref_dst, convert_policy); - } - - TensorType _target{}; - SimpleTensor _reference{}; -}; - -template -class ArithmeticAdditionBroadcastValidationFixture : public ArithmeticAdditionGenericFixture -{ -public: - template - void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy) - { - ArithmeticAdditionGenericFixture::setup(shape0, shape1, data_type0, data_type1, - output_data_type, convert_policy, QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); - } -}; - -template -class ArithmeticAdditionValidationFixture : public ArithmeticAdditionGenericFixture -{ -public: - template - void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy) - { - ArithmeticAdditionGenericFixture::setup(shape, shape, data_type0, data_type1, - output_data_type, convert_policy, QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); - } -}; - -template -class ArithmeticAdditionValidationQuantizedFixture : public ArithmeticAdditionGenericFixture -{ -public: - template - void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, - QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) - - { - ArithmeticAdditionGenericFixture::setup(shape, shape, data_type0, data_type1, - output_data_type, convert_policy, qinfo0, qinfo1, qinfo_out); - } -}; -} // namespace validation -} // namespace test -} // namespace arm_compute -#endif /* ARM_COMPUTE_TEST_ARITHMETIC_ADDITION_FIXTURE */ diff --git a/tests/validation/fixtures/ArithmeticOperationsFixture.h b/tests/validation/fixtures/ArithmeticOperationsFixture.h new file mode 100644 index 0000000000..fb46a5185e --- /dev/null +++ b/tests/validation/fixtures/ArithmeticOperationsFixture.h @@ -0,0 +1,201 @@ +/* + * Copyright (c) 2017-2018 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_ARITHMETIC_OPERATIONS_FIXTURE +#define ARM_COMPUTE_TEST_ARITHMETIC_OPERATIONS_FIXTURE + +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" +#include "tests/AssetsLibrary.h" +#include "tests/Globals.h" +#include "tests/IAccessor.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/Fixture.h" +#include "tests/validation/Helpers.h" +#include "tests/validation/reference/ArithmeticOperations.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +template +class ArithmeticOperationGenericFixture : public framework::Fixture +{ +public: + template + void setup(reference::ArithmeticOperation op, const TensorShape &shape0, const TensorShape &shape1, + DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + { + _op = op; + _target = compute_target(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, qinfo0, qinfo1, qinfo_out); + _reference = compute_reference(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, qinfo0, qinfo1, qinfo_out); + } + +protected: + template + void fill(U &&tensor, int i) + { + library->fill_tensor_uniform(tensor, i); + } + + TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + { + // Create tensors + TensorType ref_src1 = create_tensor(shape0, data_type0, 1, qinfo0); + TensorType ref_src2 = create_tensor(shape1, data_type1, 1, qinfo1); + TensorType dst = create_tensor(TensorShape::broadcast_shape(shape0, shape1), output_data_type, 1, qinfo_out); + + // Create and configure function + FunctionType arith_op; + arith_op.configure(&ref_src1, &ref_src2, &dst, convert_policy); + + ARM_COMPUTE_EXPECT(ref_src1.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(ref_src2.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Allocate tensors + ref_src1.allocator()->allocate(); + ref_src2.allocator()->allocate(); + dst.allocator()->allocate(); + + ARM_COMPUTE_EXPECT(!ref_src1.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!ref_src2.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensors + fill(AccessorType(ref_src1), 0); + fill(AccessorType(ref_src2), 1); + + // Compute function + arith_op.run(); + + return dst; + } + + SimpleTensor compute_reference(const TensorShape &shape0, const TensorShape &shape1, + DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + { + // Create reference + SimpleTensor ref_src1{ shape0, data_type0, 1, qinfo0 }; + SimpleTensor ref_src2{ shape1, data_type1, 1, qinfo1 }; + SimpleTensor ref_dst{ TensorShape::broadcast_shape(shape0, shape1), output_data_type, 1, qinfo_out }; + + // Fill reference + fill(ref_src1, 0); + fill(ref_src2, 1); + + return reference::arithmetic_operation(_op, ref_src1, ref_src2, ref_dst, convert_policy); + } + + TensorType _target{}; + SimpleTensor _reference{}; + reference::ArithmeticOperation _op{ reference::ArithmeticOperation::ADD }; +}; + +template +class ArithmeticAdditionBroadcastValidationFixture : public ArithmeticOperationGenericFixture +{ +public: + template + void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy) + { + ArithmeticOperationGenericFixture::setup(reference::ArithmeticOperation::ADD, shape0, shape1, data_type0, data_type1, + output_data_type, convert_policy, QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); + } +}; + +template +class ArithmeticAdditionValidationFixture : public ArithmeticOperationGenericFixture +{ +public: + template + void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy) + { + ArithmeticOperationGenericFixture::setup(reference::ArithmeticOperation::ADD, shape, shape, data_type0, data_type1, + output_data_type, convert_policy, QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); + } +}; + +template +class ArithmeticAdditionValidationQuantizedFixture : public ArithmeticOperationGenericFixture +{ +public: + template + void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + + { + ArithmeticOperationGenericFixture::setup(reference::ArithmeticOperation::ADD, shape, shape, data_type0, data_type1, + output_data_type, convert_policy, qinfo0, qinfo1, qinfo_out); + } +}; + +template +class ArithmeticSubtractionBroadcastValidationFixture : public ArithmeticOperationGenericFixture +{ +public: + template + void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy) + { + ArithmeticOperationGenericFixture::setup(reference::ArithmeticOperation::SUB, shape0, shape1, + data_type0, data_type1, output_data_type, convert_policy, + QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); + } +}; + +template +class ArithmeticSubtractionValidationFixture : public ArithmeticOperationGenericFixture +{ +public: + template + void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy) + { + ArithmeticOperationGenericFixture::setup(reference::ArithmeticOperation::SUB, shape, shape, + data_type0, data_type1, output_data_type, convert_policy, + QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); + } +}; + +template +class ArithmeticSubtractionValidationQuantizedFixture : public ArithmeticOperationGenericFixture +{ +public: + template + void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + + { + ArithmeticOperationGenericFixture::setup(reference::ArithmeticOperation::SUB, shape, shape, + data_type0, data_type1, output_data_type, + convert_policy, qinfo0, qinfo1, qinfo_out); + } +}; +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_ARITHMETIC_OPERATIONS_FIXTURE */ diff --git a/tests/validation/fixtures/ArithmeticSubtractionFixture.h b/tests/validation/fixtures/ArithmeticSubtractionFixture.h deleted file mode 100644 index 9897677691..0000000000 --- a/tests/validation/fixtures/ArithmeticSubtractionFixture.h +++ /dev/null @@ -1,114 +0,0 @@ -/* - * Copyright (c) 2017-2018 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_ARITHMETIC_SUBTRACTION_FIXTURE -#define ARM_COMPUTE_TEST_ARITHMETIC_SUBTRACTION_FIXTURE - -#include "arm_compute/core/TensorShape.h" -#include "arm_compute/core/Types.h" -#include "tests/AssetsLibrary.h" -#include "tests/Globals.h" -#include "tests/IAccessor.h" -#include "tests/framework/Asserts.h" -#include "tests/framework/Fixture.h" -#include "tests/validation/Helpers.h" -#include "tests/validation/reference/ArithmeticSubtraction.h" - -namespace arm_compute -{ -namespace test -{ -namespace validation -{ -template -class ArithmeticSubtractionValidationFixture : public framework::Fixture -{ -public: - template - void setup(TensorShape shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy) - { - _target = compute_target(shape, data_type0, data_type1, output_data_type, convert_policy); - _reference = compute_reference(shape, data_type0, data_type1, output_data_type, convert_policy); - } - -protected: - template - void fill(U &&tensor, int i) - { - library->fill_tensor_uniform(tensor, i); - } - - TensorType compute_target(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy) - { - // Create tensors - TensorType ref_src1 = create_tensor(shape, data_type0, 1); - TensorType ref_src2 = create_tensor(shape, data_type1, 1); - TensorType dst = create_tensor(shape, output_data_type, 1); - - // Create and configure function - FunctionType sub; - sub.configure(&ref_src1, &ref_src2, &dst, convert_policy); - - ARM_COMPUTE_EXPECT(ref_src1.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(ref_src2.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Allocate tensors - ref_src1.allocator()->allocate(); - ref_src2.allocator()->allocate(); - dst.allocator()->allocate(); - - ARM_COMPUTE_EXPECT(!ref_src1.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!ref_src2.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Fill tensors - fill(AccessorType(ref_src1), 0); - fill(AccessorType(ref_src2), 1); - - // Compute function - sub.run(); - - return dst; - } - - SimpleTensor compute_reference(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy) - { - // Create reference - SimpleTensor ref_src1{ shape, data_type0, 1 }; - SimpleTensor ref_src2{ shape, data_type1, 1 }; - - // Fill reference - fill(ref_src1, 0); - fill(ref_src2, 1); - - return reference::arithmetic_subtraction(ref_src1, ref_src2, output_data_type, convert_policy); - } - - TensorType _target{}; - SimpleTensor _reference{}; -}; -} // namespace validation -} // namespace test -} // namespace arm_compute -#endif /* ARM_COMPUTE_TEST_ARITHMETIC_SUBTRACTION_FIXTURE */ diff --git a/tests/validation/fixtures/LSTMLayerFixture.h b/tests/validation/fixtures/LSTMLayerFixture.h index 20df855242..bc892bfecf 100644 --- a/tests/validation/fixtures/LSTMLayerFixture.h +++ b/tests/validation/fixtures/LSTMLayerFixture.h @@ -28,8 +28,7 @@ #include "tests/framework/Asserts.h" #include "tests/framework/Fixture.h" #include "tests/validation/reference/ActivationLayer.h" -#include "tests/validation/reference/ArithmeticAddition.h" -#include "tests/validation/reference/ArithmeticSubtraction.h" +#include "tests/validation/reference/ArithmeticOperations.h" #include "tests/validation/reference/FullyConnectedLayer.h" #include "tests/validation/reference/GEMM.h" #include "tests/validation/reference/PixelWiseMultiplication.h" @@ -333,12 +332,12 @@ protected: SimpleTensor fully_connected_forget = reference::fully_connected_layer(input, input_to_forget_w, forget_gate_bias, output_cell_shape); SimpleTensor transposed_weights = reference::transpose(recurrent_to_forget_w); SimpleTensor gemm = reference::gemm(output_state_in, transposed_weights, cell_state_in, 1.f, 0.f); - SimpleTensor forget_gate = reference::arithmetic_addition(fully_connected_forget, gemm, data_type, ConvertPolicy::SATURATE); + SimpleTensor forget_gate = reference::arithmetic_operation(reference::ArithmeticOperation::ADD, fully_connected_forget, gemm, data_type, ConvertPolicy::SATURATE); if(peephole_opt) { SimpleTensor pixelwise_mul_forget_gate = reference::pixel_wise_multiplication(cell_state_in, cell_to_forget_w, 1, ConvertPolicy::SATURATE, RoundingPolicy::TO_NEAREST_EVEN); - forget_gate = reference::arithmetic_addition(forget_gate, pixelwise_mul_forget_gate, data_type, ConvertPolicy::SATURATE); + forget_gate = reference::arithmetic_operation(reference::ArithmeticOperation::ADD, forget_gate, pixelwise_mul_forget_gate, data_type, ConvertPolicy::SATURATE); } forget_gate = reference::activation_layer(forget_gate, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC)); @@ -349,18 +348,18 @@ protected: { SimpleTensor ones{ cell_bias_shape, data_type }; fill_custom_val(ones, 1.f, 0); - input_gate = reference::arithmetic_subtraction(ones, forget_gate, data_type, ConvertPolicy::SATURATE); + input_gate = reference::arithmetic_operation(reference::ArithmeticOperation::SUB, ones, forget_gate, data_type, ConvertPolicy::SATURATE); } else { SimpleTensor fully_connected_input = reference::fully_connected_layer(input, input_to_input_w, input_gate_bias, output_cell_shape); transposed_weights = reference::transpose(recurrent_to_input_w); gemm = reference::gemm(output_state_in, transposed_weights, cell_state_in, 1.f, 0.f); - input_gate = reference::arithmetic_addition(fully_connected_input, gemm, data_type, ConvertPolicy::SATURATE); + input_gate = reference::arithmetic_operation(reference::ArithmeticOperation::ADD, fully_connected_input, gemm, data_type, ConvertPolicy::SATURATE); if(peephole_opt) { SimpleTensor pixelwise_mul_input_gate = reference::pixel_wise_multiplication(cell_state_in, cell_to_input_w, 1, ConvertPolicy::SATURATE, RoundingPolicy::TO_NEAREST_EVEN); - input_gate = reference::arithmetic_addition(input_gate, pixelwise_mul_input_gate, data_type, ConvertPolicy::SATURATE); + input_gate = reference::arithmetic_operation(reference::ArithmeticOperation::ADD, input_gate, pixelwise_mul_input_gate, data_type, ConvertPolicy::SATURATE); } input_gate = reference::activation_layer(input_gate, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC)); } @@ -370,10 +369,10 @@ protected: transposed_weights = reference::transpose(recurrent_to_cell_w); gemm = reference::gemm(output_state_in, transposed_weights, cell_state_out, 1.f, 0.f); SimpleTensor pixelwise_mul = reference::pixel_wise_multiplication(cell_state_in, forget_gate, 1, ConvertPolicy::SATURATE, RoundingPolicy::TO_NEAREST_EVEN); - cell_state_out = reference::arithmetic_addition(fully_connected_cell_state, gemm, data_type, ConvertPolicy::SATURATE); + cell_state_out = reference::arithmetic_operation(reference::ArithmeticOperation::ADD, fully_connected_cell_state, gemm, data_type, ConvertPolicy::SATURATE); cell_state_out = reference::activation_layer(cell_state_out, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC)); cell_state_out = reference::pixel_wise_multiplication(cell_state_out, input_gate, 1, ConvertPolicy::SATURATE, RoundingPolicy::TO_NEAREST_EVEN); - cell_state_out = reference::arithmetic_addition(cell_state_out, pixelwise_mul, data_type, ConvertPolicy::SATURATE); + cell_state_out = reference::arithmetic_operation(reference::ArithmeticOperation::ADD, cell_state_out, pixelwise_mul, data_type, ConvertPolicy::SATURATE); if(cell_threshold != 0.f) { cell_state_out = reference::activation_layer(cell_state_out, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, -cell_threshold, cell_threshold)); @@ -383,11 +382,11 @@ protected: SimpleTensor fully_connected_output = reference::fully_connected_layer(input, input_to_output_w, output_gate_bias, output_cell_shape); transposed_weights = reference::transpose(recurrent_to_output_w); gemm = reference::gemm(output_state_in, transposed_weights, cell_state_out, 1.f, 0.f); - output = reference::arithmetic_addition(fully_connected_output, gemm, data_type, ConvertPolicy::SATURATE); + output = reference::arithmetic_operation(reference::ArithmeticOperation::ADD, fully_connected_output, gemm, data_type, ConvertPolicy::SATURATE); if(peephole_opt) { pixelwise_mul = reference::pixel_wise_multiplication(cell_state_out, cell_to_output_w, 1, ConvertPolicy::SATURATE, RoundingPolicy::TO_NEAREST_EVEN); - output = reference::arithmetic_addition(output, pixelwise_mul, data_type, ConvertPolicy::SATURATE); + output = reference::arithmetic_operation(reference::ArithmeticOperation::ADD, output, pixelwise_mul, data_type, ConvertPolicy::SATURATE); } output = reference::activation_layer(output, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC)); diff --git a/tests/validation/fixtures/RNNLayerFixture.h b/tests/validation/fixtures/RNNLayerFixture.h index 42b99cce1c..2645116b44 100644 --- a/tests/validation/fixtures/RNNLayerFixture.h +++ b/tests/validation/fixtures/RNNLayerFixture.h @@ -28,7 +28,7 @@ #include "tests/framework/Asserts.h" #include "tests/framework/Fixture.h" #include "tests/validation/reference/ActivationLayer.h" -#include "tests/validation/reference/ArithmeticAddition.h" +#include "tests/validation/reference/ArithmeticOperations.h" #include "tests/validation/reference/FullyConnectedLayer.h" #include "tests/validation/reference/GEMM.h" @@ -132,7 +132,7 @@ protected: SimpleTensor out_w{ out_shape, data_type }; SimpleTensor fully_connected = reference::fully_connected_layer(input, weights, bias, out_shape); SimpleTensor gemm = reference::gemm(hidden_state, recurrent_weights, out_w, 1.f, 0.f); - SimpleTensor add_res = reference::arithmetic_addition(fully_connected, gemm, data_type, ConvertPolicy::SATURATE); + SimpleTensor add_res = reference::arithmetic_operation(reference::ArithmeticOperation::ADD, fully_connected, gemm, data_type, ConvertPolicy::SATURATE); return reference::activation_layer(add_res, info); } diff --git a/tests/validation/reference/ArithmeticAddition.cpp b/tests/validation/reference/ArithmeticAddition.cpp deleted file mode 100644 index c68c6d4ed6..0000000000 --- a/tests/validation/reference/ArithmeticAddition.cpp +++ /dev/null @@ -1,147 +0,0 @@ -/* - * Copyright (c) 2017-2018 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. - */ -#include "ArithmeticAddition.h" - -#include "arm_compute/core/Types.h" -#include "tests/validation/Helpers.h" - -namespace arm_compute -{ -namespace test -{ -namespace validation -{ -namespace reference -{ -namespace -{ -template -T add(T src1, T src2, ConvertPolicy convert_policy) -{ - using intermediate_type = typename common_promoted_signed_type::intermediate_type; - - intermediate_type val = static_cast(src1) + static_cast(src2); - - T result = (convert_policy == ConvertPolicy::SATURATE) ? saturate_cast(val) : static_cast(val); - - return result; -} - -template -struct BroadcastUnroll -{ - template - static void unroll(const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, - ConvertPolicy convert_policy, Coordinates &id_src1, Coordinates &id_src2, Coordinates &id_dst) - { - const bool src1_is_broadcast = (src1.shape()[dim - 1] != dst.shape()[dim - 1]); - const bool src2_is_broadcast = (src2.shape()[dim - 1] != dst.shape()[dim - 1]); - - id_src1.set(dim - 1, 0); - id_src2.set(dim - 1, 0); - id_dst.set(dim - 1, 0); - - for(size_t i = 0; i < dst.shape()[dim - 1]; ++i, ++id_dst[dim - 1]) - { - BroadcastUnroll < dim - 1 >::unroll(src1, src2, dst, convert_policy, id_src1, id_src2, id_dst); - - id_src1[dim - 1] += !src1_is_broadcast; - id_src2[dim - 1] += !src2_is_broadcast; - } - } -}; - -template <> -struct BroadcastUnroll<0> -{ - template - static void unroll(const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, - ConvertPolicy convert_policy, Coordinates &id_src1, Coordinates &id_src2, Coordinates &id_dst) - { - dst[coord2index(dst.shape(), id_dst)] = add(src1[coord2index(src1.shape(), id_src1)], src2[coord2index(src2.shape(), id_src2)], convert_policy); - } -}; -} // namespace - -template -SimpleTensor arithmetic_addition(const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, ConvertPolicy convert_policy) -{ - Coordinates id_src1, id_src2, id_dst; - - BroadcastUnroll::unroll(src1, src2, dst, convert_policy, id_src1, id_src2, id_dst); - - return dst; -} - -template <> -SimpleTensor arithmetic_addition(const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, ConvertPolicy convert_policy) -{ - if(dst.data_type() == DataType::QASYMM8) - { - SimpleTensor src1_tmp = convert_from_asymmetric(src1); - SimpleTensor src2_tmp = convert_from_asymmetric(src2); - SimpleTensor dst_tmp(TensorShape::broadcast_shape(src1.shape(), src2.shape()), dst.data_type()); - - Coordinates id_src1, id_src2, id_dst; - - BroadcastUnroll::unroll(src1_tmp, src2_tmp, dst_tmp, convert_policy, id_src1, id_src2, id_dst); - - dst = convert_to_asymmetric(dst_tmp, dst.quantization_info()); - return dst; - } - else - { - // DataType::U8 - Coordinates id_src1, id_src2, id_dst; - - BroadcastUnroll::unroll(src1, src2, dst, convert_policy, id_src1, id_src2, id_dst); - - return dst; - } -} - -template SimpleTensor arithmetic_addition(const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, ConvertPolicy convert_policy); -template SimpleTensor arithmetic_addition(const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, ConvertPolicy convert_policy); -template SimpleTensor arithmetic_addition(const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, ConvertPolicy convert_policy); -template SimpleTensor arithmetic_addition(const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, ConvertPolicy convert_policy); - -template -SimpleTensor arithmetic_addition(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy) -{ - ARM_COMPUTE_ERROR_ON_MSG(dst_data_type == DataType::QASYMM8, "For QASYMM8, the quantized output tensor should be passed directly."); - - SimpleTensor dst(TensorShape::broadcast_shape(src1.shape(), src2.shape()), dst_data_type); - arithmetic_addition(src1, src2, dst, convert_policy); - return dst; -} - -template SimpleTensor arithmetic_addition(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); -template SimpleTensor arithmetic_addition(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); -template SimpleTensor arithmetic_addition(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); -template SimpleTensor arithmetic_addition(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); - -} // namespace reference -} // namespace validation -} // namespace test -} // namespace arm_compute diff --git a/tests/validation/reference/ArithmeticAddition.h b/tests/validation/reference/ArithmeticAddition.h deleted file mode 100644 index faeabd7a6f..0000000000 --- a/tests/validation/reference/ArithmeticAddition.h +++ /dev/null @@ -1,48 +0,0 @@ -/* - * Copyright (c) 2017-2018 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_ARITHMETIC_ADDITION_H__ -#define __ARM_COMPUTE_TEST_ARITHMETIC_ADDITION_H__ - -#include "tests/SimpleTensor.h" -#include "tests/validation/Helpers.h" - -namespace arm_compute -{ -namespace test -{ -namespace validation -{ -namespace reference -{ -template -SimpleTensor arithmetic_addition(const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, ConvertPolicy convert_policy); - -template -SimpleTensor arithmetic_addition(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); - -} // namespace reference -} // namespace validation -} // namespace test -} // namespace arm_compute -#endif /* __ARM_COMPUTE_TEST_ARITHMETIC_ADDITION_H__ */ diff --git a/tests/validation/reference/ArithmeticOperations.cpp b/tests/validation/reference/ArithmeticOperations.cpp new file mode 100644 index 0000000000..062be93b95 --- /dev/null +++ b/tests/validation/reference/ArithmeticOperations.cpp @@ -0,0 +1,149 @@ +/* + * Copyright (c) 2017-2018 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. + */ +#include "ArithmeticOperations.h" + +#include "arm_compute/core/Types.h" +#include "tests/validation/Helpers.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace reference +{ +namespace +{ +template +T arithm_op(ArithmeticOperation op, T src1, T src2, ConvertPolicy convert_policy) +{ + using intermediate_type = typename common_promoted_signed_type::intermediate_type; + + intermediate_type val = (op == ArithmeticOperation::ADD) ? static_cast(src1) + static_cast(src2) : static_cast + (src1) - static_cast(src2); + + T result = (convert_policy == ConvertPolicy::SATURATE) ? saturate_cast(val) : static_cast(val); + + return result; +} + +template +struct BroadcastUnroll +{ + template + static void unroll(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, + ConvertPolicy convert_policy, Coordinates &id_src1, Coordinates &id_src2, Coordinates &id_dst) + { + const bool src1_is_broadcast = (src1.shape()[dim - 1] != dst.shape()[dim - 1]); + const bool src2_is_broadcast = (src2.shape()[dim - 1] != dst.shape()[dim - 1]); + + id_src1.set(dim - 1, 0); + id_src2.set(dim - 1, 0); + id_dst.set(dim - 1, 0); + + for(size_t i = 0; i < dst.shape()[dim - 1]; ++i, ++id_dst[dim - 1]) + { + BroadcastUnroll < dim - 1 >::unroll(op, src1, src2, dst, convert_policy, id_src1, id_src2, id_dst); + + id_src1[dim - 1] += !src1_is_broadcast; + id_src2[dim - 1] += !src2_is_broadcast; + } + } +}; + +template <> +struct BroadcastUnroll<0> +{ + template + static void unroll(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, + ConvertPolicy convert_policy, Coordinates &id_src1, Coordinates &id_src2, Coordinates &id_dst) + { + dst[coord2index(dst.shape(), id_dst)] = arithm_op(op, src1[coord2index(src1.shape(), id_src1)], src2[coord2index(src2.shape(), id_src2)], convert_policy); + } +}; +} // namespace + +template +SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, ConvertPolicy convert_policy) +{ + Coordinates id_src1, id_src2, id_dst; + + BroadcastUnroll::unroll(op, src1, src2, dst, convert_policy, id_src1, id_src2, id_dst); + + return dst; +} + +template <> +SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, ConvertPolicy convert_policy) +{ + if(dst.data_type() == DataType::QASYMM8) + { + SimpleTensor src1_tmp = convert_from_asymmetric(src1); + SimpleTensor src2_tmp = convert_from_asymmetric(src2); + SimpleTensor dst_tmp(TensorShape::broadcast_shape(src1.shape(), src2.shape()), dst.data_type()); + + Coordinates id_src1, id_src2, id_dst; + + BroadcastUnroll::unroll(op, src1_tmp, src2_tmp, dst_tmp, convert_policy, id_src1, id_src2, id_dst); + + dst = convert_to_asymmetric(dst_tmp, dst.quantization_info()); + return dst; + } + else + { + // DataType::U8 + Coordinates id_src1, id_src2, id_dst; + + BroadcastUnroll::unroll(op, src1, src2, dst, convert_policy, id_src1, id_src2, id_dst); + + return dst; + } +} + +template SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, + ConvertPolicy convert_policy); +template SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, ConvertPolicy convert_policy); +template SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, ConvertPolicy convert_policy); +template SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, ConvertPolicy convert_policy); + +template +SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy) +{ + ARM_COMPUTE_ERROR_ON_MSG(dst_data_type == DataType::QASYMM8, "For QASYMM8, the quantized output tensor should be passed directly."); + + SimpleTensor dst(TensorShape::broadcast_shape(src1.shape(), src2.shape()), dst_data_type); + arithmetic_operation(op, src1, src2, dst, convert_policy); + return dst; +} + +template SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); +template SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); +template SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); +template SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); + +} // namespace reference +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/reference/ArithmeticOperations.h b/tests/validation/reference/ArithmeticOperations.h new file mode 100644 index 0000000000..73634823c4 --- /dev/null +++ b/tests/validation/reference/ArithmeticOperations.h @@ -0,0 +1,54 @@ +/* + * Copyright (c) 2017-2018 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_ARITHMETIC_OPERATIONS_H__ +#define __ARM_COMPUTE_TEST_ARITHMETIC_OPERATIONS_H__ + +#include "tests/SimpleTensor.h" +#include "tests/validation/Helpers.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace reference +{ +/** Arithmetic operation types */ +enum class ArithmeticOperation +{ + ADD, + SUB +}; + +template +SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, ConvertPolicy convert_policy); + +template +SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); +} // namespace reference +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif /* __ARM_COMPUTE_TEST_ARITHMETIC_OPERATIONS_H__ */ diff --git a/tests/validation/reference/ArithmeticSubtraction.cpp b/tests/validation/reference/ArithmeticSubtraction.cpp deleted file mode 100644 index f39d01f9e8..0000000000 --- a/tests/validation/reference/ArithmeticSubtraction.cpp +++ /dev/null @@ -1,63 +0,0 @@ -/* - * Copyright (c) 2017-2018 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. - */ -#include "ArithmeticSubtraction.h" - -#include "tests/validation/Helpers.h" - -namespace arm_compute -{ -namespace test -{ -namespace validation -{ -namespace reference -{ -template -SimpleTensor arithmetic_subtraction(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy) -{ - SimpleTensor result(src1.shape(), dst_data_type); - - using intermediate_type = typename common_promoted_signed_type= sizeof(T2), T1, T2>::type >::intermediate_type; - - for(int i = 0; i < src1.num_elements(); ++i) - { - intermediate_type val = static_cast(src1[i]) - static_cast(src2[i]); - result[i] = (convert_policy == ConvertPolicy::SATURATE) ? saturate_cast(val) : static_cast(val); - } - - return result; -} - -template SimpleTensor arithmetic_subtraction(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); -template SimpleTensor arithmetic_subtraction(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); -template SimpleTensor arithmetic_subtraction(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); -template SimpleTensor arithmetic_subtraction(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); -template SimpleTensor arithmetic_subtraction(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); -template SimpleTensor arithmetic_subtraction(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); -template SimpleTensor arithmetic_subtraction(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); -template SimpleTensor arithmetic_subtraction(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); -} // namespace reference -} // namespace validation -} // namespace test -} // namespace arm_compute diff --git a/tests/validation/reference/ArithmeticSubtraction.h b/tests/validation/reference/ArithmeticSubtraction.h deleted file mode 100644 index 9308314bda..0000000000 --- a/tests/validation/reference/ArithmeticSubtraction.h +++ /dev/null @@ -1,44 +0,0 @@ -/* - * 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_ARITHMETIC_SUBTRACTION_H__ -#define __ARM_COMPUTE_TEST_ARITHMETIC_SUBTRACTION_H__ - -#include "tests/SimpleTensor.h" -#include "tests/validation/Helpers.h" - -namespace arm_compute -{ -namespace test -{ -namespace validation -{ -namespace reference -{ -template -SimpleTensor arithmetic_subtraction(const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); -} // namespace reference -} // namespace validation -} // namespace test -} // namespace arm_compute -#endif /* __ARM_COMPUTE_TEST_ARITHMETIC_SUBTRACTION_H__ */ diff --git a/tests/validation/reference/LaplacianPyramid.cpp b/tests/validation/reference/LaplacianPyramid.cpp index 566847453b..21ddc1e48e 100644 --- a/tests/validation/reference/LaplacianPyramid.cpp +++ b/tests/validation/reference/LaplacianPyramid.cpp @@ -23,7 +23,7 @@ */ #include "LaplacianPyramid.h" -#include "tests/validation/reference/ArithmeticSubtraction.h" +#include "tests/validation/reference/ArithmeticOperations.h" #include "tests/validation/reference/DepthConvertLayer.h" #include "tests/validation/reference/Gaussian5x5.h" #include "tests/validation/reference/GaussianPyramidHalf.h" @@ -53,7 +53,10 @@ std::vector> laplacian_pyramid(const SimpleTensor &src, Simpl const SimpleTensor level_filtered = reference::gaussian5x5(gaussian_level_pyramid[i], border_mode, constant_border_value); pyramid_conv.push_back(level_filtered); - const SimpleTensor level_sub = reference::arithmetic_subtraction(gaussian_level_pyramid[i], level_filtered, dst.data_type(), ConvertPolicy::WRAP); + const SimpleTensor level_filtered_converted = depth_convert(level_filtered, DataType::S16, ConvertPolicy::WRAP, 0); + const SimpleTensor gaussian_level_converted = depth_convert(gaussian_level_pyramid[i], DataType::S16, ConvertPolicy::WRAP, 0); + + const SimpleTensor level_sub = reference::arithmetic_operation(reference::ArithmeticOperation::SUB, gaussian_level_converted, level_filtered_converted, dst.data_type(), ConvertPolicy::WRAP); pyramid_dst.push_back(level_sub); } diff --git a/tests/validation/reference/LaplacianReconstruct.cpp b/tests/validation/reference/LaplacianReconstruct.cpp index 23468287b0..ef14355bc8 100644 --- a/tests/validation/reference/LaplacianReconstruct.cpp +++ b/tests/validation/reference/LaplacianReconstruct.cpp @@ -24,7 +24,7 @@ #include "LaplacianReconstruct.h" #include "arm_compute/core/Types.h" -#include "tests/validation/reference/ArithmeticAddition.h" +#include "tests/validation/reference/ArithmeticOperations.h" #include "tests/validation/reference/DepthConvertLayer.h" #include "tests/validation/reference/Scale.h" @@ -45,7 +45,7 @@ SimpleTensor laplacian_reconstruct(const std::vector> &pyrami const DataType data_type = low_res.data_type(); // input + L(n-1) - tmp_pyramid[last_level] = reference::arithmetic_addition(low_res, pyramid[last_level], data_type, ConvertPolicy::SATURATE); + tmp_pyramid[last_level] = reference::arithmetic_operation(reference::ArithmeticOperation::ADD, low_res, pyramid[last_level], data_type, ConvertPolicy::SATURATE); // Scale levels n-1 to 1, and add levels n-2 to 0 for(size_t i = last_level; i-- > 0;) @@ -56,7 +56,7 @@ SimpleTensor laplacian_reconstruct(const std::vector> &pyrami tmp_pyramid[i] = reference::scale(tmp_pyramid[i + 1], scale_x, scale_y, InterpolationPolicy::NEAREST_NEIGHBOR, border_mode, constant_border_value, SamplingPolicy::CENTER, false); - tmp_pyramid[i] = reference::arithmetic_addition(tmp_pyramid[i], pyramid[i], data_type, ConvertPolicy::SATURATE); + tmp_pyramid[i] = reference::arithmetic_operation(reference::ArithmeticOperation::ADD, tmp_pyramid[i], pyramid[i], data_type, ConvertPolicy::SATURATE); } return reference::depth_convert(tmp_pyramid[0], DataType::U8, ConvertPolicy::SATURATE, 0); -- cgit v1.2.1