From ced7a8d0b4fe77d750a1e55883d5886ad9760f3b Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Thu, 1 Feb 2018 16:31:33 +0000 Subject: COMPMID-875: Deconvolution 4x4 not working -Enforces the use of the ConvolutionLayer function in the DeconvolutionLayer. -Adds tests for 4x4 Deconvolution. -Alters the ConvolutionLayer validation to support even kernels. Change-Id: Id27e285f078e690b8dd58490dd8ea6d875b3cec6 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/118632 Tested-by: Jenkins Reviewed-by: Anthony Barbier --- .../runtime/CL/functions/CLDeconvolutionLayer.h | 6 +-- .../runtime/NEON/functions/NEDeconvolutionLayer.h | 7 ++- src/runtime/CL/functions/CLDeconvolutionLayer.cpp | 4 +- .../NEON/functions/NEDeconvolutionLayer.cpp | 19 ++++--- tests/datasets/ShapeDatasets.h | 3 +- tests/validation/CL/DeconvolutionLayer.cpp | 17 +++++- tests/validation/NEON/DeconvolutionLayer.cpp | 17 +++++- tests/validation/reference/ConvolutionLayer.cpp | 60 ++++++++++++---------- tests/validation/reference/DeconvolutionLayer.cpp | 2 +- 9 files changed, 91 insertions(+), 44 deletions(-) diff --git a/arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h b/arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h index e98cc9b3d6..2383d2aa1d 100644 --- a/arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h +++ b/arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017, 2018 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -24,8 +24,8 @@ #ifndef __ARM_COMPUTE_CLDECONVOLUTIONLAYER_H__ #define __ARM_COMPUTE_CLDECONVOLUTIONLAYER_H__ +#include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h" #include "arm_compute/runtime/CL/functions/CLDeconvolutionLayerUpsample.h" -#include "arm_compute/runtime/CL/functions/CLDirectConvolutionLayer.h" #include "arm_compute/runtime/CL/CLMemoryGroup.h" #include "arm_compute/runtime/CL/CLTensor.h" @@ -96,7 +96,7 @@ public: private: CLMemoryGroup _memory_group; CLDeconvolutionLayerUpsample _scale_f; - CLDirectConvolutionLayer _conv_f; + CLConvolutionLayer _conv_f; CLTensor _scaled_output; }; } diff --git a/arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.h index 091a928db6..1b3297e8d0 100644 --- a/arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.h +++ b/arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017, 2018 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -24,6 +24,7 @@ #ifndef __ARM_COMPUTE_NEDECONVOLUTIONLAYER_H__ #define __ARM_COMPUTE_NEDECONVOLUTIONLAYER_H__ +#include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h" #include "arm_compute/runtime/NEON/functions/NEDirectConvolutionLayer.h" #include "arm_compute/core/Types.h" @@ -95,11 +96,13 @@ public: private: MemoryGroup _memory_group; - NEDirectConvolutionLayer _conv_f; + NEDirectConvolutionLayer _direct_conv_f; + NEConvolutionLayer _conv_f; Tensor _scaled_output; ITensor *_input; PadStrideInfo _info; std::pair _inner_border; + bool _run_direct_convolution; }; } // arm_compute #endif /* __ARM_COMPUTE_NEDECONVOLUTIONLAYER_H__ */ diff --git a/src/runtime/CL/functions/CLDeconvolutionLayer.cpp b/src/runtime/CL/functions/CLDeconvolutionLayer.cpp index 1c55722344..79f6d6c10e 100644 --- a/src/runtime/CL/functions/CLDeconvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLDeconvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017, 2018 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -79,7 +79,7 @@ Status CLDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInf const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); ARM_COMPUTE_RETURN_ON_ERROR(CLDeconvolutionLayerUpsample::validate(input, &scale_out_info, BorderSize(inner_border_right, inner_border_top), info)); - ARM_COMPUTE_RETURN_ON_ERROR(CLDirectConvolutionLayer::validate(&scale_out_info, weights, bias, output, conv_info)); + // TODO (COMPMID-754): Add validation of CLConvolutionLayer when added. return Status{}; } diff --git a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp index 7bce8a6b7c..b293fa080a 100644 --- a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017, 2018 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -33,11 +33,13 @@ using namespace arm_compute::misc::shape_calculator; NEDeconvolutionLayer::NEDeconvolutionLayer(std::shared_ptr memory_manager) // NOLINT : _memory_group(std::move(memory_manager)), + _direct_conv_f(), _conv_f(), _scaled_output(), _input(nullptr), _info(), - _inner_border() + _inner_border(), + _run_direct_convolution(false) { } @@ -47,11 +49,12 @@ void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, con ARM_COMPUTE_ERROR_ON_NULLPTR(output); ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); ARM_COMPUTE_ERROR_ON(weights->info()->dimension(0) != weights->info()->dimension(1)); - ARM_COMPUTE_ERROR_ON(weights->info()->dimension(0) != 1 && weights->info()->dimension(0) != 3 && weights->info()->dimension(0) != 5); _input = input; _info = info; _inner_border = std::make_pair(inner_border_right, inner_border_top); + // FIXME: ConvolutionLayer Segfaults in GEMM assembly code for 1x1 convolutions + _run_direct_convolution = (weights->info()->dimension(0) == weights->info()->dimension(1)) && (weights->info()->dimension(0) == 1); const unsigned int stride_x = info.stride().first; const unsigned int stride_y = info.stride().second; @@ -75,7 +78,9 @@ void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, con // setup the function to convolve the upscaled output const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); - _conv_f.configure(&_scaled_output, weights, bias, output, conv_info); + (_run_direct_convolution) ? _direct_conv_f.configure(&_scaled_output, weights, bias, output, conv_info) : _conv_f.configure(&_scaled_output, weights, bias, output, conv_info); + + // Allocate auxiliary tensors _scaled_output.allocator()->allocate(); } @@ -92,7 +97,7 @@ void NEDeconvolutionLayer::run() const int stride_x = _info.stride().first; const int stride_y = _info.stride().second; - std::fill_n(reinterpret_cast(_scaled_output.buffer()), _scaled_output.info()->tensor_shape().total_size(), 0.f); + std::fill_n(_scaled_output.buffer(), _scaled_output.info()->total_size(), 0); // scaled_output is the input for the forward convolution. We copy the input elements to scaled_output // and insert rows and columns with zeroes depending on the stride values. @@ -113,6 +118,8 @@ void NEDeconvolutionLayer::run() } } - _conv_f.run(); + // Run convolution layer + (_run_direct_convolution) ? _direct_conv_f.run() : _conv_f.run(); + _memory_group.release(); } diff --git a/tests/datasets/ShapeDatasets.h b/tests/datasets/ShapeDatasets.h index 9114f514aa..a5f0863746 100644 --- a/tests/datasets/ShapeDatasets.h +++ b/tests/datasets/ShapeDatasets.h @@ -269,6 +269,7 @@ public: }), ShapeDataset("Shape1", { + TensorShape{ 1921U, 1U, 2U }, TensorShape{ 1921U, 1U, 2U }, TensorShape{ 641U, 1U, 2U, 3U }, TensorShape{ 1U, 127U, 25U }, @@ -345,7 +346,7 @@ public: SmallDeconvolutionShapes() : ShapeDataset("InputShape", { - TensorShape{ 4U, 3U, 3U, 2U }, + TensorShape{ 5U, 4U, 3U, 2U }, TensorShape{ 5U, 5U, 3U }, TensorShape{ 11U, 13U, 4U, 3U } }) diff --git a/tests/validation/CL/DeconvolutionLayer.cpp b/tests/validation/CL/DeconvolutionLayer.cpp index 59e85537e5..58a20268ef 100644 --- a/tests/validation/CL/DeconvolutionLayer.cpp +++ b/tests/validation/CL/DeconvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017, 2018 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -45,6 +45,9 @@ namespace { constexpr AbsoluteTolerance tolerance_fp32(0.001f); /**< Tolerance for floating point tests */ +const auto data4x4 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 3) + * framework::dataset::make("PadY", 0, 3) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 }); + const auto data3x3 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 2) * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 }); @@ -156,6 +159,9 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi // clang-format on // *INDENT-ON* +template +using CLDeconvolutionLayerFixture4x4 = DeconvolutionValidationFixture; + template using CLDeconvolutionLayerFixture3x3 = DeconvolutionValidationFixture; @@ -165,6 +171,15 @@ using CLDeconvolutionLayerFixture1x1 = DeconvolutionValidationFixture, framework::DatasetMode::ALL, combine(data4x4, framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} +TEST_SUITE_END() + TEST_SUITE(W3x3) FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture3x3, framework::DatasetMode::ALL, combine(data3x3, framework::dataset::make("DataType", DataType::F32))) diff --git a/tests/validation/NEON/DeconvolutionLayer.cpp b/tests/validation/NEON/DeconvolutionLayer.cpp index 9573784d86..566b75a827 100644 --- a/tests/validation/NEON/DeconvolutionLayer.cpp +++ b/tests/validation/NEON/DeconvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017, 2018 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -44,6 +44,9 @@ namespace { constexpr AbsoluteTolerance tolerance_fp32(0.001f); /**< Tolerance for floating point tests */ +const auto data4x4 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 3) + * framework::dataset::make("PadY", 0, 3) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 }); + const auto data3x3 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 2) * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 }); @@ -55,6 +58,9 @@ const auto data1x1 = datasets::SmallDeconvolutionShapes() * framework::dataset:: TEST_SUITE(NEON) TEST_SUITE(DeconvolutionLayer) +template +using NEDeconvolutionLayerFixture4x4 = DeconvolutionValidationFixture; + template using NEDeconvolutionLayerFixture3x3 = DeconvolutionValidationFixture; @@ -64,6 +70,15 @@ using NEDeconvolutionLayerFixture1x1 = DeconvolutionValidationFixture, framework::DatasetMode::ALL, combine(data4x4, framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp32); +} +TEST_SUITE_END() + TEST_SUITE(W3x3) FIXTURE_DATA_TEST_CASE(Run, NEDeconvolutionLayerFixture3x3, framework::DatasetMode::ALL, combine(data3x3, framework::dataset::make("DataType", DataType::F32))) diff --git a/tests/validation/reference/ConvolutionLayer.cpp b/tests/validation/reference/ConvolutionLayer.cpp index 567fac0f5e..b7ed2f56c0 100644 --- a/tests/validation/reference/ConvolutionLayer.cpp +++ b/tests/validation/reference/ConvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -58,8 +58,10 @@ void convolution3d(const SimpleTensor &in, const SimpleTensor &weights, co const TB *b_ptr = bias.data() + b_offset; T *out_ptr = out.data() + o_offset; - const int half_width_weights = width_weights / 2; - const int half_height_weights = height_weights / 2; + const int half_width_weights_start = width_weights / 2; + const int half_width_weights_end = ((width_weights % 2) == 0) ? (half_width_weights_start - 1) : half_width_weights_start; + const int half_height_weights_start = height_weights / 2; + const int half_height_weights_end = ((height_weights % 2) == 0) ? (half_height_weights_start - 1) : half_height_weights_start; // Reset accumulator T acc(0); @@ -71,15 +73,15 @@ void convolution3d(const SimpleTensor &in, const SimpleTensor &weights, co const int offset_slice_in = xi + yi * width_in + ifm * width_in * height_in; // Compute 2D convolution - for(int yk = -half_height_weights; yk <= half_height_weights; ++yk) + for(int yk = -half_height_weights_start; yk <= half_height_weights_end; ++yk) { - for(int xk = -half_width_weights; xk <= half_width_weights; ++xk) + for(int xk = -half_width_weights_start; xk <= half_width_weights_end; ++xk) { // Check if the pixel is out-of-bound if(is_valid_pixel(xi + xk, 0, width_in) && is_valid_pixel(yi + yk, 0, height_in)) { - const int idx = xk + half_width_weights; - const int idy = yk + half_height_weights; + const int idx = xk + half_width_weights_start; + const int idy = yk + half_height_weights_start; const T i_value = in_ptr[offset_slice_in + xk + yk * width_in]; const T w_value = w_ptr[idx + idy * width_weights + ifm * width_weights * height_weights]; @@ -106,8 +108,10 @@ void convolution3d(const SimpleTensor &in, const SimpleTensor &weights, co T *out_ptr = out.data() + o_offset; int fixed_point_position = in.fixed_point_position(); - const int half_width_weights = width_weights / 2; - const int half_height_weights = height_weights / 2; + const int half_width_weights_start = width_weights / 2; + const int half_width_weights_end = ((width_weights % 2) == 0) ? (half_width_weights_start - 1) : half_width_weights_start; + const int half_height_weights_start = height_weights / 2; + const int half_height_weights_end = ((height_weights % 2) == 0) ? (half_height_weights_start - 1) : half_height_weights_start; using namespace fixed_point_arithmetic; using promoted_type = fixed_point_arithmetic::traits::promote_t; @@ -122,15 +126,15 @@ void convolution3d(const SimpleTensor &in, const SimpleTensor &weights, co const int offset_slice_in = xi + yi * width_in + ifm * width_in * height_in; // Compute 2D convolution - for(int yk = -half_height_weights; yk <= half_height_weights; ++yk) + for(int yk = -half_height_weights_start; yk <= half_height_weights_end; ++yk) { - for(int xk = -half_width_weights; xk <= half_width_weights; ++xk) + for(int xk = -half_width_weights_start; xk <= half_width_weights_end; ++xk) { // Check if the pixel is out-of-bound if(is_valid_pixel(xi + xk, 0, width_in) && is_valid_pixel(yi + yk, 0, height_in)) { - const int idx = xk + half_width_weights; - const int idy = yk + half_height_weights; + const int idx = xk + half_width_weights_start; + const int idy = yk + half_height_weights_start; const fixed_point i_value(in_ptr[offset_slice_in + xk + yk * width_in], fixed_point_position, true); const fixed_point w_value(w_ptr[idx + idy * width_weights + ifm * width_weights * height_weights], fixed_point_position, true); @@ -173,8 +177,10 @@ void convolution3d(const SimpleTensor &in, const SimpleTensor const float multiplier = input_scale * weights_scale / output_scale; arm_compute::quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); - const int half_width_weights = width_weights / 2; - const int half_height_weights = height_weights / 2; + const int half_width_weights_start = width_weights / 2; + const int half_width_weights_end = ((width_weights % 2) == 0) ? (half_width_weights_start - 1) : half_width_weights_start; + const int half_height_weights_start = height_weights / 2; + const int half_height_weights_end = ((height_weights % 2) == 0) ? (half_height_weights_start - 1) : half_height_weights_start; // Reset accumulator int32_t acc(0); @@ -186,15 +192,15 @@ void convolution3d(const SimpleTensor &in, const SimpleTensor const int offset_slice_in = xi + yi * width_in + ifm * width_in * height_in; // Compute 2D convolution - for(int yk = -half_height_weights; yk <= half_height_weights; ++yk) + for(int yk = -half_height_weights_start; yk <= half_height_weights_end; ++yk) { - for(int xk = -half_width_weights; xk <= half_width_weights; ++xk) + for(int xk = -half_width_weights_start; xk <= half_width_weights_end; ++xk) { // Check if the pixel is out-of-bound if(is_valid_pixel(xi + xk, 0, width_in) && is_valid_pixel(yi + yk, 0, height_in)) { - const int idx = xk + half_width_weights; - const int idy = yk + half_height_weights; + const int idx = xk + half_width_weights_start; + const int idy = yk + half_height_weights_start; const uint8_t i_value = in_ptr[offset_slice_in + xk + yk * width_in]; const uint8_t w_value = w_ptr[idx + idy * width_weights + ifm * width_weights * height_weights]; @@ -233,17 +239,17 @@ SimpleTensor convolution_layer(const SimpleTensor &src, const SimpleTensor const int width_weights = weights.shape().x(); const int height_weights = weights.shape().y(); const int depth_weights = weights.shape().z(); - const int pad_left = std::min(static_cast(info.pad_left()), width_weights / 2); - const int pad_top = std::min(static_cast(info.pad_top()), height_weights / 2); - const int pad_right = std::min(static_cast(info.pad_right()), width_weights / 2); - const int pad_bottom = std::min(static_cast(info.pad_bottom()), height_weights / 2); + const int pad_left = info.pad_left(); + const int pad_top = info.pad_top(); + const int stride_xi = info.stride().first; + const int stride_yi = info.stride().second; + + auto output_wh = scaled_dimensions(width_in, height_in, width_weights, height_weights, info); const int start_xi = width_weights / 2 - pad_left; const int start_yi = height_weights / 2 - pad_top; - const int end_xi = width_in + pad_left - width_weights / 2 + pad_right - width_weights / 2; - const int end_yi = height_in + pad_top - height_weights / 2 + pad_bottom - height_weights / 2; - const int stride_xi = info.stride().first; - const int stride_yi = info.stride().second; + const int end_xi = output_wh.first * stride_xi; + const int end_yi = output_wh.second * stride_yi; const int num_batches = src.shape().total_size() / (width_in * height_in * depth_in); for(int r = 0; r < num_batches; ++r) diff --git a/tests/validation/reference/DeconvolutionLayer.cpp b/tests/validation/reference/DeconvolutionLayer.cpp index 0cf1087346..617f6908e4 100644 --- a/tests/validation/reference/DeconvolutionLayer.cpp +++ b/tests/validation/reference/DeconvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017, 2018 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * -- cgit v1.2.1