COMPMID-1621 Deconvolution wrong output calculation

Change-Id: Ida71312bcf6dbd854f2ab1efc65f74910c79e152
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/151510
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Michele DiGiorgio <michele.digiorgio@arm.com>

5 files changed, 189 insertions, 38 deletions

diff --git a/src/core/CPP/kernels/CPPFlipWeightsKernel.cpp b/src/core/CPP/kernels/CPPFlipWeightsKernel.cpp
new file mode 100644
index 0000000000..741218e4f7
--- /dev/null
+++ b/src/core/CPP/kernels/CPPFlipWeightsKernel.cpp
@@ -0,0 +1,106 @@
+/*
+ * Copyright (c) 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 "arm_compute/core/CPP/kernels/CPPFlipWeightsKernel.h"
+
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+
+#include <cstddef>
+#include <cstdint>
+
+using namespace arm_compute;
+
+CPPFlipWeightsKernel::CPPFlipWeightsKernel()
+    : _input(nullptr), _output(nullptr), _func(nullptr)
+{
+}
+
+template <typename T>
+void CPPFlipWeightsKernel::flip_weights(const Window &window_input, const Window &window)
+{
+    // Create iterators
+    Iterator in(_input, window_input);
+
+    Iterator out(_output, window);
+
+    const int kernel_size = _input->info()->dimension(0);
+
+    execute_window_loop(window_input, [&](const Coordinates & id)
+    {
+        *((reinterpret_cast<T *>(out.ptr()) + kernel_size * (kernel_size - id.y() - 1) + (kernel_size - id.x() - 1))) = *(reinterpret_cast<const T *>(in.ptr()));
+    },
+    in, out);
+}
+
+void CPPFlipWeightsKernel::configure(const ITensor *input, ITensor *output)
+{
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+
+    _input  = input;
+    _output = output;
+
+    // Configure kernel window
+    Window win = calculate_max_window(*input->info(), Steps());
+
+    // The CPPFlipWeightsKernel doesn't need padding so update_window_and_padding() can be skipped
+    Coordinates coord;
+    coord.set_num_dimensions(output->info()->num_dimensions());
+    output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape()));
+
+    ICPPKernel::configure(win);
+
+    switch(input->info()->data_type())
+    {
+        case DataType::F32:
+            _func = &CPPFlipWeightsKernel::flip_weights<float>;
+            break;
+        case DataType::F16:
+            _func = &CPPFlipWeightsKernel::flip_weights<half>;
+            break;
+        case DataType::QASYMM8:
+            _func = &CPPFlipWeightsKernel::flip_weights<uint8_t>;
+            break;
+        default:
+            ARM_COMPUTE_ERROR("Not supported");
+    }
+}
+
+void CPPFlipWeightsKernel::run(const Window &window, const ThreadInfo &info)
+{
+    ARM_COMPUTE_UNUSED(info);
+    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICPPKernel::window(), window);
+    ARM_COMPUTE_ERROR_ON(_func == nullptr);
+
+    Window out_window{ window };
+    out_window.set(Window::DimX, Window::Dimension(0, 0, 0));
+    out_window.set(Window::DimY, Window::Dimension(0, 0, 0));
+
+    (this->*_func)(window, out_window);
+}
diff --git a/src/core/Utils.cpp b/src/core/Utils.cpp
index 229579d8d9..a6a5771ec1 100644
--- a/src/core/Utils.cpp
+++ b/src/core/Utils.cpp
@@ -334,17 +334,14 @@ TensorShape arm_compute::deconvolution_output_shape(const std::pair<unsigned int
 
 const std::pair<unsigned int, unsigned int> arm_compute::deconvolution_output_dimensions(
     unsigned int in_width, unsigned int in_height, unsigned int kernel_width, unsigned int kernel_height, unsigned int padx, unsigned int pady,
-    unsigned int inner_border_right, unsigned int inner_border_top, unsigned int stride_x, unsigned int stride_y)
+    unsigned int stride_x, unsigned int stride_y)
 {
     ARM_COMPUTE_ERROR_ON(in_width < 1 || in_height < 1);
-    ARM_COMPUTE_ERROR_ON(((in_width - 1) * stride_x + kernel_width + inner_border_right) < 2 * padx);
-    ARM_COMPUTE_ERROR_ON(((in_height - 1) * stride_y + kernel_height + inner_border_top) < 2 * pady);
-    const int padx_deconv = (kernel_width - padx - 1);
-    const int pady_deconv = (kernel_height - pady - 1);
-    ARM_COMPUTE_ERROR_ON(padx_deconv < 0);
-    ARM_COMPUTE_ERROR_ON(pady_deconv < 0);
-    const int w = stride_x * (in_width - 1) + kernel_width + inner_border_right - 2 * padx_deconv;
-    const int h = stride_y * (in_height - 1) + kernel_height + inner_border_top - 2 * pady_deconv;
+    ARM_COMPUTE_ERROR_ON(((in_width - 1) * stride_x + kernel_width) < 2 * padx);
+    ARM_COMPUTE_ERROR_ON(((in_height - 1) * stride_y + kernel_height) < 2 * pady);
+    const int w = stride_x * (in_width - 1) + kernel_width - 2 * padx;
+    const int h = stride_y * (in_height - 1) + kernel_height - 2 * pady;
+
     return std::make_pair<unsigned int, unsigned int>(w, h);
 }
 
diff --git a/src/graph/nodes/DeconvolutionLayerNode.cpp b/src/graph/nodes/DeconvolutionLayerNode.cpp
index 9329ae3c23..e7ccffd04f 100644
--- a/src/graph/nodes/DeconvolutionLayerNode.cpp
+++ b/src/graph/nodes/DeconvolutionLayerNode.cpp
@@ -51,8 +51,7 @@ Size2D DeconvolutionLayerNode::inner_border() const
 
 TensorDescriptor DeconvolutionLayerNode::compute_output_descriptor(const TensorDescriptor &input_descriptor,
                                                                    const TensorDescriptor &weights_descriptor,
-                                                                   const PadStrideInfo    &info,
-                                                                   const Size2D           &inner_border)
+                                                                   const PadStrideInfo    &info)
 {
     unsigned int output_width  = 0;
     unsigned int output_height = 0;
@@ -65,7 +64,6 @@ TensorDescriptor DeconvolutionLayerNode::compute_output_descriptor(const TensorD
     std::tie(output_width, output_height) = deconvolution_output_dimensions(input_width, input_height,
                                                                             kernel_width, kernel_height,
                                                                             info.pad().first, info.pad().second,
-                                                                            inner_border.x(), inner_border.y(),
                                                                             info.stride().first, info.stride().second);
 
     TensorDescriptor output_descriptor = input_descriptor;
@@ -96,7 +94,7 @@ TensorDescriptor DeconvolutionLayerNode::configure_output(size_t idx) const
 
     ARM_COMPUTE_ERROR_ON(src == nullptr || weights == nullptr);
 
-    TensorDescriptor output_info = compute_output_descriptor(src->desc(), weights->desc(), _info, _inner_border);
+    TensorDescriptor output_info = compute_output_descriptor(src->desc(), weights->desc(), _info);
     return output_info;
 }
 
diff --git a/src/runtime/CL/functions/CLDeconvolutionLayer.cpp b/src/runtime/CL/functions/CLDeconvolutionLayer.cpp
index 3f5b8c92dd..26d44e9c96 100644
--- a/src/runtime/CL/functions/CLDeconvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLDeconvolutionLayer.cpp
@@ -27,6 +27,8 @@
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/core/Validate.h"
 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/runtime/CL/CLScheduler.h"
+#include "arm_compute/runtime/CPP/CPPScheduler.h"
 
 #include <memory>
 #include <tuple>
@@ -38,7 +40,10 @@ CLDeconvolutionLayer::CLDeconvolutionLayer(std::shared_ptr<IMemoryManager> memor
     : _memory_group(std::move(memory_manager)),
       _scale_f(),
       _conv_f(),
+      _flip_weights(),
       _scaled_output(),
+      _weights(),
+      _weights_flipped(),
       _is_prepared(false)
 {
 }
@@ -59,7 +64,7 @@ Status CLDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInf
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(inner_border_top > stride_y - 1, "inner_border_top must be smaller than stride_y");
 
     auto out_dims = deconvolution_output_dimensions(input->dimension(0), input->dimension(1), weights->dimension(0), weights->dimension(1),
-                                                    info.pad().first, info.pad().second, inner_border_right, inner_border_top, stride_x, stride_y);
+                                                    info.pad().first, info.pad().second, stride_x, stride_y);
 
     const TensorShape output_shape = deconvolution_output_shape(out_dims, input->tensor_shape(), weights->tensor_shape());
 
@@ -81,8 +86,9 @@ Status CLDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInf
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimY) != output_shape.y(), "Output's height is invalid.");
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimZ) != output_shape.z(), "Output's depth is invalid.");
 
-    TensorInfo scale_out_info(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_deconvolution_shape(*input, stride_x, stride_y, inner_border_right, inner_border_top,
-                                                                                                      info)));
+    TensorInfo scale_out_info(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_deconvolution_shape(*input, *weights, stride_x, stride_y, inner_border_right,
+                                                                                                      inner_border_top,
+                                                                                                      out_dims)));
     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));
@@ -91,7 +97,7 @@ Status CLDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInf
     return Status{};
 }
 
-void CLDeconvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &info,
+void CLDeconvolutionLayer::configure(ICLTensor *input, ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &info,
                                      unsigned int inner_border_right, unsigned int inner_border_top, const WeightsInfo &weights_info)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
@@ -99,8 +105,12 @@ void CLDeconvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights,
     const unsigned int stride_x = info.stride().first;
     const unsigned int stride_y = info.stride().second;
 
+    _weights = weights;
+    _weights_flipped.allocator()->init(TensorInfo(weights->info()->tensor_shape(), 1, weights->info()->data_type()));
+    _flip_weights.configure(weights, &_weights_flipped);
+
     auto out_dims = deconvolution_output_dimensions(input->info()->dimension(0), input->info()->dimension(1), weights->info()->dimension(0), weights->info()->dimension(1),
-                                                    info.pad().first, info.pad().second, inner_border_right, inner_border_top, stride_x, stride_y);
+                                                    info.pad().first, info.pad().second, stride_x, stride_y);
 
     const TensorShape output_shape = deconvolution_output_shape(out_dims, input->info()->tensor_shape(), weights->info()->tensor_shape());
 
@@ -113,22 +123,31 @@ void CLDeconvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights,
     _is_prepared = false;
 
     _memory_group.manage(&_scaled_output);
+    _memory_group.manage(&_weights_flipped);
 
-    // configure scale function
-    // Init and allocate intermediate tensor for output, same size as input but the first two axis are the same as the output tensor
-    TensorShape        scale_out_shape(input->info()->tensor_shape());
-    const unsigned int out_x = input->info()->dimension(0) + (input->info()->dimension(0) - 1) * (stride_x - 1) + inner_border_right + 2 * info.pad().first;
-    const unsigned int out_y = input->info()->dimension(1) + (input->info()->dimension(1) - 1) * (stride_y - 1) + inner_border_top + 2 * info.pad().second;
+    // Find the upsampled dimensions
+    unsigned int out_x = (input->info()->dimension(0) - 1) * stride_x + inner_border_right + 1;
+    unsigned int out_y = (input->info()->dimension(1) - 1) * stride_y + inner_border_top + 1;
+
+    // Find the padding needed for the convolution with stride 1 in order to match output shape
+    unsigned int padx = out_dims.first - (out_x - weights->info()->dimension(0) + 1);
+    unsigned int pady = out_dims.second - (out_y - weights->info()->dimension(1) + 1);
+    out_x += padx;
+    out_y += pady;
+
+    TensorShape scale_out_shape(input->info()->tensor_shape());
     scale_out_shape.set(0, out_x);
     scale_out_shape.set(1, out_y);
     TensorInfo scale_out_info(scale_out_shape, 1, input->info()->data_type(), input->info()->quantization_info());
     _scaled_output.allocator()->init(scale_out_info);
 
-    _scale_f.configure(input, &_scaled_output, BorderSize(inner_border_top, inner_border_right), info);
+    // configure scale function
+    const PadStrideInfo upsample_info(stride_x, stride_y, padx / 2, pady / 2);
+    _scale_f.configure(input, &_scaled_output, BorderSize(inner_border_top, inner_border_right), upsample_info);
 
     // 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, weights_info);
+    _conv_f.configure(&_scaled_output, &_weights_flipped, bias, output, conv_info, weights_info);
     _scaled_output.allocator()->allocate();
 }
 
@@ -148,7 +167,14 @@ void CLDeconvolutionLayer::prepare()
 {
     if(!_is_prepared)
     {
+        _weights_flipped.allocator()->allocate();
+        _weights_flipped.map(true);
+        _weights->map(CLScheduler::get().queue(), true);
+        CPPScheduler::get().schedule(&_flip_weights, Window::DimZ);
+        _weights_flipped.unmap();
+        _weights->unmap(CLScheduler::get().queue());
         _conv_f.prepare();
+
         _is_prepared = true;
     }
 }
diff --git a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp
index fda9f57499..6ca60c66a4 100644
--- a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp
+++ b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp
@@ -27,6 +27,7 @@
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/core/Validate.h"
 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/runtime/CPP/CPPScheduler.h"
 
 using namespace arm_compute;
 using namespace arm_compute::misc::shape_calculator;
@@ -35,7 +36,9 @@ NEDeconvolutionLayer::NEDeconvolutionLayer(std::shared_ptr<IMemoryManager> memor
     : _memory_group(std::move(memory_manager)),
       _conv_f(),
       _upsample_f(),
+      _flip_weights(),
       _scaled_output(),
+      _weights_flipped(),
       _input(nullptr),
       _info(),
       _inner_border(),
@@ -60,7 +63,7 @@ Status NEDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInf
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(inner_border_top > stride_y - 1, "inner_border_top must be smaller than stride_y");
 
     auto out_dims = deconvolution_output_dimensions(input->dimension(0), input->dimension(1), weights->dimension(0), weights->dimension(1),
-                                                    info.pad().first, info.pad().second, inner_border_right, inner_border_top, stride_x, stride_y);
+                                                    info.pad().first, info.pad().second, stride_x, stride_y);
 
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights, bias);
 
@@ -74,14 +77,14 @@ Status NEDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInf
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
 
         const TensorShape output_shape = deconvolution_output_shape(out_dims, input->tensor_shape(), weights->tensor_shape());
-
         ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimX) != output_shape.x(), "Output's width is invalid.");
         ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimY) != output_shape.y(), "Output's height is invalid.");
         ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimZ) != output_shape.z(), "Output's depth is invalid.");
     }
 
-    TensorInfo scale_out_info(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_deconvolution_shape(*input, stride_x, stride_y, inner_border_right, inner_border_top,
-                                                                                                      info)));
+    TensorInfo scale_out_info(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_deconvolution_shape(*input, *weights, stride_x, stride_y, inner_border_right,
+                                                                                                      inner_border_top,
+                                                                                                      out_dims)));
     const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL);
 
     for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i)
@@ -107,25 +110,44 @@ void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, con
     const unsigned int stride_x = info.stride().first;
     const unsigned int stride_y = info.stride().second;
 
+    _weights_flipped.allocator()->init(TensorInfo(weights->info()->tensor_shape(), 1, weights->info()->data_type()));
+    _flip_weights.configure(weights, &_weights_flipped);
+
+    auto out_dims = deconvolution_output_dimensions(input->info()->dimension(0), input->info()->dimension(1), weights->info()->dimension(0), weights->info()->dimension(1),
+                                                    info.pad().first, info.pad().second, stride_x, stride_y);
+
+    const TensorShape output_shape = deconvolution_output_shape(out_dims, input->info()->tensor_shape(), weights->info()->tensor_shape());
+    // Output auto initialization if not yet initialized
+    auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->quantization_info());
+
     // Perform validation step
     ARM_COMPUTE_ERROR_THROW_ON(NEDeconvolutionLayer::validate(input->info(), weights->info(), bias == nullptr ? nullptr : bias->info(), output->info(), info, inner_border_right, inner_border_top));
 
     _memory_group.manage(&_scaled_output);
 
-    // configure scale function
-    // Init and allocate intermmidiate tensor for output, same size as input but the first two axis are the same as the output tensor
-    const TensorInfo scale_out_info(compute_deconvolution_shape(*input->info(), stride_x, stride_y, inner_border_right, inner_border_top, info), 1, input->info()->data_type());
+    // Find the upsampled dimensions
+    unsigned int out_x = (input->info()->dimension(0) - 1) * stride_x + inner_border_right + 1;
+    unsigned int out_y = (input->info()->dimension(1) - 1) * stride_y + inner_border_top + 1;
+
+    // Find the padding needed for the convolution with stride 1 in order to match output shape
+    unsigned int padx = out_dims.first - (out_x - weights->info()->dimension(0) + 1);
+    unsigned int pady = out_dims.second - (out_y - weights->info()->dimension(1) + 1);
+    out_x += padx;
+    out_y += pady;
+
+    TensorShape scale_out_shape(input->info()->tensor_shape());
+    scale_out_shape.set(0, out_x);
+    scale_out_shape.set(1, out_y);
+    TensorInfo scale_out_info(scale_out_shape, 1, input->info()->data_type(), input->info()->quantization_info());
     _scaled_output.allocator()->init(scale_out_info);
 
+    const PadStrideInfo upsample_info(stride_x, stride_y, padx / 2, pady / 2);
+    _upsample_f.configure(input, &_scaled_output, upsample_info, inner_border_right, inner_border_top);
+
     // 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);
-
-    // Allocate auxiliary tensors
+    _conv_f.configure(&_scaled_output, &_weights_flipped, bias, output, conv_info);
     _scaled_output.allocator()->allocate();
-
-    // configure upsample function
-    _upsample_f.configure(input, &_scaled_output, info, inner_border_right, inner_border_top);
 }
 
 void NEDeconvolutionLayer::run()
@@ -144,6 +166,8 @@ void NEDeconvolutionLayer::prepare()
 {
     if(!_is_prepared)
     {
+        _weights_flipped.allocator()->allocate();
+        CPPScheduler::get().schedule(&_flip_weights, Window::DimZ);
         _conv_f.prepare();
         _is_prepared = true;
     }