From fedefc3a8d76b9dea5945414324427ef5a01835d Mon Sep 17 00:00:00 2001 From: Luca Foschiani Date: Mon, 17 Feb 2020 17:02:49 +0000 Subject: COMPMID-2765 Add support for QASYMM8_SIGNED in NEDeconvolutionLayer Signed-off-by: Luca Foschiani Change-Id: I8295fadee15311a9ab846aa24c031b82c0b799eb Signed-off-by: Michalis Spyrou Signed-off-by: Michele Di Giorgio Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2952 Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins Reviewed-by: Sheri Zhang --- .../NEON/functions/NEDeconvolutionLayer.cpp | 24 ++++++++++++++-------- 1 file changed, 15 insertions(+), 9 deletions(-) (limited to 'src/runtime/NEON/functions/NEDeconvolutionLayer.cpp') diff --git a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp index 0411b41220..06885d59e5 100644 --- a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -46,6 +46,7 @@ NEDeconvolutionLayer::NEDeconvolutionLayer(std::shared_ptr memor _permuted_input(), _permuted_weights(), _permuted_output(), + _flip_axis(), _is_nchw(false), _original_weights(nullptr), _input(nullptr), @@ -57,7 +58,7 @@ NEDeconvolutionLayer::NEDeconvolutionLayer(std::shared_ptr memor Status NEDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *output, const PadStrideInfo &info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16, DataType::QASYMM8); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16, DataType::QASYMM8, DataType::QASYMM8_SIGNED); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, input); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(weights, input); const unsigned int width_idx = get_data_layout_dimension_index(weights->data_layout(), DataLayoutDimension::WIDTH); @@ -122,6 +123,7 @@ void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, con _info = info; _is_prepared = false; _is_nchw = data_layout == DataLayout::NCHW; + _flip_axis.allocator()->init(TensorInfo(TensorShape(2U), 1, DataType::U32)); const unsigned int pad_left = info.pad_left(); const unsigned int pad_right = info.pad_right(); @@ -139,6 +141,7 @@ void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, con // Output auto initialization if not yet initialized auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->quantization_info()); + _flip_axis.allocator()->init(TensorInfo(TensorShape(2U), 1, DataType::U32)); _memory_group.manage(&_scaled_output); if(!_is_nchw) @@ -185,7 +188,7 @@ void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, con _weights_flipped.allocator()->init(*_permuted_weights.info()->clone()); _weights_flipped.info()->set_quantization_info(weights->info()->quantization_info()); - _flip_weights.configure(&_permuted_weights, &_weights_flipped); + _flip_weights.configure(&_permuted_weights, &_weights_flipped, &_flip_axis); // setup the function to convolve the upscaled output const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); @@ -230,13 +233,19 @@ void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, con _upsample_f.configure(input, &_scaled_output, upsample_info); _weights_flipped.allocator()->init(weights->info()->clone()->set_data_layout(data_layout)); - _flip_weights.configure(weights, &_weights_flipped); + _flip_weights.configure(weights, &_weights_flipped, &_flip_axis); // 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_flipped, bias, output, conv_info); } _scaled_output.allocator()->allocate(); + + // Setup flip axis data + _flip_axis.allocator()->allocate(); + auto axis_data = reinterpret_cast(_flip_axis.buffer()); + axis_data[0] = 0; + axis_data[1] = 1; } void NEDeconvolutionLayer::run() @@ -276,16 +285,13 @@ void NEDeconvolutionLayer::prepare() // Run weights flipping and mark original weights tensor as unused _weights_flipped.allocator()->allocate(); - NEScheduler::get().schedule(&_flip_weights, Window::DimZ); + _flip_weights.run(); _original_weights->mark_as_unused(); // Prepare convolution _conv_f.prepare(); - if(!_weights_flipped.is_used()) - { - _weights_flipped.allocator()->free(); - } + // Unused weights are already released in _conv_f if(!_is_nchw) { -- cgit v1.2.1