From 11fedda86532cf632b9a3ae4b0f57e85f2a7c4f4 Mon Sep 17 00:00:00 2001 From: Sang-Hoon Park Date: Wed, 15 Jan 2020 14:44:04 +0000 Subject: COMPMID-2985 add data_layout to PoolingLayerInfo - use data layout from PoolingLayerInfo if it's available - deprecate constructors without data_layout - (3RDPARTY_UPDATE) modify examples and test suites to give data layout Change-Id: Ie9ae8cc4837c339ff69a16a816110be704863c2d Signed-off-by: Sang-Hoon Park Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2603 Reviewed-by: Michele Di Giorgio Reviewed-by: Georgios Pinitas Reviewed-by: Gian Marco Iodice Tested-by: Arm Jenkins Comments-Addressed: Arm Jenkins --- examples/graph_alexnet.cpp | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) (limited to 'examples/graph_alexnet.cpp') diff --git a/examples/graph_alexnet.cpp b/examples/graph_alexnet.cpp index 79d02f6ba5..0adc6a8e93 100644 --- a/examples/graph_alexnet.cpp +++ b/examples/graph_alexnet.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -69,8 +69,9 @@ public: std::unique_ptr preprocessor = arm_compute::support::cpp14::make_unique(mean_rgb); // Create input descriptor - const TensorShape tensor_shape = permute_shape(TensorShape(227U, 227U, 3U, 1U), DataLayout::NCHW, common_params.data_layout); - TensorDescriptor input_descriptor = TensorDescriptor(tensor_shape, common_params.data_type).set_layout(common_params.data_layout); + const auto operation_layout = common_params.data_layout; + const TensorShape tensor_shape = permute_shape(TensorShape(227U, 227U, 3U, 1U), DataLayout::NCHW, operation_layout); + TensorDescriptor input_descriptor = TensorDescriptor(tensor_shape, common_params.data_type).set_layout(operation_layout); // Set weights trained layout const DataLayout weights_layout = DataLayout::NCHW; @@ -87,7 +88,7 @@ public: .set_name("conv1") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("relu1") << NormalizationLayer(NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f)).set_name("norm1") - << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0))).set_name("pool1") + << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, operation_layout, PadStrideInfo(2, 2, 0, 0))).set_name("pool1") // Layer 2 << ConvolutionLayer( 5U, 5U, 256U, @@ -97,7 +98,7 @@ public: .set_name("conv2") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("relu2") << NormalizationLayer(NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f)).set_name("norm2") - << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0))).set_name("pool2") + << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, operation_layout, PadStrideInfo(2, 2, 0, 0))).set_name("pool2") // Layer 3 << ConvolutionLayer( 3U, 3U, 384U, @@ -122,7 +123,7 @@ public: PadStrideInfo(1, 1, 1, 1), 2) .set_name("conv5") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("relu5") - << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0))).set_name("pool5") + << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, operation_layout, PadStrideInfo(2, 2, 0, 0))).set_name("pool5") // Layer 6 << FullyConnectedLayer( 4096U, -- cgit v1.2.1