diff options
Diffstat (limited to 'examples/graph_resnet_v2_50.cpp')
| -rw-r--r-- | examples/graph_resnet_v2_50.cpp | 13 |
1 files changed, 7 insertions, 6 deletions
diff --git a/examples/graph_resnet_v2_50.cpp b/examples/graph_resnet_v2_50.cpp index e2325151bc..7d6b9aa3fd 100644 --- a/examples/graph_resnet_v2_50.cpp +++ b/examples/graph_resnet_v2_50.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2019 ARM Limited. + * Copyright (c) 2018-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -70,8 +70,9 @@ public: std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(); // Create input descriptor - const TensorShape tensor_shape = permute_shape(TensorShape(224U, 224U, 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(224U, 224U, 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; @@ -85,7 +86,7 @@ public: get_weights_accessor(data_path, "conv1_biases.npy", weights_layout), PadStrideInfo(2, 2, 3, 3)) .set_name("conv1/convolution") - << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 1, 0, 1, DimensionRoundingType::FLOOR))).set_name("pool1/MaxPool"); + << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, operation_layout, PadStrideInfo(2, 2, 0, 1, 0, 1, DimensionRoundingType::FLOOR))).set_name("pool1/MaxPool"); add_residual_block(data_path, "block1", weights_layout, 64, 3, 2); add_residual_block(data_path, "block2", weights_layout, 128, 4, 2); @@ -100,7 +101,7 @@ public: 0.000009999999747378752f) .set_name("postnorm/BatchNorm") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("postnorm/Relu") - << PoolingLayer(PoolingLayerInfo(PoolingType::AVG)).set_name("pool5") + << PoolingLayer(PoolingLayerInfo(PoolingType::AVG, operation_layout)).set_name("pool5") << ConvolutionLayer( 1U, 1U, 1001U, get_weights_accessor(data_path, "logits_weights.npy", weights_layout), @@ -174,7 +175,7 @@ private: { if(middle_stride != 1) { - shortcut << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 1, PadStrideInfo(middle_stride, middle_stride, 0, 0), true)).set_name(unit_name + "shortcut/MaxPool"); + shortcut << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 1, common_params.data_layout, PadStrideInfo(middle_stride, middle_stride, 0, 0), true)).set_name(unit_name + "shortcut/MaxPool"); } } else |