diff options
Diffstat (limited to 'examples/graph_squeezenet_v1_1.cpp')
| -rw-r--r-- | examples/graph_squeezenet_v1_1.cpp | 15 |
1 files changed, 8 insertions, 7 deletions
diff --git a/examples/graph_squeezenet_v1_1.cpp b/examples/graph_squeezenet_v1_1.cpp index b43c8ffdad..f648b6337d 100644 --- a/examples/graph_squeezenet_v1_1.cpp +++ b/examples/graph_squeezenet_v1_1.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2019 ARM Limited. + * Copyright (c) 2018-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -66,8 +66,9 @@ public: std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(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; @@ -82,7 +83,7 @@ public: PadStrideInfo(2, 2, 0, 0)) .set_name("conv1") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("relu_conv1") - << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))).set_name("pool1") + << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, operation_layout, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))).set_name("pool1") << ConvolutionLayer( 1U, 1U, 16U, get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire2_squeeze1x1_w.npy", weights_layout), @@ -99,7 +100,7 @@ public: .set_name("fire3/squeeze1x1") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("fire3/relu_squeeze1x1"); graph << get_expand_fire_node(data_path, "fire3", weights_layout, 64U, 64U).set_name("fire3/concat"); - graph << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))).set_name("pool3") + graph << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, operation_layout, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))).set_name("pool3") << ConvolutionLayer( 1U, 1U, 32U, get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire4_squeeze1x1_w.npy", weights_layout), @@ -116,7 +117,7 @@ public: .set_name("fire5/squeeze1x1") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("fire5/relu_squeeze1x1"); graph << get_expand_fire_node(data_path, "fire5", weights_layout, 128U, 128U).set_name("fire5/concat"); - graph << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))).set_name("pool5") + graph << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, operation_layout, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))).set_name("pool5") << ConvolutionLayer( 1U, 1U, 48U, get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire6_squeeze1x1_w.npy", weights_layout), @@ -156,7 +157,7 @@ public: PadStrideInfo(1, 1, 0, 0)) .set_name("conv10") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("relu_conv10") - << PoolingLayer(PoolingLayerInfo(PoolingType::AVG)).set_name("pool10") + << PoolingLayer(PoolingLayerInfo(PoolingType::AVG, operation_layout)).set_name("pool10") << FlattenLayer().set_name("flatten") << SoftmaxLayer().set_name("prob") << OutputLayer(get_output_accessor(common_params, 5)); |