aboutsummaryrefslogtreecommitdiff
path: root/examples/graph_vgg19.cpp
diff options
context:
space:
mode:
Diffstat (limited to 'examples/graph_vgg19.cpp')
-rw-r--r--examples/graph_vgg19.cpp17
1 files changed, 9 insertions, 8 deletions
diff --git a/examples/graph_vgg19.cpp b/examples/graph_vgg19.cpp
index e3733d859c..f9f5c213d5 100644
--- a/examples/graph_vgg19.cpp
+++ b/examples/graph_vgg19.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -75,8 +75,9 @@ 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(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;
@@ -99,7 +100,7 @@ public:
PadStrideInfo(1, 1, 1, 1))
.set_name("conv1_2")
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv1_2/Relu")
- << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0))).set_name("pool1")
+ << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 2, operation_layout, PadStrideInfo(2, 2, 0, 0))).set_name("pool1")
// Layer 2
<< ConvolutionLayer(
3U, 3U, 128U,
@@ -115,7 +116,7 @@ public:
PadStrideInfo(1, 1, 1, 1))
.set_name("conv2_2")
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv2_2/Relu")
- << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0))).set_name("pool2")
+ << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 2, operation_layout, PadStrideInfo(2, 2, 0, 0))).set_name("pool2")
// Layer 3
<< ConvolutionLayer(
3U, 3U, 256U,
@@ -145,7 +146,7 @@ public:
PadStrideInfo(1, 1, 1, 1))
.set_name("conv3_4")
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv3_4/Relu")
- << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0))).set_name("pool3")
+ << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 2, operation_layout, PadStrideInfo(2, 2, 0, 0))).set_name("pool3")
// Layer 4
<< ConvolutionLayer(
3U, 3U, 512U,
@@ -175,7 +176,7 @@ public:
PadStrideInfo(1, 1, 1, 1))
.set_name("conv4_4")
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv4_4/Relu")
- << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0))).set_name("pool4")
+ << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 2, operation_layout, PadStrideInfo(2, 2, 0, 0))).set_name("pool4")
// Layer 5
<< ConvolutionLayer(
3U, 3U, 512U,
@@ -205,7 +206,7 @@ public:
PadStrideInfo(1, 1, 1, 1))
.set_name("conv5_4")
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv5_4/Relu")
- << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0))).set_name("pool5")
+ << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 2, operation_layout, PadStrideInfo(2, 2, 0, 0))).set_name("pool5")
// Layer 6
<< FullyConnectedLayer(
4096U,