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Diffstat (limited to 'examples/graph_inception_resnet_v1.cpp')
-rw-r--r--examples/graph_inception_resnet_v1.cpp15
1 files changed, 8 insertions, 7 deletions
diff --git a/examples/graph_inception_resnet_v1.cpp b/examples/graph_inception_resnet_v1.cpp
index 89e44edc33..599aa5c8ac 100644
--- a/examples/graph_inception_resnet_v1.cpp
+++ b/examples/graph_inception_resnet_v1.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -97,8 +97,9 @@ public:
std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(0.f, 1.f);
// Create input descriptor
- const TensorShape tensor_shape = permute_shape(TensorShape(image_width, image_height, 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(image_width, image_height, 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;
@@ -146,7 +147,7 @@ public:
.set_name("Conv2d_2b_3x3/BatchNorm")
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("Conv2d_2b_3x3/Relu")
// MaxPool_3a_3x3
- << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL), true)).set_name("MaxPool_3a_3x3/MaxPool")
+ << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, operation_layout, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL), true)).set_name("MaxPool_3a_3x3/MaxPool")
// Conv2d_3b_1x1
<< ConvolutionLayer(1U, 1U, 80U,
get_weights_accessor(data_path, "Conv2d_3b_1x1_weights.npy", weights_layout),
@@ -201,7 +202,7 @@ public:
block8_repeat(data_path, weights_layout, 1, 1.f, false);
// Logits tail
- graph << PoolingLayer(PoolingLayerInfo(PoolingType::AVG)).set_name("Logits/AvgPool_1a_8x8")
+ graph << PoolingLayer(PoolingLayerInfo(PoolingType::AVG, operation_layout)).set_name("Logits/AvgPool_1a_8x8")
<< FlattenLayer().set_name("Logits/Flatten")
<< FullyConnectedLayer(
128U,
@@ -592,7 +593,7 @@ private:
// Branch 2
SubStream i_c(graph);
- i_c << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0), true)).set_name("Mixed_6a/Branch_2/MaxPool_1a_3x3");
+ i_c << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, common_params.data_layout, PadStrideInfo(2, 2, 0, 0), true)).set_name("Mixed_6a/Branch_2/MaxPool_1a_3x3");
// Concatenate
graph << ConcatLayer(std::move(i_a), std::move(i_b), std::move(i_c)).set_name("Mixed_6a/concat");
@@ -695,7 +696,7 @@ private:
// Branch 3
SubStream i_d(graph);
- i_d << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0), true)).set_name("Mixed_7a/Branch_3/MaxPool_1a_3x3");
+ i_d << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, common_params.data_layout, PadStrideInfo(2, 2, 0, 0), true)).set_name("Mixed_7a/Branch_3/MaxPool_1a_3x3");
// Concatenate
graph << ConcatLayer(std::move(i_a), std::move(i_b), std::move(i_c), std::move(i_d)).set_name("Mixed_7a/concat");