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authorGeorgios Pinitas <georgios.pinitas@arm.com>2018-08-28 13:32:02 +0100
committerAnthony Barbier <anthony.barbier@arm.com>2018-11-02 16:54:54 +0000
commit427bbbf939a37150fd6768c29c9753771806dab3 (patch)
tree9e0761046e2e0d0f960cffeef3fa8e9634ef3426 /examples/graph_inception_v3.cpp
parentea9e0dc18c408fecb6dc482b774bd900dd321610 (diff)
downloadComputeLibrary-427bbbf939a37150fd6768c29c9753771806dab3.tar.gz
COMPMID-1522: Add ElementWiseOperation node in the graph API
Change-Id: Icb428bf3b5d3634fdddc57562cce670776e7f7a3 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/145814 Tested-by: Jenkins <bsgcomp@arm.com> Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'examples/graph_inception_v3.cpp')
-rw-r--r--examples/graph_inception_v3.cpp24
1 files changed, 12 insertions, 12 deletions
diff --git a/examples/graph_inception_v3.cpp b/examples/graph_inception_v3.cpp
index 168a506c8f..80e771b135 100644
--- a/examples/graph_inception_v3.cpp
+++ b/examples/graph_inception_v3.cpp
@@ -230,7 +230,7 @@ private:
Stream graph;
private:
- BranchLayer get_inception_node_A(const std::string &data_path, std::string &&param_path, DataLayout weights_layout,
+ ConcatLayer get_inception_node_A(const std::string &data_path, std::string &&param_path, DataLayout weights_layout,
unsigned int a_filt,
std::tuple<unsigned int, unsigned int> b_filters,
std::tuple<unsigned int, unsigned int, unsigned int> c_filters,
@@ -355,10 +355,10 @@ private:
.set_name(param_path + "/Branch_3/Conv2d_0b_1x1/BatchNorm/batchnorm")
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name(param_path + "/Branch_3/Conv2d_0b_1x1/Relu");
- return BranchLayer(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_a), std::move(i_b), std::move(i_c), std::move(i_d));
+ return ConcatLayer(std::move(i_a), std::move(i_b), std::move(i_c), std::move(i_d));
}
- BranchLayer get_inception_node_B(const std::string &data_path, std::string &&param_path, DataLayout weights_layout,
+ ConcatLayer get_inception_node_B(const std::string &data_path, std::string &&param_path, DataLayout weights_layout,
unsigned int a_filt,
std::tuple<unsigned int, unsigned int, unsigned int> b_filters)
{
@@ -426,10 +426,10 @@ private:
SubStream i_c(graph);
i_c << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))).set_name(param_path + "/Branch_2/MaxPool_1a_3x3/MaxPool");
- return BranchLayer(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_a), std::move(i_b), std::move(i_c));
+ return ConcatLayer(std::move(i_a), std::move(i_b), std::move(i_c));
}
- BranchLayer get_inception_node_C(const std::string &data_path, std::string &&param_path, DataLayout weights_layout,
+ ConcatLayer get_inception_node_C(const std::string &data_path, std::string &&param_path, DataLayout weights_layout,
unsigned int a_filt,
std::tuple<unsigned int, unsigned int, unsigned int> b_filters,
std::tuple<unsigned int, unsigned int, unsigned int, unsigned int, unsigned int> c_filters,
@@ -585,10 +585,10 @@ private:
.set_name(param_path + "/Branch_3/Conv2d_0b_1x1/BatchNorm/batchnorm")
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name(param_path + "/Branch_3/Conv2d_0b_1x1/Relu");
- return BranchLayer(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_a), std::move(i_b), std::move(i_c), std::move(i_d));
+ return ConcatLayer(std::move(i_a), std::move(i_b), std::move(i_c), std::move(i_d));
}
- BranchLayer get_inception_node_D(const std::string &data_path, std::string &&param_path, DataLayout weights_layout,
+ ConcatLayer get_inception_node_D(const std::string &data_path, std::string &&param_path, DataLayout weights_layout,
std::tuple<unsigned int, unsigned int> a_filters,
std::tuple<unsigned int, unsigned int, unsigned int, unsigned int> b_filters)
{
@@ -684,10 +684,10 @@ private:
SubStream i_c(graph);
i_c << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))).set_name(param_path + "/Branch_2/MaxPool_1a_3x3/MaxPool");
- return BranchLayer(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_a), std::move(i_b), std::move(i_c));
+ return ConcatLayer(std::move(i_a), std::move(i_b), std::move(i_c));
}
- BranchLayer get_inception_node_E(const std::string &data_path, std::string &&param_path, DataLayout weights_layout,
+ ConcatLayer get_inception_node_E(const std::string &data_path, std::string &&param_path, DataLayout weights_layout,
unsigned int a_filt,
std::tuple<unsigned int, unsigned int, unsigned int> b_filters,
std::tuple<unsigned int, unsigned int, unsigned int, unsigned int> c_filters,
@@ -767,7 +767,7 @@ private:
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name(param_path + "/Branch_1/Conv2d" + conv_id + "3x1/Relu");
// Merge b1 and b2
- i_b << BranchLayer(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_b1), std::move(i_b2)).set_name(param_path + "/Branch_1/concat");
+ i_b << ConcatLayer(std::move(i_b1), std::move(i_b2)).set_name(param_path + "/Branch_1/concat");
SubStream i_c(graph);
i_c << ConvolutionLayer(
@@ -832,7 +832,7 @@ private:
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name(param_path + "/Branch_2/Conv2d_0d_3x1/Relu");
// Merge i_c1 and i_c2
- i_c << BranchLayer(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_c1), std::move(i_c2)).set_name(param_path + "/Branch_2/concat");
+ i_c << ConcatLayer(std::move(i_c1), std::move(i_c2)).set_name(param_path + "/Branch_2/concat");
SubStream i_d(graph);
i_d << PoolingLayer(PoolingLayerInfo(PoolingType::AVG, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL), true)).set_name(param_path + "/Branch_3/AvgPool_0a_3x3/AvgPool")
@@ -851,7 +851,7 @@ private:
.set_name(param_path + "/Branch_3/Conv2d_0b_1x1/BatchNorm/batchnorm")
<< ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name(param_path + "/Branch_3/Conv2d_0b_1x1/Relu");
- return BranchLayer(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_a), std::move(i_b), std::move(i_c), std::move(i_d));
+ return ConcatLayer(std::move(i_a), std::move(i_b), std::move(i_c), std::move(i_d));
}
};