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authorGeorgios Pinitas <georgios.pinitas@arm.com>2018-04-17 13:23:26 +0100
committerAnthony Barbier <anthony.barbier@arm.com>2018-11-02 16:49:37 +0000
commit41c482d672ca971c9ff49c9aec32591fcffd7b1c (patch)
treea7773e7b07304cc3ef773f67e9d0a4efb8376a1a /examples/graph_squeezenet_v1_1.cpp
parentecb1c62635b04600de0d04e8fe054283847449a0 (diff)
downloadComputeLibrary-41c482d672ca971c9ff49c9aec32591fcffd7b1c.tar.gz
COMPMID-1042: Graph / Stream not working on x86
Avoid unspecified behavior in graph construction. This is fixed in C++17. Change-Id: I4ef45cb139bbd838103a9922441e32d2d16c33d2 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/127975 Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com> Tested-by: Jenkins <bsgcomp@arm.com> Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'examples/graph_squeezenet_v1_1.cpp')
-rw-r--r--examples/graph_squeezenet_v1_1.cpp48
1 files changed, 24 insertions, 24 deletions
diff --git a/examples/graph_squeezenet_v1_1.cpp b/examples/graph_squeezenet_v1_1.cpp
index 2bdb00d7c2..1696b7df43 100644
--- a/examples/graph_squeezenet_v1_1.cpp
+++ b/examples/graph_squeezenet_v1_1.cpp
@@ -110,60 +110,60 @@ public:
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire2_squeeze1x1_w.npy"),
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire2_squeeze1x1_b.npy"),
PadStrideInfo(1, 1, 0, 0))
- << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
- << get_expand_fire_node(data_path, "fire2", 64U, 64U)
- << ConvolutionLayer(
+ << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
+ graph << get_expand_fire_node(data_path, "fire2", 64U, 64U);
+ graph << ConvolutionLayer(
1U, 1U, 16U,
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire3_squeeze1x1_w.npy"),
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire3_squeeze1x1_b.npy"),
PadStrideInfo(1, 1, 0, 0))
- << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
- << get_expand_fire_node(data_path, "fire3", 64U, 64U)
- << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)))
+ << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
+ graph << get_expand_fire_node(data_path, "fire3", 64U, 64U);
+ graph << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)))
<< ConvolutionLayer(
1U, 1U, 32U,
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire4_squeeze1x1_w.npy"),
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire4_squeeze1x1_b.npy"),
PadStrideInfo(1, 1, 0, 0))
- << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
- << get_expand_fire_node(data_path, "fire4", 128U, 128U)
- << ConvolutionLayer(
+ << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
+ graph << get_expand_fire_node(data_path, "fire4", 128U, 128U);
+ graph << ConvolutionLayer(
1U, 1U, 32U,
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire5_squeeze1x1_w.npy"),
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire5_squeeze1x1_b.npy"),
PadStrideInfo(1, 1, 0, 0))
- << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
- << get_expand_fire_node(data_path, "fire5", 128U, 128U)
- << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)))
+ << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
+ graph << get_expand_fire_node(data_path, "fire5", 128U, 128U);
+ graph << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)))
<< ConvolutionLayer(
1U, 1U, 48U,
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire6_squeeze1x1_w.npy"),
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire6_squeeze1x1_b.npy"),
PadStrideInfo(1, 1, 0, 0))
- << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
- << get_expand_fire_node(data_path, "fire6", 192U, 192U)
- << ConvolutionLayer(
+ << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
+ graph << get_expand_fire_node(data_path, "fire6", 192U, 192U);
+ graph << ConvolutionLayer(
1U, 1U, 48U,
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire7_squeeze1x1_w.npy"),
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire7_squeeze1x1_b.npy"),
PadStrideInfo(1, 1, 0, 0))
- << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
- << get_expand_fire_node(data_path, "fire7", 192U, 192U)
- << ConvolutionLayer(
+ << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
+ graph << get_expand_fire_node(data_path, "fire7", 192U, 192U);
+ graph << ConvolutionLayer(
1U, 1U, 64U,
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire8_squeeze1x1_w.npy"),
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire8_squeeze1x1_b.npy"),
PadStrideInfo(1, 1, 0, 0))
- << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
- << get_expand_fire_node(data_path, "fire8", 256U, 256U)
- << ConvolutionLayer(
+ << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
+ graph << get_expand_fire_node(data_path, "fire8", 256U, 256U);
+ graph << ConvolutionLayer(
1U, 1U, 64U,
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire9_squeeze1x1_w.npy"),
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire9_squeeze1x1_b.npy"),
PadStrideInfo(1, 1, 0, 0))
- << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
- << get_expand_fire_node(data_path, "fire9", 256U, 256U)
- << ConvolutionLayer(
+ << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
+ graph << get_expand_fire_node(data_path, "fire9", 256U, 256U);
+ graph << ConvolutionLayer(
1U, 1U, 1000U,
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/conv10_w.npy"),
get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/conv10_b.npy"),