diff options
author | giuros01 <giuseppe.rossini@arm.com> | 2019-08-23 14:27:30 +0100 |
---|---|---|
committer | Giuseppe Rossini <giuseppe.rossini@arm.com> | 2019-08-30 13:37:28 +0000 |
commit | 351bd137e48c5276963274ac741b172483e98d21 (patch) | |
tree | 3ede92537c406d24f948acc51c1e6c0fac011036 /examples | |
parent | ebe2e8ccc6f9504fdad95884a794be1e9f58803e (diff) | |
download | ComputeLibrary-351bd137e48c5276963274ac741b172483e98d21.tar.gz |
compmid-2573: Investigate FP16 Winograd reference implementations
Change-Id: I5a3e692c046a5ad28a676c03e3e51950c64cf503
Signed-off-by: giuros01 <giuseppe.rossini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1845
Reviewed-by: Pablo Marquez <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'examples')
-rw-r--r-- | examples/graph_inception_v3.cpp | 92 |
1 files changed, 46 insertions, 46 deletions
diff --git a/examples/graph_inception_v3.cpp b/examples/graph_inception_v3.cpp index bce093d0f5..1de6a5fad7 100644 --- a/examples/graph_inception_v3.cpp +++ b/examples/graph_inception_v3.cpp @@ -85,8 +85,8 @@ public: "/cnn_data/inceptionv3_model/Conv2d_1a_3x3_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, "/cnn_data/inceptionv3_model/Conv2d_1a_3x3_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), get_weights_accessor(data_path, - "/cnn_data/inceptionv3_model/Conv2d_1a_3x3_BatchNorm_beta.npy"), + nullptr, get_weights_accessor(data_path, + "/cnn_data/inceptionv3_model/Conv2d_1a_3x3_BatchNorm_beta.npy"), 0.001f) .set_name("Conv2d_1a_3x3/BatchNorm/batchnorm") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("Conv2d_1a_3x3/Relu") @@ -98,8 +98,8 @@ public: "/cnn_data/inceptionv3_model/Conv2d_2a_3x3_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, "/cnn_data/inceptionv3_model/Conv2d_2a_3x3_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), get_weights_accessor(data_path, - "/cnn_data/inceptionv3_model/Conv2d_2a_3x3_BatchNorm_beta.npy"), + nullptr, get_weights_accessor(data_path, + "/cnn_data/inceptionv3_model/Conv2d_2a_3x3_BatchNorm_beta.npy"), 0.001f) .set_name("Conv2d_2a_3x3/BatchNorm/batchnorm") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("Conv2d_2a_3x3/Relu") @@ -112,8 +112,8 @@ public: "/cnn_data/inceptionv3_model/Conv2d_2b_3x3_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, "/cnn_data/inceptionv3_model/Conv2d_2b_3x3_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), get_weights_accessor(data_path, - "/cnn_data/inceptionv3_model/Conv2d_2b_3x3_BatchNorm_beta.npy"), + nullptr, get_weights_accessor(data_path, + "/cnn_data/inceptionv3_model/Conv2d_2b_3x3_BatchNorm_beta.npy"), 0.001f) .set_name("Conv2d_2b_3x3/BatchNorm/batchnorm") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("Conv2d_2b_3x3/Relu") @@ -128,8 +128,8 @@ public: "/cnn_data/inceptionv3_model/Conv2d_3b_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, "/cnn_data/inceptionv3_model/Conv2d_3b_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), get_weights_accessor(data_path, - "/cnn_data/inceptionv3_model/Conv2d_3b_1x1_BatchNorm_beta.npy"), + nullptr, get_weights_accessor(data_path, + "/cnn_data/inceptionv3_model/Conv2d_3b_1x1_BatchNorm_beta.npy"), 0.001f) .set_name("Conv2d_3b_1x1/BatchNorm/batchnorm") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("Conv2d_3b_1x1/Relu") @@ -142,8 +142,8 @@ public: "/cnn_data/inceptionv3_model/Conv2d_4a_3x3_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, "/cnn_data/inceptionv3_model/Conv2d_4a_3x3_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), get_weights_accessor(data_path, - "/cnn_data/inceptionv3_model/Conv2d_4a_3x3_BatchNorm_beta.npy"), + nullptr, get_weights_accessor(data_path, + "/cnn_data/inceptionv3_model/Conv2d_4a_3x3_BatchNorm_beta.npy"), 0.001f) .set_name("Conv2d_4a_3x3/BatchNorm/batchnorm") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("Conv2d_4a_3x3/Relu") @@ -249,7 +249,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_0/Conv2d_0a_1x1/BatchNorm/batchnorm") @@ -265,7 +265,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv2d" + conv_id0 + "1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv2d" + conv_id0 + "1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv2d" + conv_id0 + "1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d" + conv_id0 + "1x1/BatchNorm/batchnorm") @@ -279,7 +279,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv" + conv_id1 + "5x5_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv" + conv_id1 + "5x5_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv" + conv_id1 + "5x5_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d" + conv_id1 + "5x5/BatchNorm/batchnorm") @@ -295,7 +295,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_2/Conv2d_0a_1x1/BatchNorm/batchnorm") @@ -309,7 +309,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_3x3_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_3x3_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_3x3_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_2/Conv2d_0b_3x3/BatchNorm/batchnorm") @@ -323,7 +323,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_3x3_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_3x3_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_3x3_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_2/Conv2d_0c_3x3/BatchNorm/batcnorm") @@ -340,7 +340,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_3/Conv2d_0b_1x1/BatchNorm/batchnorm") @@ -364,7 +364,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_1a_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_1a_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_1a_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_0/Conv2d_1a_1x1/BatchNorm/batchnorm") @@ -380,7 +380,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d_0a_1x1/BatchNorm/batchnorm") @@ -394,7 +394,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_3x3_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_3x3_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_3x3_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d_0b_3x3/BatchNorm/batchnorm") @@ -408,7 +408,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_1a_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_1a_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_1a_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d_1a_1x1/BatchNorm/batchnorm") @@ -437,7 +437,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_0/Conv2d_0a_1x1/BatchNorm/batchnorm") @@ -453,7 +453,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d_0a_1x1/BatchNorm/batchnorm") @@ -467,7 +467,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x7_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x7_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x7_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d_0b_1x7/BatchNorm/batchnorm") @@ -481,7 +481,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0c_7x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0c_7x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0c_7x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d_0c_7x1/BatchNorm/batchnorm") @@ -497,7 +497,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_2/Conv2d_0a_1x1/BatchNorm/batchnorm") @@ -511,7 +511,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_7x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_7x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_7x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_2/Conv2d_0b_7x1/BatchNorm/batchnorm") @@ -525,7 +525,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_1x7_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_1x7_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_1x7_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_2/Conv2d_0c_1x7/BatchNorm/batchnorm") @@ -539,7 +539,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0d_7x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0d_7x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0d_7x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_2/Conv2d_0d_7x1/BatchNorm/batchnorm") @@ -553,7 +553,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0e_1x7_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0e_1x7_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0e_1x7_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_2/Conv2d_0e_1x7/BatchNorm/batchnorm") @@ -570,7 +570,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_3/Conv2d_0b_1x1/BatchNorm/batchnorm") @@ -594,7 +594,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_0/Conv2d_0a_1x1/BatchNorm/batchnorm") @@ -608,7 +608,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_1a_3x3_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_1a_3x3_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_1a_3x3_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_0/Conv2d_1a_3x3/BatchNorm/batchnorm") @@ -624,7 +624,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d_0a_1x1/BatchNorm/batchnorm") @@ -638,7 +638,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x7_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x7_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x7_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d_0b_1x7/BatchNorm/batchnorm") @@ -652,7 +652,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0c_7x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0c_7x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0c_7x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d_0c_7x1/BatchNorm/batchnorm") @@ -666,7 +666,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_1a_3x3_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_1a_3x3_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_1a_3x3_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d_1a_3x3/BatchNorm/batchnorm") @@ -703,7 +703,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_0/Conv2d_0a_1x1/BatchNorm/batchnorm") @@ -719,7 +719,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d_0a_1x1/BatchNorm/batchnorm") @@ -735,7 +735,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x3_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x3_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x3_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d_0b_1x3/BatchNorm/batchnorm") @@ -751,7 +751,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_1_Conv2d" + conv_id + "3x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_1_Conv2d" + conv_id + "3x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_1_Conv2d" + conv_id + "3x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_1/Conv2d" + conv_id + "3x1/BatchNorm/batchnorm") @@ -770,7 +770,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_2/Conv2d_0a_1x1/BatchNorm/batchnorm") @@ -784,7 +784,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_3x3_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_3x3_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_3x3_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_2/Conv2d_0b_3x3/BatchNorm/batchnorm") @@ -800,7 +800,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_1x3_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_1x3_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_1x3_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_2/Conv2d_0c_1x3/BatchNorm/batchnorm") @@ -816,7 +816,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0d_3x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0d_3x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0d_3x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_2/Conv2d_0d_3x1/BatchNorm/batchnorm") @@ -836,7 +836,7 @@ private: << BatchNormalizationLayer( get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_moving_mean.npy"), get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_moving_variance.npy"), - get_random_accessor(1.f, 1.f), + nullptr, get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_beta.npy"), 0.001f) .set_name(param_path + "/Branch_3/Conv2d_0b_1x1/BatchNorm/batchnorm") |