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eickenbergeickenberg
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ENH add easy access to googlenet layer names
layers -> layer_names
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‎sklearn_theano/feature_extraction/caffe/googlenet.py‎

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@@ -9,6 +9,7 @@
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import os
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from ...utils import check_tensor
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from googlenet_class_labels import get_googlenet_class_label
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from googlenet_layer_names import get_googlenet_layer_names
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from sklearn.base import BaseEstimator, TransformerMixin
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import theano
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import numpy as np
@@ -117,6 +118,8 @@ class GoogLeNetTransformer(BaseEstimator, TransformerMixin):
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force_reshape currently only supports len(output_layers) == 1!
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"""
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layer_names = get_googlenet_layer_names()
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def __init__(self, output_layers=('loss3/classifier',),
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force_reshape=True, transpose_order=(0, 3, 1, 2)):
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self.output_layers = output_layers
@@ -183,6 +186,7 @@ class GoogLeNetClassifier(BaseEstimator):
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"""
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min_size = (224, 224)
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layer_names = get_googlenet_layer_names()
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def __init__(self, top_n=5, large_network=False, output_strings=True,
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transpose_order=(0, 3, 1, 2)):

‎sklearn_theano/feature_extraction/caffe/googlenet_layer_names.py‎

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_layer_names = [u'data',
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u'label_data_1_split',
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u'conv1/7x7_s2',
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u'conv1/relu_7x7',
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u'pool1/3x3_s2',
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u'pool1/norm1',
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u'conv2/3x3_reduce',
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u'conv2/relu_3x3_reduce',
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u'conv2/3x3',
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u'conv2/relu_3x3',
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u'conv2/norm2',
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u'pool2/3x3_s2',
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u'pool2/3x3_s2_pool2/3x3_s2_0_split',
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u'inception_3a/1x1',
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u'inception_3a/relu_1x1',
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u'inception_3a/3x3_reduce',
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u'inception_3a/relu_3x3_reduce',
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u'inception_3a/3x3',
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u'inception_3a/relu_3x3',
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u'inception_3a/5x5_reduce',
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u'inception_3a/relu_5x5_reduce',
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u'inception_3a/5x5',
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u'inception_3a/relu_5x5',
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u'inception_3a/pool',
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u'inception_3a/pool_proj',
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u'inception_3a/relu_pool_proj',
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u'inception_3a/output',
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u'inception_3a/output_inception_3a/output_0_split',
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u'inception_3b/1x1',
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u'inception_3b/relu_1x1',
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u'inception_3b/3x3_reduce',
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u'inception_3b/relu_3x3_reduce',
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u'inception_3b/3x3',
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u'inception_3b/relu_3x3',
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u'inception_3b/5x5_reduce',
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u'inception_3b/relu_5x5_reduce',
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u'inception_3b/5x5',
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u'inception_3b/relu_5x5',
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u'inception_3b/pool',
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u'inception_3b/pool_proj',
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u'inception_3b/relu_pool_proj',
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u'inception_3b/output',
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u'pool3/3x3_s2',
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u'pool3/3x3_s2_pool3/3x3_s2_0_split',
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u'inception_4a/1x1',
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u'inception_4a/relu_1x1',
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u'inception_4a/3x3_reduce',
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u'inception_4a/relu_3x3_reduce',
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u'inception_4a/3x3',
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u'inception_4a/relu_3x3',
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u'inception_4a/5x5_reduce',
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u'inception_4a/relu_5x5_reduce',
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u'inception_4a/5x5',
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u'inception_4a/relu_5x5',
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u'inception_4a/pool',
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u'inception_4a/pool_proj',
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u'inception_4a/relu_pool_proj',
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u'inception_4a/output',
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u'inception_4a/output_inception_4a/output_0_split',
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u'loss1/ave_pool',
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u'loss1/conv',
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u'loss1/relu_conv',
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u'loss1/fc',
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u'loss1/relu_fc',
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u'loss1/drop_fc',
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u'loss1/classifier',
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u'loss1/loss',
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u'inception_4b/1x1',
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u'inception_4b/relu_1x1',
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u'inception_4b/3x3_reduce',
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u'inception_4b/relu_3x3_reduce',
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u'inception_4b/3x3',
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u'inception_4b/relu_3x3',
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u'inception_4b/5x5_reduce',
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u'inception_4b/relu_5x5_reduce',
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u'inception_4b/5x5',
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u'inception_4b/relu_5x5',
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u'inception_4b/pool',
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u'inception_4b/pool_proj',
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u'inception_4b/relu_pool_proj',
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u'inception_4b/output',
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u'inception_4b/output_inception_4b/output_0_split',
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u'inception_4c/1x1',
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u'inception_4c/relu_1x1',
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u'inception_4c/3x3_reduce',
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u'inception_4c/relu_3x3_reduce',
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u'inception_4c/3x3',
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u'inception_4c/relu_3x3',
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u'inception_4c/5x5_reduce',
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u'inception_4c/relu_5x5_reduce',
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u'inception_4c/5x5',
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u'inception_4c/relu_5x5',
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u'inception_4c/pool',
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u'inception_4c/pool_proj',
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u'inception_4c/relu_pool_proj',
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u'inception_4c/output',
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u'inception_4c/output_inception_4c/output_0_split',
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u'inception_4d/1x1',
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u'inception_4d/relu_1x1',
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u'inception_4d/3x3_reduce',
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u'inception_4d/relu_3x3_reduce',
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u'inception_4d/3x3',
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u'inception_4d/relu_3x3',
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u'inception_4d/5x5_reduce',
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u'inception_4d/relu_5x5_reduce',
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u'inception_4d/5x5',
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u'inception_4d/relu_5x5',
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u'inception_4d/pool',
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u'inception_4d/pool_proj',
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u'inception_4d/relu_pool_proj',
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u'inception_4d/output',
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u'inception_4d/output_inception_4d/output_0_split',
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u'loss2/ave_pool',
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u'loss2/conv',
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u'loss2/relu_conv',
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u'loss2/fc',
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u'loss2/relu_fc',
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u'loss2/drop_fc',
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u'loss2/classifier',
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u'loss2/loss',
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u'inception_4e/1x1',
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u'inception_4e/relu_1x1',
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u'inception_4e/3x3_reduce',
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u'inception_4e/relu_3x3_reduce',
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u'inception_4e/3x3',
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u'inception_4e/relu_3x3',
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u'inception_4e/5x5_reduce',
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u'inception_4e/relu_5x5_reduce',
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u'inception_4e/5x5',
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u'inception_4e/relu_5x5',
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u'inception_4e/pool',
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u'inception_4e/pool_proj',
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u'inception_4e/relu_pool_proj',
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u'inception_4e/output',
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u'pool4/3x3_s2',
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u'pool4/3x3_s2_pool4/3x3_s2_0_split',
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u'inception_5a/1x1',
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u'inception_5a/relu_1x1',
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u'inception_5a/3x3_reduce',
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u'inception_5a/relu_3x3_reduce',
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u'inception_5a/3x3',
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u'inception_5a/relu_3x3',
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u'inception_5a/5x5_reduce',
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u'inception_5a/relu_5x5_reduce',
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u'inception_5a/5x5',
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u'inception_5a/relu_5x5',
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u'inception_5a/pool',
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u'inception_5a/pool_proj',
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u'inception_5a/relu_pool_proj',
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u'inception_5a/output',
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u'inception_5a/output_inception_5a/output_0_split',
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u'inception_5b/1x1',
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u'inception_5b/relu_1x1',
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u'inception_5b/3x3_reduce',
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u'inception_5b/relu_3x3_reduce',
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u'inception_5b/3x3',
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u'inception_5b/relu_3x3',
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u'inception_5b/5x5_reduce',
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u'inception_5b/relu_5x5_reduce',
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u'inception_5b/5x5',
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u'inception_5b/relu_5x5',
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u'inception_5b/pool',
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u'inception_5b/pool_proj',
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u'inception_5b/relu_pool_proj',
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u'inception_5b/output',
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u'pool5/7x7_s1',
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u'pool5/drop_7x7_s1',
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u'loss3/classifier',
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u'loss3/loss3']
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def get_googlenet_layer_names():
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return _layer_names
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