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  /external/tensorflow/tensorflow/contrib/slim/python/slim/nets/
vgg_test.py 39 logits, _ = vgg.vgg_a(inputs, num_classes)
40 self.assertEquals(logits.op.name, 'vgg_a/fc8/squeezed')
50 logits, _ = vgg.vgg_a(inputs, num_classes, spatial_squeeze=False)
51 self.assertEquals(logits.op.name, 'vgg_a/fc8/BiasAdd')
62 _, end_points = vgg.vgg_a(inputs, num_classes, is_training=is_training)
64 'vgg_a/conv1/conv1_1', 'vgg_a/pool1', 'vgg_a/conv2/conv2_1',
65 'vgg_a/pool2', 'vgg_a/conv3/conv3_1', 'vgg_a/conv3/conv3_2'
    [all...]
vgg.py 31 outputs, end_points = vgg.vgg_a(inputs)
36 @@vgg_a
74 def vgg_a(inputs, function
79 scope='vgg_a'):
98 with variable_scope.variable_scope(scope, 'vgg_a', [inputs]) as sc:
136 vgg_a.default_image_size = 224
  /external/tensorflow/tensorflow/contrib/slim/
nets.py 26 @@vgg_a
  /external/tensorflow/tensorflow/contrib/receptive_field/python/util/examples/
rf_benchmark.py 77 # - vgg: vgg_a (with 11 layers) and vgg_16 (version D).
78 _SUPPORTED_VGG_VARIANTS = ['vgg_a', 'vgg_16']
118 elif model_type == 'vgg_a':
119 _, end_points = vgg.vgg_a(images)

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