/external/tensorflow/tensorflow/contrib/slim/python/slim/nets/ |
D | vgg.py | 102 [layers.conv2d, layers_lib.max_pool2d], 106 net = layers_lib.max_pool2d(net, [2, 2], scope='pool1') 108 net = layers_lib.max_pool2d(net, [2, 2], scope='pool2') 110 net = layers_lib.max_pool2d(net, [2, 2], scope='pool3') 112 net = layers_lib.max_pool2d(net, [2, 2], scope='pool4') 114 net = layers_lib.max_pool2d(net, [2, 2], scope='pool5') 167 [layers.conv2d, layers_lib.fully_connected, layers_lib.max_pool2d], 171 net = layers_lib.max_pool2d(net, [2, 2], scope='pool1') 173 net = layers_lib.max_pool2d(net, [2, 2], scope='pool2') 175 net = layers_lib.max_pool2d(net, [2, 2], scope='pool3') [all …]
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D | inception_v1.py | 65 [layers.conv2d, layers_lib.max_pool2d], stride=1, padding='SAME'): 72 net = layers_lib.max_pool2d(net, [3, 3], stride=2, scope=end_point) 87 net = layers_lib.max_pool2d(net, [3, 3], stride=2, scope=end_point) 105 branch_3 = layers_lib.max_pool2d( 127 branch_3 = layers_lib.max_pool2d( 137 net = layers_lib.max_pool2d(net, [3, 3], stride=2, scope=end_point) 155 branch_3 = layers_lib.max_pool2d( 177 branch_3 = layers_lib.max_pool2d( 199 branch_3 = layers_lib.max_pool2d( 221 branch_3 = layers_lib.max_pool2d( [all …]
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D | overfeat.py | 55 with arg_scope([layers_lib.max_pool2d], padding='VALID') as arg_sc: 96 [layers.conv2d, layers_lib.fully_connected, layers_lib.max_pool2d], 100 net = layers_lib.max_pool2d(net, [2, 2], scope='pool1') 102 net = layers_lib.max_pool2d(net, [2, 2], scope='pool2') 106 net = layers_lib.max_pool2d(net, [2, 2], scope='pool5')
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D | alexnet.py | 59 with arg_scope([layers_lib.max_pool2d], padding='VALID') as arg_sc: 99 [layers.conv2d, layers_lib.fully_connected, layers_lib.max_pool2d], 103 net = layers_lib.max_pool2d(net, [3, 3], 2, scope='pool1') 105 net = layers_lib.max_pool2d(net, [3, 3], 2, scope='pool2') 109 net = layers_lib.max_pool2d(net, [3, 3], 2, scope='pool5')
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D | inception_v2.py | 84 layers.conv2d, layers_lib.max_pool2d, layers_lib.avg_pool2d, 115 net = layers_lib.max_pool2d(net, [3, 3], scope=end_point, stride=2) 137 net = layers_lib.max_pool2d(net, [3, 3], scope=end_point, stride=2) 234 branch_2 = layers_lib.max_pool2d( 403 branch_2 = layers_lib.max_pool2d( 470 branch_3 = layers_lib.max_pool2d(net, [3, 3], scope='MaxPool_0a_3x3')
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D | inception_v3.py | 107 [layers.conv2d, layers_lib.max_pool2d, layers_lib.avg_pool2d], 131 net = layers_lib.max_pool2d(net, [3, 3], stride=2, scope=end_point) 149 net = layers_lib.max_pool2d(net, [3, 3], stride=2, scope=end_point) 157 [layers.conv2d, layers_lib.max_pool2d, layers_lib.avg_pool2d], 263 branch_2 = layers_lib.max_pool2d( 427 branch_2 = layers_lib.max_pool2d( 584 [layers.conv2d, layers_lib.max_pool2d, layers_lib.avg_pool2d],
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D | resnet_utils.py | 84 return layers.max_pool2d(inputs, [1, 1], stride=factor, scope=scope) 269 with arg_scope([layers.max_pool2d], padding='SAME') as arg_sc:
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D | resnet_v1.py | 206 net = layers_lib.max_pool2d(net, [3, 3], stride=2, scope='pool1')
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D | resnet_v2.py | 215 net = layers.max_pool2d(net, [3, 3], stride=2, scope='pool1')
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/external/tensorflow/tensorflow/contrib/receptive_field/python/util/ |
D | graph_compute_order_test.py | 47 l3 = slim.max_pool2d(l2, [3, 3], stride=2, scope='L3', padding='SAME')
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D | parse_layer_parameters_test.py | 49 l3 = slim.max_pool2d(l2, [3, 3], stride=2, scope='L3', padding='SAME')
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D | receptive_field_test.py | 82 l2 = slim.max_pool2d(l2_pad, [3, 3], stride=2, scope='L2', padding='VALID') 83 l3 = slim.max_pool2d(l2, [1, 1], stride=2, scope='L3', padding='VALID')
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/external/tensorflow/tensorflow/contrib/slim/ |
D | README.md | 216 MaxPool2D | [slim.max_pool2d](https://www.tensorflow.org/code/tensorflow/contrib/layers/python/laye… 232 net = slim.max_pool2d(net, [2, 2], scope='pool2') 241 net = slim.max_pool2d(net, [2, 2], scope='pool2') 248 net = slim.max_pool2d(net, [2, 2], scope='pool2') 395 net = slim.max_pool2d(net, [2, 2], scope='pool1') 397 net = slim.max_pool2d(net, [2, 2], scope='pool2') 399 net = slim.max_pool2d(net, [2, 2], scope='pool3') 401 net = slim.max_pool2d(net, [2, 2], scope='pool4') 403 net = slim.max_pool2d(net, [2, 2], scope='pool5')
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/external/tensorflow/tensorflow/contrib/specs/python/ |
D | specs_ops.py | 98 Mp = Fun(layers.max_pool2d)
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/external/tensorflow/tensorflow/python/layers/ |
D | pooling.py | 477 max_pool2d = max_pooling2d variable
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/external/tensorflow/tensorflow/python/ops/parallel_for/ |
D | gradients_test.py | 240 self.max_pool2d = tf_layers.MaxPooling2D( 256 y = self.max_pool2d(y) 258 y = self.max_pool2d(y)
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/external/tensorflow/tensorflow/contrib/layers/python/layers/ |
D | layers_test.py | 3036 _layers.max_pool2d(images, [3, 3], data_format='CHWN') 3041 output = _layers.max_pool2d(images, [3, 3]) 3048 output = _layers.max_pool2d(images, [3, 3], data_format='NCHW') 3054 output = _layers.max_pool2d(images, [3, 3], outputs_collections='outputs') 3062 output = _layers.max_pool2d(images, 3) 3069 output = _layers.max_pool2d(images, [3, 3], scope='pool1') 3075 output = _layers.max_pool2d(images, [3, 3], padding='SAME') 3081 output = _layers.max_pool2d( 3088 output = _layers.max_pool2d(images, [3, 3], stride=1, padding='SAME') 3094 output = _layers.max_pool2d(images, images.get_shape()[1:3], stride=1)
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D | layers.py | 2367 def max_pool2d(inputs, function
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/external/tensorflow/tensorflow/contrib/specs/ |
D | README.md | 30 - `Mp` = tf.contrib.layers.max_pool2d
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/external/tensorflow/tensorflow/tools/api/golden/v2/ |
D | tensorflow.nn.pbtxt | 216 name: "max_pool2d"
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/external/tensorflow/tensorflow/tools/api/golden/v1/ |
D | tensorflow.nn.pbtxt | 264 name: "max_pool2d"
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/external/tensorflow/tensorflow/python/ops/ |
D | nn_ops.py | 3747 def max_pool2d(input, ksize, strides, padding, data_format="NHWC", name=None): function
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