Tensorflow打印网络结构与变量
发布于2019-10-07 01:01:10
在用tensorflow搭建好网络之后，如果可视化一下网络的结构与变量，会对网络结构有一个更直观的了解。
网络结构与变量的可视化方法如下：
在搭建好网络之后，如下代码可以打印出网络的变量
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variables = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES)
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for v
in variables:
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print(v)
活动的输出如下：
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<tf.Variable 'resnet_v2_152/conv1/weights:0' shape=(7, 7, 3, 64) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/conv1/biases:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_1/bottleneck_v2/preact/gamma:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_1/bottleneck_v2/preact/beta:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_1/bottleneck_v2/shortcut/weights:0' shape=(1, 1, 64, 256) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_1/bottleneck_v2/shortcut/biases:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_1/bottleneck_v2/conv1/weights:0' shape=(1, 1, 64, 64) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_1/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_1/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_1/bottleneck_v2/conv2/weights:0' shape=(3, 3, 64, 64) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_1/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_1/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_1/bottleneck_v2/conv3/weights:0' shape=(1, 1, 64, 256) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_1/bottleneck_v2/conv3/biases:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_2/bottleneck_v2/preact/gamma:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_2/bottleneck_v2/preact/beta:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_2/bottleneck_v2/conv1/weights:0' shape=(1, 1, 256, 64) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_2/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_2/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_2/bottleneck_v2/conv2/weights:0' shape=(3, 3, 64, 64) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_2/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_2/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_2/bottleneck_v2/conv3/weights:0' shape=(1, 1, 64, 256) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_2/bottleneck_v2/conv3/biases:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_3/bottleneck_v2/preact/gamma:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_3/bottleneck_v2/preact/beta:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_3/bottleneck_v2/conv1/weights:0' shape=(1, 1, 256, 64) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_3/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_3/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_3/bottleneck_v2/conv2/weights:0' shape=(3, 3, 64, 64) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_3/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_3/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(64,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_3/bottleneck_v2/conv3/weights:0' shape=(1, 1, 64, 256) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block1/unit_3/bottleneck_v2/conv3/biases:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_1/bottleneck_v2/preact/gamma:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_1/bottleneck_v2/preact/beta:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_1/bottleneck_v2/shortcut/weights:0' shape=(1, 1, 256, 512) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_1/bottleneck_v2/shortcut/biases:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_1/bottleneck_v2/conv1/weights:0' shape=(1, 1, 256, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_1/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_1/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_1/bottleneck_v2/conv2/weights:0' shape=(3, 3, 128, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_1/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_1/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_1/bottleneck_v2/conv3/weights:0' shape=(1, 1, 128, 512) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_1/bottleneck_v2/conv3/biases:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_2/bottleneck_v2/preact/gamma:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_2/bottleneck_v2/preact/beta:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_2/bottleneck_v2/conv1/weights:0' shape=(1, 1, 512, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_2/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_2/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_2/bottleneck_v2/conv2/weights:0' shape=(3, 3, 128, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_2/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_2/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_2/bottleneck_v2/conv3/weights:0' shape=(1, 1, 128, 512) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_2/bottleneck_v2/conv3/biases:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_3/bottleneck_v2/preact/gamma:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_3/bottleneck_v2/preact/beta:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_3/bottleneck_v2/conv1/weights:0' shape=(1, 1, 512, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_3/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_3/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_3/bottleneck_v2/conv2/weights:0' shape=(3, 3, 128, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_3/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_3/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_3/bottleneck_v2/conv3/weights:0' shape=(1, 1, 128, 512) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_3/bottleneck_v2/conv3/biases:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_4/bottleneck_v2/preact/gamma:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_4/bottleneck_v2/preact/beta:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_4/bottleneck_v2/conv1/weights:0' shape=(1, 1, 512, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_4/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_4/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_4/bottleneck_v2/conv2/weights:0' shape=(3, 3, 128, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_4/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_4/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_4/bottleneck_v2/conv3/weights:0' shape=(1, 1, 128, 512) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_4/bottleneck_v2/conv3/biases:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_5/bottleneck_v2/preact/gamma:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_5/bottleneck_v2/preact/beta:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_5/bottleneck_v2/conv1/weights:0' shape=(1, 1, 512, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_5/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_5/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_5/bottleneck_v2/conv2/weights:0' shape=(3, 3, 128, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_5/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_5/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_5/bottleneck_v2/conv3/weights:0' shape=(1, 1, 128, 512) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_5/bottleneck_v2/conv3/biases:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_6/bottleneck_v2/preact/gamma:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_6/bottleneck_v2/preact/beta:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_6/bottleneck_v2/conv1/weights:0' shape=(1, 1, 512, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_6/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_6/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_6/bottleneck_v2/conv2/weights:0' shape=(3, 3, 128, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_6/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_6/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_6/bottleneck_v2/conv3/weights:0' shape=(1, 1, 128, 512) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_6/bottleneck_v2/conv3/biases:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_7/bottleneck_v2/preact/gamma:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_7/bottleneck_v2/preact/beta:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_7/bottleneck_v2/conv1/weights:0' shape=(1, 1, 512, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_7/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_7/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_7/bottleneck_v2/conv2/weights:0' shape=(3, 3, 128, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_7/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_7/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_7/bottleneck_v2/conv3/weights:0' shape=(1, 1, 128, 512) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_7/bottleneck_v2/conv3/biases:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_8/bottleneck_v2/preact/gamma:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_8/bottleneck_v2/preact/beta:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_8/bottleneck_v2/conv1/weights:0' shape=(1, 1, 512, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_8/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_8/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_8/bottleneck_v2/conv2/weights:0' shape=(3, 3, 128, 128) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_8/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_8/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(128,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_8/bottleneck_v2/conv3/weights:0' shape=(1, 1, 128, 512) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block2/unit_8/bottleneck_v2/conv3/biases:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_1/bottleneck_v2/preact/gamma:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_1/bottleneck_v2/preact/beta:0' shape=(512,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_1/bottleneck_v2/shortcut/weights:0' shape=(1, 1, 512, 1024) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_1/bottleneck_v2/shortcut/biases:0' shape=(1024,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_1/bottleneck_v2/conv1/weights:0' shape=(1, 1, 512, 256) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_1/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_1/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_1/bottleneck_v2/conv2/weights:0' shape=(3, 3, 256, 256) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_1/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_1/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_1/bottleneck_v2/conv3/weights:0' shape=(1, 1, 256, 1024) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_1/bottleneck_v2/conv3/biases:0' shape=(1024,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_2/bottleneck_v2/preact/gamma:0' shape=(1024,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_2/bottleneck_v2/preact/beta:0' shape=(1024,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_2/bottleneck_v2/conv1/weights:0' shape=(1, 1, 1024, 256) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_2/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_2/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_2/bottleneck_v2/conv2/weights:0' shape=(3, 3, 256, 256) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_2/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_2/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_2/bottleneck_v2/conv3/weights:0' shape=(1, 1, 256, 1024) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_2/bottleneck_v2/conv3/biases:0' shape=(1024,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_3/bottleneck_v2/preact/gamma:0' shape=(1024,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_3/bottleneck_v2/preact/beta:0' shape=(1024,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_3/bottleneck_v2/conv1/weights:0' shape=(1, 1, 1024, 256) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_3/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_3/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_3/bottleneck_v2/conv2/weights:0' shape=(3, 3, 256, 256) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_3/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_3/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(256,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_3/bottleneck_v2/conv3/weights:0' shape=(1, 1, 256, 1024) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_3/bottleneck_v2/conv3/biases:0' shape=(1024,) dtype=float32_ref>
-
<tf.Variable 'resnet_v2_152/block3/unit_4/bottleneck_v2/preact/gamma:0' shape=(1024,) dtype=float32_ref>
-
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