在用tensorflow搭建好網絡之後，如果可視化一下網絡的結構與變量，會對網絡結構有一個更直觀的瞭解。
網絡結構與變量的可視化方法如下：
在搭建好網絡之後，如下代碼可以打印出網絡的變量
variables = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES)
for v in variables:
print(v)
活動的輸出如下：
<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>
<tf.Variable 'resnet_v2_152/block3/unit_4/bottleneck_v2/preact/beta:0' shape=(1024,) dtype=float32_ref>
<tf.Variable 'resnet_v2_152/block3/unit_4/bottleneck_v2/conv1/weights:0' shape=(1, 1, 1024, 256) dtype=float32_ref>
<tf.Variable 'resnet_v2_152/block3/unit_4/bottleneck_v2/conv1/BatchNorm/gamma:0' shape=(256,) dtype=float32_ref>
<tf.Variable 'resnet_v2_152/block3/unit_4/bottleneck_v2/conv1/BatchNorm/beta:0' shape=(256,) dtype=float32_ref>
<tf.Variable 'resnet_v2_152/block3/unit_4/bottleneck_v2/conv2/weights:0' shape=(3, 3, 256, 256) dtype=float32_ref>
<tf.Variable 'resnet_v2_152/block3/unit_4/bottleneck_v2/conv2/BatchNorm/gamma:0' shape=(256,) dtype=float32_ref>
<tf.Variable 'resnet_v2_152/block3/unit_4/bottleneck_v2/conv2/BatchNorm/beta:0' shape=(256,) dtype=float32_ref>
<tf.Variable 'resnet_v2_152/block3/unit_4/bottleneck_v2/conv3/weights:0' shape=(1, 1, 256, 1024) dtype=float32_ref>
<tf.Variable 'resnet_v2_152/block3/unit_4/bottleneck_v2/conv3/biases:0' shape=(1024,) dtype=float32_ref>
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