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rename network again
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@ -21,7 +21,7 @@ def train():
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local_completion = tf.placeholder(tf.float32, [BATCH_SIZE, LOCAL_SIZE, LOCAL_SIZE, 3])
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local_completion = tf.placeholder(tf.float32, [BATCH_SIZE, LOCAL_SIZE, LOCAL_SIZE, 3])
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is_training = tf.placeholder(tf.bool, [])
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is_training = tf.placeholder(tf.bool, [])
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model = Network(x, mask, local_x, global_completion, local_completion, is_training, batch_size=BATCH_SIZE)
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model = Model(x, mask, local_x, global_completion, local_completion, is_training, batch_size=BATCH_SIZE)
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sess = tf.Session()
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sess = tf.Session()
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global_step = tf.Variable(0, name='global_step', trainable=False)
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global_step = tf.Variable(0, name='global_step', trainable=False)
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epoch = tf.Variable(0, name='epoch', trainable=False)
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epoch = tf.Variable(0, name='epoch', trainable=False)
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