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9 行
351 B
9 行
351 B
import tensorflow as tf
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import numpy as np
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sess = tf.Session()
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inputs = tf.placeholder(dtype=tf.float32, shape=(1, 300, 300, 3))
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net = tf.layers.Conv2D(filters=2, kernel_size=3)(inputs)
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net = tf.nn.softmax(net, axis=-1)
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sess.run(tf.global_variables_initializer())
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sess.run(net, feed_dict={inputs: np.zeros(shape=(1, 300, 300, 3), dtype=np.float32)})
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