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January 18, 2017 23:21
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Deconvolution with tensorflow
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| import numpy as np | |
| import tensorflow as tf | |
| def unpool(input_images, argmax, output_shape, name='unpooling'): | |
| os = output_shape.as_list() | |
| output_sz = np.prod(os) | |
| b = os[0] | |
| output_hwc = np.prod(os[1:]) | |
| input_hwc = np.prod(argmax.get_shape().as_list()[1:]) | |
| offset = tf.tile(tf.reshape(tf.range(b, dtype=tf.int64), [b, 1]), [1, input_hwc]) * output_hwc | |
| reshaped_argmax = tf.reshape(argmax, [b, input_hwc]) | |
| indices = tf.reshape(reshaped_argmax + offset, [-1, 1]) | |
| updates = tf.reshape(input_images, [-1]) | |
| scatter = tf.scatter_nd(indices=indices, | |
| updates=updates, | |
| shape=tf.constant([output_sz], dtype=tf.int64)) | |
| return tf.reshape(scatter, output_shape, name=name) |
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