From https://github.com/ethereon/caffe-tensorflow
(input, kernel, biases, k_h, k_w, c_o, s_h, s_w, padding="VALID", group=1)
| 4 | |
| 5 | |
| 6 | def conv(input, kernel, biases, k_h, k_w, c_o, s_h, s_w, padding="VALID", group=1): |
| 7 | '''From https://github.com/ethereon/caffe-tensorflow |
| 8 | ''' |
| 9 | c_i = input.get_shape()[-1] |
| 10 | assert c_i % group == 0 |
| 11 | assert c_o % group == 0 |
| 12 | |
| 13 | def convolve(i, k): |
| 14 | return tf.nn.conv2d(i, k, [1, s_h, s_w, 1], padding=padding) |
| 15 | |
| 16 | if group == 1: |
| 17 | conv = convolve(input, kernel) |
| 18 | else: |
| 19 | input_groups = tf.split(input, group, 3) |
| 20 | kernel_groups = tf.split(kernel, group, 3) |
| 21 | output_groups = [convolve(i, k) for i, k in zip(input_groups, kernel_groups)] |
| 22 | conv = tf.concat(output_groups, 3) |
| 23 | return tf.reshape(tf.nn.bias_add(conv, biases), [-1] + conv.get_shape().as_list()[1:]) |
| 24 | |
| 25 | |
| 26 | def conv2d(x, name, num_features, kernel_size, stride, group): |