Adds separable convolution block #19
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FloopCZ
reviewed
Nov 20, 2018
| raise ValueError('SeparableConvBlock only supports inputs with rank 4 \ | ||
| (i.e. batch_size, height, width, channels)') | ||
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| x = slim.separable_conv2d(x, num_outputs=self._channels, kernel_size=(self._kernel, self._kernel), |
Contributor
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(I have to admit that I would prefer tf.layers in new code, but the variable scopes would not work. :-/)
https://www.tensorflow.org/api_docs/python/tf/layers/separable_conv2d
| **kwargs) | ||
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| def _handle_parsed_args(self, channels: str, kernel: str, | ||
| __, stride: Union[str, int]) -> None: |
| **code**: ``(num_filters)sep(kernel_size)[s(stride)]`` | ||
| **examples**: ``64sep3``, ``64sep3s2``, ``64sep3-5s2`` |
Contributor
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Does 64sep3-5s2 actually work? 🙂
| self._channels, self._kernel, self._stride = int(channels), int(kernel), int(stride) | ||
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| def apply(self, x: tf.Tensor) -> tf.Tensor: | ||
| if len(self._extra_dim) >= 1: |
Contributor
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Why not check the length of the shape of x directly?
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| def inverse_code(self) -> str: | ||
| if self._stride > 1: | ||
| raise ValueError('Inverse code for conv block is not defined for stride `{}`'.format(self._stride)) |
blazekadam
approved these changes
Nov 21, 2018
| raise ValueError('SeparableConvBlock only supports inputs with rank 4 \ | ||
| (i.e. batch_size, height, width, channels)') | ||
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| x = slim.separable_conv2d(x, num_outputs=self._channels, kernel_size=(self._kernel, self._kernel), |
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