diff options
Diffstat (limited to 'tensorflow/python/layers/convolutional.py')
| -rw-r--r-- | tensorflow/python/layers/convolutional.py | 15 |
1 files changed, 8 insertions, 7 deletions
diff --git a/tensorflow/python/layers/convolutional.py b/tensorflow/python/layers/convolutional.py index 5967180f5b..3594ced259 100644 --- a/tensorflow/python/layers/convolutional.py +++ b/tensorflow/python/layers/convolutional.py @@ -741,7 +741,7 @@ class SeparableConv2D(Conv2D): filters: Integer, the dimensionality of the output space (i.e. the number of filters in the convolution). kernel_size: A tuple or list of 2 integers specifying the spatial - dimensions of of the filters. Can be a single integer to specify the same + dimensions of the filters. Can be a single integer to specify the same value for all spatial dimensions. strides: A tuple or list of 2 positive integers specifying the strides of the convolution. Can be a single integer to specify the same value for @@ -950,7 +950,7 @@ def separable_conv2d(inputs, filters: Integer, the dimensionality of the output space (i.e. the number of filters in the convolution). kernel_size: A tuple or list of 2 integers specifying the spatial - dimensions of of the filters. Can be a single integer to specify the same + dimensions of the filters. Can be a single integer to specify the same value for all spatial dimensions. strides: A tuple or list of 2 positive integers specifying the strides of the convolution. Can be a single integer to specify the same value for @@ -1033,7 +1033,7 @@ class Conv2DTranspose(Conv2D): filters: Integer, the dimensionality of the output space (i.e. the number of filters in the convolution). kernel_size: A tuple or list of 2 positive integers specifying the spatial - dimensions of of the filters. Can be a single integer to specify the same + dimensions of the filters. Can be a single integer to specify the same value for all spatial dimensions. strides: A tuple or list of 2 positive integers specifying the strides of the convolution. Can be a single integer to specify the same value for @@ -1233,7 +1233,7 @@ def conv2d_transpose(inputs, filters: Integer, the dimensionality of the output space (i.e. the number of filters in the convolution). kernel_size: A tuple or list of 2 positive integers specifying the spatial - dimensions of of the filters. Can be a single integer to specify the same + dimensions of the filters. Can be a single integer to specify the same value for all spatial dimensions. strides: A tuple or list of 2 positive integers specifying the strides of the convolution. Can be a single integer to specify the same value for @@ -1516,7 +1516,7 @@ def conv3d_transpose(inputs, filters: Integer, the dimensionality of the output space (i.e. the number of filters in the convolution). kernel_size: A tuple or list of 3 positive integers specifying the spatial - dimensions of of the filters. Can be a single integer to specify the same + dimensions of the filters. Can be a single integer to specify the same value for all spatial dimensions. strides: A tuple or list of 3 positive integers specifying the strides of the convolution. Can be a single integer to specify the same value for @@ -1525,8 +1525,9 @@ def conv3d_transpose(inputs, data_format: A string, one of `channels_last` (default) or `channels_first`. The ordering of the dimensions in the inputs. `channels_last` corresponds to inputs with shape - `(batch, height, width, channels)` while `channels_first` corresponds to - inputs with shape `(batch, channels, height, width)`. + `(batch, depth, height, width, channels)` while `channels_first` + corresponds to inputs with shape + `(batch, channels, depth, height, width)`. activation: Activation function. Set it to None to maintain a linear activation. use_bias: Boolean, whether the layer uses a bias. |