Update core.py
`channels_first` -> `'channels_first'`
`channels_last`, "channels_last" -> `'channels_last'`
data_format='channels_first' -> `data_format='channels_first'`
data_format='channels_last' -> `data_format='channels_last'`
@@ -188,19 +188,19 @@ class SpatialDropout2D(Dropout):
# Arguments
rate: float between 0 and 1. Fraction of the input units to drop.
- data_format: 'channels_first' or 'channels_last'.
- In 'channels_first' mode, the channels dimension
+ data_format: `'channels_first'` or `'channels_last'`.
+ In `'channels_first'` mode, the channels dimension
(the depth) is at index 1,
- in 'channels_last' mode is it at index 3.
+ in `'channels_last'` mode is it at index 3.
It defaults to the `image_data_format` value found in your
Keras config file at `~/.keras/keras.json`.
- If you never set it, then it will be "channels_last".
+ If you never set it, then it will be `'channels_last'`.
# Input shape
4D tensor with shape:
- `(samples, channels, rows, cols)` if data_format='channels_first'
+ `(samples, channels, rows, cols)` if `data_format='channels_first'`
or 4D tensor with shape:
- `(samples, rows, cols, channels)` if data_format='channels_last'.
+ `(samples, rows, cols, channels)` if `data_format='channels_last'`.
# Output shape
Same as input
@@ -238,18 +238,18 @@ class SpatialDropout3D(Dropout):
# Arguments
rate: float between 0 and 1. Fraction of the input units to drop.
- data_format: 'channels_first' or 'channels_last'.
- In 'channels_first' mode, the channels dimension (the depth)
- is at index 1, in 'channels_last' mode is it at index 4.
+ data_format: `'channels_first'` or `'channels_last'`.
+ In `'channels_first'` mode, the channels dimension (the depth)
+ is at index 1, in `'channels_last'` mode is it at index 4.
It defaults to the `image_data_format` value found in your
Keras config file at `~/.keras/keras.json`.
- If you never set it, then it will be "channels_last".
+ If you never set it, then it will be `'channels_last'`.
# Input shape
5D tensor with shape:
- `(samples, channels, dim1, dim2, dim3)` if data_format='channels_first'
+ `(samples, channels, dim1, dim2, dim3)` if `data_format='channels_first'`
or 5D tensor with shape:
- `(samples, dim1, dim2, dim3, channels)` if data_format='channels_last'.
+ `(samples, dim1, dim2, dim3, channels)` if `data_format='channels_last'`.
# Output shape
Same as input
@@ -464,17 +464,17 @@ class Flatten(Layer):
# Arguments
data_format: A string,
- one of `channels_last` (default) or `channels_first`.
+ one of `'channels_last'` (default) or `'channels_first'`.
The ordering of the dimensions in the inputs.
The purpose of this argument is to preserve weight
ordering when switching a model from one data format
to another.
- `channels_last` corresponds to inputs with shape
- `(batch, ..., channels)` while `channels_first` corresponds to
+ `'channels_last'` corresponds to inputs with shape
+ `(batch, ..., channels)` while `'channels_first'` corresponds to
inputs with shape `(batch, channels, ...)`.
It defaults to the `image_data_format` value found in your
Keras config file at `~/.keras/keras.json`.
- If you never set it, then it will be "channels_last".
+ If you never set it, then it will be `'channels_last'`.
# Example
