Global Max pooling operation for 3D data.
Inherits From: Layer
, Module
tf.keras.layers.GlobalMaxPooling3D(
data_format=None, keepdims=False, **kwargs
)
Args |
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, spatial_dim1, spatial_dim2, spatial_dim3, channels)
while channels_first corresponds to inputs with shape
(batch, channels, spatial_dim1, spatial_dim2, spatial_dim3) .
When unspecified, uses
image_data_format value found in your Keras config file at
~/.keras/keras.json (if exists) else 'channels_last'.
Defaults to 'channels_last'.
|
keepdims
|
A boolean, whether to keep the spatial dimensions or not.
If keepdims is False (default), the rank of the tensor is reduced
for spatial dimensions.
If keepdims is True , the spatial dimensions are retained with
length 1.
The behavior is the same as for tf.reduce_max or np.max .
|
|
- If
data_format='channels_last' :
5D tensor with shape:
(batch_size, spatial_dim1, spatial_dim2, spatial_dim3, channels)
- If
data_format='channels_first' :
5D tensor with shape:
(batch_size, channels, spatial_dim1, spatial_dim2, spatial_dim3)
|
Output shape |
- If
keepdims =False:
2D tensor with shape (batch_size, channels) .
- If
keepdims =True:
- If
data_format='channels_last' :
5D tensor with shape (batch_size, 1, 1, 1, channels)
- If
data_format='channels_first' :
5D tensor with shape (batch_size, channels, 1, 1, 1)
|