TensorFlow 1 version | View source on GitHub |
Global max pooling operation for spatial data.
tf.keras.layers.GlobalMaxPool2D(
data_format=None, **kwargs
)
Examples:
input_shape = (2, 4, 5, 3)
x = tf.random.normal(input_shape)
y = tf.keras.layers.GlobalMaxPool2D()(x)
print(y.shape)
(2, 3)
Arguments | |
---|---|
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) .
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".
|
Input shape:
- If
data_format='channels_last'
: 4D tensor with shape(batch_size, rows, cols, channels)
. - If
data_format='channels_first'
: 4D tensor with shape(batch_size, channels, rows, cols)
.
Output shape:
2D tensor with shape (batch_size, channels)
.