TensorFlow 1 version
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View source on GitHub
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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 | |
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data_format
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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".
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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).
TensorFlow 1 version
View source on GitHub