tf.keras.layers.GlobalMaxPool2D
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Global max pooling operation for spatial data.
Inherits From: Layer
, Module
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".
|
- 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)
.
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Last updated 2021-02-18 UTC.
[null,null,["Last updated 2021-02-18 UTC."],[],[],null,["# tf.keras.layers.GlobalMaxPool2D\n\n\u003cbr /\u003e\n\n|-----------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 1 version](/versions/r1.15/api_docs/python/tf/keras/layers/GlobalMaxPool2D) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.4.0/tensorflow/python/keras/layers/pooling.py#L925-L962) |\n\nGlobal max pooling operation for spatial data.\n\nInherits From: [`Layer`](../../../tf/keras/layers/Layer), [`Module`](../../../tf/Module)\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tf.keras.layers.GlobalMaxPooling2D`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/GlobalMaxPool2D)\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.keras.layers.GlobalMaxPool2D`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/GlobalMaxPool2D), [`tf.compat.v1.keras.layers.GlobalMaxPooling2D`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/GlobalMaxPool2D)\n\n\u003cbr /\u003e\n\n tf.keras.layers.GlobalMaxPool2D(\n data_format=None, **kwargs\n )\n\n#### Examples:\n\n input_shape = (2, 4, 5, 3)\n x = tf.random.normal(input_shape)\n y = tf.keras.layers.GlobalMaxPool2D()(x)\n print(y.shape)\n (2, 3)\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Arguments --------- ||\n|---------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `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\". |\n\n\u003cbr /\u003e\n\n#### Input shape:\n\n- If `data_format='channels_last'`: 4D tensor with shape `(batch_size, rows, cols, channels)`.\n- If `data_format='channels_first'`: 4D tensor with shape `(batch_size, channels, rows, cols)`.\n\n#### Output shape:\n\n2D tensor with shape `(batch_size, channels)`."]]