View source on GitHub |
Max pooling layer for 3D inputs (e.g.
tf.compat.v1.layers.max_pooling3d(
inputs, pool_size, strides, padding='valid',
data_format='channels_last', name=None
)
Migrate to TF2
This API is not compatible with eager execution or tf.function
.
Please refer to tf.layers section of the migration guide
to migrate a TensorFlow v1 model to Keras. The corresponding TensorFlow v2
layer is tf.keras.layers.MaxPooling3D
.
Structural Mapping to Native TF2
None of the supported arguments have changed name.
Before:
y = tf.compat.v1.layers.max_pooling3d(x, pool_size=2, strides=2)
After:
To migrate code using TF1 functional layers use the Keras Functional API:
x = tf.keras.Input((28, 28, 1))
y = tf.keras.layers.MaxPooling3D(pool_size=2, strides=2)(x)
model = tf.keras.Model(x, y)
Description
volumes).
Args | |
---|---|
inputs
|
The tensor over which to pool. Must have rank 5. |
pool_size
|
An integer or tuple/list of 3 integers: (pool_depth, pool_height, pool_width) specifying the size of the pooling window. Can be a single integer to specify the same value for all spatial dimensions. |
strides
|
An integer or tuple/list of 3 integers, specifying the strides of the pooling operation. Can be a single integer to specify the same value for all spatial dimensions. |
padding
|
A string. The padding method, either 'valid' or 'same'. Case-insensitive. |
data_format
|
A string. The ordering of the dimensions in the inputs.
channels_last (default) and channels_first are supported.
channels_last corresponds to inputs with shape (batch, depth, height,
width, channels) while channels_first corresponds to inputs with shape
(batch, channels, depth, height, width) .
|
name
|
A string, the name of the layer. |
Returns | |
---|---|
Output tensor. |
Raises | |
---|---|
ValueError
|
if eager execution is enabled. |