tf.keras.layers.UpSampling3D
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Upsampling layer for 3D inputs.
Inherits From: Layer
tf.keras.layers.UpSampling3D(
size=(2, 2, 2), data_format=None, **kwargs
)
Repeats the 1st, 2nd and 3rd dimensions
of the data by size[0]
, size[1]
and size[2]
respectively.
Arguments |
size
|
Int, or tuple of 3 integers.
The upsampling factors for dim1, dim2 and dim3.
|
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) .
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".
|
5D tensor with shape:
- If
data_format
is "channels_last"
:
(batch, dim1, dim2, dim3, channels)
- If
data_format
is "channels_first"
:
(batch, channels, dim1, dim2, dim3)
Output shape:
5D tensor with shape:
- If
data_format
is "channels_last"
:
(batch, upsampled_dim1, upsampled_dim2, upsampled_dim3, channels)
- If
data_format
is "channels_first"
:
(batch, channels, upsampled_dim1, upsampled_dim2, upsampled_dim3)
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Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.keras.layers.UpSampling3D\n\n\u003cbr /\u003e\n\n|-----------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 2 version](/api_docs/python/tf/keras/layers/UpSampling3D) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/keras/layers/convolutional.py#L2000-L2069) |\n\nUpsampling layer for 3D inputs.\n\nInherits From: [`Layer`](../../../tf/keras/layers/Layer)\n\n#### View aliases\n\n\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.UpSampling3D`](/api_docs/python/tf/keras/layers/UpSampling3D), \\`tf.compat.v2.keras.layers.UpSampling3D\\`\n\n\u003cbr /\u003e\n\n tf.keras.layers.UpSampling3D(\n size=(2, 2, 2), data_format=None, **kwargs\n )\n\nRepeats the 1st, 2nd and 3rd dimensions\nof the data by `size[0]`, `size[1]` and `size[2]` respectively.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Arguments --------- ||\n|---------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `size` | Int, or tuple of 3 integers. The upsampling factors for dim1, dim2 and dim3. |\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, spatial_dim1, spatial_dim2, spatial_dim3, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, spatial_dim1, spatial_dim2, spatial_dim3)`. 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\n5D tensor with shape:\n\n- If `data_format` is `\"channels_last\"`: `(batch, dim1, dim2, dim3, channels)`\n- If `data_format` is `\"channels_first\"`: `(batch, channels, dim1, dim2, dim3)`\n\n#### Output shape:\n\n5D tensor with shape:\n\n- If `data_format` is `\"channels_last\"`: `(batch, upsampled_dim1, upsampled_dim2, upsampled_dim3, channels)`\n- If `data_format` is `\"channels_first\"`: `(batch, channels, upsampled_dim1, upsampled_dim2, upsampled_dim3)`"]]