tf.keras.layers.UpSampling2D | TensorFlow v2.16.1 (original) (raw)
tf.keras.layers.UpSampling2D
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Upsampling layer for 2D inputs.
Inherits From: Layer, Operation
tf.keras.layers.UpSampling2D(
size=(2, 2), data_format=None, interpolation='nearest', **kwargs
)
The implementation uses interpolative resizing, given the resize method (specified by the interpolation argument). Use interpolation=nearestto repeat the rows and columns of the data.
Example:
input_shape = (2, 2, 1, 3)
x = np.arange(np.prod(input_shape)).reshape(input_shape)
print(x)
[[[[ 0 1 2]]
[[ 3 4 5]]]
[[[ 6 7 8]]
[[ 9 10 11]]]]
y = keras.layers.UpSampling2D(size=(1, 2))(x)
print(y)
[[[[ 0 1 2]
[ 0 1 2]]
[[ 3 4 5]
[ 3 4 5]]]
[[[ 6 7 8]
[ 6 7 8]]
[[ 9 10 11]
[ 9 10 11]]]]
| Args | |
|---|---|
| size | Int, or tuple of 2 integers. The upsampling factors for rows and columns. |
| 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_size, height, width, channels) while "channels_first"corresponds to inputs with shape(batch_size, channels, height, width). When unspecified, usesimage_data_format value found in your Keras config file at~/.keras/keras.json (if exists) else "channels_last". Defaults to "channels_last". |
| interpolation | A string, one of "bicubic", "bilinear", "lanczos3","lanczos5", "nearest". |
| Input shape |
|---|
| 4D tensor with shape: If data_format is "channels_last":(batch_size, rows, cols, channels) If data_format is "channels_first":(batch_size, channels, rows, cols) |
| Output shape |
|---|
| 4D tensor with shape: If data_format is "channels_last":(batch_size, upsampled_rows, upsampled_cols, channels) If data_format is "channels_first":(batch_size, channels, upsampled_rows, upsampled_cols) |
| Attributes | |
|---|---|
| input | Retrieves the input tensor(s) of a symbolic operation.Only returns the tensor(s) corresponding to the _first time_the operation was called. |
| output | Retrieves the output tensor(s) of a layer.Only returns the tensor(s) corresponding to the _first time_the operation was called. |
Methods
from_config
@classmethod
from_config( config )
Creates a layer from its config.
This method is the reverse of get_config, capable of instantiating the same layer from the config dictionary. It does not handle layer connectivity (handled by Network), nor weights (handled by set_weights).
| Args | |
|---|---|
| config | A Python dictionary, typically the output of get_config. |
| Returns |
|---|
| A layer instance. |
symbolic_call
symbolic_call(
*args, **kwargs
)