Keras 3 API documentation
Models API Layers API The base Layer class Layer activations Layer weight initializers Layer weight regularizers Layer weight constraints Core layers Convolution layers Pooling layers Recurrent layers Preprocessing layers Normalization layers Regularization layers Attention layers Reshaping layers Merging layers Activation layers Backend-specific layers Callbacks API Ops API Optimizers Metrics Losses Data loading Built-in small datasets Keras Applications Mixed precision Multi-device distribution RNG API Rematerialization Utilities
Keras 2 API documentation
► Keras 3 API documentation / Layers API / Reshaping layers / Reshape layer

Reshape layer

[source]

Reshape class

keras.layers.Reshape(target_shape, **kwargs)

Layer that reshapes inputs into the given shape.

Arguments

  • target_shape: Target shape. Tuple of integers, does not include the samples dimension (batch size). One element of the target_shape can be -1 in which case the missing value is inferred from the size of the array and remaining dimensions.

Input shape

Arbitrary, but required to be compatible with target_shape.

Output shape

(batch_size, *target_shape)

Example

>>> x = keras.Input(shape=(12,))
>>> y = keras.layers.Reshape((3, 4))(x)
>>> y.shape
(None, 3, 4)

>>> # another example with shape inference using `-1` as dimension
>>> y = keras.layers.Reshape((-1, 2, 2))(x)
>>> y.shape
(None, 3, 2, 2)
Reshape layer
Reshape class