tf.keras.layers.InputLayer
View source on GitHub |
Layer to be used as an entry point into a Network (a graph of layers).
tf.keras.layers.InputLayer( input_shape=None, batch_size=None, dtype=None, input_tensor=None, sparse=None, name=None, ragged=None, type_spec=None, **kwargs )
It can either wrap an existing tensor (pass an input_tensor
argument) or create a placeholder tensor (pass arguments input_shape
, and optionally, dtype
).
It is generally recommend to use the Keras Functional model via Input
, (which creates an InputLayer
) without directly using InputLayer
.
When using InputLayer
with the Keras Sequential model, it can be skipped by moving the input_shape
parameter to the first layer after the InputLayer
.
This class can create placeholders for tf.Tensors
, tf.SparseTensors
, and tf.RaggedTensors
by choosing sparse=True
or ragged=True
. Note that sparse
and ragged
can't be configured to True
at the same time. Usage:
# With explicit InputLayer. model = tf.keras.Sequential([ tf.keras.layers.InputLayer(input_shape=(4,)), tf.keras.layers.Dense(8)]) model.compile(tf.optimizers.RMSprop(0.001), loss='mse') model.fit(np.zeros((10, 4)), np.ones((10, 8))) # Without InputLayer and let the first layer to have the input_shape. # Keras will add a input for the model behind the scene. model = tf.keras.Sequential([ tf.keras.layers.Dense(8, input_shape=(4,))]) model.compile(tf.optimizers.RMSprop(0.001), loss='mse') model.fit(np.zeros((10, 4)), np.ones((10, 8)))
Args | |
---|---|
input_shape |
Shape tuple (not including the batch axis), or TensorShape instance (not including the batch axis). |
batch_size |
Optional input batch size (integer or None ). |
dtype |
Optional datatype of the input. When not provided, the Keras default float type will be used. |
input_tensor |
Optional tensor to use as layer input. If set, the layer will use the tf.TypeSpec of this tensor rather than creating a new placeholder tensor. |
sparse |
Boolean, whether the placeholder created is meant to be sparse. Default to False . |
ragged |
Boolean, whether the placeholder created is meant to be ragged. In this case, values of None in the shape argument represent ragged dimensions. For more information about tf.RaggedTensor , see this guide. Default to False . |
type_spec |
A tf.TypeSpec object to create Input from. This tf.TypeSpec represents the entire batch. When provided, all other args except name must be None . |
name |
Optional name of the layer (string). |
© 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/keras/layers/InputLayer