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Small update to the documentation of lambda layers.

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PiperOrigin-RevId: 355070948
Change-Id: I2f32fff3373ca331e00cc56d3a798994910cd31d
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Tomer Kaftan 2021-02-01 18:26:30 -08:00 committed by TensorFlower Gardener
parent 16e7f80686
commit 229cbce4ca
1 changed files with 6 additions and 4 deletions
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10
tensorflow/python/keras/layers/core.py
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@ -756,13 +756,15 @@ class RepeatVector(Layer):
class Lambda(Layer):
"""Wraps arbitrary expressions as a `Layer` object.
The `Lambda` layer exists so that arbitrary TensorFlow functions
can be used when constructing `Sequential` and Functional API
models. `Lambda` layers are best suited for simple operations or
quick experimentation. For more advanced use cases, follow
The `Lambda` layer exists so that arbitrary expressions can be used
as a `Layer` when constructing `Sequential`
and Functional API models. `Lambda` layers are best suited for simple
operations or quick experimentation. For more advanced use cases, follow
[this guide](https://www.tensorflow.org/guide/keras/custom_layers_and_models)
for subclassing `tf.keras.layers.Layer`.
WARNING: `tf.keras.layers.Lambda` layers have (de)serialization limitations!
The main reason to subclass `tf.keras.layers.Layer` instead of using a
`Lambda` layer is saving and inspecting a Model. `Lambda` layers
are saved by serializing the Python bytecode, which is fundamentally