The following things updated in this CL
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@@ -42,15 +42,15 @@ class InputLayer(base_layer.Layer):
or create a placeholder tensor (pass arguments `input_shape`, and
optionally, `dtype`).
- It is generally recommend to use the functional layer API via `Input`,
+ It is generally recommend to use the Keras Functional model via `Input`,
(which creates an `InputLayer`) without directly using `InputLayer`.
- When using InputLayer with Keras Sequential model, it can be skipped by
- moving the input_shape parameter to the first layer after the 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 same time.
+ 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:
```python
@@ -74,22 +74,22 @@ class InputLayer(base_layer.Layer):
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).
+ 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.
+ 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.
+ 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 RaggedTensors, see
- [this guide](https://www.tensorflow.org/guide/ragged_tensors).
- Default to False.
+ In this case, values of `None` in the `shape` argument represent
+ ragged dimensions. For more information about `tf.RaggedTensor`, see
+ [this guide](https://www.tensorflow.org/guide/ragged_tensor).
+ 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 must be `None`.
name: Optional name of the layer (string).
"""
