Add Input docstring

keras_core/layers/core/input_layer.py

@@ -84,6 +84,45 @@ def Input(
     name=None,
     tensor=None,
 ):
+    """Used to instantiate a Keras tensor.
+
+    A Keras tensor is a symbolic tensor-like object, which we augment with
+    certain attributes that allow us to build a Keras model just by knowing the
+    inputs and outputs of the model.
+
+    For instance, if `a`, `b` and `c` are Keras tensors,
+    it becomes possible to do:
+    `model = Model(input=[a, b], output=c)`
+
+    Args:
+        shape: A shape tuple (tuple of integers or `None` objects),
+            not including the batch size.
+            For instance, `shape=(32,)` indicates that the expected input
+            will be batches of 32-dimensional vectors. Elements of this tuple
+            can be `None`; `None` elements represent dimensions where the shape
+            is not known and may vary (e.g. sequence length).
+        batch_size: Optional static batch size (integer).
+        dtype: The data type expected by the input, as a string
+            (e.g. `"float32"`, `"int32"`...)
+        name: Optional name string for the layer.
+            Should be unique in a model (do not reuse the same name twice).
+            It will be autogenerated if it isn't provided.
+        tensor: Optional existing tensor to wrap into the `Input` layer.
+            If set, the layer will use this tensor rather
+            than creating a new placeholder tensor.
+
+    Returns:
+      A Keras tensor.
+
+    Example:
+
+    ```python
+    # This is a logistic regression in Keras
+    x = Input(shape=(32,))
+    y = Dense(16, activation='softmax')(x)
+    model = Model(x, y)
+    ```
+    """
     layer = InputLayer(
         shape=shape,
         batch_size=batch_size,