{ }
View source on GitHub |
Used to instantiate a Keras tensor.
tf.keras.Input(
shape=None,
batch_size=None,
dtype=None,
sparse=None,
batch_shape=None,
name=None,
tensor=None
)
Used in the notebooks
Used in the guide | Used in the tutorials |
---|---|
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)
Returns | |
---|---|
A Keras tensor. |
Example:
# This is a logistic regression in Keras
x = Input(shape=(32,))
y = Dense(16, activation='softmax')(x)
model = Model(x, y)