tf.keras.Function

Class that encapsulates a computation graph of Keras operations.

Inherits From: Operation

tf.keras.Function(
    inputs, outputs, name=None
)

You can use a Function to capture the computation graph linking some input tensors to some output tensors, and reapply the same computation on new inputs.

A Function is similar to a Functional Model, with the difference that it is stateless (it does not track state variables) and does not implement the Layer API.

Example:

input_1 = keras.KerasTensor(shape=(None, 2, 3))
input_2 = keras.KerasTensor(shape=(None, 2, 3))
x = input_1 + input_2
output = keras.ops.sigmoid(x)
fn = keras.Function(inputs=[input_1, input_2], outputs=output)

input_1_val = np.random.random((4, 2, 3))
input_2_val = np.random.random((4, 2, 3))
output_val = fn([input_1_val, input_2_val])

inputs KerasTensor instance or nested structured of KerasTensor instances.
outputs KerasTensor instance or nested structured of KerasTensor instances. They should be computable given only the values of inputs.
name String. The name of the function.

input Retrieves the input tensor(s) of a symbolic operation.

Only returns the tensor(s) corresponding to the first time the operation was called.

inputs Flat list of the symbolic inputs of the Function.
operations

output Retrieves the output tensor(s) of a layer.

Only returns the tensor(s) corresponding to the first time the operation was called.

outputs Flat list of the symbolic outputs of the Function.

Methods

call

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call(
    inputs
)

Computes output tensors for new inputs.

compute_output_shape

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compute_output_shape(
    input_shape
)

compute_output_spec

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compute_output_spec(
    inputs
)

from_config

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@classmethod
from_config(
    config
)

Creates an operation from its config.

This method is the reverse of get_config, capable of instantiating the same operation from the config dictionary.

if "dtype" in config and isinstance(config["dtype"], dict):
    policy = dtype_policies.deserialize(config["dtype"])

Args
config A Python dictionary, typically the output of get_config.

Returns
An operation instance.

get_config

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get_config()

Returns the config of the object.

An object config is a Python dictionary (serializable) containing the information needed to re-instantiate it.

quantized_call

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quantized_call(
    *args, **kwargs
)

rematerialized_call

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rematerialized_call(
    fn, *args, **kwargs
)

Enable rematerialization dynamically for an operation's call method.

Args
fn The original call or quantized_call method of an operation.

Returns
Rematerialized method.

symbolic_call

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symbolic_call(
    *args, **kwargs
)

__call__

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__call__(
    *args, **kwargs
)

Call self as a function.