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tf.keras.layers.TFSMLayer

Reload a Keras model/layer that was saved via SavedModel / ExportArchive.

Inherits From: Layer, Operation

tf.keras.layers.TFSMLayer(
    filepath,
    call_endpoint='serve',
    call_training_endpoint=None,
    trainable=True,
    name=None,
    dtype=None
)

Arguments
`filepath`	`str` or `pathlib.Path` object. The path to the SavedModel.
`call_endpoint`	Name of the endpoint to use as the `call()` method of the reloaded layer. If the SavedModel was created via `model.export()`, then the default endpoint name is `'serve'`. In other cases it may be named `'serving_default'`.

Example:

model.export("path/to/artifact")
reloaded_layer = TFSMLayer("path/to/artifact")
outputs = reloaded_layer(inputs)

The reloaded object can be used like a regular Keras layer, and supports training/fine-tuning of its trainable weights. Note that the reloaded object retains none of the internal structure or custom methods of the original object -- it's a brand new layer created around the saved function.

Limitations:

Only call endpoints with a single inputs tensor argument (which may optionally be a dict/tuple/list of tensors) are supported. For endpoints with multiple separate input tensor arguments, consider subclassing TFSMLayer and implementing a call() method with a custom signature.
If you need training-time behavior to differ from inference-time behavior (i.e. if you need the reloaded object to support a training=True argument in __call__()), make sure that the training-time call function is saved as a standalone endpoint in the artifact, and provide its name to the TFSMLayer via the call_training_endpoint argument.

Attributes
`input`	Retrieves the input tensor(s) of a symbolic operation. Only returns the tensor(s) corresponding to the first time the operation was called.
`output`	Retrieves the output tensor(s) of a layer. Only returns the tensor(s) corresponding to the first time the operation was called.

Attributes

input

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

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

output

Retrieves the output tensor(s) of a layer.

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

Methods

`from_config`

View source

@classmethod
from_config(
    config
)

Creates a layer from its config.

This method is the reverse of get_config, capable of instantiating the same layer from the config dictionary. It does not handle layer connectivity (handled by Network), nor weights (handled by set_weights).

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

Returns
A layer instance.

`symbolic_call`