tf.raw

Represents a file asset to hermetically include in a SavedModel.

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Compat aliases for migration

tf.compat.v1.saved_model.Asset

tf.saved_model.Asset(
    path
)

A SavedModel can include arbitrary files, called assets, that are needed for its use. For example a vocabulary file used initialize a lookup table.

When a trackable object is exported via tf.saved_model.save(), all the Assets reachable from it are copied into the SavedModel assets directory. Upon loading, the assets and the serialized functions that depend on them will refer to the correct filepaths inside the SavedModel directory.

Example:

filename = tf.saved_model.Asset("file.txt")

@tf.function(input_signature=[])
def func():
  return tf.io.read_file(filename)

trackable_obj = tf.train.Checkpoint()
trackable_obj.func = func
trackable_obj.filename = filename
tf.saved_model.save(trackable_obj, "/tmp/saved_model")

# The created SavedModel is hermetic, it does not depend on
# the original file and can be moved to another path.
tf.io.gfile.remove("file.txt")
tf.io.gfile.rename("/tmp/saved_model", "/tmp/new_location")

reloaded_obj = tf.saved_model.load("/tmp/new_location")
print(reloaded_obj.func())

Attributes
`asset_path`	A 0-D `tf.string` tensor with path to the asset.

TensorFlow

tf.raw_ops / Overview

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Example:

Attributes

TensorFlow

tf

tf.audio

tf.autograph

tf.bitwise

tf.compat

tf.config

tf.data

tf.debugging

tf.distribute

tf.dtypes

tf.errors

tf.estimator

tf.experimental

tf.feature_column

tf.graph_util

tf.image

tf.initializers

tf.io

tf.keras

tf.linalg

tf.lite

tf.lookup

tf.losses

tf.math

tf.metrics

tf.nest

tf.nn

tf.optimizers

tf.quantization

tf.queue

tf.ragged

tf.random

tf.raw_ops

tf.saved_model

tf.sets

tf.signal

tf.sparse

tf.strings

tf.summary

tf.sysconfig

tf.test

tf.tpu

tf.train

tf.version

tf.xla

tf.raw_ops / Overview

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Example:

Attributes