tf.keras.models.model_from

TensorFlow 1 version

View source on GitHub

Parses a yaml model configuration file and returns a model instance.

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.models.model_from_yaml

tf.keras.models.model_from_yaml(
    yaml_string, custom_objects=None
)

Usage:

model = tf.keras.Sequential([
    tf.keras.layers.Dense(5, input_shape=(3,)),
    tf.keras.layers.Softmax()])
try:
  import yaml
  config = model.to_yaml()
  loaded_model = tf.keras.models.model_from_yaml(config)
except ImportError:
  pass

Arguments
`yaml_string`	YAML string or open file encoding a model configuration.
`custom_objects`	Optional dictionary mapping names (strings) to custom classes or functions to be considered during deserialization.

Returns
A Keras model instance (uncompiled).

Raises
`ImportError`	if yaml module is not found.

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.keras / models / models.model_from_config

View aliases

Usage:

Arguments

Returns

Raises