def load_module_spec(path): """Loads a ModuleSpec from a TF Hub service or the filesystem. Warning: Deprecated. This belongs to the hub.Module API and TF1 Hub format. For TF2, switch to plain SavedModels and hub.load(); see also hub.resolve(). THIS FUNCTION IS DEPRECATED. Args: path: string describing the location of a module. There are several supported path encoding schemes: a) A URL like "https://tfhub.dev/the/module/1" referring to tfhub.dev or another service implementing https://www.tensorflow.org/hub/hosting. b) A URL like "https://example.com/module.tar.gz" that points to a compressed tarball directly, as long as that web server ignores the query parameters added by https://www.tensorflow.org/hub/hosting. c) Any filesystem location of a module directory (e.g. /module_dir for a local filesystem). All filesystems implementations provided by Tensorflow are supported. d) Private name resolution schemes added by the maintainer of your local installation of the tensorflow_hub library (usually none). Returns: A ModuleSpec. Raises: ValueError: on unexpected values in the module spec. tf.errors.OpError: on file handling exceptions. """ path = registry.resolver(path) return registry.loader(path)
def load_module_spec(path): """Loads a ModuleSpec from the filesystem. Args: path: string describing the location of a module. There are several supported path encoding schemes: a) URL location specifying an archived module (e.g. http://domain/module.tgz) b) Any filesystem location of a module directory (e.g. /module_dir for a local filesystem). All filesystems implementations provided by Tensorflow are supported. Returns: A ModuleSpec. Raises: ValueError: on unexpected values in the module spec. tf.OpError: on file handling exceptions. """ path = registry.resolver(path) return registry.loader(path)
def load_module_spec(path): """Loads a ModuleSpec from the filesystem. DEPRECATION NOTE: This belongs to the hub.Module API and file format for TF1. For TF2, switch to plain SavedModels and hub.load(). Args: path: string describing the location of a module. There are several supported path encoding schemes: a) URL location specifying an archived module (e.g. http://domain/module.tgz) b) Any filesystem location of a module directory (e.g. /module_dir for a local filesystem). All filesystems implementations provided by Tensorflow are supported. Returns: A ModuleSpec. Raises: ValueError: on unexpected values in the module spec. tf.errors.OpError: on file handling exceptions. """ path = registry.resolver(path) return registry.loader(path)