def export(self, export_dir, signature_fn=None, input_fn=None, default_batch_size=1, exports_to_keep=None): """Exports inference graph into given dir. Args: export_dir: A string containing a directory to write the exported graph and checkpoints. signature_fn: Function that returns a default signature and a named signature map, given `Tensor` of `Example` strings, `dict` of `Tensor`s for features and `Tensor` or `dict` of `Tensor`s for predictions. input_fn: Function that given `Tensor` of `Example` strings, parses it into features that are then passed to the model. default_batch_size: Default batch size of the `Example` placeholder. exports_to_keep: Number of exports to keep. """ # pylint: disable=protected-access export._export_estimator(estimator=self, export_dir=export_dir, signature_fn=signature_fn, input_fn=input_fn, default_batch_size=default_batch_size, exports_to_keep=exports_to_keep)
def export( self, export_dir, input_fn=export._default_input_fn, # pylint: disable=protected-access input_feature_key=None, use_deprecated_input_fn=True, signature_fn=None, prediction_key=None, default_batch_size=1, exports_to_keep=None): """Exports inference graph into given dir. Args: export_dir: A string containing a directory to write the exported graph and checkpoints. input_fn: If `use_deprecated_input_fn` is true, then a function that given `Tensor` of `Example` strings, parses it into features that are then passed to the model. Otherwise, a function that takes no argument and returns a tuple of (features, targets), where features is a dict of string key to `Tensor` and targets is a `Tensor` that's currently not used (and so can be `None`). input_feature_key: Only used if `use_deprecated_input_fn` is false. String key into the features dict returned by `input_fn` that corresponds to the raw `Example` strings `Tensor` that the exported model will take as input. use_deprecated_input_fn: Determines the signature format of `input_fn`. signature_fn: Function that returns a default signature and a named signature map, given `Tensor` of `Example` strings, `dict` of `Tensor`s for features and `Tensor` or `dict` of `Tensor`s for predictions. prediction_key: The key for a tensor in the `predictions` dict (output from the `model_fn`) to use as the `predictions` input to the `signature_fn`. Optional. If `None`, predictions will pass to `signature_fn` without filtering. default_batch_size: Default batch size of the `Example` placeholder. exports_to_keep: Number of exports to keep. """ # pylint: disable=protected-access export._export_estimator( estimator=self, export_dir=export_dir, signature_fn=signature_fn, prediction_key=prediction_key, input_fn=input_fn, input_feature_key=input_feature_key, use_deprecated_input_fn=use_deprecated_input_fn, default_batch_size=default_batch_size, exports_to_keep=exports_to_keep)
def export(self, export_dir, input_fn=export._default_input_fn, # pylint: disable=protected-access input_feature_key=None, use_deprecated_input_fn=True, signature_fn=None, prediction_key=None, default_batch_size=1, exports_to_keep=None): """Exports inference graph into given dir. Args: export_dir: A string containing a directory to write the exported graph and checkpoints. input_fn: If `use_deprecated_input_fn` is true, then a function that given `Tensor` of `Example` strings, parses it into features that are then passed to the model. Otherwise, a function that takes no argument and returns a tuple of (features, targets), where features is a dict of string key to `Tensor` and targets is a `Tensor` that's currently not used (and so can be `None`). input_feature_key: Only used if `use_deprecated_input_fn` is false. String key into the features dict returned by `input_fn` that corresponds to the raw `Example` strings `Tensor` that the exported model will take as input. use_deprecated_input_fn: Determines the signature format of `input_fn`. signature_fn: Function that returns a default signature and a named signature map, given `Tensor` of `Example` strings, `dict` of `Tensor`s for features and `Tensor` or `dict` of `Tensor`s for predictions. prediction_key: The key for a tensor in the `predictions` dict (output from the `model_fn`) to use as the `predictions` input to the `signature_fn`. Optional. If `None`, predictions will pass to `signature_fn` without filtering. default_batch_size: Default batch size of the `Example` placeholder. exports_to_keep: Number of exports to keep. """ # pylint: disable=protected-access export._export_estimator(estimator=self, export_dir=export_dir, signature_fn=signature_fn, prediction_key=prediction_key, input_fn=input_fn, input_feature_key=input_feature_key, use_deprecated_input_fn=use_deprecated_input_fn, default_batch_size=default_batch_size, exports_to_keep=exports_to_keep)
def export(self, export_dir, signature_fn=None, input_fn=None, default_batch_size=1, exports_to_keep=None): """Exports inference graph into given dir. Args: export_dir: A string containing a directory to write the exported graph and checkpoints. signature_fn: Function that returns a default signature and a named signature map, given `Tensor` of `Example` strings, `dict` of `Tensor`s for features and `Tensor` or `dict` of `Tensor`s for predictions. input_fn: Function that given `Tensor` of `Example` strings, parses it into features that are then passed to the model. default_batch_size: Default batch size of the `Example` placeholder. exports_to_keep: Number of exports to keep. """ # pylint: disable=protected-access export._export_estimator(estimator=self, export_dir=export_dir, signature_fn=signature_fn, input_fn=input_fn, default_batch_size=default_batch_size, exports_to_keep=exports_to_keep)