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)
