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Exports a single train/eval/predict graph as a SavedModel. (deprecated)
tf.contrib.estimator.export_saved_model_for_mode(
estimator, export_dir_base, input_receiver_fn, assets_extra=None, as_text=False,
checkpoint_path=None, mode=model_fn_lib.ModeKeys.PREDICT
)
For a detailed guide, see Using SavedModel with Estimators.
Sample usage:
classifier = tf.estimator.LinearClassifier(
feature_columns=[age, language])
classifier.train(input_fn=input_fn, steps=1000)
feature_spec = {
'age': tf.placeholder(dtype=tf.int64),
'language': array_ops.placeholder(dtype=tf.string)
}
label_spec = tf.placeholder(dtype=dtypes.int64)
train_rcvr_fn = tf.contrib.estimator.build_raw_supervised_input_receiver_fn(
feature_spec, label_spec)
export_dir = tf.contrib.estimator.export_saved_model_for_mode(
classifier,
export_dir_base='my_model/',
input_receiver_fn=train_rcvr_fn,
mode=model_fn_lib.ModeKeys.TRAIN)
# export_dir is a timestamped directory with the SavedModel, which
# can be used for serving, analysis with TFMA, or directly loaded in.
with ops.Graph().as_default() as graph:
with session.Session(graph=graph) as sess:
loader.load(sess, [tag_constants.TRAINING], export_dir)
weights = graph.get_tensor_by_name(''linear/linear_model/age/weights')
...
This method is a wrapper for _export_all_saved_models, and wraps a raw input_receiver_fn in a dictionary to pass in to that function. See _export_all_saved_models for full docs.
See tf.contrib.estimator.export_saved_model_for_mode for the currently exposed version of this function.
Args | |
---|---|
estimator
|
an instance of tf.estimator.Estimator |
export_dir_base
|
A string containing a directory in which to create timestamped subdirectories containing exported SavedModels. |
input_receiver_fn
|
a function that takes no argument and
returns the appropriate subclass of InputReceiver .
|
assets_extra
|
A dict specifying how to populate the assets.extra directory
within the exported SavedModel, or None if no extra assets are needed.
|
as_text
|
whether to write the SavedModel proto in text format. |
checkpoint_path
|
The checkpoint path to export. If None (the default),
the most recent checkpoint found within the model directory is chosen.
|
mode
|
tf.estimator.ModeKeys value indicating with mode will be exported. |
Returns | |
---|---|
The string path to the exported directory. |
Raises | |
---|---|
ValueError
|
if input_receiver_fn is None, no export_outputs are provided, or no checkpoint can be found. |