Configuration for the "eval" part for the train_and_evaluate call.
tf.estimator.EvalSpec(
input_fn, steps=100, name=None, hooks=None, exporters=None,
start_delay_secs=120, throttle_secs=600
)
Used in the notebooks
| Used in the guide |
Used in the tutorials |
|
|
|
EvalSpec combines details of evaluation of the trained model as well as its
export. Evaluation consists of computing metrics to judge the performance of
the trained model. Export writes out the trained model on to external
storage.
Args |
|---|
input_fn
|
A function that constructs the input data for evaluation. See
Premade Estimators
for more information. The function should construct and return one of
the following:
- A 'tf.data.Dataset' object: Outputs of
Dataset object must be a
tuple (features, labels) with same constraints as below.
- A tuple (features, labels): Where features is a
Tensor or a
dictionary of string feature name to Tensor and labels is a
Tensor or a dictionary of string label name to Tensor.
|
steps
|
Int. Positive number of steps for which to evaluate model. If
None, evaluates until input_fn raises an end-of-input exception. See
Estimator.evaluate for details.
|
name
|
String. Name of the evaluation if user needs to run multiple
evaluations on different data sets. Metrics for different evaluations
are saved in separate folders, and appear separately in tensorboard.
|
hooks
|
Iterable of tf.train.SessionRunHook objects to run during
evaluation.
|
exporters
|
Iterable of Exporters, or a single one, or None.
exporters will be invoked after each evaluation.
|
start_delay_secs
|
Int. Start evaluating after waiting for this many
seconds.
|
throttle_secs
|
Int. Do not re-evaluate unless the last evaluation was
started at least this many seconds ago. Of course, evaluation does not
occur if no new checkpoints are available, hence, this is the minimum.
|
Raises |
|---|
ValueError
|
If any of the input arguments is invalid.
|
TypeError
|
If any of the arguments is not of the expected type.
|
Attributes |
|---|
input_fn
|
|
steps
|
|
name
|
|
hooks
|
|
exporters
|
|
start_delay_secs
|
|
throttle_secs
|
|
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TensorFlow 1 version
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