tf.estimator.EstimatorSpec
Ops and objects returned from a model_fn
and passed to an Estimator
.
tf.estimator.EstimatorSpec(
mode,
predictions=None,
loss=None,
train_op=None,
eval_metric_ops=None,
export_outputs=None,
training_chief_hooks=None,
training_hooks=None,
scaffold=None,
evaluation_hooks=None,
prediction_hooks=None
)
EstimatorSpec
fully defines the model to be run by an Estimator
.
Args |
mode | A ModeKeys . Specifies if this is training, evaluation or prediction. |
predictions | Predictions Tensor or dict of Tensor . |
loss | Training loss Tensor . Must be either scalar, or with shape [1] . |
train_op | Op for the training step. |
eval_metric_ops | Dict of metric results keyed by name. The values of the dict can be one of the following: (1) instance of Metric class. (2) Results of calling a metric function, namely a (metric_tensor, update_op) tuple. metric_tensor should be evaluated without any impact on state (typically is a pure computation results based on variables.). For example, it should not trigger the update_op or requires any input fetching. |
export_outputs | Describes the output signatures to be exported to SavedModel and used during serving. A dict {name: output} where: - name: An arbitrary name for this output.
- output: an
ExportOutput object such as ClassificationOutput , RegressionOutput , or PredictOutput . Single-headed models only need to specify one entry in this dictionary. Multi-headed models should specify one entry for each head, one of which must be named using tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY . If no entry is provided, a default PredictOutput mapping to predictions will be created.
|
training_chief_hooks | Iterable of tf.train.SessionRunHook objects to run on the chief worker during training. |
training_hooks | Iterable of tf.train.SessionRunHook objects to run on all workers during training. |
scaffold | A tf.train.Scaffold object that can be used to set initialization, saver, and more to be used in training. |
evaluation_hooks | Iterable of tf.train.SessionRunHook objects to run during evaluation. |
prediction_hooks | Iterable of tf.train.SessionRunHook objects to run during predictions. |
Raises |
ValueError | If validation fails. |
TypeError | If any of the arguments is not the expected type. |
Attributes |
mode | A namedtuple alias for field number 0 |
predictions | A namedtuple alias for field number 1 |
loss | A namedtuple alias for field number 2 |
train_op | A namedtuple alias for field number 3 |
eval_metric_ops | A namedtuple alias for field number 4 |
export_outputs | A namedtuple alias for field number 5 |
training_chief_hooks | A namedtuple alias for field number 6 |
training_hooks | A namedtuple alias for field number 7 |
scaffold | A namedtuple alias for field number 8 |
evaluation_hooks | A namedtuple alias for field number 9 |
prediction_hooks | A namedtuple alias for field number 10 |