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Ops returned from a model_fn.

THIS CLASS IS DEPRECATED. See contrib/learn/ for general migration instructions.

mode One of ModeKeys. Specifies if this training, evaluation or prediction.
predictions Predictions Tensor or dict of Tensor.
loss Training loss Tensor.
train_op Op for the training step.
eval_metric_ops Dict of metric results keyed by name. The values of the dict are the results of calling a metric function, such as Tensor.
output_alternatives a dict of {submodel_name: (problem_type, {tensor_name: Tensor})}, where submodel_name is a submodel identifier that should be consistent across the pipeline (here likely taken from the name of each Head, for models that use them), problem_type is a ProblemType, tensor_name is a symbolic name for an output Tensor possibly but not necessarily taken from PredictionKey, and Tensor is the corresponding output Tensor itself.
training_chief_hooks A list of SessionRunHook objects that will be run on the chief worker during training.
training_hooks A list of SessionRunHook objects that will be run on all workers during training.
scaffold A tf.compat.v1.train.Scaffold object that can be used to set initialization, saver, and more to be used in training.

ValueError If validation fails.












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Creates an equivalent EstimatorSpec.

default_serving_output_alternative_key Required for multiple heads. If you have multiple entries in output_alternatives dict (comparable to multiple heads), EstimatorSpec requires a default head that will be used if a Servo request does not explicitly mention which head to infer on. Pass the key of the output alternative here that you want to designate as default. A separate ExportOutpout for this default head will be added to the export_outputs dict with the special key saved_model.DEFAULT_SERVING_SIGNATURE_DEF_KEY, unless there is already an enry in output_alternatives with this special key.

Instance of EstimatorSpec that is equivalent to this ModelFnOps

ValueError If problem type is unknown.