Module: tf.contrib.estimator

Defined in tensorflow/contrib/estimator/

Experimental utilities re:tf.estimator.*.


class BaselineEstimator: An estimator that can establish a simple baseline.

class DNNEstimator: An estimator for TensorFlow DNN models with user-specified head.

class DNNLinearCombinedEstimator: An estimator for TensorFlow Linear and DNN joined models with custom head.

class InMemoryEvaluatorHook: Hook to run evaluation in training without a checkpoint.

class LinearEstimator: An estimator for TensorFlow linear models with user-specified head.

class RNNClassifier: A classifier for TensorFlow RNN models.

class RNNEstimator: An Estimator for TensorFlow RNN models with user-specified head.

class SavedModelEstimator: Create an Estimator from a SavedModel.

class TowerOptimizer: Gathers gradients from all towers and reduces them in the last one.


add_metrics(...): Creates a new tf.estimator.Estimator which has given metrics.

binary_classification_head(...): Creates a _Head for single label binary classification.

boosted_trees_classifier_train_in_memory(...): Trains a boosted tree classifier with in memory dataset.

boosted_trees_regressor_train_in_memory(...): Trains a boosted tree regressor with in memory dataset.

build_raw_supervised_input_receiver_fn(...): Build a supervised_input_receiver_fn for raw features and labels.

build_supervised_input_receiver_fn_from_input_fn(...): Get a function that returns a SupervisedInputReceiver matching an input_fn.

call_logit_fn(...): Calls logit_fn.

clip_gradients_by_norm(...): Returns an optimizer which clips gradients before applying them.

dnn_logit_fn_builder(...): Function builder for a dnn logit_fn.

export_all_saved_models(...): Exports requested train/eval/predict graphs as separate SavedModels.

export_saved_model_for_mode(...): Exports a single train/eval/predict graph as a SavedModel.

forward_features(...): Forward features to predictions dictionary.

linear_logit_fn_builder(...): Function builder for a linear logit_fn.

logistic_regression_head(...): Creates a _Head for logistic regression.

make_early_stopping_hook(...): Creates early-stopping hook.

make_stop_at_checkpoint_step_hook(...): Creates a proper StopAtCheckpointStepHook based on chief status.

multi_class_head(...): Creates a _Head for multi class classification.

multi_head(...): Creates a _Head for multi-objective learning.

multi_label_head(...): Creates a _Head for multi-label classification.

poisson_regression_head(...): Creates a _Head for poisson regression using tf.nn.log_poisson_loss.

read_eval_metrics(...): Helper to read eval metrics from eval summary files.

regression_head(...): Creates a _Head for regression using the mean_squared_error loss.

replicate_model_fn(...): Replicate Estimator.model_fn over GPUs. (deprecated)

stop_if_higher_hook(...): Creates hook to stop if the given metric is higher than the threshold.

stop_if_lower_hook(...): Creates hook to stop if the given metric is lower than the threshold.

stop_if_no_decrease_hook(...): Creates hook to stop if metric does not decrease within given max steps.

stop_if_no_increase_hook(...): Creates hook to stop if metric does not increase within given max steps.