tf.contrib.learn

 

upper level

 

Modules

 

datasets:

Dataset utilities and synthetic/reference datasets.

graph_actions:

High level operations on graphs.

head:

Abstractions for the head(s) of a model.

io:

Tools to allow different io formats.

learn_runner:

Utilities to run and tune an Experiment.

models:

Various high level TF models.

monitors:

Monitors instrument the training process.

ops:

Various TensorFlow Ops.

preprocessing:

Preprocessing tools useful for building models.

utils:

TensorFlow Learn Utils.

 

Classes

 

BaseEstimator:

Abstract BaseEstimator class to train and evaluate TensorFlow models.

DNNClassifier:

A classifier for TensorFlow DNN models.

DNNEstimator:

A Estimator for TensorFlow DNN models with user specified _Head.

DNNLinearCombinedClassifier:

A classifier for TensorFlow Linear and DNN joined training models.

DNNLinearCombinedEstimator:

An estimator for TensorFlow Linear and DNN joined training models.

DNNLinearCombinedRegressor:

A regressor for TensorFlow Linear and DNN joined training models.

DNNRegressor:

A regressor for TensorFlow DNN models.

DynamicRnnEstimator:

Estimator:

Estimator class is the basic TensorFlow model trainer/evaluator.

Evaluable:

Interface for objects that are evaluatable by, e.g., Experiment.

Experiment:

Experiment is a class containing all information needed to train a model.

ExportStrategy:

A class representing a type of model export.

Head:

Interface for the head/top of a model.

InputFnOps:

A return type for an input_fn.

KMeansClustering:

An Estimator for K-Means clustering.

LinearClassifier:

Linear classifier model.

LinearEstimator:

Linear model with user specified head.

LinearRegressor:

Linear regressor model.

MetricSpec:

MetricSpec connects a model to metric functions.

ModeKeys:

Standard names for model modes.

ModelFnOps:

Ops returned from a model_fn.

NanLossDuringTrainingError:

NotFittedError:

Exception class to raise if estimator is used before fitting.

PredictionKey:

ProblemType:

Enum-like values for the type of problem that the model solves.

RunConfig:

This class specifies the configurations for an Estimator run.

SKCompat:

Scikit learn wrapper for TensorFlow Learn Estimator.

SVM:

Support Vector Machine (SVM) model for binary classification.

TaskType:

Trainable:

Interface for objects that are trainable by, e.g., Experiment.

 

Functions

 

LogisticRegressor(…):

Builds a logistic regression Estimator for binary classification.

binary_svm_head(…):

Creates a Head for binary classification with SVMs.

build_parsing_serving_input_fn(…):

Build an input_fn appropriate for serving, expecting fed tf.Examples.

evaluate(…):

Evaluate a model loaded from a checkpoint. (deprecated)

extract_dask_data(…):

Extract data from dask.Series or dask.DataFrame for predictors.

extract_dask_labels(…):

Extract data from dask.Series or dask.DataFrame for labels.

extract_pandas_data(…):

Extract data from pandas.DataFrame for predictors.

extract_pandas_labels(…):

Extract data from pandas.DataFrame for labels.

extract_pandas_matrix(…):

Extracts numpy matrix from pandas DataFrame.

infer(…):

Restore graph from restore_checkpoint_path and run output_dict tensors. (deprecated)

infer_real_valued_columns_from_input(…):

Creates FeatureColumn objects for inputs defined by input x.

infer_real_valued_columns_from_input_fn(…):

Creates FeatureColumn objects for inputs defined by input_fn.

make_export_strategy(…):

Create an ExportStrategy for use with Experiment.

multi_class_head(…):

Creates a Head for multi class single label classification.

multi_head(…):

Creates a MultiHead stemming from same logits/hidden layer.

multi_label_head(…):

Creates a Head for multi label classification.

no_op_train_fn(…):

poisson_regression_head(…):

Creates a Head for poisson regression.

read_batch_examples(…):

Adds operations to read, queue, batch Example protos.

read_batch_features(…):

Adds operations to read, queue, batch and parse Example protos.

read_batch_record_features(…):

Reads TFRecord, queues, batches and parses Example proto.

read_keyed_batch_examples(…):

Adds operations to read, queue, batch Example protos.

read_keyed_batch_examples_shared_queue(…):

Adds operations to read, queue, batch Example protos.

read_keyed_batch_features(…):

Adds operations to read, queue, batch and parse Example protos.

read_keyed_batch_features_shared_queue(…):

Adds operations to read, queue, batch and parse Example protos.

regression_head(…):

Creates a Head for linear regression.

run_feeds(…):

See run_feeds_iter(). Returns a list instead of an iterator. (deprecated)

run_n(…):

Run output_dict tensors n times, with the same feed_dict each run. (deprecated)

train(…):

Train a model. (deprecated)