tf.contrib.learn.BaseEstimator.partial_fit(x=None, y=None, input_fn=None, steps=1, batch_size=None, monitors=None) Incremental fit on a batch of samples. This method is expected to be called several times consecutively on different or the same chunks of the dataset. This either can implement iterative training or out-of-core/online training. This is especially useful when the whole dataset is too big to fit in memory at the same time. Or when model is taking long time to converge, and you want

tf.contrib.learn.BaseEstimator.model_dir

tf.contrib.learn.BaseEstimator.get_variable_value(name) Returns value of the variable given by name. Args: name: string, name of the tensor. Returns: Numpy array - value of the tensor.

tf.contrib.learn.BaseEstimator.get_variable_names() Returns list of all variable names in this model. Returns: List of names.

tf.contrib.learn.BaseEstimator.get_params(deep=True) Get parameters for this estimator. Args: deep: boolean, optional If True, will return the parameters for this estimator and contained subobjects that are estimators. Returns: params : mapping of string to any Parameter names mapped to their values.

tf.contrib.learn.BaseEstimator.fit(x=None, y=None, input_fn=None, steps=None, batch_size=None, monitors=None, max_steps=None) See Trainable. Raises: ValueError: If x or y are not None while input_fn is not None. ValueError: If both steps and max_steps are not None.

tf.contrib.learn.BaseEstimator.export(*args, **kwargs) Exports inference graph into given dir. (deprecated arguments) SOME ARGUMENTS ARE DEPRECATED. They will be removed after 2016-09-23. Instructions for updating: The signature of the input_fn accepted by export is changing to be consistent with what's used by tf.Learn Estimator's train/evaluate. input_fn (and in most cases, input_feature_key) will become required args, and use_deprecated_input_fn will default to False and be removed altogeth

tf.contrib.learn.BaseEstimator.evaluate(x=None, y=None, input_fn=None, feed_fn=None, batch_size=None, steps=None, metrics=None, name=None) See Evaluable. Raises: ValueError: If at least one of x or y is provided, and at least one of input_fn or feed_fn is provided. Or if metrics is not None or dict.

tf.contrib.learn.BaseEstimator.config

class tf.contrib.learn.BaseEstimator Abstract BaseEstimator class to train and evaluate TensorFlow models. Concrete implementation of this class should provide the following functions: _get_train_ops _get_eval_ops _get_predict_ops Estimator implemented below is a good example of how to use this class.