tf.contrib.learn.monitors.StopAtStep.set_estimator(estimator) A setter called automatically by the target estimator. If the estimator is locked, this method does nothing. Args: estimator: the estimator that this monitor monitors. Raises: ValueError: if the estimator is None.

tf.contrib.distributions.WishartFull.log_cdf(value, name='log_cdf') Log cumulative distribution function. Given random variable X, the cumulative distribution function cdf is: log_cdf(x) := Log[ P[X <= x] ] Often, a numerical approximation can be used for log_cdf(x) that yields a more accurate answer than simply taking the logarithm of the cdf when x << -1. Args: value: float or double Tensor. name: The name to give this op. Returns: logcdf: a Tensor of shape sample_shape(x) + s

tf.nn.rnn_cell.GRUCell.state_size

tf.image.adjust_brightness(image, delta) Adjust the brightness of RGB or Grayscale images. This is a convenience method that converts an RGB image to float representation, adjusts its brightness, and then converts it back to the original data type. If several adjustments are chained it is advisable to minimize the number of redundant conversions. The value delta is added to all components of the tensor image. Both image and delta are converted to float before adding (and image is scaled approp

class tf.contrib.graph_editor.ControlOutputs The control outputs topology.

tf.contrib.distributions.Beta.parameters Dictionary of parameters used by this Distribution.

bool tensorflow::PartialTensorShape::AsTensorShape(TensorShape *tensor_shape) const

tf.contrib.distributions.MultivariateNormalDiag.mode(name='mode') Mode.

tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.__init__(alpha, beta, validate_args=False, allow_nan_stats=True, name='InverseGammaWithSoftplusAlphaBeta')

string tensorflow::Status::State::msg