tf.contrib.distributions.BernoulliWithSigmoidP.is_continuous

tf.contrib.learn.TensorFlowEstimator.evaluate(x=None, y=None, input_fn=None, feed_fn=None, batch_size=None, steps=None, metrics=None, name=None)

tf.contrib.distributions.DirichletMultinomial.cdf(value, name='cdf') Cumulative distribution function. Given

tf.contrib.distributions.Normal.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32 Tensor

tf.contrib.distributions.matrix_diag_transform(matrix, transform=None, name=None) Transform diagonal of [batch-]matrix, leave

tf.contrib.distributions.ExponentialWithSoftplusLam.event_shape(name='event_shape') Shape of a single sample from a single batch

tf.image.grayscale_to_rgb(images, name=None) Converts one or more images from Grayscale to RGB. Outputs

tf.contrib.distributions.Normal.log_cdf(value, name='log_cdf') Log cumulative distribution function. Given

tf.image.resize_area(images, size, align_corners=None, name=None) Resize images to size using area interpolation

class tf.contrib.learn.TensorFlowRNNClassifier TensorFlow RNN Classifier model.