tf.SparseTensorValue.values Alias for field number 1

tf.contrib.distributions.ExponentialWithSoftplusLam.log_pmf(value, name='log_pmf') Log probability mass function. Args: value: float or double Tensor. name: The name to give this op. Returns: log_pmf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if is_continuous.

tf.contrib.learn.monitors.SummarySaver.every_n_step_end(step, outputs)

tf.nn.rnn_cell.DropoutWrapper.__call__(inputs, state, scope=None) Run the cell with the declared dropouts.

tf.contrib.distributions.Binomial.std(name='std') Standard deviation.

tf.contrib.distributions.DirichletMultinomial.pmf(value, name='pmf') Probability mass function. Args: value: float or double Tensor. name: The name to give this op. Returns: pmf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if is_continuous.

tf.contrib.learn.monitors.GraphDump.step_end(step, output)

tf.contrib.distributions.BetaWithSoftplusAB.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32 Tensor. Args: name: name to give to the op Returns: event_shape: Tensor.

static bool tensorflow::TensorShapeUtils::IsVectorOrHigher(const TensorShape &shape)

tf.image.sample_distorted_bounding_box(image_size, bounding_boxes, seed=None, seed2=None, min_object_covered=None, aspect_ratio_range=None, area_range=None, max_attempts=None, use_image_if_no_bounding_boxes=None, name=None) Generate a single randomly distorted bounding box for an image. Bounding box annotations are often supplied in addition to ground-truth labels in image recognition or object localization tasks. A common technique for training such a system is to randomly distort an image wh