tf.contrib.learn.monitors.StepCounter.every_n_step_begin(step) Callback before every n'th step begins. Args: step: int, the current value of the global step. Returns: A list of tensors that will be evaluated at this step.

tf.contrib.distributions.Multinomial.is_reparameterized

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

tf.image.decode_jpeg(contents, channels=None, ratio=None, fancy_upscaling=None, try_recover_truncated=None, acceptable_fraction=None, name=None) Decode a JPEG-encoded image to a uint8 tensor. The attr channels indicates the desired number of color channels for the decoded image. Accepted values are: 0: Use the number of channels in the JPEG-encoded image. 1: output a grayscale image. 3: output an RGB image. If needed, the JPEG-encoded image is transformed to match the requested number of col

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.sigma Dense (batch) covariance matrix, if available.

tf.contrib.learn.DNNClassifier.weights_ DEPRECATED FUNCTION THIS FUNCTION IS DEPRECATED. It will be removed after 2016-10-13. Instructions for updating: This method inspects the private state of the object, and should not be used

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.__init__(mu, diag_stdev, validate_args=False, allow_nan_stats=True, name='MultivariateNormalDiagWithSoftplusStdDev')

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

tf.contrib.distributions.WishartCholesky.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.distributions.WishartCholesky.dtype The DType of Tensors handled by this Distribution.