tf.contrib.learn.extract_pandas_data(data) Extract data from pandas.DataFrame for predictors. Given a DataFrame, will extract the values and cast them to float. The DataFrame is expected to contain values of type int, float or bool. Args: data: pandas.DataFrame containing the data to be extracted. Returns: A numpy ndarray of the DataFrame's values as floats. Raises: ValueError: if data contains types other than int, float or bool.

tf.contrib.learn.extract_pandas_matrix(data) Extracts numpy matrix from pandas DataFrame. Args: data: pandas.DataFrame containing the data to be extracted. Returns: A numpy ndarray of the DataFrame's values.

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

tf.FixedLengthRecordReader.reset(name=None) Restore a reader to its initial clean state. Args: name: A name for the operation (optional). Returns: The created Operation.

tf.contrib.bayesflow.stochastic_tensor.LaplaceWithSoftplusScaleTensor.name

class tf.errors.FailedPreconditionError Operation was rejected because the system is not in a state to execute it. This exception is most commonly raised when running an operation that reads a tf.Variable before it has been initialized.

tf.contrib.distributions.Exponential.is_reparameterized

void tensorflow::Tensor::UnsafeCopyFromInternal(const Tensor &, const TensorShape &) Copy the other tensor into this tensor and reshape it and reinterpret the buffer's datatype. This tensor shares other's underlying storage.

tf.contrib.distributions.StudentT.df Degrees of freedom in these Student's t distribution(s).

tf.contrib.rnn.GRUBlockCell.zero_state(batch_size, dtype) Return zero-filled state tensor(s). Args: batch_size: int, float, or unit Tensor representing the batch size. dtype: the data type to use for the state. Returns: If state_size is an int or TensorShape, then the return value is a N-D tensor of shape [batch_size x state_size] filled with zeros. If state_size is a nested list or tuple, then the return value is a nested list or tuple (of the same structure) of 2-D tensors with the shape