tf.placeholder(dtype, shape=None, name=None) Inserts a placeholder for a tensor that will be always fed. Important: This tensor will produce an error if evaluated. Its value must be fed using the feed_dict optional argument to Session.run(), Tensor.eval(), or Operation.run(). For example: x = tf.placeholder(tf.float32, shape=(1024, 1024)) y = tf.matmul(x, x) with tf.Session() as sess: print(sess.run(y)) # ERROR: will fail because x was not fed. rand_array = np.random.rand(1024, 1024)

tf.parse_single_example(serialized, features, name=None, example_names=None) Parses a single Example proto. Similar to parse_example, except: For dense tensors, the returned Tensor is identical to the output of parse_example, except there is no batch dimension, the output shape is the same as the shape given in dense_shape. For SparseTensors, the first (batch) column of the indices matrix is removed (the indices matrix is a column vector), the values vector is unchanged, and the first (batch_s

tf.parse_example(serialized, features, name=None, example_names=None) Parses Example protos into a dict of tensors. Parses a number of serialized Example protos given in serialized. example_names may contain descriptive names for the corresponding serialized protos. These may be useful for debugging purposes, but they have no effect on the output. If not None, example_names must be the same length as serialized. This op parses serialized examples into a dictionary mapping keys to Tensor and Sp

tf.OpError.node_def The NodeDef proto representing the op that failed.

tf.OpError.__init__(node_def, op, message, error_code) Creates a new OpError indicating that a particular op failed. Args: node_def: The node_def_pb2.NodeDef proto representing the op that failed, if known; otherwise None. op: The ops.Operation that failed, if known; otherwise None. message: The message string describing the failure. error_code: The error_codes_pb2.Code describing the error.

tf.OpError.op The operation that failed, if known. N.B. If the failed op was synthesized at runtime, e.g. a Send or Recv op, there will be no corresponding Operation object. In that case, this will return None, and you should instead use the OpError.node_def to discover information about the op. Returns: The Operation that failed, or None.

class tf.PaddingFIFOQueue A FIFOQueue that supports batching variable-sized tensors by padding. A PaddingFIFOQueue may contain components with dynamic shape, while also supporting dequeue_many. See the constructor for more details. See tf.QueueBase for a description of the methods on this class.

tf.PaddingFIFOQueue.__init__(capacity, dtypes, shapes, names=None, shared_name=None, name='padding_fifo_queue') Creates a queue that dequeues elements in a first-in first-out order. A PaddingFIFOQueue has bounded capacity; supports multiple concurrent producers and consumers; and provides exactly-once delivery. A PaddingFIFOQueue holds a list of up to capacity elements. Each element is a fixed-length tuple of tensors whose dtypes are described by dtypes, and whose shapes are described by the s

tf.OpError.__str__()

tf.ones(shape, dtype=tf.float32, name=None) Creates a tensor with all elements set to 1. This operation returns a tensor of type dtype with shape shape and all elements set to 1. For example: tf.ones([2, 3], int32) ==> [[1, 1, 1], [1, 1, 1]] Args: shape: Either a list of integers, or a 1-D Tensor of type int32. dtype: The type of an element in the resulting Tensor. name: A name for the operation (optional). Returns: A Tensor with all elements set to 1.