Dequeues and concatenates `n` elements from this queue. This operation concatenates queue-element component tensors along the 0th dimension t

Request that the threads stop. After this is called, calls to `should_stop()` will return `True`. Note: If an exception is being passed in,

Attempts to push value to the back of this. If the slice has already been filled, this method has no effect on the underlying data, but it changes the

Returns the maximum representable value in this data type. Raises: TypeError: if this is a non-numeric, unordered, or quantized type.

\brief Returns the number of micro-seconds since the Unix epoch.

Creates an `Iterator` for enumerating the elements of this dataset. **N.B.** The returned iterator will be initialized automatically. A "one-

Overrides the shape for this variable. Args: shape: the `TensorShape` representing the overridden shape.

Checks whether StringPiece starts with x and if so advances the beginning of it to past the match. It's basically a shortcut for starts_with followed

Computes the loss on some input data, batch by batch. Arguments: x: input data, as a Numpy array or list of Numpy arrays (if

Return a slot named `name` created for `var` by the Optimizer. Some `Optimizer` subclasses use additional variables. For example `Momentum`

Returns the buffer defined at the given instruction and index.

Returns the data type.

Creates a `Dataset` whose elements are slices of the given tensors. Args: tensors: A nested structure of tensors, each having the same size

DEPRECATED: Use outputs.

Gets the instructions in this computation. The returned type is a range of HloInstruction*s, so you can iterate over it using a range-based for loop

Returns `ModelFnOps` that a model_fn can return. Please note that, + Exactly one of `logits` and `logits_input` must be provided. + All a

Dequeues one element from this queue. If the queue is empty when this operation executes, it will block until there is an element to dequeue.

Returns word's id in the vocabulary. If category is new, creates a new id for it. Args: category: string or integer to lookup in vocab

Gets a numpy-style shape tuple giving the dataset dimensions. Returns: A numpy-style shape tuple.

Helper to construct a NodeDef.

Parses a serialized DataColumn produced from the SerializeToString() function of a python data_ops.DataColumn object. It should look like a proto ASCI

Verifies that 'op' produces 'expected' when fed input 'inp' . Args: op: operator to test inp: numpy input array to use as input to 'o

Return pointer to variable length section.

Asserts that ProtoEq says a != b.

Repeats this dataset `count` times. Args: count: (Optional.) A `tf.int64` scalar `tf.Tensor`, representing the number of times the

Returns the `TensorShape` that represents the shape of this tensor. The shape is computed using shape inference functions that are registered

Stores `value` in the collections given by `names`. Note that collections are not sets, so it is possible to add a value to a collection seve

Creates a Tensor from a Java object. <p>A {@code Tensor} is a multi-dimensional array of elements of a limited set of types. Not all Java objects can

Add operations to minimize `loss` by updating `var_list`. This method simply combines calls `compute_gradients()` and `apply_gradients()`. If

Bitwise reduction (logical OR). Arguments: x: Tensor or variable. axis: axis along which to perform the reduction. keepdims: whet

Creates an `Operation` in this graph. This is a low-level interface for creating an `Operation`. Most programs will not call this method dire

Handles a command by dispatching it to a registered command handler. Args: prefix: Command prefix, as a str, e.g., "print". argv: Com

Associates `keys` with `values`. Args: keys: Keys to insert. Can be a tensor of any shape. Must match the table's key type. v

Creates a `Dataset` of a step-separated range of values. For example: ```python Dataset.range(5) == [0, 1, 2, 3, 4] Dataset.range(2,

Repeats this dataset `count` times. Args: count: (Optional.) A `tf.int64` scalar `tf.Tensor`, representing the number of times the

Looks up `keys` in a table, outputs the corresponding values. The `default_value` is used for keys not present in the table. Args: key

Push 'v'. If the maximum number of elements was exceeded, drop the lowest element and return it in 'dropped' (if given). If the maximum is not exceed