Asserts that two numpy arrays have the same values. Args: a: the expected numpy ndarray or anything can be converted to one. b: the a

All of Input's constructors are implicit. Input can be implicitly constructed from the following objects : Output: This is so that the output of an Op

Returns a TensorFlow Session for use in executing tests. This method should be used for all functional tests. This method behaves different

Evaluates this tensor in a `Session`. Calling this method will execute all preceding operations that produce the inputs needed for the operat

Runs this operation in a `Session`. Calling this method will execute all preceding operations that produce the inputs needed for this operati

Custom implementation of test_session() for XLA tests. We override the standard Tensorflow test_session() since it is too specific to CPU and

Creates a sequence of numbers. Creates a sequence of numbers that begins at `start` and extends by increments of `delta` up to but not including

Asserts that two numpy arrays, or dicts of same, have near values. This does not support nested dicts. Args: a: The expected numpy nda

Returns true iff the status indicates success.

MakeShape returns a Shape with the provided size of each dimension. A value of -1 implies that the size of the corresponding dimension is not known.

Returns a list of integers or `None` for each dimension. Returns: A list of integers or `None` for each dimension. Raises: Value

Append t to the vector. Increases size() by one. Amortized complexity: O(1) Worst-case complexity: O(size())

Blocks until the server has shut down. This method currently blocks forever. Raises: tf.errors.OpError: Or one of its subclasses if an

r"""Returns a context manager that creates hierarchical names for operations. A graph maintains a stack of name scopes. A `with name_scope(...):`

Get a pseudorandom value.

Alias of Tensor.shape.

Returns the TensorShape that represents the shape of this tensor. See tf.Tensor.get_shape(). Returns: A TensorShape representing the s

Add an error to the collection. Args: full_name: The path to the file in which the error occurred. message: The message to display wi

Returns the variable scope object created by this Template.

Asserts that ProtoEq says a == b.

\brief Convenience accessor for the tensor shape. For all shape accessors, see comments for relevant methods of `TensorShape` in `tensor_shape.h`.

Returns a context manager that makes this `Graph` the default graph. This method should be used if you want to create multiple graphs in the

Append an item to the Menu. Args: item: (MenuItem) the item to be appended.

Maximum value in a tensor. Arguments: x: A tensor or variable. axis: An integer, the axis to find maximum values. keepdims: A boo

static */

Output returns the i-th output of op.

Err returns the error, if any, encountered during the construction of the Graph managed by s. Once Err returns a non-nil error, all future calls will

Returns a context manager that specifies control dependencies. Use with the `with` keyword to specify that all operations constructed within

Gets an existing variable with this name or create a new one.

AddOperation adds the operation to the Graph managed by s. If there is a name prefix associated with s (such as if s was created by a call to SubScop

Return the values in the TensorArray as a concatenated `Tensor`. All of the values must have been written, their ranks must match, and and th

idx can be negative for an offset from end of dimensions. idx must be in the range [-1 * s.rank, s.rank).

Alias of Variable.shape.

Returns the opcode for this instruction.

Transform [batch] matrix `x` with left multiplication: `x --> Ax`. ```python # Make an operator acting like batch matrix A. Assume A.shape

In a session, computes and returns the value of this variable. This is not a graph construction method, it does not add ops to the graph. Th

Extend this instance of RichTextLines with another instance. The extension takes effect on the text lines, the font attribute segments, as we

Minimum value in a tensor. Arguments: x: A tensor or variable. axis: An integer, the axis to find minimum values. keepdims: A boo

Return the root instruction of the computation. The root instruction is the instruction which produces the output of the computation.

Returns this->status().ok()

Returns a list of values in the collection with the given `name`. This is different from `get_collection_ref()` which always returns the actu