Returns the loss value & metrics values for the model in test mode. Computation is done in batches. Arguments: x: Input data. It cou

Returns the full name of the Operation.

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

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 structures of numpy arrays or Tensors, have near values. `a` and `b` can be arbitrarily nested structures. A layer of a nested

Returns a TensorFlow Session for use in executing tests. This method behaves differently than self.session(): for performance reasons `cached

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.

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

Returns true iff the status indicates success.

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

Get a pseudorandom value.

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

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

Methods for accessing the format.

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

Returns the bound of the tile in the given dimension index.

Helper to construct a NodeDef.

Alias of Tensor.shape.

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

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

Output returns the i-th output of op.

Parse an expression. Args: expression: the expression to be parsed. Returns: The result of the evaluation. Raises: Va

Returns the variable scope object created by this Template.

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

Returns the opcode for this instruction.

Returns True if current thread has eager executing enabled.

Asserts that ProtoEq says a == b.

Return p or (1-p).

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

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

A deterministic random uniform if seed is passed.

Evaluates tensors and returns numpy values. Args: tensors: A Tensor or a nested list/tuple of Tensors. Returns: tensors numpy va

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

Like assertAllClose, but also suitable for comparing fp16 arrays. In particular, the tolerance is reduced to 1e-3 if at least one of the argu

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