Returns the value of this variable, read in the current context. Can be different from value() if it's on another device, with control depend

Returns true if the indicated dimension is ragged.

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

Returns the number of input tensors.

Returns the values captured so far. Returns: `dict` mapping `int` step numbers to that values of the variable at the respective s

Initializes the module.

Returns the adjoint of the current `LinearOperator`. Given `A` representing this `LinearOperator`, return `A*`. Note that calling `self.adjoi

Creates a `RaggedTensor` with rows partitioned by `row_splits`. The returned `RaggedTensor` corresponds with the python list defined by: ```

Returns the `name` hyper parameter, optionally cast to `dtype`.

Invoke the interpreter. Be sure to set the input sizes, allocate tensors and fill values before calling this. Also, note that this function r

Methods for accessing the tuple subshapes. This field only non-empty for tuple shapes.

Returns whether the shape is of the specified type (array, tuple, etc).

Returns the total number of elements, or none for incomplete shapes.

Returns this->status().ok()

Value converts the Tensor to a Go value. For now, not all Tensor types are supported, and this function may panic if it encounters an unsupported Data

Returns the current control flow context. Returns: A context object.

TODO(apassos) make this return a constant reference

Overload to call Or with 3 or more operands. As with `And`, we need the following complicated overload set to handle the default arg in the `Or` over

Returns the list of all local per-replica values contained in `value`. Note: This only returns values on the worker initiated by this client.

Returns value of the variable given by name. Args: name: string, name of the tensor. Returns: Numpy array - value of the tensor.

The input tensors of this subgraph view.

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

Gets the total dataset size (number of elements). Returns: An integer denoting the number of elements in the dataset.

Converts a char (8 bits) into a 6-bit value for decoding. If the input char is invalid for base64 encoding, the return value has at least its upper 25

Returns 1D 64-bit dense elements attribute with the given values.

Anything other than the special Source & Sink nodes.

Returns a `numpy.dtype` based on this `DType`.

The prefix of the most recent checkpoint in `directory`. Equivalent to `tf.train.latest_checkpoint(directory)` where `directory` is the const

Runs restore ops from the checkpoint. Requires a valid checkpoint.

Get the OneDNN shape from the second string tensor

Returns a context manager that specifies the resource container to use. Stateful operations, such as variables and queues, can maintain their

Retrieves the weights of the model. Returns: A flat list of Numpy arrays.

Returns True if the `other` DType will be converted to this DType. The conversion rules are as follows: ```python DType(T) .is_com

Scope class for bfloat16 variables so that the model uses custom getter. This enables variables to be read as bfloat16 type when using get_variab

Generates a 'Unique Identifier' based on all internal fields. Caller should use the uid string to check `RunConfig` instance integrity in one

Updates the progress bar. Arguments: current: Index of current step. values: List of tuples: `(name, value_for_last_s

Exit this control flow context.

Returns the location of the current token.