Returns a callable that returns the next element of the dataset. Example use: ```python # In both graph and eager modes dataset = ...

The graph-level random seed of this graph.

Convenience method for making a new DeviceSpec by overriding fields. For instance: ``` my_spec = DeviceSpec=(job="my_job", device="CPU")

Methods for accessing the dimensions array.

Performs a mean reduction on `x` across pfor iterations. Note that this currently may not work inside a control flow construct. Args: x

TODO: implement as constexpr

Creates an instruction pattern that will capture the matched instruction in the argument.

Returns cuDNN handle. To be passed directly to cuDNN APIs, don't keep a copy.

Mean.

A transformation that models performance. Returns: A `Dataset` transformation function, which can be passed to `tf.data.Dataset.apply`.

Asserts that a dataset produces the expected output / error. Args: dataset: A dataset to check for the expected output / error. expec

Return selected values in the TensorArray as a packed `Tensor`. All of selected values must have been written and their shapes must all match

Build the {@link Operation}. <p>The following action will also be performed depending on the current execution environment. <ul> <li>In eager mode

Return a pointer to the data pointers of all tensors in the list. For example: float* const* f = v.data(); f[0][1] is the second element of the first

Returns the number of regular fanins.

Applies a transformation function to this dataset. `apply` enables chaining of custom `Dataset` transformations, which are represented as fun

Assign `value` to all replicas. Outside of the tpu.rewrite context, assign explicitly to all replicas. Inside of the tpu.rewrite context, ass

The `TensorShape` of this variable. Returns: A `TensorShape`.

Const adds an operation to graph that produces value as output.

Add a new trackable value.

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

Creates a `Dataset` with a single element, comprising the given tensors. Note that if `tensors` contains a NumPy array, and eager execution is no

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

Proto-style accessors

Returns a nested structure of `tf.Tensor`s representing the next element. In graph mode, you should typically call this method *once* and use its

Ensures that `tensor` is being traced by this tape. Args: tensor: a Tensor or list of Tensors. Raises: ValueError: if it encount

Returns the (mutable) result shape of this instruction.

Runs a single gradient update on a single batch of data. Arguments: x: Input data. It could be: - A Numpy array (or array-like)

Sorts a tensor. Usage: ```python import tensorflow as tf a = [1, 10, 26.9, 2.8, 166.32, 62.3] b = tf.sort(a,axis=-1,direction='ASCENDING

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

Add a function definition to the context. Once added, the function (identified by its name) can be executed like any other operation. Ar

Returns a const iterator pointing to the first wrapped tensor input.

Entry point for C node plugin API to report an error.

Returns a context manager that specifies an op to colocate with. Note: this function is not for public use, only for internal libraries. For