} TF_FilesystemPluginOps;

/// This structure gathers together all the operations provided by the plugin.
///
/// Plugins must provide exactly `num_schemes` elements in the `ops` array.
///
/// Since memory that is allocated by the DSO gets transferred to core
/// TensorFlow, we need to provide a way for the allocation and deallocation to

the Machine Intelligence team at Google Brain to conduct research in machine
learning and neural networks. However, the framework is versatile enough to be
used in other areas as well.

TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)
and [C++](https://www.tensorflow.org/api_docs/cc) APIs, as well as a
non-guaranteed backward compatible API for
[other languages](https://www.tensorflow.org/api_docs).

    which is a NumPy-compatible API for writing TF programs. This module
    provides class `ndarray`, which mimics the `ndarray` class in NumPy, and
    wraps an immutable `tf.Tensor` under the hood. A subset of NumPy functions
    (e.g. `numpy.add`) are provided. Their inter-operation with TF facilities is
    seamless in most cases. See

      const std::vector<Gradient*>& in_grads, absl::Span<Gradient*> out_grads);

  // Maps from tensor IDs to corresponding JVPs.
  std::unordered_map<int64_t, Gradient*> accumulated_gradients_;
  // Not owned; provides operations on Tensors which are currently only
  // available in language bindings (e.g. Python).
  const VSpace<Gradient, BackwardFunction, TapeTensor>& vspace_;

  // Decides if tangents are vectorized or not

    visibility = ["//visibility:public"],
)

# DO NOT ADD ANY NEW EXCEPTIONS TO THIS LIST!
# Instead, please use public APIs or public build rules TF provides.
# If you need functionality that is not exposed, we will work with you to expand our public APIs.
# TODO(b/173549186): Move Google-internal TF code out of learning/brain
package_group(
    name = "internal",

  // Set up distributed execution environment on local and remote tasks.
  // When `reset_context` is true, initialize new cluster context state based
  // on cluster configurations provided in `server_def`; otherwise, update
  // existing context state with the provided `server_def`. Contexts created
  // on remote tasks will be considered stale and garbage collected after
  // `keep_alive_secs` of inactivity.

```
(You can paste links or attach files by dragging & dropping them below)
- Provide links to your updated versions of the above two colab notebooks.
- Provide links to your TensorFlow model and (optionally) TensorFlow Lite Model.
```

#### Option B: Paste your code here or provide a link to a custom end-to-end colab

```
(You can paste links or attach files by dragging & dropping them below)

## Enforcement

// found in the provided `op`.
TF_CAPI_EXPORT extern int TFE_OpGetInputLength(TFE_Op* op,
                                               const char* input_name,
                                               TF_Status* status);

// Returns the length (number of tensors) of the output argument `output_name`
// found in the provided `op`.
TF_CAPI_EXPORT extern int TFE_OpGetOutputLength(TFE_Op* op,

// returned through the provided TF_OutputList.
// Any active tape will observe the effects of this execution.
void TF_ExecuteOperation(TF_AbstractOp* op, int num_inputs,
                         TF_AbstractTensor* const* inputs, TF_OutputList* o,
                         TF_Status* s);

// Creates a new TF_AbstractFunction from the current tracing states in the
// context. The provided `ctx` is consumed by this API call and deleted.