# tensorflow/core/public/version.h and tools/pip_package/setup.py.
#
# These variables aren't available by default. Scripts must source this file
# explicitly, *after* checking if update_version.py needs to be run for a
# nightly job. update_version.py affects TF_VER_SUFFIX, TF_VER_PYTHON, and
# TF_VER_FULL.

"tf.foo" being imported first.

The `_api/v2/api_packages.txt` file is generated during the TensorFlow API v2
init files creation process and is subsequently stored in the wheel file after
the build. It also contains a few paths that cannot be directly imported. These
paths point to attributes or sub-modules within a module's namespace, but they

  ~TF_Operation() = default;
};

struct TF_Session {
  TF_Session(tensorflow::Session* s, TF_Graph* g);

  tensorflow::Session* session;
  TF_Graph* const graph;

  tensorflow::mutex mu TF_ACQUIRED_AFTER(TF_Graph::mu);
  int last_num_graph_nodes;

  // If true, TF_SessionRun and similar methods will call
  // ExtendSessionGraphHelper before running the graph (this is the default

// The URI schemes that need to be tested are provided by the user via flags
// (or, if none is supplied, all existing schemes are used). As a scheme can
// become available after a shared object with a filesystem implementation is
// loaded, we can only check for availability after all arguments have been
// parsed.
//
// Furthermore, as `INSTANTIATE_TEST_SUITE_P` needs to be at global level and we

#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/file_system_helper.h"
#include "tsl/platform/errors.h"

// TODO(b/139060984): After all filesystems are converted, all calls to
// methods from `FileSystem` will have to be replaced to calls to private
// methods here, as part of making this class a singleton and the only way to
// register/use filesystems.

  TF_DeleteStatus(status);
}
BENCHMARK(BM_ReadVariable);

TEST(CAPI, StringAttributes) {
  // Test that TFE_OpSetAttrString doesn't hold on to the value after it
  // returns.
  TF_Status* status = TF_NewStatus();
  TFE_ContextOptions* opts = TFE_NewContextOptions();
  TFE_Context* ctx = TFE_NewContext(opts, status);

  // 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.
  virtual Status SetOrUpdateServerDef(const ServerDef& server_def,
                                      bool reset_context, int keep_alive_secs,

- Include code to invoke the TFLite Converter Python API and the errors.
- Provide links to your TensorFlow model and (optionally) TensorFlow Lite Model.
```

### 3. Failure after conversion
If the conversion is successful, but the generated model is wrong, then state what is wrong:

- Model produces wrong results and/or has lesser accuracy.
- Model produces correct results, but it is slower than expected.

// things like the available devices, resource manager etc.
// TFE_Context must outlive all tensor handles created using it. In other
// words, TFE_DeleteContext() must be called after all tensor handles have
// been deleted (with TFE_DeleteTensorHandle).
//
// TODO(ashankar): Merge with TF_Session?
typedef struct TFE_Context TFE_Context;

TF_CAPI_EXPORT extern TFE_Context* TFE_NewContext(

  /// and fix this.
  ///
  /// TODO(b/139060984): After all filesystems are converted, revisit note.
  ///
  /// This operation must be provided. See "REQUIRED OPERATIONS" above.
  void (*cleanup)(TF_Filesystem* filesystem);

  /// Creates a new random access read-only file from given `path`.
  ///
  /// After this call `file` may be concurrently accessed by multiple threads.
  ///
  /// Plugins: