the whole community, e.g., fixing bugs and adding features. Individual support
should be sought on Stack Overflow or other non-GitHub channels. It helps us to

  // timestamp of the entry.
  cache.Insert(key, 41);
  env->SetNowSeconds(2);
  cache.Insert(key, 42);
  // 1 second after the most recent insertion, the entry is still valid.
  env->SetNowSeconds(3);
  int value = 0;
  EXPECT_TRUE(cache.Lookup(key, &value));
  EXPECT_EQ(value, 42);
  // 2 seconds after the most recent insertion, the entry is no longer valid.
  env->SetNowSeconds(4);
  EXPECT_FALSE(cache.Lookup(key, &value));

# 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

// here.
void TF_SetTracingImplementation(const char* name, TF_Status*);

// Creates a new TensorFlow function. A Function is an execution context, and as
// such it can trace operations through TF_ExecuteOperation. After completing
// tracing, a function can be obtained by TF_FinalizeFunction.
TF_ExecutionContext* TF_CreateFunction(const char* fn_name, TF_Status* status);

// Creates a context for eager execution of operations.

- 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.

    InsertLocked(key, value);
  }

  // Delete the entry with key `key`. Return true if the entry was found for
  // `key`, false if the entry was not found. In both cases, there is no entry
  // with key `key` existed after the call.
  bool Delete(const std::string& key) {
    absl::MutexLock lock(&mu_);
    return DeleteLocked(key);
  }

  /// Look up the entry with key `key` and copy it to `value` if found. Returns

  // 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,

However, for the vast majority of issues, we aim to empower individuals to first resolve conflicts themselves, asking for help when needed, and only after that fails to escalate further. This approach gives people more control over the outcome of their dispute. 

If you are experiencing or witnessing conflict, we ask you to use the following escalation strategy to address the conflict: