# Sourcing this enables local disk cache
if [[ $(uname -s) == "Darwin" ]]; then
  echo "Please note that using disk cache on macOS is not recommended because the"
  echo "cache can end up being pretty big and make the build process inefficient."
fi

Packages are imported one by one in alphabetical order during runtime.

The test doesn't identify package's order-dependent issues; for instance,
importing "tf.foo" followed by "tf.bar" won't reveal that "tf.bar" depends on
"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

                                   absl::Span<AbstractTensorHandle* const>,
                                   absl::Span<AbstractTensorHandle*>)>;

// Runs `model` maybe wrapped in a function call op. This can be thought as
// being equivalent to the following python code.
//
// if use_function:
//   outputs = tf.function(model)(inputs)
// else:
//   outputs = model(inputs)
Status RunModel(Model model, AbstractContext* ctx,

      EXPECT_EQ(orig_ptr, TF_TensorData(t));
    } else {
      // In sync mode, forwarding can't really happen since the client code will
      // have a reference count on the input tensor while the kernel is being
      // executed and thus it cannot be re-used for the return tensor.
      EXPECT_NE(orig_ptr, TF_TensorData(t));
    }
  }

  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  if (TF_GetCode(status) == TF_OK) {
    // This modification only updates the destination node for
    // the purposes of running this graph in a session. Thus, we don't
    // record the source node as being modified.
    RecordMutation(graph, *dst.oper, "updating input tensor");
  }
}

// Apis that are corresponding to python c api. --------------------------

// setting the same key will lead to errors.
//
// Note that the key-values are only expected to be used for cluster
// configuration data, and should not be used for storing a large amount of data
// or being accessed very frequently.
TF_CAPI_EXPORT extern void TFE_InsertConfigKeyValue(TFE_Context* ctx,
                                                    const char* key,

                     TapeTensor>::IsPersistent;

  // Adds this tensor to the list of watched tensors.
  //
  // This is a no-op if the tensor is already being watched either from an
  // earlier call to `GradientTape::Watch` or being an output of an op with
  // watched inputs.
  void Watch(const AbstractTensorHandle*);
  // Records an operation with given inputs and outputs

and follow the sandboxing guideline above to protect against these types of
vulnerabilities.

## Security properties of execution modes

TensorFlow has several execution modes, with Eager-mode being the default in v2.
Eager mode lets users write imperative-style statements that can be easily
inspected and debugged and it is intended to be used during the development
phase.

Abhinav Upadhyay, Aggelos Avgerinos, Alan Wu, Alexander G. de G. Matthews,
Aleksandr Yahnev, @amchercashin, Andy Kitchen, Aurelien Geron, Awni Hannun,
@BanditCat, Bas Veeling, Cameron Chen, @cg31, Cheng-Lung Sung, Christopher
Bonnett, Dan Becker, Dan Van Boxel, Daniel Golden, Danijar Hafner, Danny
Goodman, Dave Decker, David Dao, David Kretch, Dongjoon Hyun, Dustin Dorroh,

  }

  const char* func_name_ = "MyFunc";
  const char* func_node_name_ = "MyFunc_0";
  TF_Status* s_;
  TF_Graph* func_graph_;
  TF_Graph* host_graph_;
  TF_Function* func_;

  // Workaround for not being able to initialize empty map using {}
  std::unordered_set<string> empty_;
};

TEST_F(CApiFunctionTest, OneOp_ZeroInputs_OneOutput) {
  /*
   *                constant
   *                   |