ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_OpSetAttrType(op, "dtype", TF_FLOAT);
  TFE_OpAddInput(op, var, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  int num_retvals = 1;
  TFE_Execute(op, out_value, &num_retvals, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_DeleteOp(op);
  TF_DeleteStatus(status);
}

  TF_DeleteStatus(status);

  return var_handle;
}

TFE_Op* AddOp(TFE_Context* ctx, TFE_TensorHandle* a, TFE_TensorHandle* b) {
  TF_Status* status = TF_NewStatus();

  TFE_Op* op = TFE_NewOp(ctx, "AddV2", status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_OpAddInput(op, a, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_OpAddInput(op, b, status);

  if (h == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid handle");
    return -1;
  }
  return tensorflow::unwrap(h)->DeviceId(&status->status);
}

TF_CAPI_EXPORT extern void TFE_TensorHandleGetStatus(TFE_TensorHandle* h,
                                                     TF_Status* status) {
  status->status = tensorflow::unwrap(h)->TensorHandleStatus();
}

    TFE_TensorHandle* h = TFE_NewTensorHandle(t, status);
    ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
    TF_DeleteTensor(t);

    TFE_Op* op = TFE_NewOp(ctx, "ident", status);
    ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
    TFE_OpAddInput(op, h, status);
    ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);

    std::vector<TFE_TensorHandle*> result;

  if (TF_GetCode(status) != TF_OK) return;
  if (!grad) return;

  status->status = g->graph.AddFunctionDef(grad->record->fdef(),
                                           grad->record->stack_traces());
  if (TF_GetCode(status) != TF_OK) return;

  tensorflow::GradientDef gdef;
  gdef.set_function_name(func->record->fdef().signature().name());
  gdef.set_gradient_func(grad->record->fdef().signature().name());

  status->status = c.construction_status();
  if (!status->status.ok()) return;

  if (op_reg_data->shape_inference_fn == nullptr) {
    status->status =
        InvalidArgument("No shape inference function exists for op '",
                        node_def.op(), "', did you forget to define it?");
    return;
  }

  status->status = c.Run(op_reg_data->shape_inference_fn);

      TF_NewStatus(), TF_DeleteStatus);
  int assign = TF_OpIsStateful("AssignAddVariableOp", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  EXPECT_EQ(assign, 1);
  int id = TF_OpIsStateful("Identity", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  EXPECT_EQ(id, 0);
}

class ShapeInferenceTest : public ::testing::Test {
 protected:

xmlns="http://s3.amazonaws.com/doc/2006-03-01/"><Role></Role><Rule><Status>Enabled</Status><DeleteMarkerReplication><Status>Disabled</Status></DeleteMarkerReplication><DeleteReplication><Status>Disabled</Status></DeleteReplication><Prefix>key-prefix</Prefix><Destination><Bucket>arn:minio:replication:::destinationbucket</Bucket></Destination></Rule><Rule><Status>Enabled</Status><Priority>3</Priority><DeleteMarkerReplication><Status>Disabled</Status></DeleteMarkerReplication><DeleteReplication><Status>Disab...

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

  TFE_Op* func = TFE_NewOp(ctx, "AddVariablesFunction", status);
  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  TFE_OpAddInput(func, packed_handle, status);
  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  if (remote) {
    TFE_OpSetDevice(func, task1_name, status);

// the error and a nullptr is returned.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_TensorHandleCopySharingTensor(
    TFE_TensorHandle* h, TF_Status* status);

// This function will block till the operation that produces `h` has
// completed. The memory returned might alias the internal memory used by
// TensorFlow. Hence, callers should not mutate this memory (for example by