using ::tensorflow::error::Code;

// As we need to test multiple URI schemes we need a parameterized test.
// Furthermore, since each test creates and deletes files, we will use the same
// fixture to create new directories in `SetUp`. Each directory will reside in
// `::testing::TempDir()`, will use a RNG component and the test name. This
// ensures that two consecutive runs are unlikely to clash.

  TF_DeleteTensor(fetchValues[1]);
}

// REGISTER_OP for CApiAttributesTest test cases.
// Registers two ops, each with a single attribute called 'v'.
// The attribute in one op will have a type 'type', the other
// will have list(type).
#define ATTR_TEST_REGISTER_OP(type)                           \
  REGISTER_OP("CApiAttributesTestOp" #type)                   \

      // and hence expect the input to be forwarded to the return tensor.
      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));
    }
  }

// Retrieves the full name of the device (e.g. /job:worker/replica:0/...)
// The return value will be a pointer to a null terminated string. The caller
// must not modify or delete the string. It will be deallocated upon a call to
// TF_DeleteDeviceList.
//
// If index is out of bounds, an error code will be set in the status object,
// and a null pointer will be returned.
TF_CAPI_EXPORT extern const char* TF_DeviceListName(const TF_DeviceList* list,

      scripting error, and will continue to provide invalid input.
      Raise the error to avoid infinitely looping.
  """
  if not question:
    question = 'Do you wish to build TensorFlow with {} support?'.format(
        query_item)
  if not yes_reply:
    yes_reply = '{} support will be enabled for TensorFlow.'.format(query_item)
  if not no_reply:

build:ios_fat --config=ios
build:ios_fat --ios_multi_cpus=armv7,arm64,i386,x86_64

# Config to use a mostly-static build and disable modular op registration
# support (this will revert to loading TensorFlow with RTLD_GLOBAL in Python).
# By default, TensorFlow will build with a dependence on
# //tensorflow:libtensorflow_framework.so.
build:monolithic --define framework_shared_object=false
build:monolithic --define tsl_protobuf_header_only=false

/// pointed to by the `void*` members is always owned by the plugin. The plugin
/// will provide functions to call to allocate and deallocate this data (see
/// next sections) and core TensorFlow ensures to call these at the proper time.
///
/// Plugins will never receive a `TF_*` pointer that is `nullptr`. Core
/// TensorFlow will never touch the `void*` wrapped by these structures, except
/// to initialize it as `nullptr`.

    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",
    packages = [
        "//devtools/python/indexer/...",

  TF_Operation* feed1 = Placeholder(func_graph_, s_, "feed1");
  TF_Operation* feed2 = Placeholder(func_graph_, s_, "feed2");

  // Outputs of the while loop corresponding to the two inputs above
  // The first one will the function's output
  std::vector<TF_Output> outputs;

  // Add while loop to func_graph_
  {
    // The inputs to the while loop
    std::vector<TF_Output> inputs = {{feed1, 0}, {feed2, 0}};