TF_RETURN_IF_ERROR(
      tensorflow::TensorShapeToXLAShape(type, shape, &xla_shape));
  ApiConverter::StackHelper<XLA_Shape> se_shape(xla_shape);
  ApiConverter::StackHelper<XLA_Shape> tpu_shape;
  StatusHelper status;
  stream_executor::tpu::ExecutorApiFn()->XlaShapeToTpuShapeRepresentationFn(
      &se_shape.value, type, use_fast_memory, &tpu_shape.value,
      status.c_status);
  if (!status.status().ok()) {
    return status.status();

      OperationState new_state(quantizing_op->getLoc(),
                               quantizing_op->getName().getStringRef(), inputs,
                               output_types, quantizing_op->getAttrs());
      for (int i = 0; i < quantizing_op->getNumRegions(); ++i) {
        new_state.addRegion();
      }
      Operation* quantized_op = rewriter.create(new_state);
      if (quantizing_op->getNumRegions() != 0) {

      OperationState new_state(op_with_region->getLoc(),
                               op_with_region->getName().getStringRef(), inputs,
                               output_types, op_with_region->getAttrs());
      for (int i = 0; i < op_with_region->getNumRegions(); ++i) {
        new_state.addRegion();
      }
      Operation* quantized_op = rewriter.create(new_state);
      for (const auto& [index, region] :

  Location loc = call_op.getLoc();
  rewriter.setInsertionPointAfter(call_op);
  std::string tf_op_name = GetTFOpName(call_op.getCallee());
  OperationState new_state(loc, tf_op_name, inputs, output_types, attr_list);
  Operation* new_op = rewriter.create(new_state);
  if (materialize_derived_attrs_) {
    for (const auto& attr : derived_attrs) {
      // Add or update the derived attribute with the value. Skip the fixed

}

void TensorInterface::SetShape(const int64_t* dims, int num_dims) {
  tensorflow::TensorShape s;
  for (int i = 0; i < num_dims; ++i) {
    s.AddDim(dims[i]);
  }
  tensor_.set_shape(s);
}

Status TensorInterface::BitcastFrom(const TensorInterface& from, DataType type,
                                    const int64_t* new_dims, int num_new_dims) {
  tensorflow::TensorShape s;

        Please use input_signature or reduce_retracing to minimize retracing.

*   `tf.SparseTensor`:
    *   Introduced `set_shape`, which sets the static dense shape of the sparse tensor and has the same semantics as `tf.Tensor.set_shape`.

## Security