src = GetOrAddFrameNodeId(frame_name);
        src_type = "frame";
      }

      if (!cycles->InsertEdge(src, dst)) {
        // TODO(b/127521408): We can probably handle this situation with a more
        // sophisticated SCC based algorithm, but for now we bail out.
        VLOG(1) << "Cycle detected when adding " << src_type << "->" << dst_type

    return errors::InvalidArgument("Cast grad requires 1 grad input");
  }

  auto src_type = op.input_type(0);
  auto dst_type = grad_inputs[0].type();
  if (IsFloatingPointDtype(src_type) && IsFloatingPointDtype(dst_type)) {
    grad_outputs->push_back(Cast(scope, grad_inputs[0], src_type));
  } else {
    grad_outputs->push_back(NoGradient());
  }
  return scope.status();
}

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#include "tensorflow/c/experimental/ops/gen/model/arg_type.h"

namespace tensorflow {
namespace generator {

ArgType ArgType::CreateInput(const OpDef::ArgDef& arg_def) {
  return ArgType(arg_def, kInput);
}

Jeremy Meredith <******@****.***> 1623780830 -0700

	dstType := dst.Type()
	if dstType.Kind() != reflect.Struct {
		return false
	}
	src := reflect.ValueOf(e)
	srcType := src.Type()
	numField := srcType.NumField()
	if dstType.NumField() != numField {
		return false
	}
	for i := 0; i < numField; i++ {
		sf := srcType.Field(i)
		df := dstType.Field(i)
		if sf.Name != df.Name || !sf.Type.ConvertibleTo(df.Type) {
			return false
		}
	}

#define TENSORFLOW_C_EXPERIMENTAL_OPS_GEN_CPP_VIEWS_ARG_TYPE_VIEW_H_

#include "tensorflow/c/experimental/ops/gen/model/arg_type.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace generator {
namespace cpp {

class ArgTypeView {
 public:
  explicit ArgTypeView(ArgType arg_type);

  string TypeName() const;

 private:
  ArgType arg_type_;
};

}  // namespace cpp

    for (BlockArgument arg : block.getArguments()) {
      Type arg_type = arg.getType();
      if (auto quant_type = arg_type.cast<TensorType>()
                                .getElementType()
                                .dyn_cast<quant::QuantizedType>()) {
        if (arg.hasOneUse() && llvm::isa<TFR::CastOp>(*arg.user_begin())) {
          arg.setType(
              arg_type.cast<TensorType>().clone(quant_type.getStorageType()));

	var iov Iovec
	if len(p) > 0 {
		iov.Base = &p[0]
		iov.SetLen(len(p))
	}
	var dummy byte
	if len(oob) > 0 {
		var sockType int
		sockType, err = GetsockoptInt(fd, SOL_SOCKET, SO_TYPE)
		if err != nil {
			return
		}
		// receive at least one normal byte
		if sockType != SOCK_DGRAM && len(p) == 0 {
			iov.Base = &dummy
			iov.SetLen(1)
		}
		msg.Control = &oob[0]
		msg.SetControllen(len(oob))

// the convertee value to the heap.
func ConvIfaceSrcRType(pos src.XPos, n *ir.ConvExpr) ir.Node {
	assertOp(n, ir.OCONVIFACE)
	if hasRType(n, n.SrcRType, "SrcRType") {
		return n.SrcRType
	}
	return concreteRType(pos, n.X.Type())
}

// CopyElemRType asserts that n is a "copy" operation, and returns an
// expression that yields the *runtime._type value representing the

class MySuperContextManager:
    def __init__(self):
        self.db = DBSession()

    def __enter__(self):
        return self.db

    def __exit__(self, exc_type, exc_value, traceback):
        self.db.close()


async def get_db():
    with MySuperContextManager() as db: