MOVD	fd+0(FP), R3
	MOVD	p+8(FP), R4
	MOVW	n+16(FP), R5
	SYSCALL	$SYS_write
	BVC	2(PC)
	NEG	R3	// caller expects negative errno
	MOVW	R3, ret+24(FP)
	RET

TEXT runtime·read(SB),NOSPLIT|NOFRAME,$0-28
	MOVW	fd+0(FP), R3
	MOVD	p+8(FP), R4
	MOVW	n+16(FP), R5
	SYSCALL	$SYS_read
	BVC	2(PC)
	NEG	R3	// caller expects negative errno
	MOVW	R3, ret+24(FP)
	RET

(RotateLeft64 <t> x (MOVWconst [c])) => (Or64 (Lsh64x32 <t> x (MOVWconst [c&63])) (Rsh64Ux32 <t> x (MOVWconst [-c&63])))

// unary ops
(Neg(32|16|8) ...) => (NEG ...)
(Neg(32|64)F ...) => (NEG(F|D) ...)

(Com(32|16|8) x) => (NORconst [0] x)

(Sqrt ...) => (SQRTD ...)
(Sqrt32 ...) => (SQRTF ...)

// TODO: optimize this case?
(Ctz32NonZero ...) => (Ctz32 ...)

               const std::vector<Output>& grad_inputs,
               std::vector<Output>* grad_outputs) {
  // dx = -dy;
  grad_outputs->push_back(Neg(scope, grad_inputs[0]));
  return scope.status();
}
REGISTER_GRADIENT_OP("Neg", NegGrad);

Status InvGrad(const Scope& scope, const Operation& op,
               const std::vector<Output>& grad_inputs,
               std::vector<Output>* grad_outputs) {

                                                           TF_DeleteStatus);

  TF_Operation* feed = Placeholder(func_graph.get(), s.get());
  TF_Operation* neg = Neg(feed, func_graph.get(), s.get());

  TF_Output inputs[] = {{feed, 0}};
  TF_Output outputs[] = {{neg, 0}};
  *func = TF_GraphToFunction(func_graph.get(), name, append_hash, -1,
                             /*opers=*/nullptr, 1, inputs, 1, outputs,

		// An oddball encoding of offset for hashchk and similar.
		// e.g hashchk offset is 0b1111111000000000 | DX << 8 | D << 3
		off := a.BitFields.ParseSigned(i) << a.Shift
		neg := int64(-1) << (int(a.Shift) + a.BitFields.NumBits())
		return Offset(neg | off)
	}
}

type ArgType int8

const (
	TypeUnknown      ArgType = iota
	TypePCRel                // PC-relative address
	TypeLabel                // absolute address

  int num_retvals = 1;
  return op_ptr->Execute(absl::MakeSpan(product, 1), &num_retvals);
}

// Op: Neg()
// Summary: Computes numerical negative value element-wise.
//
// Description:
//   I.e., \\(y = -x\\).
Status Neg(AbstractContext* ctx, AbstractTensorHandle* const x,
           AbstractTensorHandle** y, const char* name,
           const char* raw_device_name) {

	"BLTZ",
	"BNEZ",
	"FABSD",
	"FABSS",
	"FNEGD",
	"FNEGS",
	"FNED",
	"FNES",
	"MOV",
	"MOVB",
	"MOVBU",
	"MOVF",
	"MOVD",
	"MOVH",
	"MOVHU",
	"MOVW",
	"MOVWU",
	"NEG",
	"NEGW",
	"NOT",
	"SEQZ",
	"SNEZ",
	"LAST",

  string name_space = "tensorflow::ops";
  string output_dir = "tensorflow/c/experimental/ops/gen/cpp/golden";
  string source_dir = "tensorflow";
  string api_dirs = "";
  std::vector<string> ops = {
      "Neg",        // Simple unary Op
      "MatMul",     // 2 inputs & attrs with default values
      "IdentityN",  // Variadic input+output
      "SparseSoftmaxCrossEntropyWithLogits",  // 2 outputs

	CALL	libc_errno(SB)
	MOVW	(R3), R3		// errno
	NEG	R3, R3			// caller expects negative errno value
noerr:
	RET

TEXT runtime·write_trampoline(SB),NOSPLIT,$32
	MOVD	8(R3), R4		// arg 2 - buf
	MOVW	16(R3), R5		// arg 3 - count
	MOVD	0(R3), R3		// arg 1 - fd (uintptr)
	CALL	libc_write(SB)
	CMP	R3, $-1
	BNE	noerr
	CALL	libc_errno(SB)
	MOVW	(R3), R3		// errno
	NEG	R3, R3			// caller expects negative errno value
noerr:

               TF_Operation** op) {
  TF_OperationDescription* desc = TF_NewOperation(graph, "Neg", name);
  TF_Output neg_input = {n, 0};
  TF_AddInput(desc, neg_input);
  *op = TF_FinishOperation(desc, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  ASSERT_NE(*op, nullptr);
}

TF_Operation* Neg(TF_Operation* n, TF_Graph* graph, TF_Status* s,
                  const char* name) {
  TF_Operation* op;