Pure]> {
  let summary = "Return the shape of s0 op s1 with broadcast.";

  let description = [{
Given `s0` and `s1`, tensors that represent shapes, compute `r0`, the
broadcasted shape. `s0`, `s1` and `r0` are all integer vectors.
  }];

  let arguments = (ins
    TFL_I32OrI64Tensor:$s0,
    TFL_I32OrI64Tensor:$s1
  );

  let results = (outs
    TFL_I32OrI64Tensor:$r0
  );

			break
		}
		sym := auxToCall(call.Aux)
		s1 := call.Args[0]
		if s1.Op != OpPPC64MOVDstore {
			break
		}
		_ = s1.Args[2]
		s1_1 := s1.Args[1]
		if s1_1.Op != OpPPC64MOVDconst {
			break
		}
		sz := auxIntToInt64(s1_1.AuxInt)
		s2 := s1.Args[2]
		if s2.Op != OpPPC64MOVDstore {
			break
		}
		_ = s2.Args[2]

 public:
  using OpRewritePattern::OpRewritePattern;
  // clang-format off
  // Converts Tile op to HLO DBroadcastInDim and DReshape ops.
  //   For shape [S1, S2] and multiples [M1, M2],
  //     MS1 = M1 * S1; MS2 = M2 * S2
  //
  //   %out_dim_size = [S1, M1, S2, M2]
  //   %broadcast_dimensions = [1, 3];
  //   %broadcast = mhlo.d_broadcast_in_dim(%input, %out_dim_size, %braodcast_dimensions);
  //   %shape = [MS1, MS2]

// Arch-specific inlining for small or disjoint runtime.memmove
(SelectN [0] call:(CALLstatic {sym} s1:(MOVDstore _ (MOVDconst [sz]) s2:(MOVDstore  _ src s3:(MOVDstore {t} _ dst mem)))))
	&& sz >= 0
	&& isSameCall(sym, "runtime.memmove")
	&& s1.Uses == 1 && s2.Uses == 1 && s3.Uses == 1
	&& isInlinableMemmove(dst, src, sz, config)
	&& clobber(s1, s2, s3, call)
	=> (Move [sz] dst src mem)

// Match post-lowering calls, register version.

//
// Match post-expansion calls, memory version.
(SelectN [0] call:(StaticCall {sym} s1:(Store _ (Const(64|32) [sz]) s2:(Store  _ src s3:(Store {t} _ dst mem)))))
	&& sz >= 0
	&& isSameCall(sym, "runtime.memmove")
	&& s1.Uses == 1 && s2.Uses == 1 && s3.Uses == 1
	&& isInlinableMemmove(dst, src, int64(sz), config)
	&& clobber(s1, s2, s3, call)
	=> (Move {types.Types[types.TUINT8]} [int64(sz)] dst src mem)

			break
		}
		sym := auxToCall(call.Aux)
		s1 := call.Args[0]
		if s1.Op != OpStore {
			break
		}
		_ = s1.Args[2]
		s1_1 := s1.Args[1]
		if s1_1.Op != OpConst64 {
			break
		}
		sz := auxIntToInt64(s1_1.AuxInt)
		s2 := s1.Args[2]
		if s2.Op != OpStore {
			break
		}
		_ = s2.Args[2]
		src := s2.Args[1]

			break
		}
		sym := auxToCall(call.Aux)
		s1 := call.Args[0]
		if s1.Op != OpARM64MOVDstore {
			break
		}
		_ = s1.Args[2]
		s1_1 := s1.Args[1]
		if s1_1.Op != OpARM64MOVDconst {
			break
		}
		sz := auxIntToInt64(s1_1.AuxInt)
		s2 := s1.Args[2]
		if s2.Op != OpARM64MOVDstore {
			break
		}
		_ = s2.Args[2]

	return SRError{
		Cause: err,
		Code:  ErrSiteReplicationConfigMissing,
	}
}

func errSRIAMConfigMismatch(peer1, peer2 string, s1, s2 madmin.IDPSettings) SRError {
	return SRError{
		Cause: fmt.Errorf("IAM/IDP settings mismatch between %s and %s: %#v vs %#v", peer1, peer2, s1, s2),
		Code:  ErrSiteReplicationIAMConfigMismatch,
	}
}

var errSRObjectLayerNotReady = SRError{

  let summary = "Return the shape of s0 op s1 with broadcast.";

  let description = [{
Given `s0` and `s1`, tensors that represent shapes, compute `r0`, the
broadcasted shape. `s0`, `s1` and `r0` are all integer vectors.
  }];

  let arguments = (ins
    TF_I32OrI64Tensor:$s0,
    TF_I32OrI64Tensor:$s1
  );

  let results = (outs
    TF_I32OrI64Tensor:$r0
  );

ia=Object.setPrototypeOf?Object.setPrototypeOf.bind():function(r,n){return r.__proto__=n,r},ia(i,e)}var s1=function(i){n1(e,i);function e(r){var n;return n=i.call(this,r)||this,n.type=r1.PSEUDO,n}var t=e.prototype;return t.toString=function(){var n=this.length?"("+this.map(String).join(",")+")":"";return[this.rawSpaceBefore,this.stringifyProperty("value"),n,this.rawSpaceAfter].join("")},e}(t1.default);Br.default=s1;Jc.exports=Br.default});var Xc={};Ae(Xc,{deprecate:()=>a1});function a1(i){return i}var Kc=C(()=>{l()});var...