T splat_x, splat_y;
  if (!GetSplatValue(x, splat_x) || !GetSplatValue(y, splat_y)) {
    return false;
  }

  return splat_x == splat_y;
}

// Clones an operation with new operands while keeping attributes.
SmallVector<Value> CloneOpWithReplacedOperands(OpBuilder& builder,
                                               Operation* op,
                                               ArrayRef<Value> new_operands);

    // Write the mocking script.
    peer.sendFrame().settings(Settings())
    peer.acceptFrame() // ACK
    peer.sendFrame().ping(false, 2, 3)
    peer.acceptFrame() // PING
    peer.play()

    // Play it back.
    connect(peer)

    // Verify the peer received what was expected.
    val ping = peer.takeFrame()
    assertThat(ping.type).isEqualTo(Http2.TYPE_PING)
    assertThat(ping.streamId).isEqualTo(0)

#include "xla/mlir_hlo/mhlo/IR/hlo_ops.h"

namespace mlir {
namespace odml {
namespace {

#define DEBUG_TYPE "unfold-splat-constant-pass"

#define GEN_PASS_DEF_UNFOLDSPLATCONSTANTPASS
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/passes.h.inc"

// Undo the MHLO::BroadcastInDimOp folding pattern on splat tensor.
// TODO(b/295966255): Remove this pass after moving MHLO folders to a separate

// The threshold of constant bits to be unfolded (1Mb). If there is a splat
// constant with size equal or greater to this threshold, then it will be
// unfolded back to a regular `tfl.fill` operation.
constexpr int64_t kConstantSizeThresholdInBits = 1e+6;

// Pass which will replace large splat constant tensors to `tfl.Fill` op to
// reduce the size of the generated flatbuffer model size.

  let dependentDialects = ["mlir::stablehlo::StablehloDialect"];
}

def UnfoldSplatConstantPass : Pass<"unfold-splat-constant-pass", "ModuleOp"> {
  let summary = "Replaces a splat constant tensor with a BroadcastInDim op.";
  let constructor = "mlir::odml::CreateUnfoldSplatConstantPass()";
}

def CompositeLoweringPass : Pass<"composite-lowering", "ModuleOp"> {

    const GraphdefToMlirOptions& import_options, mlir::MLIRContext* context);

// Similar as the above function, but replaces all constant tensors
// with randomly generated splat values.
absl::StatusOr<mlir::OwningOpRef<mlir::ModuleOp>>
GraphdefToSplattedMlirTranslateFunction(
    llvm::StringRef input, const std::vector<std::string>& input_arrays,
    const std::vector<std::string>& input_dtypes,

		echo "FAILED"
		mkdir -p inspects
		(
			cd inspects
			"${WORK_DIR}/mc" admin inspect minio/healing-rewrite-bucket/verify-build.sh/**
		)

		"${WORK_DIR}/mc" mb play/inspects
		"${WORK_DIR}/mc" mirror inspects play/inspects

		purge "$WORK_DIR"
		exit 1
	fi

	go run ./buildscripts/heal-manual.go "127.0.0.1:${start_port}" "minio" "minio123"
	sleep 1

	if ! ./s3-check-md5 \

  Type etype = type.getElementType();

  // Evaluate for element types.
  if (!mlir::isa<ElementType>(etype)) {
    return {};
  }

  // Special case for folding splats no matter how large.
  // Only covers the case of both attrs being splats; operation-specific cases
  // like adding a zero or multiplying by one are handled elsewhere.
  SplatElementsAttr splatLhs = mlir::dyn_cast<SplatElementsAttr>(lhs);

                                               bool is_intermediate = false,
                                               bool get_storage = false);

// Gets a constant splat for the given value of type. Requires value to be of
// type static shaped RankedTensorType. `unique_index` is used to get the unique
// value for the attribute.

    id: what-did-you-do
    attributes:
      label: "What did you do?"
      description: "If possible, provide a recipe for reproducing the error. A complete runnable program is good. A link on [go.dev/play](https://go.dev/play) is better. A failing unit test is the best."
    validations:
      required: true
  - type: textarea
    id: actual-behavior
    attributes:
      label: "What did you see happen?"
    validations: