// CHECK:           [[CM2:%.*]] = arith.constant -2 : index
// CHECK:           [[LHSHEAD:%.*]], [[LHSTAIL:%.*]] = "shape.split_at"([[LHSSHAPE]], [[CM2]])
// CHECK:           [[RHSHEAD:%.*]], [[RHSTAIL:%.*]] = "shape.split_at"([[RHSSHAPE]], [[CM2]])
// CHECK:           [[BCASTHEAD:%.*]] = shape.broadcast [[LHSHEAD]], [[RHSHEAD]]

										}
									}
									reconstructAbleConfig = valid >= m.data-hasParity && valid < m.data
									startOffset = offset
									offset++
									continue
								}
								for shardIdx, ok := range shardConfig {
									if ok != 0 {
										shards[shardIdx] = append(shards[shardIdx], splitData[shardIdx][offset])
									}

LogicalResult UnrollSplit::matchAndRewrite(TFL::SplitOp split_op,
                                           PatternRewriter& rewriter) const {
  auto num_splits = split_op.getNumSplits();
  auto input = split_op.getValue();
  auto input_type = mlir::dyn_cast<RankedTensorType>(input.getType());
  if (input_type == nullptr || !input_type.hasStaticShape()) return failure();

  for (auto result : split_op.getResults()) {

)

// IsPathSeparator reports whether c is a directory separator character.
func IsPathSeparator(c uint8) bool {
	return PathSeparator == c
}

// splitPath returns the base name and parent directory.
func splitPath(path string) (string, string) {
	// if no better parent is found, the path is relative from "here"
	dirname := "."

	// Remove all but one leading slash.

  }

  // Creates a split op that splits |src_input| along |split_dimension|.
  llvm::SmallVector<mlir::Type, 4> output_types(num_split, output_type);
  *split_op = builder->create<mlir::TF::SplitOp>(
      location, output_types, split_dimension_op.getOutput(), src_input);
  (*split_op)->setAttr(
      kNumSplitAttr,
      builder->getIntegerAttr(builder->getIntegerType(32), num_split));
  return mlir::success();
}

bool NotFromDequant(mlir::Value value) {
  auto dequant_op = value.getDefiningOp<DequantizeOp>();
  if (dequant_op) {
    return false;
  }
  auto split_op = value.getDefiningOp<SplitOp>();
  if (!split_op) {
    return true;
  }
  return !split_op.getValue().getDefiningOp<DequantizeOp>();
}

// Optimize TFLite operations in functions.
class OptimizeBatchMatmulPass

    auto split_op = rewriter.create<TF::SplitOp>(loc, output_types,
                                                 split_dimension_op.getOutput(),
                                                 reshape_op.getOutput());

    // Squeeze each batch, i.e. reshape
    // [1, num_rows, num_cols] -> [num_rows, num_cols]
    for (const auto& split_value : split_op.getOutput()) {

  %size_splits = arith.constant dense<[]> : tensor<0xi32>
  %split_dim = arith.constant dense<0> : tensor<i32>
  // expected-error @+1 {{'tfl.split_v' op attribute 'num_splits' failed to satisfy constraint: 32-bit signless integer attribute whose value is positive}}
  "tfl.split_v"(%arg0, %size_splits, %split_dim) {num_splits = 0 : i32} : (tensor<16xf32>, tensor<0xi32>, tensor<i32>) -> ()
  func.return
}

// -----

  %2:3 = "tfl.split_v"(%arg0, %0, %1) {num_splits = 3 : i32} : (tensor<?x13x13x85xf32>, tensor<3xi32>, tensor<i32>) -> (tensor<*xf32>, tensor<*xf32>, tensor<*xf32>)
  func.return %2#0, %2#1, %2#2 : tensor<*xf32>, tensor<*xf32>, tensor<*xf32>
}

// CHECK-LABEL: @unrollSplitVUnknownRankResults
// CHECK-NOT: "tfl.slice"
// CHECK: "tfl.split_v"

// -----

	policyDBUsersListKey    = "policydb/users/"
	policyDBSTSUsersListKey = "policydb/sts-users/"
	policyDBGroupsListKey   = "policydb/groups/"
)

// splitPath splits a path into a top-level directory and a child item. The
// parent directory retains the trailing slash.
func splitPath(s string, lastIndex bool) (string, string) {
	var i int
	if lastIndex {
		i = strings.LastIndex(s, "/")
	} else {
		i = strings.Index(s, "/")
	}