{
            "detail": [
                {
                    "type": "float_parsing",
                    "loc": ["body", "price"],
                    "msg": "Input should be a valid number, unable to parse string as a number",
                    "input": "twenty",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [

        {
            "detail": [
                {
                    "type": "float_parsing",
                    "loc": ["body", "price"],
                    "msg": "Input should be a valid number, unable to parse string as a number",
                    "input": "twenty",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [

        *module_op->getBodyRegion().getOps().begin());
    if (!func_op) {
      return absl::InternalError("Input MLIR must have only 1 func");
    }
    if (arguments.size() != func_op.getNumArguments()) {
      return absl::InternalError("Input argument has wrong size");
    }

    // Convert input xla::Literal arguments to constants, this allows using
    // constant folding to evaluate function return value.

  private static void testReverse(short[] input, short[] expectedOutput) {
    input = Arrays.copyOf(input, input.length);
    Shorts.reverse(input);
    assertThat(input).isEqualTo(expectedOutput);
  }

  private static void testReverse(
      short[] input, int fromIndex, int toIndex, short[] expectedOutput) {
    input = Arrays.copyOf(input, input.length);
    Shorts.reverse(input, fromIndex, toIndex);

	return x.Pos, x.Pos.add(")")
}

// An input represents a single input file being parsed.
type input struct {
	// Lexing state.
	filename   string    // name of input file, for errors
	complete   []byte    // entire input
	remaining  []byte    // remaining input
	tokenStart []byte    // token being scanned to end of input
	token      token     // next token to be returned by lex, peek

  return fill;
}

// Add parallel collection of inputs to the replicated op.
LogicalResult AppendReplicatedInput(OpBuilder& builder, ReplicateOp replicate,
                                    ValueRange inputs, Type type,
                                    BlockArgument& block_arg) {
  // check that inputs length is same as num_replicas.
  if (inputs.size() != replicate.getN()) {
    return replicate.emitError()

  Output constant =
      ops::Const(s.WithOpName("constant_ref"), Input::Initializer(0.0));
  s.graph()->AddControlEdge(constant.node(), variable.node());
}

void CreateSubgraphNotTouchingRefVar(const Scope& s) {
  Output constant =
      ops::Const(s.WithOpName("constant_normal"), Input::Initializer(0.0));
  Output neg = ops::Negate(s.WithOpName("negate_normal"), constant);

  }

  private static void testReverse(long[] input, long[] expectedOutput) {
    input = Arrays.copyOf(input, input.length);
    Longs.reverse(input);
    assertThat(input).isEqualTo(expectedOutput);
  }

  private static void testReverse(long[] input, int fromIndex, int toIndex, long[] expectedOutput) {
    input = Arrays.copyOf(input, input.length);
    Longs.reverse(input, fromIndex, toIndex);

 * Converter.apply (like Converter.convert) is capable of accepting null inputs. However, a
 * supertype of `Function<A, B>` turns out to be massively more useful to callers in practice: They
 * want their output to be non-null in operations like `stream.map(myConverter)`, and we can
 * guarantee that as long as we also require the input type to be non-null[*] (which is a
 * requirement that existing callers already fulfill).
 *

}

// Convenience function to create a `TransposeOp` with a given `permutation`.
// The Location is set as `input`'s loc.
TransposeOp CreateTransposeOp(Value input, const ArrayRef<int64_t> permutation,
                              PatternRewriter& rewriter) {
  return rewriter.create<TransposeOp>(
      input.getLoc(), input, rewriter.getDenseI64ArrayAttr(permutation));
}