result.attributes))
      return failure();
  }
  bool has_constant = succeeded(parser.parseOptionalKeyword("constant"));
  result.addAttribute("is_constant", BoolAttr::get(context, has_constant));

  SmallVector<Type, 1> types;
  if (parser.parseColonTypeList(types)) return failure();
  if (types.size() != 1)
    return parser.emitError(loc) << " expects only a single data type";

                              const Attribute min, const Attribute max,
                              const int quant_dim, const IntegerAttr num_bits,
                              const BoolAttr narrow_range, const bool is_signed,
                              const bool legacy_float_scale,
                              const bool use_fake_quant_num_bits) {
  SmallVector<double, 4> min_value, max_value;

                        Value filter, Value bias,
                        StringAttr fused_activation_function,
                        StringAttr weights_format, BoolAttr keep_num_dims,
                        BoolAttr asymmetric_quantize_inputs) {
  auto fc_op = builder->create<FullyConnectedOp>(
      result[0].getLoc(), result.getTypes(), input, filter, bias,

  return mlir::OpTrait::impl::verifyCompatibleOperandBroadcast(
      op.getOperation());
}

void NotEqualOp::build(OpBuilder &builder, OperationState &result, Value x,
                       Value y, BoolAttr incompatible_shape_error) {
  auto result_type = DeduceEqualCmpOpType(&builder, result.location, x, y,
                                          incompatible_shape_error);

  }

  // Default to non-time_major.
  std::optional<mlir::NamedAttribute> time_major_attr =
      attr.getNamed("time_major");
  bool time_majored =
      time_major_attr ? time_major_attr->getValue().cast<BoolAttr>().getValue()
                      : false;

  int64_t batch =
      time_majored ? input_type.getDimSize(1) : input_type.getDimSize(0);
  int64_t time =

  auto composite_control_flow_op = [&](const std::string& name) {
    result.name = mlir::OperationName(get_full_op_name(name), context_);
    bool stateless = absl::StartsWith(node_type_name, "Stateless");
    mlir::BoolAttr val = builder_.getBoolAttr(stateless);
    result.attributes.push_back(builder_.getNamedAttr("is_stateless", val));
  };

  // Map Case/If/While and StatelessCase/If/While op in TensorFlow to the common

// If the 'transpose' attribute is true returns ElementsAttr to transpose 2D
// matrix. Otherwise, returns ElementsAttr for identity transpose.
static DenseIntElementsAttr Get2DTransposePerm(BoolAttr transpose, Builder *b) {
  if (transpose.getValue()) return GetI64ElementsAttr({1, 0}, b);
  return GetI64ElementsAttr({0, 1}, b);
}

//===----------------------------------------------------------------------===//