/*device_ordinal=*/builder.getI64IntegerAttr(0), device_type_attr),
      builder);
}

// Clones an IfRegionOp 'if_region' and attributes and creates then/else regions
// with yield op and an empty block.
mlir::TF::IfRegionOp CloneEmptyIfWithPredicate(mlir::TF::IfRegionOp if_region,
                                               OpBuilder& builder) {

// profile that event by storing a pointer to the lock in its "to be profiled
// upon unlock" field. If that field is already set, it uses the relative
// magnitudes to weight a random choice between itself and the other lock, with
// the loser's time being added to the "additional contention" field. Otherwise
// if the M's call stack buffer is occupied, it does the comparison against that
// sample's magnitude.
//

        and dtypes.int64 for int
      num_examples: Number of examples in the representative dataset.

    Yields:
      data_gen: A `quantize_model._RepresentativeSample` filled with random
        values.
    """
    for _ in range(num_examples):
      yield {input_key: random_ops.random_uniform(shape, minval, maxval, dtype)}

  def _save_tf1_model(
      self,
      sess: session.Session,

      tmp[5 - i] = hex.charAt(c & 0xF);
      c = (char) (c >> 4);
    }
    return String.copyValueOf(tmp);
  }

  // Fast matchers

  /** A matcher for which precomputation will not yield any significant benefit. */
  abstract static class FastMatcher extends CharMatcher {

    @Override
    public final CharMatcher precomputed() {
      return this;
    }

    @Override

}

// Returns a (recursive) strategic merge patch that yields modified when applied to original.
// Including:
// - Adding fields to the patch present in modified, missing from original
// - Setting fields to the patch present in modified and original with different values
// - Delete fields present in original, missing from modified through
// - IFF map field - set to nil in patch

  region.push_back(new mlir::Block);
  auto saved_pos = op_builder.saveInsertionPoint();
  op_builder.setInsertionPointToEnd(&region.front());
  mlir::Operation* cloned_op = op_builder.clone(*op);
  // Add the yield operation.
  op_builder.create<mlir::TFL::YieldOp>(op_loc, cloned_op->getResults());
  // Now emit into the function body again.
  op_builder.restoreInsertionPoint(saved_pos);

      tmp[5 - i] = hex.charAt(c & 0xF);
      c = (char) (c >> 4);
    }
    return String.copyValueOf(tmp);
  }

  // Fast matchers

  /** A matcher for which precomputation will not yield any significant benefit. */
  abstract static class FastMatcher extends CharMatcher {

    @Override
    public final CharMatcher precomputed() {
      return this;
    }

    @Override

		// is the respective default type.
		check.updateExprType(x.expr, Default(x.typ), true)
		check.updateExprType(y.expr, Default(y.typ), true)
	}

	// spec: "Comparison operators compare two operands and yield
	//        an untyped boolean value."
	x.typ = Typ[UntypedBool]
	return

Error:
	// We have an offending operand errOp and possibly an error cause.
	if cause == "" {

    %7 = "tf.FakeQuantWithMinMaxVarsPerChannel"(%arg1, %arg2, %arg3) {device = "", narrow_range = false, num_bits = 8 : i64} : (tensor<*xf32>, tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
    "tfl.yield"(%7) : (tensor<*xf32>) -> ()
  }) {device = "", narrow_range = false, num_bits = 8 : i64} : (tensor<3x4xf32>, tensor<4xf32>, tensor<4xf32>) -> tensor<3x4xf32>

		// is the respective default type.
		check.updateExprType(x.expr, Default(x.typ), true)
		check.updateExprType(y.expr, Default(y.typ), true)
	}

	// spec: "Comparison operators compare two operands and yield
	//        an untyped boolean value."
	x.typ = Typ[UntypedBool]
	return

Error:
	// We have an offending operand errOp and possibly an error cause.
	if cause == "" {