regions accept the current value of the iteration variables as inputs.

  The condition region yields a tensor<i1> which, if false, will exit the loop.
  It can also, optionally and additionally, yield the iteration variables, which
  must be unchanged.

  The body region always has to yield the (possibly updated) iteration variables.

  The iteration variables are initialized to the Op input, and the results of the

// isPaddedField reports whether the i'th field of struct type t is followed
// by padding.
func isPaddedField(t Type, i int) bool {
	field := t.Field(i)
	if i+1 < t.NumField() {
		return field.Offset+field.Type.Size() != t.Field(i+1).Offset
	}
	return field.Offset+field.Type.Size() != t.Size()
}

// StructOf returns the struct type containing fields.
// The Offset and Index fields are ignored and computed as they would be

}

// 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

  def visit_block(self, block):
    return [self.visit(item) for item in block]

  def visit_Pass(self, node):
    if self.symbol_table.in_scf_scope():
      self._emit_with_loc('\nscf.yield', node)
    else:
      self._emit_with_loc('\ntfr.return', node)

  def visit_Attribute(self, node):
    node_type = self._get_inferred_type(node, None)
    if isinstance(node.value, ast.Name):

// are all in the testing namespace:
//
//
//  Range(begin, end [, step]) - Yields values {begin, begin+step,
//                               begin+step+step, ...}. The values do not
//                               include end. step defaults to 1.
//  Values(v1, v2, ..., vN)    - Yields values {v1, v2, ..., vN}.
//  ValuesIn(container)        - Yields values from a C-style array, an STL

        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,

// are all in the testing namespace:
//
//
//  Range(begin, end [, step]) - Yields values {begin, begin+step,
//                               begin+step+step, ...}. The values do not
//                               include end. step defaults to 1.
//  Values(v1, v2, ..., vN)    - Yields values {v1, v2, ..., vN}.
//  ValuesIn(container)        - Yields values from a C-style array, an STL

  /**
   * Divides an iterator into unmodifiable sublists of the given size (the final list may be
   * smaller). For example, partitioning an iterator containing {@code [a, b, c, d, e]} with a
   * partition size of 3 yields {@code [[a, b, c], [d, e]]} -- an outer iterator containing two
   * inner lists of three and two elements, all in the original order.
   *
   * <p>The returned lists implement {@link java.util.RandomAccess}.
   *

  /**
   * Divides an iterator into unmodifiable sublists of the given size (the final list may be
   * smaller). For example, partitioning an iterator containing {@code [a, b, c, d, e]} with a
   * partition size of 3 yields {@code [[a, b, c], [d, e]]} -- an outer iterator containing two
   * inner lists of three and two elements, all in the original order.
   *
   * <p>The returned lists implement {@link java.util.RandomAccess}.
   *

     * the encoded path will have a trailing '/'.
     *
     * Popping "/a/b/c/" yields "/a/b/". In this case the list of path segments goes from ["a",
     * "b", "c", ""] to ["a", "b", ""].
     *
     * Popping "/a/b/c" also yields "/a/b/". The list of path segments goes from ["a", "b", "c"]
     * to ["a", "b", ""].
     */
    private fun pop() {