message: Getting rid of MOVING_AVERAGE_VARIABLES collection usage in quantize_ops.
diff: @@ -49,7 +49,7 @@ def _ModelVariable(name,
  collections=None,
  trainable=None):
  collections = list(collections or [])
  - collections += [ops.GraphKeys.GLOBAL_VARIABLES, ops.GraphKeys.MODEL_VARIABLES]
  + collections += [ops.GraphKeys.GLOBAL_VARIABLES]
  return variable_scope.get_variable(
  name,
  shape=shape,
  @@ -62,7 +62,7 @@ def LastValueQuantize(inputs,
  per_channel=False,
  init_min=-6.0,
  init_max=6.0,
  - vars_collection=ops.GraphKeys.MOVING_AVERAGE_VARIABLES,
  + vars_collection=None,
  name_prefix='LastValueQuant',
  reuse=None,
  is_training=True,
  @@ -104,17 +104,18 @@ def LastValueQuantize(inputs,
  else:
  min_max_shape = []
  + vars_collections = [vars_collection] if vars_collection else []
  min_var = _ModelVariable(
  'min',
  shape=min_max_shape,
  initializer=init_ops.constant_initializer(init_min),
  - collections=[vars_collection],
  + collections=vars_collections,
  trainable=False)
  max_var = _ModelVariable(
  'max',
  shape=min_max_shape,
  initializer=init_ops.constant_initializer(init_max),
  - collections=[vars_collection],
  + collections=vars_collections,
  trainable=False)
  if not is_training:
  return _FakeQuantWithMinMaxVars(
  @@ -212,17 +213,18 @@ def MovingAvgQuantize(inputs,
  else:
  min_max_shape = []
  + vars_collections = [vars_collection] if vars_collection else []
  min_var = _ModelVariable(
  'min',
  shape=min_max_shape,
  initializer=init_ops.constant_initializer(init_min),
  - collections=[vars_collection],
  + collections=vars_collections,
  trainable=False)
  max_var = _ModelVariable(
  'max',
  shape=min_max_shape,
  initializer=init_ops.constant_initializer(init_max),
  - collections=[vars_collection],
  + collections=vars_collections,
  trainable=False)
  if not is_training:
  return _FakeQuantWithMinMaxVars(
  