message: Remove partitioned_info as argument to initializer in Keras make_variable to work with the v2 initializers
diff: @@ -25,6 +25,7 @@ from tensorflow.python.framework import ops
  from tensorflow.python.keras import backend
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import init_ops
  +from tensorflow.python.ops import init_ops_v2
  from tensorflow.python.ops import variables as tf_variables
  from tensorflow.python.util import nest
  @@ -55,7 +56,6 @@ def make_variable(name,
  shape=None,
  dtype=dtypes.float32,
  initializer=None,
  - partition_info=None,
  trainable=None,
  caching_device=None,
  validate_shape=True,
  @@ -76,14 +76,12 @@ def make_variable(name,
  rid of this temporary solution.
  TODO(fchollet): remove this method when no longer needed.
  - TODO(fchollet): handle `partitioner` argument.
  Arguments:
  name: Variable name.
  shape: Variable shape.
  dtype: The type of the variable. Defaults to `self.dtype` or `float32`.
  initializer: Initializer instance (callable).
  - partition_info: Not handled at this time.
  trainable: Whether the variable should be part of the layer's
  "trainable_variables" (e.g. variables, biases)
  or "non_trainable_variables" (e.g. BatchNorm mean, stddev).
  @@ -123,8 +121,9 @@ def make_variable(name,
  # Instantiate initializer if provided initializer is a type object.
  if isinstance(initializer, type(init_ops.Initializer)):
  initializer = initializer(dtype=dtype)
  - init_val = lambda: initializer( # pylint: disable=g-long-lambda
  - shape, dtype=dtype, partition_info=partition_info)
  + elif isinstance(initializer, type(init_ops_v2.Initializer)):
  + initializer = initializer()
  + init_val = lambda: initializer(shape, dtype=dtype)
  variable_dtype = dtype.base_dtype
  if use_resource is None:
  use_resource = True
  