Fork the tf initializer logic to keras initializer.

PiperOrigin-RevId: 348571002
Change-Id: I753afd8a2eabb87991f3ff263a763e0e7c1531fa

tensorflow/python/keras/initializers/initializers_v2.py

@@ -19,12 +19,23 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import math
+
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.keras import backend
+from tensorflow.python.ops import array_ops
+from tensorflow.python.ops import gen_linalg_ops
 from tensorflow.python.ops import init_ops_v2
+from tensorflow.python.ops import linalg_ops
+from tensorflow.python.ops import math_ops
+from tensorflow.python.ops import random_ops
+from tensorflow.python.ops import stateless_random_ops
 from tensorflow.python.util.tf_export import keras_export
 
+_PARTITION_SHAPE = 'partition_shape'
+_PARTITION_OFFSET = 'partition_offset'
+
 
 @keras_export('keras.initializers.Initializer')
 class Initializer(object):
@@ -308,7 +319,7 @@ class RandomNormal(init_ops_v2.RandomNormal, Initializer):
 @keras_export('keras.initializers.TruncatedNormal',
               'keras.initializers.truncated_normal',
               v1=[])
-class TruncatedNormal(init_ops_v2.TruncatedNormal, Initializer):
+class TruncatedNormal(Initializer):
   """Initializer that generates a truncated normal distribution.
 
   Also available via the shortcut function
@@ -338,6 +349,12 @@ class TruncatedNormal(init_ops_v2.TruncatedNormal, Initializer):
       always produce the same random tensor for a given shape and dtype.
   """
 
+  def __init__(self, mean=0.0, stddev=0.05, seed=None):
+    self.mean = mean
+    self.stddev = stddev
+    self.seed = seed
+    self._random_generator = _RandomGenerator(seed)
+
   def __call__(self, shape, dtype=None, **kwargs):
     """Returns a tensor object initialized to random normal values (truncated).
 
@@ -349,14 +366,25 @@ class TruncatedNormal(init_ops_v2.TruncatedNormal, Initializer):
         `tf.keras.backend.set_floatx(float_dtype)`)
       **kwargs: Additional keyword arguments.
     """
-    return super(TruncatedNormal, self).__call__(
+    _validate_kwargs(self.__class__.__name__, kwargs)
-        shape, dtype=_get_dtype(dtype), **kwargs)
+    dtype = _assert_float_dtype(_get_dtype(dtype))
+    if _PARTITION_SHAPE in kwargs:
+      shape = kwargs[_PARTITION_SHAPE]
+    return self._random_generator.truncated_normal(shape, self.mean,
+                                                   self.stddev, dtype)
+
+  def get_config(self):
+    return {
+        'mean': self.mean,
+        'stddev': self.stddev,
+        'seed': self.seed
+    }
 
 
 @keras_export('keras.initializers.VarianceScaling',
               'keras.initializers.variance_scaling',
               v1=[])
-class VarianceScaling(init_ops_v2.VarianceScaling, Initializer):
+class VarianceScaling(Initializer):
   """Initializer capable of adapting its scale to the shape of weights tensors.
 
   Also available via the shortcut function
@@ -395,6 +423,28 @@ class VarianceScaling(init_ops_v2.VarianceScaling, Initializer):
       always produce the same random tensor for a given shape and dtype.
   """
 
+  def __init__(self,
+               scale=1.0,
+               mode='fan_in',
+               distribution='truncated_normal',
+               seed=None):
+    if scale <= 0.:
+      raise ValueError('`scale` must be positive float.')
+    if mode not in {'fan_in', 'fan_out', 'fan_avg'}:
+      raise ValueError('Invalid `mode` argument:', mode)
+    distribution = distribution.lower()
+    # Compatibility with keras-team/keras.
+    if distribution == 'normal':
+      distribution = 'truncated_normal'
+    if distribution not in {'uniform', 'truncated_normal',
+                            'untruncated_normal'}:
+      raise ValueError('Invalid `distribution` argument:', distribution)
+    self.scale = scale
+    self.mode = mode
+    self.distribution = distribution
+    self.seed = seed
+    self._random_generator = _RandomGenerator(seed)
+
   def __call__(self, shape, dtype=None, **kwargs):
     """Returns a tensor object initialized as specified by the initializer.
 
@@ -406,14 +456,42 @@ class VarianceScaling(init_ops_v2.VarianceScaling, Initializer):
         `tf.keras.backend.set_floatx(float_dtype)`)
       **kwargs: Additional keyword arguments.
     """
-    return super(VarianceScaling, self).__call__(
+    _validate_kwargs(self.__class__.__name__, kwargs)
-        shape, dtype=_get_dtype(dtype), **kwargs)
+    dtype = _assert_float_dtype(_get_dtype(dtype))
+    scale = self.scale
+    fan_in, fan_out = _compute_fans(shape)
+    if _PARTITION_SHAPE in kwargs:
+      shape = kwargs[_PARTITION_SHAPE]
+    if self.mode == 'fan_in':
+      scale /= max(1., fan_in)
+    elif self.mode == 'fan_out':
+      scale /= max(1., fan_out)
+    else:
+      scale /= max(1., (fan_in + fan_out) / 2.)
+    if self.distribution == 'truncated_normal':
+      # constant from scipy.stats.truncnorm.std(a=-2, b=2, loc=0., scale=1.)
+      stddev = math.sqrt(scale) / .87962566103423978
+      return self._random_generator.truncated_normal(shape, 0.0, stddev, dtype)
+    elif self.distribution == 'untruncated_normal':
+      stddev = math.sqrt(scale)
+      return self._random_generator.random_normal(shape, 0.0, stddev, dtype)
+    else:
+      limit = math.sqrt(3.0 * scale)
+      return self._random_generator.random_uniform(shape, -limit, limit, dtype)
+
+  def get_config(self):
+    return {
+        'scale': self.scale,
+        'mode': self.mode,
+        'distribution': self.distribution,
+        'seed': self.seed
+    }
 
 
 @keras_export('keras.initializers.Orthogonal',
               'keras.initializers.orthogonal',
               v1=[])
-class Orthogonal(init_ops_v2.Orthogonal, Initializer):
+class Orthogonal(Initializer):
   """Initializer that generates an orthogonal matrix.
 
   Also available via the shortcut function `tf.keras.initializers.orthogonal`.
@@ -449,6 +527,11 @@ class Orthogonal(init_ops_v2.Orthogonal, Initializer):
       ([pdf](https://arxiv.org/pdf/1312.6120.pdf))
   """
 
+  def __init__(self, gain=1.0, seed=None):
+    self.gain = gain
+    self.seed = seed
+    self._random_generator = _RandomGenerator(seed)
+
   def __call__(self, shape, dtype=None, **kwargs):
     """Returns a tensor object initialized to an orthogonal matrix.
 
@@ -460,14 +543,39 @@ class Orthogonal(init_ops_v2.Orthogonal, Initializer):
        (via `tf.keras.backend.set_floatx(float_dtype)`)
       **kwargs: Additional keyword arguments.
     """
-    return super(Orthogonal, self).__call__(
+    _validate_kwargs(self.__class__.__name__, kwargs, support_partition=False)
-        shape, dtype=_get_dtype(dtype), **kwargs)
+    dtype = _assert_float_dtype(_get_dtype(dtype))
+    # Check the shape
+    if len(shape) < 2:
+      raise ValueError('The tensor to initialize must be '
+                       'at least two-dimensional')
+    # Flatten the input shape with the last dimension remaining
+    # its original shape so it works for conv2d
+    num_rows = 1
+    for dim in shape[:-1]:
+      num_rows *= dim
+    num_cols = shape[-1]
+    flat_shape = (max(num_cols, num_rows), min(num_cols, num_rows))
+
+    # Generate a random matrix
+    a = self._random_generator.random_normal(flat_shape, dtype=dtype)
+    # Compute the qr factorization
+    q, r = gen_linalg_ops.qr(a, full_matrices=False)
+    # Make Q uniform
+    d = array_ops.tensor_diag_part(r)
+    q *= math_ops.sign(d)
+    if num_rows < num_cols:
+      q = array_ops.matrix_transpose(q)
+    return self.gain * array_ops.reshape(q, shape)
+
+  def get_config(self):
+    return {'gain': self.gain, 'seed': self.seed}
 
 
 @keras_export('keras.initializers.Identity',
               'keras.initializers.identity',
               v1=[])
-class Identity(init_ops_v2.Identity, Initializer):
+class Identity(Initializer):
   """Initializer that generates the identity matrix.
 
   Also available via the shortcut function `tf.keras.initializers.identity`.
@@ -488,6 +596,9 @@ class Identity(init_ops_v2.Identity, Initializer):
     gain: Multiplicative factor to apply to the identity matrix.
   """
 
+  def __init__(self, gain=1.0):
+    self.gain = gain
+
   def __call__(self, shape, dtype=None, **kwargs):
     """Returns a tensor object initialized to a 2D identity matrix.
 
@@ -499,8 +610,16 @@ class Identity(init_ops_v2.Identity, Initializer):
        (via `tf.keras.backend.set_floatx(float_dtype)`)
       **kwargs: Additional keyword arguments.
     """
-    return super(Identity, self).__call__(
+    _validate_kwargs(self.__class__.__name__, kwargs, support_partition=False)
-        shape, dtype=_get_dtype(dtype), **kwargs)
+    dtype = _assert_float_dtype(_get_dtype(dtype))
+    if len(shape) != 2:
+      raise ValueError(
+          'Identity matrix initializer can only be used for 2D matrices.')
+    initializer = linalg_ops.eye(*shape, dtype=dtype)
+    return self.gain * initializer
+
+  def get_config(self):
+    return {'gain': self.gain}
 
 
 @keras_export('keras.initializers.GlorotUniform',
@@ -765,3 +884,98 @@ def _get_dtype(dtype):
   if dtype is None:
     dtype = backend.floatx()
   return dtypes.as_dtype(dtype)
+
+
+def _assert_float_dtype(dtype):
+  """Validate and return floating point type based on `dtype`.
+
+  `dtype` must be a floating point type.
+
+  Args:
+    dtype: The data type to validate.
+
+  Returns:
+    Validated type.
+
+  Raises:
+    ValueError: if `dtype` is not a floating point type.
+  """
+  dtype = dtypes.as_dtype(dtype)
+  if not dtype.is_floating:
+    raise ValueError('Expected floating point type, got %s.' % dtype)
+  return dtype
+
+
+class _RandomGenerator(object):
+  """Random generator that selects appropriate random ops."""
+
+  def __init__(self, seed=None):
+    super(_RandomGenerator, self).__init__()
+    if seed is not None:
+      # Stateless random ops requires 2-int seed.
+      self.seed = [seed, 0]
+    else:
+      self.seed = None
+
+  def random_normal(self, shape, mean=0.0, stddev=1, dtype=dtypes.float32):
+    """A deterministic random normal if seed is passed."""
+    if self.seed:
+      op = stateless_random_ops.stateless_random_normal
+    else:
+      op = random_ops.random_normal
+    return op(
+        shape=shape, mean=mean, stddev=stddev, dtype=dtype, seed=self.seed)
+
+  def random_uniform(self, shape, minval, maxval, dtype):
+    """A deterministic random uniform if seed is passed."""
+    if self.seed:
+      op = stateless_random_ops.stateless_random_uniform
+    else:
+      op = random_ops.random_uniform
+    return op(
+        shape=shape, minval=minval, maxval=maxval, dtype=dtype, seed=self.seed)
+
+  def truncated_normal(self, shape, mean, stddev, dtype):
+    """A deterministic truncated normal if seed is passed."""
+    if self.seed:
+      op = stateless_random_ops.stateless_truncated_normal
+    else:
+      op = random_ops.truncated_normal
+    return op(
+        shape=shape, mean=mean, stddev=stddev, dtype=dtype, seed=self.seed)
+
+
+def _compute_fans(shape):
+  """Computes the number of input and output units for a weight shape.
+
+  Args:
+    shape: Integer shape tuple or TF tensor shape.
+
+  Returns:
+    A tuple of integer scalars (fan_in, fan_out).
+  """
+  if len(shape) < 1:  # Just to avoid errors for constants.
+    fan_in = fan_out = 1
+  elif len(shape) == 1:
+    fan_in = fan_out = shape[0]
+  elif len(shape) == 2:
+    fan_in = shape[0]
+    fan_out = shape[1]
+  else:
+    # Assuming convolution kernels (2D, 3D, or more).
+    # kernel shape: (..., input_depth, depth)
+    receptive_field_size = 1
+    for dim in shape[:-2]:
+      receptive_field_size *= dim
+    fan_in = shape[-2] * receptive_field_size
+    fan_out = shape[-1] * receptive_field_size
+  return int(fan_in), int(fan_out)
+
+
+def _validate_kwargs(cls_name, kwargs, support_partition=True):
+  for kwarg in kwargs:
+    if kwarg not in [_PARTITION_SHAPE, _PARTITION_OFFSET]:
+      raise TypeError('Unknown keyword arguments: %s' % kwarg)
+    elif not support_partition:
+      raise ValueError('%s initializer doesn\'t support partition-related '
+                       'arguments' % cls_name)

tensorflow/tools/api/golden/v2/tensorflow.initializers.-glorot-normal.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.initializers.GlorotNormal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.GlorotNormal\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.-glorot-uniform.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.initializers.GlorotUniform"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.GlorotUniform\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.-he-normal.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.initializers.HeNormal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.HeNormal\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.-he-uniform.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.initializers.HeUniform"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.HeUniform\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.-identity.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.initializers.Identity"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Identity\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Identity\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.-lecun-normal.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.initializers.LecunNormal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.LecunNormal\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.-lecun-uniform.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.initializers.LecunUniform"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.LecunUniform\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.-orthogonal.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.initializers.Orthogonal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Orthogonal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Orthogonal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.-truncated-normal.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.initializers.TruncatedNormal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.TruncatedNormal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.TruncatedNormal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.-variance-scaling.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.initializers.VarianceScaling"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.glorot_normal.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.initializers.glorot_normal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.GlorotNormal\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.glorot_uniform.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.initializers.glorot_uniform"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.GlorotUniform\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.he_normal.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.initializers.he_normal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.HeNormal\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.he_uniform.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.initializers.he_uniform"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.HeUniform\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.identity.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.initializers.identity"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Identity\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Identity\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.lecun_normal.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.initializers.lecun_normal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.LecunNormal\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.lecun_uniform.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.initializers.lecun_uniform"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.LecunUniform\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.orthogonal.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.initializers.orthogonal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Orthogonal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Orthogonal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.truncated_normal.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.initializers.truncated_normal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.TruncatedNormal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.TruncatedNormal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.initializers.variance_scaling.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.initializers.variance_scaling"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.-glorot-normal.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.keras.initializers.GlorotNormal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.GlorotNormal\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.-glorot-uniform.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.keras.initializers.GlorotUniform"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.GlorotUniform\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.-he-normal.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.keras.initializers.HeNormal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.HeNormal\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.-he-uniform.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.keras.initializers.HeUniform"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.HeUniform\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.-identity.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.keras.initializers.Identity"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Identity\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Identity\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.-lecun-normal.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.keras.initializers.LecunNormal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.LecunNormal\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.-lecun-uniform.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.keras.initializers.LecunUniform"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.LecunUniform\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.-orthogonal.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.keras.initializers.Orthogonal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Orthogonal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Orthogonal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.-truncated-normal.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.keras.initializers.TruncatedNormal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.TruncatedNormal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.TruncatedNormal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.-variance-scaling.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.keras.initializers.VarianceScaling"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.glorot_normal.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.keras.initializers.glorot_normal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.GlorotNormal\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.glorot_uniform.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.keras.initializers.glorot_uniform"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.GlorotUniform\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.he_normal.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.keras.initializers.he_normal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.HeNormal\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.he_uniform.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.keras.initializers.he_uniform"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.HeUniform\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.identity.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.keras.initializers.identity"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Identity\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Identity\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.lecun_normal.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.keras.initializers.lecun_normal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.LecunNormal\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.lecun_uniform.pbtxt

@@ -2,8 +2,6 @@ path: "tensorflow.keras.initializers.lecun_uniform"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.LecunUniform\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.orthogonal.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.keras.initializers.orthogonal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Orthogonal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Orthogonal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.truncated_normal.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.keras.initializers.truncated_normal"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.TruncatedNormal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.TruncatedNormal\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {

tensorflow/tools/api/golden/v2/tensorflow.keras.initializers.variance_scaling.pbtxt

@@ -1,8 +1,6 @@
 path: "tensorflow.keras.initializers.variance_scaling"
 tf_class {
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.VarianceScaling\'>"
-  is_instance: "<class \'tensorflow.python.ops.init_ops_v2.Initializer\'>"
   is_instance: "<class \'tensorflow.python.keras.initializers.initializers_v2.Initializer\'>"
   is_instance: "<type \'object\'>"
   member_method {