Use distribution_util.arguments instead of locals. This fixes a bug in newer python version

where locals is a dynamic list.

PiperOrigin-RevId: 196150149

35 files changed, 49 insertions, 40 deletions

diff --git a/tensorflow/contrib/distributions/python/ops/autoregressive.py b/tensorflow/contrib/distributions/python/ops/autoregressive.py
index 88ed012784..d813831bef 100644
--- a/tensorflow/contrib/distributions/python/ops/autoregressive.py
+++ b/tensorflow/contrib/distributions/python/ops/autoregressive.py
@@ -144,7 +144,7 @@ class Autoregressive(distribution_lib.Distribution):
         `distribution_fn(sample0).event_shape.num_elements()` are both `None`.
       ValueError: if `num_steps < 1`.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name) as name:
       self._distribution_fn = distribution_fn
       self._sample0 = sample0
diff --git a/tensorflow/contrib/distributions/python/ops/batch_reshape.py b/tensorflow/contrib/distributions/python/ops/batch_reshape.py
index bf5590cd55..8a4041cf43 100644
--- a/tensorflow/contrib/distributions/python/ops/batch_reshape.py
+++ b/tensorflow/contrib/distributions/python/ops/batch_reshape.py
@@ -28,6 +28,7 @@ from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import check_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.ops.distributions import distribution as distribution_lib
+from tensorflow.python.ops.distributions import util as distribution_util
 
 
 __all__ = [
@@ -104,7 +105,7 @@ class BatchReshape(distribution_lib.Distribution):
       ValueError: if `batch_shape` size is not the same as a
         `distribution.batch_shape` size.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     name = name or "BatchReshape" + distribution.name
     self._distribution = distribution
     with ops.name_scope(name, values=[batch_shape]) as name:
diff --git a/tensorflow/contrib/distributions/python/ops/binomial.py b/tensorflow/contrib/distributions/python/ops/binomial.py
index 12d1603178..24b26bf124 100644
--- a/tensorflow/contrib/distributions/python/ops/binomial.py
+++ b/tensorflow/contrib/distributions/python/ops/binomial.py
@@ -163,7 +163,7 @@ class Binomial(distribution.Distribution):
         more of the statistic's batch members are undefined.
       name: Python `str` name prefixed to Ops created by this class.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[total_count, logits, probs]) as name:
       self._total_count = self._maybe_assert_valid_total_count(
           ops.convert_to_tensor(total_count, name="total_count"),
diff --git a/tensorflow/contrib/distributions/python/ops/cauchy.py b/tensorflow/contrib/distributions/python/ops/cauchy.py
index daacfe657f..f5ffdd8731 100644
--- a/tensorflow/contrib/distributions/python/ops/cauchy.py
+++ b/tensorflow/contrib/distributions/python/ops/cauchy.py
@@ -29,6 +29,7 @@ from tensorflow.python.ops import check_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.ops import random_ops
 from tensorflow.python.ops.distributions import distribution
+from tensorflow.python.ops.distributions import util as distribution_util
 
 __all__ = [
     "Cauchy",
@@ -120,7 +121,7 @@ class Cauchy(distribution.Distribution):
     Raises:
       TypeError: if `loc` and `scale` have different `dtype`.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[loc, scale]) as name:
       with ops.control_dependencies([check_ops.assert_positive(scale)]
                                     if validate_args else []):
diff --git a/tensorflow/contrib/distributions/python/ops/chi2.py b/tensorflow/contrib/distributions/python/ops/chi2.py
index c77c5fd208..08cdc15828 100644
--- a/tensorflow/contrib/distributions/python/ops/chi2.py
+++ b/tensorflow/contrib/distributions/python/ops/chi2.py
@@ -25,6 +25,7 @@ from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import check_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.ops.distributions import gamma
+from tensorflow.python.ops.distributions import util as distribution_util
 
 
 __all__ = [
@@ -83,7 +84,7 @@ class Chi2(gamma.Gamma):
         more of the statistic's batch members are undefined.
       name: Python `str` name prefixed to Ops created by this class.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     # Even though all stats of chi2 are defined for valid parameters, this is
     # not true in the parent class "gamma."  therefore, passing
     # allow_nan_stats=True
@@ -119,7 +120,7 @@ class Chi2WithAbsDf(Chi2):
                validate_args=False,
                allow_nan_stats=True,
                name="Chi2WithAbsDf"):
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[df]) as name:
       super(Chi2WithAbsDf, self).__init__(
           df=math_ops.floor(
diff --git a/tensorflow/contrib/distributions/python/ops/deterministic.py b/tensorflow/contrib/distributions/python/ops/deterministic.py
index a42350430e..6d7d6d307b 100644
--- a/tensorflow/contrib/distributions/python/ops/deterministic.py
+++ b/tensorflow/contrib/distributions/python/ops/deterministic.py
@@ -32,6 +32,7 @@ from tensorflow.python.ops import check_ops
 from tensorflow.python.ops import control_flow_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.ops.distributions import distribution
+from tensorflow.python.ops.distributions import util as distribution_util
 
 __all__ = [
     "Deterministic",
@@ -86,7 +87,7 @@ class _BaseDeterministic(distribution.Distribution):
     Raises:
       ValueError:  If `loc` is a scalar.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[loc, atol, rtol]) as name:
       loc = ops.convert_to_tensor(loc, name="loc")
       if is_vector and validate_args:
diff --git a/tensorflow/contrib/distributions/python/ops/geometric.py b/tensorflow/contrib/distributions/python/ops/geometric.py
index 53dd42f4c8..446cff6ec2 100644
--- a/tensorflow/contrib/distributions/python/ops/geometric.py
+++ b/tensorflow/contrib/distributions/python/ops/geometric.py
@@ -85,7 +85,7 @@ class Geometric(distribution.Distribution):
       name: Python `str` name prefixed to Ops created by this class.
     """
 
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[logits, probs]) as name:
       self._logits, self._probs = distribution_util.get_logits_and_probs(
           logits, probs, validate_args=validate_args, name=name)
diff --git a/tensorflow/contrib/distributions/python/ops/gumbel.py b/tensorflow/contrib/distributions/python/ops/gumbel.py
index 2c261073ee..ed9ea6f4f3 100644
--- a/tensorflow/contrib/distributions/python/ops/gumbel.py
+++ b/tensorflow/contrib/distributions/python/ops/gumbel.py
@@ -29,6 +29,7 @@ from tensorflow.python.ops import check_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.ops import random_ops
 from tensorflow.python.ops.distributions import distribution
+from tensorflow.python.ops.distributions import util as distribution_util
 
 
 class _Gumbel(distribution.Distribution):
@@ -124,7 +125,7 @@ class _Gumbel(distribution.Distribution):
     Raises:
       TypeError: if loc and scale are different dtypes.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[loc, scale]) as name:
       with ops.control_dependencies([check_ops.assert_positive(scale)] if
                                     validate_args else []):
diff --git a/tensorflow/contrib/distributions/python/ops/half_normal.py b/tensorflow/contrib/distributions/python/ops/half_normal.py
index d0df2befd6..7e12767f6d 100644
--- a/tensorflow/contrib/distributions/python/ops/half_normal.py
+++ b/tensorflow/contrib/distributions/python/ops/half_normal.py
@@ -31,6 +31,7 @@ from tensorflow.python.ops import nn
 from tensorflow.python.ops import random_ops
 from tensorflow.python.ops.distributions import distribution
 from tensorflow.python.ops.distributions import special_math
+from tensorflow.python.ops.distributions import util as distribution_util
 
 
 __all__ = [
@@ -105,7 +106,7 @@ class HalfNormal(distribution.Distribution):
         if one or more of the statistic's batch members are undefined.
       name: Python `str` name prefixed to Ops created by this class.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[scale]) as name:
       with ops.control_dependencies([check_ops.assert_positive(scale)] if
                                     validate_args else []):
diff --git a/tensorflow/contrib/distributions/python/ops/independent.py b/tensorflow/contrib/distributions/python/ops/independent.py
index fbde55ef31..fa89fff3b7 100644
--- a/tensorflow/contrib/distributions/python/ops/independent.py
+++ b/tensorflow/contrib/distributions/python/ops/independent.py
@@ -29,6 +29,7 @@ from tensorflow.python.ops import check_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.ops.distributions import distribution as distribution_lib
 from tensorflow.python.ops.distributions import kullback_leibler
+from tensorflow.python.ops.distributions import util as distribution_util
 
 
 class Independent(distribution_lib.Distribution):
@@ -116,7 +117,7 @@ class Independent(distribution_lib.Distribution):
       ValueError: if `reinterpreted_batch_ndims` exceeds
         `distribution.batch_ndims`
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     name = name or "Independent" + distribution.name
     self._distribution = distribution
     with ops.name_scope(name) as name:
diff --git a/tensorflow/contrib/distributions/python/ops/inverse_gamma.py b/tensorflow/contrib/distributions/python/ops/inverse_gamma.py
index 502bd4f493..85e8e10466 100644
--- a/tensorflow/contrib/distributions/python/ops/inverse_gamma.py
+++ b/tensorflow/contrib/distributions/python/ops/inverse_gamma.py
@@ -125,7 +125,7 @@ class InverseGamma(distribution.Distribution):
     Raises:
       TypeError: if `concentration` and `rate` are different dtypes.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[concentration, rate]) as name:
       with ops.control_dependencies([
           check_ops.assert_positive(concentration),
@@ -280,7 +280,7 @@ class InverseGammaWithSoftplusConcentrationRate(InverseGamma):
                validate_args=False,
                allow_nan_stats=True,
                name="InverseGammaWithSoftplusConcentrationRate"):
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[concentration, rate]) as name:
       super(InverseGammaWithSoftplusConcentrationRate, self).__init__(
           concentration=nn.softplus(concentration,
diff --git a/tensorflow/contrib/distributions/python/ops/logistic.py b/tensorflow/contrib/distributions/python/ops/logistic.py
index c83b5bc2e3..0103283259 100644
--- a/tensorflow/contrib/distributions/python/ops/logistic.py
+++ b/tensorflow/contrib/distributions/python/ops/logistic.py
@@ -31,6 +31,7 @@ from tensorflow.python.ops import math_ops
 from tensorflow.python.ops import nn_ops
 from tensorflow.python.ops import random_ops
 from tensorflow.python.ops.distributions import distribution
+from tensorflow.python.ops.distributions import util as distribution_util
 
 
 class Logistic(distribution.Distribution):
@@ -119,7 +120,7 @@ class Logistic(distribution.Distribution):
     Raises:
       TypeError: if loc and scale are different dtypes.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[loc, scale]) as name:
       with ops.control_dependencies([check_ops.assert_positive(scale)] if
                                     validate_args else []):
diff --git a/tensorflow/contrib/distributions/python/ops/mixture.py b/tensorflow/contrib/distributions/python/ops/mixture.py
index 2ef294af2e..d54f30dc63 100644
--- a/tensorflow/contrib/distributions/python/ops/mixture.py
+++ b/tensorflow/contrib/distributions/python/ops/mixture.py
@@ -116,7 +116,7 @@ class Mixture(distribution.Distribution):
         matching static batch shapes, or all components do not
         have matching static event shapes.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     if not isinstance(cat, categorical.Categorical):
       raise TypeError("cat must be a Categorical distribution, but saw: %s" %
                       cat)
diff --git a/tensorflow/contrib/distributions/python/ops/mixture_same_family.py b/tensorflow/contrib/distributions/python/ops/mixture_same_family.py
index 0b1301e551..c7c90cf875 100644
--- a/tensorflow/contrib/distributions/python/ops/mixture_same_family.py
+++ b/tensorflow/contrib/distributions/python/ops/mixture_same_family.py
@@ -130,7 +130,7 @@ class MixtureSameFamily(distribution.Distribution):
       ValueError: if `mixture_distribution` categories does not equal
         `components_distribution` rightmost batch shape.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name) as name:
       self._mixture_distribution = mixture_distribution
       self._components_distribution = components_distribution
diff --git a/tensorflow/contrib/distributions/python/ops/mvn_diag.py b/tensorflow/contrib/distributions/python/ops/mvn_diag.py
index e3236c2db9..cad398582b 100644
--- a/tensorflow/contrib/distributions/python/ops/mvn_diag.py
+++ b/tensorflow/contrib/distributions/python/ops/mvn_diag.py
@@ -193,7 +193,7 @@ class MultivariateNormalDiag(
     Raises:
       ValueError: if at most `scale_identity_multiplier` is specified.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name) as name:
       with ops.name_scope("init", values=[
           loc, scale_diag, scale_identity_multiplier]):
@@ -224,7 +224,7 @@ class MultivariateNormalDiagWithSoftplusScale(MultivariateNormalDiag):
                validate_args=False,
                allow_nan_stats=True,
                name="MultivariateNormalDiagWithSoftplusScale"):
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[scale_diag]) as name:
       super(MultivariateNormalDiagWithSoftplusScale, self).__init__(
           loc=loc,
diff --git a/tensorflow/contrib/distributions/python/ops/mvn_diag_plus_low_rank.py b/tensorflow/contrib/distributions/python/ops/mvn_diag_plus_low_rank.py
index 2f6a6f198c..1c11594df3 100644
--- a/tensorflow/contrib/distributions/python/ops/mvn_diag_plus_low_rank.py
+++ b/tensorflow/contrib/distributions/python/ops/mvn_diag_plus_low_rank.py
@@ -215,7 +215,7 @@ class MultivariateNormalDiagPlusLowRank(
     Raises:
       ValueError: if at most `scale_identity_multiplier` is specified.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     def _convert_to_tensor(x, name):
       return None if x is None else ops.convert_to_tensor(x, name=name)
     with ops.name_scope(name) as name:
diff --git a/tensorflow/contrib/distributions/python/ops/mvn_full_covariance.py b/tensorflow/contrib/distributions/python/ops/mvn_full_covariance.py
index 5d06a396fe..47d7d13cf3 100644
--- a/tensorflow/contrib/distributions/python/ops/mvn_full_covariance.py
+++ b/tensorflow/contrib/distributions/python/ops/mvn_full_covariance.py
@@ -24,6 +24,7 @@ from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import check_ops
 from tensorflow.python.ops import control_flow_ops
 from tensorflow.python.ops import linalg_ops
+from tensorflow.python.ops.distributions import util as distribution_util
 
 
 __all__ = [
@@ -155,7 +156,7 @@ class MultivariateNormalFullCovariance(mvn_tril.MultivariateNormalTriL):
     Raises:
       ValueError: if neither `loc` nor `covariance_matrix` are specified.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
 
     # Convert the covariance_matrix up to a scale_tril and call MVNTriL.
     with ops.name_scope(name) as name:
diff --git a/tensorflow/contrib/distributions/python/ops/mvn_linear_operator.py b/tensorflow/contrib/distributions/python/ops/mvn_linear_operator.py
index 44c92312c7..79916fef8d 100644
--- a/tensorflow/contrib/distributions/python/ops/mvn_linear_operator.py
+++ b/tensorflow/contrib/distributions/python/ops/mvn_linear_operator.py
@@ -170,7 +170,7 @@ class MultivariateNormalLinearOperator(
       ValueError: if `scale` is unspecified.
       TypeError: if not `scale.dtype.is_floating`
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     if scale is None:
       raise ValueError("Missing required `scale` parameter.")
     if not scale.dtype.is_floating:
diff --git a/tensorflow/contrib/distributions/python/ops/mvn_tril.py b/tensorflow/contrib/distributions/python/ops/mvn_tril.py
index d6f8b731cb..d6b0ed994e 100644
--- a/tensorflow/contrib/distributions/python/ops/mvn_tril.py
+++ b/tensorflow/contrib/distributions/python/ops/mvn_tril.py
@@ -179,7 +179,7 @@ class MultivariateNormalTriL(
     Raises:
       ValueError: if neither `loc` nor `scale_tril` are specified.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     def _convert_to_tensor(x, name):
       return None if x is None else ops.convert_to_tensor(x, name=name)
     if loc is None and scale_tril is None:
diff --git a/tensorflow/contrib/distributions/python/ops/negative_binomial.py b/tensorflow/contrib/distributions/python/ops/negative_binomial.py
index eeaf9c0a5e..1085c56dc8 100644
--- a/tensorflow/contrib/distributions/python/ops/negative_binomial.py
+++ b/tensorflow/contrib/distributions/python/ops/negative_binomial.py
@@ -90,7 +90,7 @@ class NegativeBinomial(distribution.Distribution):
       name: Python `str` name prefixed to Ops created by this class.
     """
 
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[total_count, logits, probs]) as name:
       self._logits, self._probs = distribution_util.get_logits_and_probs(
           logits, probs, validate_args=validate_args, name=name)
diff --git a/tensorflow/contrib/distributions/python/ops/onehot_categorical.py b/tensorflow/contrib/distributions/python/ops/onehot_categorical.py
index 305b138fdc..a4b9f3b78d 100644
--- a/tensorflow/contrib/distributions/python/ops/onehot_categorical.py
+++ b/tensorflow/contrib/distributions/python/ops/onehot_categorical.py
@@ -115,7 +115,7 @@ class OneHotCategorical(distribution.Distribution):
         more of the statistic's batch members are undefined.
       name: Python `str` name prefixed to Ops created by this class.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[logits, probs]) as name:
       self._logits, self._probs = distribution_util.get_logits_and_probs(
           name=name, logits=logits, probs=probs, validate_args=validate_args,
diff --git a/tensorflow/contrib/distributions/python/ops/poisson.py b/tensorflow/contrib/distributions/python/ops/poisson.py
index a84aad6fc9..b345394021 100644
--- a/tensorflow/contrib/distributions/python/ops/poisson.py
+++ b/tensorflow/contrib/distributions/python/ops/poisson.py
@@ -93,7 +93,7 @@ class Poisson(distribution.Distribution):
       TypeError: if `rate` is not a float-type.
       TypeError: if `log_rate` is not a float-type.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[rate]) as name:
       if (rate is None) == (log_rate is None):
         raise ValueError("Must specify exactly one of `rate` and `log_rate`.")
diff --git a/tensorflow/contrib/distributions/python/ops/poisson_lognormal.py b/tensorflow/contrib/distributions/python/ops/poisson_lognormal.py
index 19c99dcee9..fe72091d7d 100644
--- a/tensorflow/contrib/distributions/python/ops/poisson_lognormal.py
+++ b/tensorflow/contrib/distributions/python/ops/poisson_lognormal.py
@@ -255,7 +255,7 @@ class PoissonLogNormalQuadratureCompound(distribution_lib.Distribution):
       TypeError: if `quadrature_grid` and `quadrature_probs` have different base
         `dtype`.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[loc, scale]) as name:
       if loc is not None:
         loc = ops.convert_to_tensor(loc, name="loc")
diff --git a/tensorflow/contrib/distributions/python/ops/quantized_distribution.py b/tensorflow/contrib/distributions/python/ops/quantized_distribution.py
index eb94760ad7..584d2c385f 100644
--- a/tensorflow/contrib/distributions/python/ops/quantized_distribution.py
+++ b/tensorflow/contrib/distributions/python/ops/quantized_distribution.py
@@ -263,7 +263,7 @@ class QuantizedDistribution(distributions.Distribution):
           `Distribution` or continuous.
       NotImplementedError:  If the base distribution does not implement `cdf`.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     values = (
         list(distribution.parameters.values()) +
         [low, high])
diff --git a/tensorflow/contrib/distributions/python/ops/relaxed_bernoulli.py b/tensorflow/contrib/distributions/python/ops/relaxed_bernoulli.py
index 84c8d29072..0362996e68 100644
--- a/tensorflow/contrib/distributions/python/ops/relaxed_bernoulli.py
+++ b/tensorflow/contrib/distributions/python/ops/relaxed_bernoulli.py
@@ -165,7 +165,7 @@ class RelaxedBernoulli(transformed_distribution.TransformedDistribution):
     Raises:
       ValueError: If both `probs` and `logits` are passed, or if neither.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[logits, probs, temperature]) as name:
       with ops.control_dependencies([check_ops.assert_positive(temperature)]
                                     if validate_args else []):
diff --git a/tensorflow/contrib/distributions/python/ops/relaxed_onehot_categorical.py b/tensorflow/contrib/distributions/python/ops/relaxed_onehot_categorical.py
index 325f41e37c..910c430ae7 100644
--- a/tensorflow/contrib/distributions/python/ops/relaxed_onehot_categorical.py
+++ b/tensorflow/contrib/distributions/python/ops/relaxed_onehot_categorical.py
@@ -162,7 +162,7 @@ class ExpRelaxedOneHotCategorical(distribution.Distribution):
         more of the statistic's batch members are undefined.
       name: Python `str` name prefixed to Ops created by this class.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[logits, probs, temperature]) as name:
 
       self._logits, self._probs = distribution_util.get_logits_and_probs(
diff --git a/tensorflow/contrib/distributions/python/ops/sinh_arcsinh.py b/tensorflow/contrib/distributions/python/ops/sinh_arcsinh.py
index 03828fa612..f04dc8da39 100644
--- a/tensorflow/contrib/distributions/python/ops/sinh_arcsinh.py
+++ b/tensorflow/contrib/distributions/python/ops/sinh_arcsinh.py
@@ -132,7 +132,7 @@ class SinhArcsinh(transformed_distribution.TransformedDistribution):
         if one or more of the statistic's batch members are undefined.
       name: Python `str` name prefixed to Ops created by this class.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
 
     with ops.name_scope(name,
                         values=[loc, scale, skewness, tailweight]) as name:
diff --git a/tensorflow/contrib/distributions/python/ops/vector_diffeomixture.py b/tensorflow/contrib/distributions/python/ops/vector_diffeomixture.py
index af6ff8162b..cd6d749959 100644
--- a/tensorflow/contrib/distributions/python/ops/vector_diffeomixture.py
+++ b/tensorflow/contrib/distributions/python/ops/vector_diffeomixture.py
@@ -395,7 +395,7 @@ class VectorDiffeomixture(distribution_lib.Distribution):
       ValueError: if `not distribution.is_scalar_batch`.
       ValueError: if `not distribution.is_scalar_event`.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[mix_loc, temperature]) as name:
       if not scale or len(scale) < 2:
         raise ValueError("Must specify list (or list-like object) of scale "
diff --git a/tensorflow/contrib/distributions/python/ops/vector_exponential_diag.py b/tensorflow/contrib/distributions/python/ops/vector_exponential_diag.py
index e265b5d0f7..3465d66b30 100644
--- a/tensorflow/contrib/distributions/python/ops/vector_exponential_diag.py
+++ b/tensorflow/contrib/distributions/python/ops/vector_exponential_diag.py
@@ -175,7 +175,7 @@ class VectorExponentialDiag(
     Raises:
       ValueError: if at most `scale_identity_multiplier` is specified.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name) as name:
       with ops.name_scope("init", values=[
           loc, scale_diag, scale_identity_multiplier]):
diff --git a/tensorflow/contrib/distributions/python/ops/vector_exponential_linear_operator.py b/tensorflow/contrib/distributions/python/ops/vector_exponential_linear_operator.py
index 89136d6760..2c31b01984 100644
--- a/tensorflow/contrib/distributions/python/ops/vector_exponential_linear_operator.py
+++ b/tensorflow/contrib/distributions/python/ops/vector_exponential_linear_operator.py
@@ -175,7 +175,7 @@ class VectorExponentialLinearOperator(
       ValueError: if `scale` is unspecified.
       TypeError: if not `scale.dtype.is_floating`
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     if scale is None:
       raise ValueError("Missing required `scale` parameter.")
     if not scale.dtype.is_floating:
diff --git a/tensorflow/contrib/distributions/python/ops/vector_laplace_diag.py b/tensorflow/contrib/distributions/python/ops/vector_laplace_diag.py
index 8dd983b750..6a36018d6f 100644
--- a/tensorflow/contrib/distributions/python/ops/vector_laplace_diag.py
+++ b/tensorflow/contrib/distributions/python/ops/vector_laplace_diag.py
@@ -210,7 +210,7 @@ class VectorLaplaceDiag(
     Raises:
       ValueError: if at most `scale_identity_multiplier` is specified.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name):
       with ops.name_scope("init", values=[
           loc, scale_diag, scale_identity_multiplier]):
diff --git a/tensorflow/contrib/distributions/python/ops/vector_laplace_linear_operator.py b/tensorflow/contrib/distributions/python/ops/vector_laplace_linear_operator.py
index ec485c95c1..97e5c76d80 100644
--- a/tensorflow/contrib/distributions/python/ops/vector_laplace_linear_operator.py
+++ b/tensorflow/contrib/distributions/python/ops/vector_laplace_linear_operator.py
@@ -191,7 +191,7 @@ class VectorLaplaceLinearOperator(
       ValueError: if `scale` is unspecified.
       TypeError: if not `scale.dtype.is_floating`
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     if scale is None:
       raise ValueError("Missing required `scale` parameter.")
     if not scale.dtype.is_floating:
diff --git a/tensorflow/contrib/distributions/python/ops/vector_sinh_arcsinh_diag.py b/tensorflow/contrib/distributions/python/ops/vector_sinh_arcsinh_diag.py
index 1438ede265..ff5ca45257 100644
--- a/tensorflow/contrib/distributions/python/ops/vector_sinh_arcsinh_diag.py
+++ b/tensorflow/contrib/distributions/python/ops/vector_sinh_arcsinh_diag.py
@@ -163,7 +163,7 @@ class VectorSinhArcsinhDiag(transformed_distribution.TransformedDistribution):
     Raises:
       ValueError: if at most `scale_identity_multiplier` is specified.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
 
     with ops.name_scope(
         name,
diff --git a/tensorflow/contrib/distributions/python/ops/vector_student_t.py b/tensorflow/contrib/distributions/python/ops/vector_student_t.py
index 7e78ded9df..4742f75218 100644
--- a/tensorflow/contrib/distributions/python/ops/vector_student_t.py
+++ b/tensorflow/contrib/distributions/python/ops/vector_student_t.py
@@ -175,7 +175,7 @@ class _VectorStudentT(transformed_distribution.TransformedDistribution):
         if one or more of the statistic's batch members are undefined.
       name: Python `str` name prefixed to Ops created by this class.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     graph_parents = [df, loc, scale_identity_multiplier, scale_diag,
                      scale_tril, scale_perturb_factor, scale_perturb_diag]
     with ops.name_scope(name) as name:
diff --git a/tensorflow/contrib/distributions/python/ops/wishart.py b/tensorflow/contrib/distributions/python/ops/wishart.py
index 91453fed5d..f555867e7f 100644
--- a/tensorflow/contrib/distributions/python/ops/wishart.py
+++ b/tensorflow/contrib/distributions/python/ops/wishart.py
@@ -107,7 +107,7 @@ class _WishartLinearOperator(distribution.Distribution):
       ValueError: if df < k, where scale operator event shape is
         `(k, k)`
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     self._cholesky_input_output_matrices = cholesky_input_output_matrices
     with ops.name_scope(name) as name:
       with ops.name_scope("init", values=[df, scale_operator]):
@@ -530,7 +530,7 @@ class WishartCholesky(_WishartLinearOperator):
         more of the statistic's batch members are undefined.
       name: Python `str` name prefixed to Ops created by this class.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name, values=[scale]) as name:
       with ops.name_scope("init", values=[scale]):
         scale = ops.convert_to_tensor(scale)
@@ -646,7 +646,7 @@ class WishartFull(_WishartLinearOperator):
         more of the statistic's batch members are undefined.
       name: Python `str` name prefixed to Ops created by this class.
     """
-    parameters = locals()
+    parameters = distribution_util.parent_frame_arguments()
     with ops.name_scope(name) as name:
       with ops.name_scope("init", values=[scale]):
         scale = ops.convert_to_tensor(scale)