Branch 151792071

tensorflow/contrib/distributions/BUILD

@@ -15,7 +15,6 @@ py_library(
     srcs = glob(["python/ops/bijectors/*.py"]),
     srcs_version = "PY2AND3",
     deps = [
-        "//tensorflow/contrib/framework:framework_py",
         "//tensorflow/contrib/linalg:linalg_py",
         "//tensorflow/python:array_ops",
         "//tensorflow/python:check_ops",
@@ -41,7 +40,6 @@ py_library(
     srcs_version = "PY2AND3",
     deps = [
         ":bijectors_py",
-        "//tensorflow/contrib/framework:framework_py",
         "//tensorflow/contrib/linalg:linalg_py",
         "//tensorflow/python:array_ops",
         "//tensorflow/python:check_ops",

tensorflow/contrib/distributions/python/ops/beta.py

@@ -23,7 +23,6 @@
 from tensorflow.contrib.distributions.python.ops import distribution
 from tensorflow.contrib.distributions.python.ops import distribution_util
 from tensorflow.contrib.distributions.python.ops import kullback_leibler
-from tensorflow.contrib.framework.python.framework import tensor_util as contrib_tensor_util
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -157,7 +156,7 @@ def __init__(self,
       self._concentration0 = self._maybe_assert_valid_concentration(
           ops.convert_to_tensor(concentration0, name="concentration0"),
           validate_args)
-      contrib_tensor_util.assert_same_float_dtype([
+      check_ops.assert_same_float_dtype([
           self._concentration1, self._concentration0])
       self._total_concentration = self._concentration1 + self._concentration0
     super(Beta, self).__init__(

tensorflow/contrib/distributions/python/ops/bijectors/affine_impl.py

@@ -18,7 +18,6 @@
 from __future__ import division
 from __future__ import print_function
 
-from tensorflow.contrib import framework as contrib_framework
 from tensorflow.contrib.distributions.python.ops import operator_pd_cholesky
 from tensorflow.contrib.distributions.python.ops import operator_pd_diag
 from tensorflow.contrib.distributions.python.ops import operator_pd_identity
@@ -27,6 +26,7 @@
 from tensorflow.contrib.distributions.python.ops.shape import _DistributionShape
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
+from tensorflow.python.framework import tensor_util
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import check_ops
 from tensorflow.python.ops import control_flow_ops
@@ -359,7 +359,7 @@ def __init__(self,
           event_ndims=event_ndims,
           graph_parents=(
               [event_ndims] +
-              [self._scale] if contrib_framework.is_tensor(self._scale)
+              [self._scale] if tensor_util.is_tensor(self._scale)
               else self._scale.inputs +
               [self._shift] if self._shift is not None else []),
           is_constant_jacobian=True,

tensorflow/contrib/distributions/python/ops/distribution.py

@@ -26,7 +26,6 @@
 import numpy as np
 import six
 
-from tensorflow.contrib import framework as contrib_framework
 from tensorflow.contrib.distributions.python.ops import distribution_util
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -381,7 +380,7 @@ def __init__(self,
     """
     graph_parents = [] if graph_parents is None else graph_parents
     for i, t in enumerate(graph_parents):
-      if t is None or not contrib_framework.is_tensor(t):
+      if t is None or not tensor_util.is_tensor(t):
         raise ValueError("Graph parent item %d is not a Tensor; %s." % (i, t))
     self._dtype = dtype
     self._reparameterization_type = reparameterization_type

tensorflow/contrib/distributions/python/ops/distribution_util.py

@@ -23,7 +23,6 @@
 import math
 import numpy as np
 
-from tensorflow.contrib import framework as contrib_framework
 from tensorflow.contrib import linalg
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
@@ -514,7 +513,7 @@ def fill_lower_triangular(x, validate_args=False, name="fill_lower_triangular"):
     def tril_ids(n):
       """Internal helper to create vector of linear indices into y."""
       # Build the ids statically; chose 512 because it implies 1MiB.
-      if not contrib_framework.is_tensor(n) and n <= 512:
+      if not tensor_util.is_tensor(n) and n <= 512:
         ids = np.arange(n**2, dtype=np.int32)
         rows = (ids / n).astype(np.int32)  # Implicit floor.
         # We need to stop incrementing the index when we encounter

tensorflow/contrib/distributions/python/ops/gamma.py

@@ -23,7 +23,6 @@
 from tensorflow.contrib.distributions.python.ops import distribution
 from tensorflow.contrib.distributions.python.ops import distribution_util
 from tensorflow.contrib.distributions.python.ops import kullback_leibler
-from tensorflow.contrib.framework.python.framework import tensor_util as contrib_tensor_util
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -134,7 +133,7 @@ def __init__(self,
         self._concentration = array_ops.identity(
             concentration, name="concentration")
         self._rate = array_ops.identity(rate, name="rate")
-        contrib_tensor_util.assert_same_float_dtype(
+        check_ops.assert_same_float_dtype(
             [self._concentration, self._rate])
     super(Gamma, self).__init__(
         dtype=self._concentration.dtype,
@@ -249,7 +248,7 @@ def _mode(self):
           ], mode)
 
   def _maybe_assert_valid_sample(self, x):
-    contrib_tensor_util.assert_same_float_dtype(tensors=[x], dtype=self.dtype)
+    check_ops.assert_same_float_dtype(tensors=[x], dtype=self.dtype)
     if not self.validate_args:
       return x
     return control_flow_ops.with_dependencies([

tensorflow/contrib/distributions/python/ops/gumbel.py

@@ -21,7 +21,6 @@
 import math
 import numpy as np
 from tensorflow.contrib.distributions.python.ops import distribution
-from tensorflow.contrib.framework.python.framework import tensor_util as contrib_tensor_util
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -129,7 +128,7 @@ def __init__(self,
                                     validate_args else []):
         self._loc = array_ops.identity(loc, name="loc")
         self._scale = array_ops.identity(scale, name="scale")
-        contrib_tensor_util.assert_same_float_dtype([self._loc, self._scale])
+        check_ops.assert_same_float_dtype([self._loc, self._scale])
     super(_Gumbel, self).__init__(
         dtype=self._scale.dtype,
         reparameterization_type=distribution.FULLY_REPARAMETERIZED,

tensorflow/contrib/distributions/python/ops/inverse_gamma.py

@@ -22,7 +22,6 @@
 
 from tensorflow.contrib.distributions.python.ops import distribution
 from tensorflow.contrib.distributions.python.ops import distribution_util
-from tensorflow.contrib.framework.python.framework import tensor_util as contrib_tensor_util
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -134,7 +133,7 @@ def __init__(self,
         self._concentration = array_ops.identity(
             concentration, name="concentration")
         self._rate = array_ops.identity(rate, name="rate")
-        contrib_tensor_util.assert_same_float_dtype(
+        check_ops.assert_same_float_dtype(
             [self._concentration, self._rate])
     super(InverseGamma, self).__init__(
         dtype=self._concentration.dtype,
@@ -268,7 +267,7 @@ def _mode(self):
     return self.rate / (1. + self.concentration)
 
   def _maybe_assert_valid_sample(self, x):
-    contrib_tensor_util.assert_same_float_dtype(
+    check_ops.assert_same_float_dtype(
         tensors=[x], dtype=self.dtype)
     if not self.validate_args:
       return x

tensorflow/contrib/distributions/python/ops/laplace.py

@@ -24,7 +24,6 @@
 
 from tensorflow.contrib.distributions.python.ops import distribution
 from tensorflow.contrib.distributions.python.ops import special_math
-from tensorflow.contrib.framework.python.framework import tensor_util as contrib_tensor_util
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -105,7 +104,7 @@ def __init__(self,
                                     validate_args else []):
         self._loc = array_ops.identity(loc, name="loc")
         self._scale = array_ops.identity(scale, name="scale")
-        contrib_tensor_util.assert_same_float_dtype([self._loc, self._scale])
+        check_ops.assert_same_float_dtype([self._loc, self._scale])
       super(Laplace, self).__init__(
           dtype=self._loc.dtype,
           reparameterization_type=distribution.FULLY_REPARAMETERIZED,

tensorflow/contrib/distributions/python/ops/logistic.py

@@ -22,7 +22,6 @@
 import numpy as np
 
 from tensorflow.contrib.distributions.python.ops import distribution
-from tensorflow.contrib.framework.python.framework import tensor_util as contrib_tensor_util
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -127,7 +126,7 @@ def __init__(self,
                                     validate_args else []):
         self._loc = array_ops.identity(loc, name="loc")
         self._scale = array_ops.identity(scale, name="scale")
-        contrib_tensor_util.assert_same_float_dtype([self._loc, self._scale])
+        check_ops.assert_same_float_dtype([self._loc, self._scale])
     super(Logistic, self).__init__(
         dtype=self._scale.dtype,
         reparameterization_type=distribution.FULLY_REPARAMETERIZED,

tensorflow/contrib/distributions/python/ops/normal.py

@@ -23,7 +23,6 @@
 from tensorflow.contrib.distributions.python.ops import distribution
 from tensorflow.contrib.distributions.python.ops import kullback_leibler
 from tensorflow.contrib.distributions.python.ops import special_math
-from tensorflow.contrib.framework.python.framework import tensor_util as contrib_tensor_util
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -136,7 +135,7 @@ def __init__(self,
                                     validate_args else []):
         self._loc = array_ops.identity(loc, name="loc")
         self._scale = array_ops.identity(scale, name="scale")
-        contrib_tensor_util.assert_same_float_dtype([self._loc, self._scale])
+        check_ops.assert_same_float_dtype([self._loc, self._scale])
     super(Normal, self).__init__(
         dtype=self._scale.dtype,
         reparameterization_type=distribution.FULLY_REPARAMETERIZED,

tensorflow/contrib/distributions/python/ops/operator_pd_identity.py

@@ -20,7 +20,6 @@
 
 
 from tensorflow.contrib.distributions.python.ops import operator_pd
-from tensorflow.contrib.framework.python.framework import tensor_util as contrib_tensor_util
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -108,7 +107,7 @@ def _check_scale(self, scale, dtype):
       return scale
 
     # Further check that this is a rank 0, positive tensor.
-    scale = contrib_tensor_util.assert_scalar(scale)
+    scale = check_ops.assert_scalar(scale)
     return control_flow_ops.with_dependencies(
         [check_ops.assert_positive(scale)], scale)
 

tensorflow/contrib/distributions/python/ops/quantized_distribution.py

@@ -22,7 +22,6 @@
 
 from tensorflow.contrib.distributions.python.ops import distribution as distributions
 from tensorflow.contrib.distributions.python.ops import distribution_util
-from tensorflow.contrib.framework.python.framework import tensor_util as contrib_tensor_util
 from tensorflow.python.framework import ops
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import check_ops
@@ -225,7 +224,7 @@ def __init__(self,
         low = ops.convert_to_tensor(low, name="low")
       if high is not None:
         high = ops.convert_to_tensor(high, name="high")
-      contrib_tensor_util.assert_same_float_dtype(
+      check_ops.assert_same_float_dtype(
           tensors=[self.distribution, low, high])
 
       # We let QuantizedDistribution access _graph_parents since this class is

tensorflow/contrib/distributions/python/ops/student_t.py

@@ -22,7 +22,6 @@
 
 from tensorflow.contrib.distributions.python.ops import distribution
 from tensorflow.contrib.distributions.python.ops import distribution_util
-from tensorflow.contrib.framework.python.framework import tensor_util as contrib_tensor_util
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -161,7 +160,7 @@ def __init__(self,
         self._df = array_ops.identity(df, name="df")
         self._loc = array_ops.identity(loc, name="loc")
         self._scale = array_ops.identity(scale, name="scale")
-        contrib_tensor_util.assert_same_float_dtype(
+        check_ops.assert_same_float_dtype(
             (self._df, self._loc, self._scale))
     super(StudentT, self).__init__(
         dtype=self._scale.dtype,

tensorflow/contrib/distributions/python/ops/uniform.py

@@ -21,7 +21,6 @@
 import math
 
 from tensorflow.contrib.distributions.python.ops import distribution
-from tensorflow.contrib.framework.python.framework import tensor_util as contrib_tensor_util
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -108,7 +107,7 @@ def __init__(self,
       ] if validate_args else []):
         self._low = array_ops.identity(low, name="low")
         self._high = array_ops.identity(high, name="high")
-        contrib_tensor_util.assert_same_float_dtype([self._low, self._high])
+        check_ops.assert_same_float_dtype([self._low, self._high])
     super(Uniform, self).__init__(
         dtype=self._low.dtype,
         reparameterization_type=distribution.FULLY_REPARAMETERIZED,

tensorflow/contrib/distributions/python/ops/wishart.py

@@ -25,7 +25,6 @@
 from tensorflow.contrib.distributions.python.ops import distribution_util
 from tensorflow.contrib.distributions.python.ops import operator_pd_cholesky
 from tensorflow.contrib.distributions.python.ops import operator_pd_full
-from tensorflow.contrib.framework.python.framework import tensor_util as contrib_tensor_util
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -121,7 +120,7 @@ def __init__(self,
             df,
             dtype=scale_operator_pd.dtype,
             name="df")
-        contrib_tensor_util.assert_same_float_dtype(
+        check_ops.assert_same_float_dtype(
             (self._df, self._scale_operator_pd))
         if (self._scale_operator_pd.get_shape().ndims is None or
             self._scale_operator_pd.get_shape()[-1].value is None):

tensorflow/contrib/slim/python/slim/data/tfexample_decoder.py

@@ -417,7 +417,6 @@ def decode(self, serialized_example, items=None):
     """
     example = parsing_ops.parse_single_example(serialized_example,
                                                self._keys_to_features)
-    print(example.keys())
 
     # Reshape non-sparse elements just once:
     for k in self._keys_to_features:

tensorflow/core/BUILD

@@ -416,6 +416,14 @@ tf_cuda_library(
     deps = [":framework_internal"],
 )
 
+cc_library(
+    name = "overflow",
+    hdrs = ["util/overflow.h"],
+    deps = [
+        ":framework_lite",
+    ],
+)
+
 cc_library(
     name = "reader_base",
     srcs = ["framework/reader_base.cc"],
@@ -1852,6 +1860,18 @@ tf_cc_test(
     ],
 )
 
+tf_cc_test(
+    name = "util_overflow_test",
+    size = "small",
+    srcs = ["util/overflow_test.cc"],
+    deps = [
+        ":framework_lite",
+        ":overflow",
+        ":test",
+        ":test_main",
+    ],
+)
+
 cc_test(
     name = "lib_jpeg_jpeg_mem_unittest",
     srcs = ["lib/jpeg/jpeg_mem_unittest.cc"],

tensorflow/core/framework/node_def.proto

@@ -29,17 +29,15 @@ message NodeDef {
   // node should be placed.
   // The expected syntax for this string is as follows:
   //
-  // DEVICE_SPEC ::= COLOCATED_NODE | PARTIAL_SPEC
+  // DEVICE_SPEC ::= PARTIAL_SPEC
   //
-  // COLOCATED_NODE ::= "@" NODE_NAME  // See NodeDef.name above.
   // PARTIAL_SPEC ::= ("/" CONSTRAINT) *
   // CONSTRAINT ::= ("job:" JOB_NAME)
   //              | ("replica:" [1-9][0-9]*)
   //              | ("task:" [1-9][0-9]*)
   //              | ( ("gpu" | "cpu") ":" ([1-9][0-9]* | "*") )
   //
   // Valid values for this string include:
-  // * "@other/node"                         (colocate with "other/node")
   // * "/job:worker/replica:0/task:1/gpu:3"  (full specification)
   // * "/job:worker/gpu:3"                   (partial specification)
   // * ""                                    (no specification)

tensorflow/core/framework/remote_fused_graph_execute_info.proto

@@ -6,7 +6,7 @@ option java_outer_classname = "RemoteFusedGraphExecuteInfoProto";
 option java_multiple_files = true;
 option java_package = "org.tensorflow.framework";
 
-import "tensorflow/core/framework/node_def.proto";
+import "tensorflow/core/framework/graph.proto";
 import "tensorflow/core/framework/tensor_shape.proto";
 import "tensorflow/core/framework/types.proto";
 
@@ -19,8 +19,8 @@ message RemoteFusedGraphExecuteInfo {
     TensorShapeProto shape = 2;
   }
 
-  // Nodes in remote fused graph
-  repeated NodeDef node = 1;
+  // Definition of remote graph
+  GraphDef remote_graph = 1;
 
   // Remote fused graph input node name
   repeated string graph_input_node_name = 2;