TensorFlow: Removal of large assets and small other fixes.

Changes:

- Remove all large assets from the repoistory, incuding the other 50MiB
  model protobuf and a lot of images in our g3doc directory. We will
  maintain these assets externally for now.  g3doc images may be
  broken for a little bit, but the website will be fine, which
  is the important resource. By @vrv and @petewarden.  Updates
  READMES to reflect the external model resources.

- Fix to saver's latest_checkpoint function by Zhifeng

- Made protos visibility public by @vrv

- Updates to docs by @mrry, Andy

- Embed tensorboard resource for summary icon by Daniel

- More updates to backwars compat by @josh11b

Base CL: 108194981

Author: Vijay Vasudevan

tensorflow/core/BUILD

@@ -301,7 +301,7 @@ tf_proto_library(
     go_api_version = 2,
     java_api_version = 2,
     py_api_version = 2,  # TODO(irving): Handle 3
-    visibility = ["//tensorflow:internal"],
+    visibility = ["//visibility:public"],
 )
 
 cc_library(

tensorflow/core/framework/op_def_util.cc

@@ -499,4 +499,43 @@ Status OpDefCompatible(const OpDef& old_op, const OpDef& new_op) {
   return Status::OK();
 }
 
+Status OpDefAddedDefaultsUnchanged(const OpDef& old_op,
+                                   const OpDef& penultimate_op,
+                                   const OpDef& new_op) {
+  AttrMap new_attrs, old_attrs;
+  FillAttrMap(old_op, &old_attrs);
+  FillAttrMap(new_op, &new_attrs);
+
+  for (const auto& penultimate_attr : penultimate_op.attr()) {
+    const OpDef::AttrDef* old_attr =
+        gtl::FindPtrOrNull(old_attrs, penultimate_attr.name());
+    if (old_attr != nullptr) continue;  // attr wasn't added
+    const OpDef::AttrDef* new_attr =
+        gtl::FindPtrOrNull(new_attrs, penultimate_attr.name());
+
+    // These shouldn't happen if the op passed OpDefCompatible().
+    if (new_attr == nullptr) {
+      return errors::InvalidArgument("Missing attr '", penultimate_attr.name(),
+                                     "' in op: ", SummarizeOpDef(new_op));
+    }
+    if (!penultimate_attr.has_default_value() ||
+        !new_attr->has_default_value()) {
+      return errors::InvalidArgument("Missing default for attr '",
+                                     penultimate_attr.name(), "' in op: ",
+                                     SummarizeOpDef(new_op));
+    }
+
+    // Actually test that the attr's default value hasn't changed.
+    if (!AreAttrValuesEqual(penultimate_attr.default_value(),
+                            new_attr->default_value())) {
+      return errors::InvalidArgument(
+          "Can't change default value for attr '", penultimate_attr.name(),
+          "' from ", SummarizeAttrValue(penultimate_attr.default_value()),
+          " in op: ", SummarizeOpDef(new_op));
+    }
+  }
+
+  return Status::OK();
+}
+
 }  // namespace tensorflow

tensorflow/core/framework/op_def_util.h

@@ -32,6 +32,13 @@ string SummarizeOpDef(const OpDef& op_def);
 // REQUIRES: old_op and new_op must pass validation.
 Status OpDefCompatible(const OpDef& old_op, const OpDef& new_op);
 
+// Returns an error if any attr in penultimate_op that is not in old_op
+// has a different default value in new_op.  In general it is not safe
+// to change the default for an attr that has been added to an op.
+Status OpDefAddedDefaultsUnchanged(const OpDef& old_op,
+                                   const OpDef& penultimate_op,
+                                   const OpDef& new_op);
+
 }  // namespace tensorflow
 
 #endif  // TENSORFLOW_FRAMEWORK_OP_DEF_UTIL_H_

tensorflow/core/graph/graph_partition.cc

@@ -996,6 +996,10 @@ Status Partition(const PartitionOptions& opts, Graph* g,
 
       if (!edge->IsControlEdge() &&
           IsRefType(src->output_type(edge->src_output()))) {
+        AddNodeAttr("_start_time", recv_start_time, recv);
+        if (real_recv != recv) {
+          AddNodeAttr("_start_time", recv_start_time, real_recv);
+        }
         // If src is of ref type and the edge is not a control edge, dst has
         // read semantics and therefore we must control the recv.
         ref_recvs.push_back(real_recv);

tensorflow/examples/android/README.md

@@ -5,9 +5,7 @@ This folder contains a simple camera-based demo application utilizing Tensorflow
 ## Description
 
 This demo uses a Google Inception model to classify camera frames in real-time,
-displaying the top results in an overlay on the camera image. See
-[`assets/imagenet_comp_graph_label_strings.txt`](assets/imagenet_comp_graph_label_strings.txt)
-for the possible classifications.
+displaying the top results in an overlay on the camera image.
 
 ## To build/install/run
 
@@ -21,7 +19,21 @@ installed the NDK and SDK. Otherwise an error such as:
 "The external label '//external:android/sdk' is not bound to anything" will
 be reported.
 
-To build the APK, run this from your workspace root:
+The TensorFlow `GraphDef` that contains the model definition and weights
+is not packaged in the repo because of its size. Instead, you must
+first download the file to the `assets` directory in the source tree:
+
+```bash
+$ wget https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip -O tensorflow/examples/android/assets/inception5h.zip
+
+$ unzip tensorflow/examples/android/assets/inception5h.zip -d tensorflow/examples/android/assets/
+```
+
+The labels file describing the possible classification will also be in the
+assets directory.
+
+Then, after editing your WORKSPACE file, you must build the APK. Run this from
+your workspace root:
 
 ```bash
 $ bazel build //tensorflow/examples/android:tensorflow_demo -c opt --copt=-mfpu=neon