Cherrypick fix windows gpu build (#8603)

Cherrypicking Asim's changes.

This is one step towards #6926.
The idea is that if the native libraries are packaged in a .jar file available
in the classpath of the JVM, then they can be extracted and used.
Change: 150697993

* Release notes for 1.1

* Indented RNNCell note

* Removed duplicate note

* Updated RNN cell note

* Updated RNN cell note

* Updated spectral comment, mac gpu support comment and fixed username

* Reword tf.spectral message.

* implemented partial shape inference for tensordot
tensordot should now correctly infer the partial shape of the product, whenever possible

* updated tensordot tests to test partial shape inference

* removed TODO note

In e8aefd21, a dependency:

//tensorflow/tools/pip_package:build_pip_package
//tensorflow/tools/pip_package:simple_console_for_windows
//tensorflow/python/debug:debug_pip
//tensorflow/python/debug:debug_examples
//tensorflow/python/debug:debug_mnist
//tensorflow/examples/tutorials/mnist:input_data
//tensorflow/contrib/learn/python/learn/datasets:datasets
//tensorflow/contrib/framework:framework_py
//tensorflow/contrib/framework:python/ops/_variable_ops.so

was introduced.

Cut this dependency by excluding :debug_examples on Windows

Fix some comments in the run() method of the BaseSession class.

Comment referring to the wrong variable

Fixed the order of arguments for softmax_loss_function in two places, including a semantic code change.
Change: 150685391

Change: 150680902

This is calling Square<int32>(65280), the result doesn't fit into an int32.
LLVM takes advantage of this and changes the behavior of the code, making the
test fail when optimization is enabled (e.g. in msan and tsan mode).
Change: 150672767

Change: 150671385

Change: 150670512

Older versions of Windows (e.g., Windows 7) have lower temporal resolution in timestamps than other platforms. On such Windows machines, multiple dumps of the same or different tensors may end up with the same timestamp, causing
1) failures in the causality check in the constructor of DebugDumpDir,
2) occasional overwriting of previous tensor dumps and core metadata files,
3) loss of ordering information for debug watches of a tensor that is dumped multiple times during a Session::Run() call, e.g., due to While loops.

This CL addresses those two issues:
1) DebugDumpDir._validate_dump_with_graphs now examines tensor dumps of the same timestamp to take into account the possibility of timestamp collision during dependency validation.
2) During the dumping of tensors, file path collisions are checked and if they occur, an index suffix (e.g., "-1", "-2") is appended to the file path.
3) The core metadata Events files now include session_run_count in their names, to avoid collision due to same timestamps.
Change: 150670298

Added three attributes to the debug op "DebugNumericSummary" used in tfdbg-based TensorBoard health pills:
1) lower_bound (type: float)
2) upper_bound (type: float)
3) mute_if_healthy (type: bool)

lower_bound and upper_bound make it possible to customize thresholds beyond which tensor elements are counted as -inf or inf. mute_if_healthy makes it possible to mute a DebugNumericSummary op unless there are nan, -inf or inf elements in the watched tensor, which is useful for reducing the amount of health pill data.

Changes are made in the C++ DebugNodeInserter class, so that these attributes can be directly set from Python methods such as tf_debug.watch_graph() using the following syntax in the debug_ops argument:
debug_ops=["DebugNumericSummary(attribute_name=attribute_value)"]

e.g.,
debug_ops=["DebugNumericSummary(lower_bound=-100.0; mute_if_healthy=true)"]

Currently, string, float, int, and bool attribute value types are supported.
Change: 150665493

Change: 150664674

Change: 150664185

Change: 150663008

Change: 150659388

Branch 150655275

Resolved conflicts in :
tensorflow/compiler/xla/service/call_graph.cc
tensorflow/compiler/xla/service/call_graph.h
tensorflow/compiler/xla/service/call_graph_test.cc
tensorflow/core/BUILD
tensorflow/python/ops/image_ops_test.py

Change: 150655275

Change: 150653208

Change: 150652150

Change: 150651883

Change: 150650257

Change: 150648734

Change: 150648084

Change: 150646570

Change: 150645199

Change: 150642610

Include option to run TensorForest eval locally even if training is distributed, which is a common setup.
Change: 150640056

Change: 150633544

Fixes: #8047
Change: 150631022

Change: 150630961