* Ignore Windows built project

* Fix deprecated methods in tf.contrib.python

* Fix regex match for Windows build in contrib.keras

* Fix Regex match for Windows build in session_bundle

* * Fix deprecated methods
* Fix regex match for Windows
* Fix compatibility issue with Python 3.x

* Add missing ops into Windows build for test

* Enabled more testcases for Windows build

* Clean code and fix typo

* Add conditional cmake mode for enabling more unit testcase

* Add Cmake mode for major Contrib packages

* Add supplementary info in RAEDME for new cmake option

* * Update tf_tests after testing with TF 1.3
* Clean code and resolve conflicts

* Fix unsafe regex matches and format code

* Update exclude list after testing with latest master branch

* Fix missing module

* Dynamic ksize with max_pool

This fix tries to fix the issue raised in 4746 where ksize
is static (attr) with max_pool.
This fix changes ksize to input tensor so that it is dynamic now.

This fix fixes 4746.
Signed-off-by: NYong Tang <yong.tang.github@outlook.com>

* Add dynamic ksize to MaxPoolGrad and MaxPoolGradGrad
Signed-off-by: NYong Tang <yong.tang.github@outlook.com>

* Add test cases for max_pool_v2
Signed-off-by: NYong Tang <yong.tang.github@outlook.com>

* Fix GPU Jenkins issue.
Signed-off-by: NYong Tang <yong.tang.github@outlook.com>

* Enable MaxPoolV2 in GPU
Signed-off-by: NYong Tang <yong.tang.github@outlook.com>

* Hide MaxPoolV2 and other fixes.
Signed-off-by: NYong Tang <yong.tang.github@outlook.com>

Fix typos

* Add bool type supports for GPU kernels

* Add bool type test codes for GPU kernels

* Implement CRF decoding for tensors

* add test code for tensor version's CRF decoding

* made modifications according to pylint

* add some comments for crf decode

* remove useless code

* add comments at the top comment of crf module and add more comments in crf_test

* capitalize first char of first word in comments

* replace crf_decode test code with a deterministic example

Branch 164929133

* Create CI build script for Raspberry Pi

* Moved location of Pi build script

Merge code from PR #11940 with internal changes from cl/164796436, and update Python tests to also run on GPU.

PiperOrigin-RevId: 164929133

* [OpenCL] Extends matmul_benchmark.py to cover SYCL

* Fixed typo

* /gpu:0 -> /device:GPU:0

* Fixes control_flow_ops_py_test

* /gpu: -> /device:GPU:

* Fixes //tensorflow/python/profiler/internal:run_metadata_test

* gpu: -> GPU:

* Fixes tfprof_node

* [OpenCL] Fixes device path to name with many colons (#123)

The device path is constructed from a device name by replacing all
colons with underscores. Some device names contain more than one colon,
for example 'device:SYCL:0' which gives a path 'device_SYCL_0'. The
previous code would not convert this back to the original device name,
but rather to 'device:SYCL_0'.

An alternative fix would be to convert all underscores to colons in the
device name (i.e. remove the restriction inside `replace("_", ":", 1)`),
however I'm not sure if there are any device names which contain
underscores.

* If no gpu device aviable fake one

* gpu: -> device:GPU

* Fixes profiler test

* /gpu:x -> /device:GPU:x

* Fixes debug_io_utils_test.cc test

* Fixes device_name_utils_test.cc

This fix remove unneeded cast of int64 for reverse_sequence:
```
lengths = math_ops.to_int64(lengths)
```
as int32 has already been enabled for reverse_sequence.
Signed-off-by: NYong Tang <yong.tang.github@outlook.com>

description for Benchmarks page to Community index page.

PiperOrigin-RevId: 164924906

As part of this change make HloAliasAnalysis a thinner layer which
basically only holds a map from HloValue to HloBuffer and vice versa.

PiperOrigin-RevId: 164923041

164923041  by meheff:

    Make HloAliasAnalysis updatable after changes to the HLO graph.
    As part of this change make HloAliasAnalysis a thinner layer which
    basically only holds a map from HloValue to HloBuffer and vice versa.

--

PiperOrigin-RevId: 164923041

PiperOrigin-RevId: 164920220

PiperOrigin-RevId: 164917891

* [OpenCL] Fixes double memcpy bug (#151)

As the debg CopyOp is called on a Tensor without type, we need to use
the DataType enum to get type information, and use this to pass the type
on to Eigen. This is a workaround Eigen's need to have a type when
calling memcpy. If the Eigen memcpy can be provided without a type
requirement, then the memcpy in sycl_util is unnecessary.

* Acts on feedback from: https://github.com/tensorflow/tensorflow/pull/12173/files/32cb12a9001b672425867b5a3110fd98e737a20b#r132496277

PiperOrigin-RevId: 164916465

PiperOrigin-RevId: 164914552

PiperOrigin-RevId: 164911656

destination. It will reuse the same underlying buffer in those cases.

PiperOrigin-RevId: 164909906

PiperOrigin-RevId: 164902588

PiperOrigin-RevId: 164894867

PiperOrigin-RevId: 164894645

PiperOrigin-RevId: 164890915

Bugfix: number of input channels is not necessarily in the last dimension, after introduction of data_format param.

PiperOrigin-RevId: 164889729

Recover MonitoredSession when the Coordinator is requested to stop with one of the _PREEMPTION_ERRORS.

When SyncReplicasOptimizer is used, a preemption in the Coordinator may result in two cases:
Case 1) the session gets silently marked as complete
Case 2) the session gets stuck

This CL aims to solve and verify solutions for both of these problems. Fix 1 changes the should_stop logic. Fix 2 changes the CoordinatedSession.run() logic.

SyncReplicasOptimizer runs a separate set of threads using a Coordinator instance. Those threads do FIFOQueue.enqueue; the main thread does a blocking FIFOQueue.dequeue.

`sync_token_q` FIFOQueue is on parameter-servers. When one of the PS instances gets preempted, an AbortedError causes the Coordinator to stop via request_stop(ex). That by itself changes the state of MonitoredSession.should_stop() to True (Fix 1).

Results of the blocking Dequeue operation are sent to the chief worker via Recv. What happens next depends on the amount of tokens in `sync_token_q`. If there are enough for the next call to Dequeue to return, then the low-level "tf session run() call" returns. The next iteration of the `while not MonitoredSession.should_stop()` loop decides that the training is complete (Case 1).

If there are not enough tokens in `sync_token_q`, then the blocking Dequeue is going to keep waiting for them. This results in the graph execution getting stuck and the whole session getting garbage collected after 10 minutes (Case 2).

We decided to fix that by re-creating a session after it gets garbage collected (Fix 2). An alternative was to try to cancel the pending Dequeue operation, but it's not clear that it is the right thing to do and it is also not easy.

PiperOrigin-RevId: 164888390

END_PUBLIC
RELNOTES: n/a

BEGIN_PUBLIC
Automated g4 rollback of changelist 164825735

PiperOrigin-RevId: 164883478

PiperOrigin-RevId: 164881593

point accuracy is not high enough across all supported platforms.

PiperOrigin-RevId: 164879933

PiperOrigin-RevId: 164879220

* Enable int32 on GPU for tf.tile.

This fix enabled int32 on GPU for tf.tile, to fix the following error:
```
import tensorflow as tf

with tf.device('/gpu:0'):
    tt = tf.tile(tf.range(4), [3])

with tf.Session() as sess:
    print(sess.run(tt))
```

This fix fixes 12169.
Signed-off-by: NYong Tang <yong.tang.github@outlook.com>

* Enable int32 for TileGradOp
Signed-off-by: NYong Tang <yong.tang.github@outlook.com>

Fixing an issue with merge back with rc2.