Goals:
- Have enough of each summary type that tag grouping is useful.
(Wound up recording e.g. mean and stddev and min/max for each variable)
- Use every summary type (adds images)
- Write to multiple directories so there are several "runs"
Change: 119585022

Change: 119591021

Merge internal changes

Usage example: ./remote_test.sh --num-workers 3 --sync-replicas

Also changed:
    1) In local and remote tests, let different workers contact separate GRPC
    sessions.
    2) In local and remote tests, adding the capacity to specify the number of
    workers. Before it was hard-coded at 2.
    Usage example:
    ./remote_test.sh --num-workers 2 --sync-replicas
    3) Using device setter in mnist_replica.py
Change: 119599547

Merge internal changes

…nsorflow#1864)

* Moved mnist reading from input_data in tutorial to learn/datasets

…w#1866)

* Update TF Mechanics 101 Tutorial to match recent code
In the section of Inputs and Placeholders, the IMAGE_PIXELS should be mnist.IMAGE_PIXELS

Change: 119605636

Change: 119643238

Change: 120185825

Change: 120186451

Change: 120186712

Change: 120192253

Change: 120192816

- Oneof values should be printed even when equal to the default.
- Fields should be printed in tag number order, not declaration order.
Change: 120223509

Change: 120231603

…eedback

* Removed TensorInt interface
* Remove unsupported data types

…rsen and @rakyll feedback

…w#1987)

During initialization, we check whether the loaded version
of the cudnn library matches the version of the library that
the binary was compiled against.  When there is a mismatch,
throw an error.

Example: I built with cudnnv5 but I am loading V4, and I get:

E tensorflow/stream_executor/cuda/cuda_dnn.cc:298] Loaded cudnn library: 4007 but source was compiled against 5004.  If using a binary install, upgrade your cudnn library to match.  If building from sources, make sure the library loaded matches the version you specified during compile configuration.

I then copy the v5 version of libcudnn.so into /usr/local/cuda/lib64
and when I re-run the program, the error goes away.

Thoughts, @zheng-xq, @leary-google ?

…#2027)

CUDNN_TENSOR_NHWC the only other format is still not supported
since kInputYXOutput would correspond to CUDNN_TENSOR_CHWN which
doesn’t exist

for issue tensorflow#1786

Upstream changes from internal

The keys in the _word2id are bytes literals.

The keys in the _word2id are bytes literals.

* Fixed some typos
* Relocated errors after types