* initial matmul operator

Similar to np.matmul, but also has transpose_X and transpose_Y flags,
and only supports tensors from rank 1 to 3 inclusive.

For GPU, uses cublas?gemmStridedBatched. For CPU, uses
cblas_?gemm_batch if available via MKL; otherwise a simple serial
implementation that loops over the batch dimension is employed for now.

* add cudnn_conv_op

* WIP

* update

* update

* fix grad check

* use platform::memory

* add support group for cudnn

* update

* follow comments

* fix onlycpu build

* update cuda define

* follow comments

* follow comments

* merge with updates

* fix compile error

* follow comments

* follow comments

By shell command

```bash
sed -i 's#ifdef PADDLE_ONLY_CPU#ifndef PADDLE_WITH_GPU#g' `find ./paddle/ -name '*.h' -o -name '*.cc' -o -name '*.cpp' -o -name '*.c' -o -name '*.cu'`
sed -i 's#ifndef PADDLE_ONLY_CPU#ifdef PADDLE_WITH_GPU#g' `find ./paddle/ -name '*.h' -o -name '*.cc' -o -name '*.cpp' -o -name '*.c' -o -name '*.cu'`
```

* fix nv_library

* fix symbol in gpu_info.h

* If stat is an integer, bool value will implicit cast to int before
  pass to PADDLE_ENFORCE

* Since GPU is an async device by default. We should sync computation
  when Python invoke `run`. So Python can get the correct computation
  result

Using DeviceContext, not Place to get stream

* Also use `const DeviceContext&` all the time, to prevent `const_cast`

Fix #4169
Fix #3468
Fix #3475

* refind accuracy_op

* follow comments

* follow comments

Note: If no symbol with a suitable value is found, both this field and dli_saddr shall be set to NULL.

Fix TravisCI

It is buggy in some Linux because the unique_ptr will be free however
the std::string trying to use that char*.

Moreover, it is no need to demangle for error log by Paddle.
Just use `c++filt` or other shell utilities to do this.

* with unit-tests
* Also complete `memcpy`