nvcodec: Add support for CUDA device context sharing

nvcodec: Wrap CUDA API return check with gst_cuda_result

The gst_cuda_result macro function is more helpful for debugging
than previous cuda_OK because gst_cuda_result prints the function
and line number. If the CUDA API return was not CUDA_SUCCESS,
gst_cuda_result will print WARNING level debug message with
error name, error text strings.

nvdec: Port to GstCUDAContext

... and drop CUvideoctxlock usage. The CUvideoctxlock basically
has the identical role of cuda context push/pop but nvdec specific
way. Since we can share the CUDA context among encoders and decoders,
use CUDA context directly for accessing GPU API.

nvenc: Port to GstCudaContext

... and add support CUDA context sharing similar to glcontext sharing.
Multiple CUDA context per GPU is not the best practice. The context
sharing method is very similar to that of glcontext. The difference
is that there can be multiple context object on a pipeline since
the CUDA context is created per GPU id. For example, a pipeline
has nvh264dec (uses GPU #0) and nvh264device0dec (uses GPU #1),
then two CUDA context will propagated to all pipeline.

nvcodec: Introduce NVIDA CUDA helpers

New object and helper functions can remove duplicated code
from nvenc/nvdec. Also this is prework for CUDA device context sharing
among nvdec(s)/nvenc(s).