Summary:
## Description
This PR added support for LSQ on GPU. Only the encoding part is running on GPU and the others are still running on CPU.
Multi-GPU is also supported.
## Usage
``` python
lsq = faiss.LocalSearchQuantizer(d, M, nbits)
ngpus = faiss.get_num_gpus()
lsq.icm_encoder_factory = faiss.GpuIcmEncoderFactory(ngpus) # we use all gpus
lsq.train(xt)
codes = lsq.compute_codes(xb)
decoded = lsq.decode(codes)
```
## Performance on SIFT1M
On 1 GPU:
```
===== lsq-gpu:
mean square error = 17337.878528
training time: 40.9857234954834 s
encoding time: 27.12640070915222 s
```
On 2 GPUs:
```
===== lsq-gpu:
mean square error = 17364.658176
training time: 25.832106113433838 s
encoding time: 14.879548072814941 s
```
On CPU:
```
===== lsq:
mean square error = 17305.880576
training time: 152.57522344589233 s
encoding time: 110.01779270172119 s
```
Pull Request resolved: https://github.com/facebookresearch/faiss/pull/1978
Test Plan: buck test mode/dev-nosan //faiss/gpu/test/:test_gpu_index_py -- TestLSQIcmEncoder
Reviewed By: wickedfoo
Differential Revision: D29609763
Pulled By: mdouze
fbshipit-source-id: b6ffa2a3c02bf696a4e52348132affa0dd838870
eba1cb1a90