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2.添加环境变量APEX_ROCBLAS_GEMM_ALLOW_HALF用于控制是否使用fp16r
3.添加dcu版本信息

whl包名修改

readme更新安装步骤

* remove pyprof

* remove reparameterization

* remove pyprof test

* clean up

* update ngc link and dockerhub container tag

* update

* update

* update

* Update README.md
Co-authored-by: Masaki Kozuki <mkozuki@nvidia.com>

This reverts commit 74e04667.

* copy-paste friendly

* fix import container_abcs issue

Nightly PyTorch has removed `container_abcs` from `torch._six`.  https://github.com/pytorch/pytorch/commit/58eb23378f2a376565a66ac32c93a316c45b6131#diff-b3c160475f0fbe8ad50310f92d3534172ba98203387a962b7dc8f4a23b15cf4dL35

* fix import container_abcs issue

Nightly PyTorch has removed `container_abcs` from `torch._six`.
https://github.com/pytorch/pytorch/commit/58eb23378f2a376565a66ac32c93a316c45b6131#diff-b3c160475f0fbe8ad50310f92d3534172ba98203387a962b7dc8f4a23b15cf4dL35

* keep existing for pytorch1.7 and earlier

Co-authored-by: Michael Carilli <mcarilli@nvidia.com>

* add state_dict, load_state_dict

* add test_restoring, test_loss_scale_decrease

* disable amp outputs for checkpoint tests

* add test for amp.state_dict, cleanup

* add state_dict patch, add test

* fixed testing, cleanup

* add readme for checkpointing

* add docs to source/amp

* add review changes to doc

Co-authored-by: Aditya Agrawal <aditya.iitb@gmail.com>
Co-authored-by: Marek Kolodziej <mkolod@gmail.com>

* Pre-release of fused layer norm apex extension

* Remove half and __half2 specializations

* Code changes from review

* [syncBN]
  added syncBN in native pure python apex
  added fused cuda kernels used for sync BN. Using welford for mean/var
    optional installation using 'python setup.py install --cuda_ext'
  added unit test with side to side comparison between apex sync BN with
    PyTorch BN. Notice that for pytorch BN implementation, because of
    numerical issue for mean/var, the output will be slightly off.

* [syncBN PR]
  added fp16 support
  addressing review comments on:
    1. updating last pow 2
    2. look for import error when importing syncBN kernel

* [syncBN PR]
  added convert function to insert SyncBatchNorm
  refactored some kernel code

* fixing type issue (fp16/fp32/fp64)
added Kahan summation
editing unit test to use pytorch primitive ops with double, passing reasonable tests now

* updating tensor creation calls

* fixing the all_reduce contiguous tensor

* transposed all reduce results

* [syncBN]
support fp16 input & fp32 layer for apex fp16
partially fixing launch configs
enabling imagenet example to run with --sync_bn

* [syncBN PR]
Documentation added

* adjusting README

* adjusting again

* added some doc to imagenet example

* [syncBN]
  warp-level reduction
  bug fix: warp reduction logic updated. check for dummy element to avoid nan.
  improved launch config for better reduction kernels. Further improvements
would be to increase grid size.

* [syncBN]
  fixing undefined behavior in __shfl_down_sync from divergent threads in warp
reduction.
  changing at::native::empty to at::empty (upstream comments)