GitLab

**Description**
Remove fp16 samples type converting time for training cnn and lstm inference.

**Description**
Remove fp16  samples type converting time for cnn and lstm models.

**Description**
The BatchNorm operator is not numerically stable in fp16.  PyTorch documentation recommends to keep the BN op in fp32 for fp16 AMP models.  Refer to https://pytorch.org/docs/stable/amp.html#ops-that-can-autocast-to-float32.  Preserving BN in fp32 for superbench more accurately reflects real workloads.

**Description**
Add support for pytorch>=1.9.0 of init_process_group.

**Major Revision**
- Use PrefixStore(TCPStore) to init_process_group manully for each model run

**Description**
Please write a brief description and link the related issue if have.

**Major Revision**
- Sync (do allreduce max) the E2E training results among all workers.
- Avoid using ':0' in metric name if there has only one rank having output.

**Description**
Add 50th, 90th, 95th, 99th, 99.9th latency metrics for ORT and pytorch inference benchmarks.

Add transformers for TensorRT inference.

**Description**
Unify metric names of benchmarks.

**Description**
Fix typo when set force_fp32 option.

**Description**
Add option `force_fp32` to use fp32 instead of tf32, only takes effect on Ampere or newer GPUs.

**Description**

Cherry-pick  bug fixes from v0.3.0 to main.

**Major Revisions**
* Docs - Upgrade version and release note (#209)
* Benchmarks: Build Pipeline - Update rccl-test git submodule to dc1ad48 (#210)
* Benchmarks: Update - Update benchmarks in configuration file (#208)
* CI/CD - Update GitHub Action VM (#211)
* Benchmarks: Fix Bug - Fix wrong parameters for gpu-sm-copy-bw in configuration examples (#203)
* CI/CD - Fix bug in build image for push event (#205)
* Benchmark: Fix Bug - fix error message of communication-computation-overlap (#204)
* Tool: Fix bug - Fix function naming issue in system info  (#200)
* CI/CD - Push images in GitHub Action (#202)
* Bug - Fix torch.distributed command for single node (#201)
* CLI - Integrate system info for node (#199)
* Benchmarks: Code Revision - Revise CMake files for microbenchmarks. (#196)
* CI/CD - Add ROCm image build in GitHub Actions (#194)
* Bug: Fix bug - fix bug of hipBusBandwidth build (#193)
* Benchmarks: Build Pipeline - Restore rocblas build logic (#197)
* Bug: Fix Bug - Add barrier before 'destroy_process_group' in model benchmarks (#198)
* Bug - Revise 'docker run' in sb deploy (#195)
* Bug - Fix Bug : fix bug of error param operations to operation in rccl-bw of hpe config (#190)
Co-authored-by: Yuting Jiang <v-yujiang@microsoft.com>
Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>
Co-authored-by: Ziyue Yang <ziyyang@microsoft.com>

**Description**
Set reduce type for current benchmarks' metrics, including model benchmarks and ShardingMatmul.

**Description**
Replace `sum(results) / len(results)` with `statistics.mean(results)`

__Description__
Cherry-pick bug fixes from v0.2.1 to main.

__Major Revisions__
* Fix bug of VGG models failed on A100 GPU with batch_size=128.
* Fix Ansible connection issue when running in localhost.
* Update version in packages and docs.

* add config file for ndv4.

* replace torch.optim.AdamW with transformers.AdamW.

Benchmarks: Add Feature - Add DistributedImpl and DistributedBackend arguments for micro benchmark. (#100)

Fix bugs and refine log in single GPU benchmarks:

* Fix none framework issue
* Fix empty parameter bug
* Remove missed mobilenet_v3 models
* Change benchmark registration log to debug level
* Add pid in logging
* Add missing benchmarks in default config
* Fix deprecated logging warn

* Clean up the cache.

* fix return code reset issue

* Benchmarks: Add Benchmark - Add LSTM model benchmarks.

* Benchmarks: Add Benchmark - Add CNN model benchmarks.

Benchmarks: Code Revision - Fix some issue for BERT benchmark. (#58)

* Benchmarks: Add Benchmark - Add GPT2 model benchmark.

Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>

* revise result process interface

* add more comments
Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>

Benchmarks: Add Benchmark - Add Pytorch BERT benchmarks, including bert-base and bert-large.   (#20)

* add pytorch bert benchmarks.

* revise code

* fix issue

* revise code.
Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>

* move benchmarks registration from registry.py to __init__.py

* revise __init__.
Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>

Benchmarks: Add Feature - Add benchmark finish check according to num_warmup/num_steps and duration in ModelBenchmark class. (#25)

* add is_finished function

* reuse current time.
Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>

* add sample_count argument.

* handle more condidatins.

* address comments.
Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>

Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>

* add random dataset.

* install pytorch-cpu for test docker.

* fix typo

* add more test cases.

* address comments.
Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>

* add flag to disable GPU.

* fix spelling

* fix unittest.

* address comments.
Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>

Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>

* add pytorch base class

* address comments
Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>

* add optimizer definition and function to create torch optimizer.

* move optimizer enum into model_base module.
Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>

Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>