GitLab

Adds opt-in deterministic training mode to SuperBench's PyTorch model
benchmarks. When enabled --enable-determinism. PyTorch deterministic
algorithms are enforced, and per-step numerical fingerprints (loss,
activation means) are recorded as metrics. These can be compared across
runs using the existing sb result diagnosis pipeline to verify bit-exact
reproducibility — useful for hardware validation and platform
comparison.
 
Flags added - 

--enable-determinism
--check-frequency: Number of steps after which you want the metrics to
be recorded
--deterministic-seed

Changes - 

Updated pytorch_base.py to handle deterministic settings, logging.
Added a new example script: pytorch_deterministic_example.py
Added a test file: test_pytorch_determinism_all.py to verify everything
works as expected.

Usage - 

Step 1: Run 1 - Run with --enable-determinism and the necessary metrics
will be recorded in the results-summary.jsonl file
Step 2: Generate the baseline file from the Run 1 results using - sb
result generate-baseline
Step 3: Run 2 - Run with --enable-determinism and the necessary metrics
will be recorded in the results-summary.jsonl file on a different
machine (or the same machine)
Step 4: Run diagnosis on the results generated from the 2 runs using the
- sb result diagnosis command

Note - 
1. Make sure all the parameters are constant between the 2 runs 
2. Running the diagnosis command requires the rules.yaml file

---------
Co-authored-by: Aishwarya Tonpe <aishwarya.tonpe25@gmail.com>
Co-authored-by: Ubuntu <rdadmin@HPCPLTNODE0.n3kgq4m0lhoednrx3hxtad2nha.cdmx.internal.cloudapp.net>

**Description**

- When building the CUDA 11.1.1 image, pip (Python 3.8) cannot find a
pre-built wheel for the latest wandb release (v0.23.1). As a result, pip
attempts to build wandb from source. However, the build fails because
the image does not have Go installed, which is required for building
wandb from source. Then the error appears.

**Solution**

- For the CUDA 11.1.1 build, install the required build tools (e.g., Go,
Rust, and Cargo) needed for wandb.

---------
Co-authored-by: Hongtao Zhang <hongtaozhang@microsoft.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

Improves logging info for diagnosis rule op baseline errors. This allows
developers to easily detect errors in their rule files as well as
baseline files, improving end-user experience.

**Description**
Fix bug of failure test and warning of pandas in data diagnosis.

**Major Revision**
- fix warning of pandas in replace and fillna due to type downcast
- fix bug of failure check function only check one matched metric rather
than all matched metrics
- fix bug when converting regex into str of metrics when there're more
than one match group

**Description**
Generate baseline given results from multiple nodes. 

**Major Revision**
- Add sub command `sb result generate-baseline`
- Add UT and docs

---------
Co-authored-by: 454314380 <454314380@qq.com>
Co-authored-by: Yuting Jiang <yutingjiang@microsoft.com>

**Description**

Cherry-pick bug fixes from v0.8.0 to main.

**Major Revisions**

* Monitor - Fix the cgroup version checking logic (#502)
* Benchmark - Fix matrix size overflow issue in cuBLASLt GEMM (#503)
* Fix wrong torch usage in communication wrapper for Distributed
Inference Benchmark (#505)
* Analyzer: Fix bug in python3.8 due to pandas api change (#504)
* Bug - Fix bug to get metric from cmd when error happens (#506)
* Monitor - Collect realtime GPU power when benchmarking (#507)
* Add num_workers argument in model benchmark (#511)
* Remove unreachable condition when write host list (#512)
* Update cuda11.8 image to cuda12.1 based on nvcr23.03 (#513)
* Doc - Fix wrong unit of cpu-memory-bw-latency in doc (#515)
* Docs - Upgrade version and release note (#508)
Co-authored-by: guoshzhao <guzhao@microsoft.com>
Co-authored-by: Ziyue Yang <ziyyang@microsoft.com>
Co-authored-by: Yuting Jiang <yutingjiang@microsoft.com>

**Description**
Add c source code of correctness check for cublas functions.

**Major Revision**
- add correctness check for all supported cublas functions
- add --correctness option into binary

**Minor Revision**
- fix bug and template fill_data and prepare_tensor to get right memory-alignment output matrix for different datatype

**Description**

Cherry-pick bug fixes from v0.6.0 to main.

**Major Revisions**

* Enable latency test in ib traffic validation distributed benchmark (#396)
* Enhance parameter parsing to allow spaces in value (#397)
* Update apt packages in dockerfile (#398)
* Upgrade colorlog for NO_COLOR support (#404)
* Analyzer - Update error handling to support exit code of sb result diagnosis (#403)
* Analyzer - Make baseline file optional in data diagnosis and fix bugs (#399)
* Enhance timeout cleanup to avoid possible hanging (#405)
* Auto generate ibstat file by pssh (#402)
* Analyzer - Format int type and unify empty value to N/A in diagnosis output file (#406)
* Docs - Upgrade version and release note (#407)
* Docs - Fix issues in document (#408)
Co-authored-by: Yang Wang <yangwang1@microsoft.com>
Co-authored-by: Yuting Jiang <yutingjiang@microsoft.com>

**Description**
Add support to store values of metrics in data diagnosis.

Take the following rules as example: 
```
    nccl_store_rule:
      categories: NCCL_DIS
      store: True
      metrics:
        - nccl-bw:allreduce-run0/allreduce_1073741824_busbw
        - nccl-bw:allreduce-run1/allreduce_1073741824_busbw
        - nccl-bw:allreduce-run2/allreduce_1073741824_busbw
        - nccl-bw:allreduce-run3/allreduce_1073741824_busbw
        - nccl-bw:allreduce-run4/allreduce_1073741824_busbw
    nccl_rule:
      function: multi_rules
      criteria: 'lambda label:True if min(label["nccl_store_rule"].values())/max(label["nccl_store_rule"].values())<0.95 else False'
      categories: NCCL_DIS
```
**nccl_store_rule** will store the values of the metrics in dict and save them into `label["nccl_store_rule"]` , and then **rccl_rule** can use the values of metrics through `label["nccl_store_rule"].values()` in criteria

**Description**
Add support for both jsonl and json format in data diagnosis.

**Major Revision**
- Add support for both jsonl and json format in data diagnosis


**Minor Revision**
- change related doc
- add jsonl support in cli

**Description**
Rename field in data diagnosis to be more readable.

**Major Revision**
- rename fields according to diagnosis/metric format

**Minor Revision**
- change type of diagnosis/issue_num to be int

**Description**
Add failure check feature in data diagnosis.

**Major Revision**
- Add failure check rule op to support that if there exists metric_regex not been matched by any metric in result, label as failedtest
- Split performance issue and failedtest in categories


**Minor Revision**
- replace DataFrame.append() with pd.concat since append() will be removed in later version of pandas

**Description**
Fix bugs in data diagnosis.

**Major Revision**
- add support to get baseline of the metric which uses custom benchmark naming with ':' like 'nccl-bw:default/allreduce_8_bw:0'
- save raw data of all metrics rather than metrics defined in diagnosis_rules.yaml when output_all is True
- fix bug of using wrong column index when applying format(red color and percentile) in the excel

**Description**

Cherry-pick  bug fixes from v0.5.0 to main.

**Major Revisions**

* Bug - Force to fix ort version as '1.10.0' (#343)
* Bug - Support no matching rules and unify the output name in result_summary (#345)
* Analyzer - Support regex in annotations of benchmark naming for metrics in rules (#344)
* Bug - Fix bugs in sync results on root rank for e2e model benchmarks (#342)
* Bug - Fix bug of duration feature for model benchmarks in distributed mode (#347)
* Docs - Upgrade version and release note (#348)
Co-authored-by: Yuting Jiang <v-yutjiang@microsoft.com>

**Description**
Output results of all nodes in data diagnosis.

**Description**
Add result summary in excel,md,html format.

**Major Revision**
- Add ResultSummary class to support result summary in excel,md,html format.
- Abstract RuleBase class for common-used functions in DataDiagnosis and ResultSummary.

**Description**
Add md and html output format for DataDiagnosis.

**Major Revision**
- add md and html support in file_handler
- add interface in DataDiagnosis for md and HTML output

**Minor Revision**
- move excel and json output interface into DataDiagnosis

**Description**
Abstract RuleBase from DataDiagnosis.

**Description**
Add multi-rules feature for data diagnosis to support multiple rules' combined check.

**Major Revision**
- revise rule design to support multiple rules combination check
- update related codes and tests

__Description__

Cherry-pick  bug fixes from v0.4.0 to main.

__Major Revisions__

* Bug - Fix issues for Ansible and benchmarks (#267)
* Tests - Refine test cases for microbenchmark (#268)
* Bug - Build openmpi with ucx support in rocm dockerfiles (#269)
* Benchmarks: Fix Bug - Fix fio build issue (#272)
* Docs - Unify metric and add doc for cublas and cudnn functions (#271)
* Monitor: Revision - Add 'monitor/' prefix to monitor metrics in result summary (#274)
* Bug - Fix bug of detecting if gpu_index is none (#275)
* Bug - Fix bugs in data diagnosis (#273)
* Bug - Fix issue that the root mpi rank may not be the first in the hostfile (#270)
* Benchmarks: Configuration - Update inference and network benchmarks in configs (#276)
* Docs - Upgrade version and release note (#277)
Co-authored-by: Yuting Jiang <v-yutjiang@microsoft.com>

**Description**
Add basic analysis features.

**Major Revision**
- Add statistics, correlations of the raw data
- Add numeric outlier detection(inter_quartile_range)
- Add boxplot for selected metric

**Description**
Add data diagnosis module.

**Major Revision**
- Add DataDiagnosis class to support rule-based data diagnosis for result summary jsonl file of multi nodes
- Add RuleOp class to define rule operators