* add batch 2&4 and exclude to perf_test
* modify the perf-test&437 yaml
* modify llm_performance_test.yml
* remove batch 4
* modify check_results.py to support batch 2&4
* change the batch_size format
* remove genxir
* add str(batch_size)
* change actual_test_casese in check_results file to support batch_size
* change html highlight
* less models to test html and html_path
* delete the moe model
* split batch html
* split
* use installing from pypi
* use installing from pypi - batch2
* revert cpp
* revert cpp
* merge two jobs into one, test batch_size in one job
* merge two jobs into one, test batch_size in one job
* change file directory in workflow
* try catch deal with odd file without batch_size
* modify pandas version
* change the dir
* organize the code
* organize the code
* remove Qwen-MOE
* modify based on feedback
* modify based on feedback
* modify based on second round of feedback
* modify based on second round of feedback + change run-arc.sh mode
* modify based on second round of feedback + revert config
* modify based on second round of feedback + revert config
* modify based on second round of feedback + remove comments
* modify based on second round of feedback + remove comments
* modify based on second round of feedback + revert arc-perf-test
* modify based on third round of feedback
* change error type
* change error type
* modify check_results.html
* split batch into two folders
* add all models
* move csv_name
* revert pr test
* revert pr test
---------
Co-authored-by: Yishuo Wang <yishuo.wang@intel.com>
* add lookahead in allinone
* delete save to csv in run_transformer_int4_gpu
* change lookup to lookahead
* fix the error of add model.peak_memory
* Set transformer_int4_gpu as the default option
* add comment of transformer_int4_fp16_lookahead_gpu
* LLM: add whisper models into nightly test
* small fix
* small fix
* add more whisper models
* test all cases
* test specific cases
* collect the csv
* store the resut
* to html
* small fix
* small test
* test all cases
* modify whisper_csv_to_html
* Add new example Deepseek
* Add new example Deepseek
* Add new example Deepseek
* Add new example Deepseek
* Add new example Deepseek
* modify deepseek
* modify deepseek
* Add verified model in README
* Turn cpu_embedding=True in Deepseek example
---------
Co-authored-by: Shengsheng Huang <shengsheng.huang@intel.com>
* remove include and language option, select the corresponding dataset based on the model name in Run
* change the nightly test time
* change the nightly test time of harness and ppl
* save the ppl result to json file
* generate csv file and print table result
* generate html
* modify the way to get parent folder
* update html in parent folder
* add llm-ppl-summary and llm-ppl-summary-html
* modify echo single result
* remove download fp16.csv
* change model name of PR
* move ppl nightly related files to llm/test folder
* reformat
* seperate make_table from make_table_and_csv.py
* separate make_csv from make_table_and_csv.py
* update llm-ppl-html
* remove comment
* add Download fp16.results
* Add is_last parameter and fix logical operator in highlight_vals
* Add script to update HTML files in parent folder
* Add running update_html_in_parent_folder.py in summarize step
* Add licence info
* Remove update_html_in_parent_folder.py in Summarize the results for pull request
* Add support for low_low_bit performance test on Windows GPU
* Small fix
* Small fix
* Save memory during converting model process
* Drop the results for first time when loading in low bit on mtl igpu for better performance
* Small fix
* Modify table head in harness
* Specify the file path of fp16.csv
* change run to run nightly and run pr to debug
* Modify the way to get fp16.csv to downloading from github
* Change the method to calculate diff in html table
* Change the method to calculate diff in html table
* Re-arrange job order
* Re-arrange job order
* Change limit
* Change fp16.csv path
* Change highlight rules
* Change limit
* add llm-ppl workflow
* update the DATASET_DIR
* test multiple precisions
* modify nightly test
* match the updated ppl code
* add matrix.include
* fix the include error
* update the include
* add more model
* update the precision of include
* update nightly time and add more models
* fix the workflow_dispatch description, change default model of pr and modify the env
* modify workflow_dispatch language options
* modify options
* modify language options
* modeify workflow_dispatch type
* modify type
* modify the type of language
* change seq_len type
* fix some typos
* revert changes to stress_test.txt
* Specify the version of pandas in harness evaluation workflow
* Specify the version of pandas in harness evaluation workflow
* Modify html table style and add fp16.csv in harness
* Modify comments
* chnage storage
* fix typo
* change label
* change label to arc03
* change needs in the last step
* add generate csv in harness/make_table_results.py
* modify needs in the last job
* add csv to html
* mfix path issue in llm-harness-summary-nightly
* modify output_path
* modify args in make_table_results.py
* modify make table command in summary
* change pr env label
* remove irrelevant code in summary; add set output path step; add limit in harness run
* re-organize code structure
* modify limit in run harness
* modify csv_to_html input path
* modify needs in summary-nightly
* add batch_size in stable version test
* add batch_size in excludes
* add excludes for batch_size
* fix ci
* triger regression test
* fix xpu version
* disable ci
* address kai's comment
---------
Co-authored-by: Ariadne <wyn2000330@126.com>
* ensure the result of daily arc perf test
* small fix
* small fix
* small fix
* small fix
* small fix
* small fix
* small fix
* small fix
* small fix
* small fix
* concat more csvs
* small fix
* revert some files