* 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
* separate linux window llmcpp build
* harness run on linux only
* fix platform
* skip error
* change to linux only build
* add judgement of platform
* add download args
* remove ||true
* 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
* 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
* 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
* 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 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
* 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
* 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
* 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>
* add new models and change schedule to nightly
* correct syntax error
* modify env set up and job
* change label and schedule time
* change schedule time
* change label
* 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
* Change to install from pypi and have a check to make sure the installed bigdl-llm version is as expected
* Make sure result date is the same as tested bigdl-llm version
* Small fixes
* Small fix
* Small fixes
* Small fix
* Small fixes
* Small updates
* Update default xpu to ipex 2.1
* Update related install ut support correspondingly
* Add arc ut tests for both ipex 2.0 and 2.1
* Small fix
* Diable ipex 2.1 test for now as oneapi 2024.0 has not beed installed on the test machine
* Update document for default PyTorch 2.1
* Small fix
* Small fix
* Small doc fixes
* Small fixes
* test support bitsandbytesconfig
* update style
* update cpu example
* update example
* update readme
* update unit test
* use bfloat16
* update logic
* use int4
* set defalut bnb_4bit_use_double_quant
* update
* update example
* update model.py
* update
* support lora example
* add arc stable version regression test
* empty gpu mem between different models
* triger ci
* comment spr test
* triger ci
* address kai's comments and disable ci
* merge fp8 and int4
* disable ci
* Move 1024 test just after 32-32 test; and enable all model for 1024-128
* Make sure python output encoding in utf-8 so that redirect to txt can always be success
* Upload results to ftp
* Small fix
* Add test for 1024-128 and enable more tests for 512-64
* Fix date in results csv name to the time when the performance is triggered
* Small fix
* Small fix
* further fixes
* LLM: check csv and its corresponding yaml file
* run PR arc perf test
* modify the name of some variables
* execute the check results script in right place
* use cp to replace mv command
* resolve some comments
* resolve more comments
* revert the llm_performance_test.yaml file
* Change igpu win tests for ipex 2.1 and oneapi 2024.0
* Qwen model repo id updates; updates model list for 512-64
* Add .eval for win igpu all-in-one benchmark for best performance
* trigger pr temparorily
* Saparate benchmark run for win igpu based in in-out pairs
* Rename fix
* Test workflow
* Small fix
* Skip generation of html for now
* Change back to nightly triggered
* update bigdl_llm.py
* update the installation of harness
* fix partial function
* import ipex
* force seq len in decrease order
* put func outside class
* move comments
* default 'trust_remote_code' as True
* Update llm-harness-evaluation.yml
* Temp enable PR
* Enable tests for 256-64
* Try again 128-64
* Empty cache after each iteration for igpu benchmark scripts
* Try tests for 512
* change order for 512
* Skip chatglm3 and llama2 for now
* Separate tests for 512-64
* Small fix
* Further fixes
* Change back to nightly again
* Add support for win gpu benchmark with peak gpu memory monitoring
* Add win igpu tests
* Small fix
* Forward outputs
* Small fix
* Test and small fixes
* Small fix
* Small fix and test
* Small fixes
* Add tests for 512-64 and change back to nightly tests
* Small fix
* modify output_path as a directory
* schedule nightly at 21 on Friday
* add tasks and models for nightly
* add accuracy regression
* comment out if to test
* mixed fp4
* for test
* add missing delimiter
* remove comma
* fixed golden results
* add mixed 4 golden result
* add more options
* add mistral results
* get golden result of stable lm
* move nightly scripts and results to test folder
* add license
* add fp8 stable lm golden
* run on all available devices
* trigger only when ready for review
* fix new line
* update golden
* add mistral
