A framework for training and evaluating AI models on a variety of openly available dialogue datasets.

Overview

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ParlAI (pronounced “par-lay”) is a python framework for sharing, training and testing dialogue models, from open-domain chitchat, to task-oriented dialogue, to visual question answering.

Its goal is to provide researchers:

ParlAI is described in the following paper: “ParlAI: A Dialog Research Software Platform", arXiv:1705.06476 or see these more up-to-date slides.

Follow us on Twitter and check out our Release notes to see the latest information about new features & updates, and the website http://parl.ai for further docs. For an archived list of updates, check out NEWS.md.

Interactive Tutorial

For those who want to start with ParlAI now, you can try our Colab Tutorial.

Installing ParlAI

ParlAI currently requires Python3.7+ and Pytorch 1.6 or higher. Dependencies of the core modules are listed in requirements.txt. Some models included (in parlai/agents) have additional requirements. We strongly recommend you install ParlAI in a venv or conda environment.

Standard Installation

If you want to use ParlAI without modifications, you can install it with:

pip install parlai

Development Installation

Many users will want to modify some parts of ParlAI. To set up a development environment, run the following commands to clone the repository and install ParlAI:

git clone https://github.com/facebookresearch/ParlAI.git ~/ParlAI
cd ~/ParlAI; python setup.py develop

All needed data will be downloaded to ~/ParlAI/data. If you need to clear out the space used by these files, you can safely delete these directories and any files needed will be downloaded again.

Documentation

Examples

A large set of scripts can be found in parlai/scripts. Here are a few of them. Note: If any of these examples fail, check the installation section to see if you have missed something.

Display 10 random examples from the SQuAD task

parlai display_data -t squad

Evaluate an IR baseline model on the validation set of the Personachat task:

parlai eval_model -m ir_baseline -t personachat -dt valid

Train a single layer transformer on PersonaChat (requires pytorch and torchtext). Detail: embedding size 300, 4 attention heads, 2 epochs using batchsize 64, word vectors are initialized with fasttext and the other elements of the batch are used as negative during training.

parlai train_model -t personachat -m transformer/ranker -mf /tmp/model_tr6 --n-layers 1 --embedding-size 300 --ffn-size 600 --n-heads 4 --num-epochs 2 -veps 0.25 -bs 64 -lr 0.001 --dropout 0.1 --embedding-type fasttext_cc --candidates batch

Code Organization

The code is set up into several main directories:

  • core: contains the primary code for the framework
  • agents: contains agents which can interact with the different tasks (e.g. machine learning models)
  • scripts: contains a number of useful scripts, like training, evaluating, interactive chatting, ...
  • tasks: contains code for the different tasks available from within ParlAI
  • mturk: contains code for setting up Mechanical Turk, as well as sample MTurk tasks
  • messenger: contains code for interfacing with Facebook Messenger
  • utils: contains a wide number of frequently used utility methods
  • crowdsourcing: contains code for running crowdsourcing tasks, such as on Amazon Mechanical Turk
  • chat_service: contains code for interfacing with services such as Facebook Messenger
  • zoo: contains code to directly download and use pretrained models from our model zoo

Support

If you have any questions, bug reports or feature requests, please don't hesitate to post on our Github Issues page. You may also be interested in checking out our FAQ and our Tips n Tricks.

Please remember to follow our Code of Conduct.

Contributing

We welcome PRs from the community!

You can find information about contributing to ParlAI in our Contributing document.

The Team

ParlAI is currently maintained by Moya Chen, Emily Dinan, Dexter Ju, Mojtaba Komeili, Spencer Poff, Pratik Ringshia, Stephen Roller, Kurt Shuster, Eric Michael Smith, Megan Ung, Jack Urbanek, Jason Weston, Mary Williamson, and Jing Xu. Stephen Roller is the current Tech Lead.

Former major contributors and maintainers include Alexander H. Miller, Margaret Li, Will Feng, Adam Fisch, Jiasen Lu, Antoine Bordes, Devi Parikh, Dhruv Batra, Filipe de Avila Belbute Peres, Chao Pan, and Vedant Puri.

Citation

Please cite the arXiv paper if you use ParlAI in your work:

@article{miller2017parlai,
  title={ParlAI: A Dialog Research Software Platform},
  author={{Miller}, A.~H. and {Feng}, W. and {Fisch}, A. and {Lu}, J. and {Batra}, D. and {Bordes}, A. and {Parikh}, D. and {Weston}, J.},
  journal={arXiv preprint arXiv:{1705.06476}},
  year={2017}
}

License

ParlAI is MIT licensed. See the LICENSE file for details.

Comments
  • Personality-Captions Dataset

    Personality-Captions Dataset

    I have downloaded the dataset, but when i go through the data set training dataset has one caption per image, where as testing has 5 different columns, can someone tell me in the final output of the paper you guys have shown that one image has 5 different personality trait outputs, but from the dataset i can see that there is only one comment and personality trait per image, How is it possible to get 5 different output for a single image, can someone please explain

    stale 
    opened by Neha10252018 56
  • Dialcrowd

    Dialcrowd

    Patch description DialCrowd is a dialogue crowdsourcing toolkit that helps requesters write clear HITs, view and analyze results, and obtain higher-quality data. This integration allows for the requester interface, worker interface, and analysis interface to be integrated into ParlAI so requesters can have access to ParlAI's tools with DialCrowd's tools.

    Testing steps The testing steps can be found in the README; there are 3 components: configuration page, annotation page, quality page. The configuration script should allow a download of a config.json file, to be manually put into the task_config folder. The annotation page should use the config.json file to load a HIT that a worker can fully do. The quality page should use the information pulled from Mephisto for the annotation page to display the results and analysis.

    CLA Signed 
    opened by jessicah25 48
  • How many HITS are created/Understanding the formatting when running Multi-agent dialog

    How many HITS are created/Understanding the formatting when running Multi-agent dialog

    Hi, I'm having trouble understanding how many hits are posted when I run with specific arguments. I am trying to only get one conversation with two workers and I ran:

    python run.py -nc 1 -r 0.25 --max-connections 2 --live

    Is this correct in thinking that max-connections limits the number of workers I am allowing to access my task so I don't make more hits than I want?

    I am doing this because when I ran:

    python run.py -nc 1 -r 0.25 --live

    It started creating more HITS than I wanted

    opened by damiomit 45
  • How can I train a BART FiD model on custom data with gold retrieved passages?

    How can I train a BART FiD model on custom data with gold retrieved passages?

    Hello, Thanks for the great effort. I am new to parlai. I am interested in training a BART FiD model on my custom data using gold retrieved passages instead of using a DPR-style retriever. I understand how to add new dataset from here.

    And in the project page here, I see the second to the last command is for training a FiD RAG. Is there a way to modify RagModel or FidModel class to pass gold passages? I saw this recent paper, that they have experiments using Retrieved Gold knowledge.

    I would appreciate if you can point me to right direction.

    stale 
    opened by fabrahman 38
  • Ascii error when running messenger integration

    Ascii error when running messenger integration

    Everytime i run python run.py --config-path ../../tasks/chatbot/config.yml I get Please install 3rd-party dependencies by running: pip install joblib websocket-client sh and then when i run pip install joblib websocket-client sh I get Requirement already satisfied: joblib in f:\achilliosomega\ai_framework\conv_learning_ai\parlai\.parlai\lib\site-packages\joblib-0.14.1-py3.6.egg (0.14.1) Requirement already satisfied: websocket-client in f:\achilliosomega\ai_framework\conv_learning_ai\parlai\.parlai\lib\site-packages\websocket_client-0.56.0-py3.6.egg (0.56.0) Requirement already satisfied: sh in f:\achilliosomega\ai_framework\conv_learning_ai\parlai\.parlai\lib\site-packages\sh-1.12.14-py3.6.egg (1.12.14) Requirement already satisfied: six in f:\achilliosomega\ai_framework\conv_learning_ai\parlai\.parlai\lib\site-packages\six-1.14.0-py3.6.egg (from websocket-client) (1.14.0)

    MTurk windows stale-issue 
    opened by ghost 34
  • Starting a chat_service with Blender 90M model

    Starting a chat_service with Blender 90M model

    Hi, I would like to integrate blender with my application and send text to it remotely. I would like to start a WebSocket based server with Blender 90M version but I am not able to understand what changes are required in this config file to load blender 90M model with the server.

    https://github.com/facebookresearch/ParlAI/tree/master/parlai/chat_service/tasks/chatbot

    Any help?

    stale 
    opened by DasShubhadeep 32
  • Removed empty key/value in validate_onboarding

    Removed empty key/value in validate_onboarding

    I removed submitted_data in validate_onboarding, as data was not in status_message and caused an empty value in the final_status

    Patch description In per_turn_eval's worlds.py, the function validate_onboarding was trying to get the variable data in the dict of status_message.But data does not exist in the status_message and it is causing final_status to always be None, therefore blocking all workers.

    Here's the issue https://github.com/facebookresearch/Mephisto/issues/748 where I wanted to reset onboarding qualification, I used a different worker id but found out validate_onboarding ended up keep blocking me because the final_status is always None.

    Testing steps Launch run.py and do onboarding. Perform onboarding correctly and incorrectly to test qualified and disqualified workers and check if data ever exists in status_message for this task.

    CLA Signed stale 
    opened by evelynkyl 30
  • Unable to use BlenderBot2 model

    Unable to use BlenderBot2 model

    I tried to use pretrained blenderbot2 model from https://parl.ai/projects/blenderbot2/ but got error. Command and error message are as below:

    parlai interactive --model-file zoo:blenderbot2/blenderbot2_400M/model

    `Traceback (most recent call last): File "/root/miniconda3/envs/myconda/lib/python3.7/site-packages/parlai/core/build_data.py", line 490, in modelzoo_path my_module = importlib.import_module(module_name) File "/root/miniconda3/envs/myconda/lib/python3.7/importlib/init.py", line 127, in import_module return _bootstrap._gcd_import(name[level:], package, level) File "", line 1006, in _gcd_import File "", line 983, in _find_and_load File "", line 953, in _find_and_load_unlocked File "", line 219, in _call_with_frames_removed File "", line 1006, in _gcd_import File "", line 983, in _find_and_load File "", line 965, in _find_and_load_unlocked ModuleNotFoundError: No module named 'parlai.zoo.blenderbot2'

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last): File "/root/miniconda3/envs/myconda/lib/python3.7/site-packages/parlai/core/build_data.py", line 497, in modelzoo_path my_module = importlib.import_module(module_name_) File "/root/miniconda3/envs/myconda/lib/python3.7/importlib/init.py", line 127, in import_module return _bootstrap._gcd_import(name[level:], package, level) File "", line 1006, in _gcd_import File "", line 983, in _find_and_load File "", line 953, in _find_and_load_unlocked File "", line 219, in _call_with_frames_removed File "", line 1006, in _gcd_import File "", line 983, in _find_and_load File "", line 965, in _find_and_load_unlocked ModuleNotFoundError: No module named 'parlai.zoo.blenderbot2'

    The above exception was the direct cause of the following exception:

    Traceback (most recent call last): File "/root/miniconda3/envs/myconda/bin/parlai", line 8, in sys.exit(main()) File "/root/miniconda3/envs/myconda/lib/python3.7/site-packages/parlai/main.py", line 14, in main superscript_main() File "/root/miniconda3/envs/myconda/lib/python3.7/site-packages/parlai/core/script.py", line 316, in superscript_main opt = parser.parse_args(args) File "/root/miniconda3/envs/myconda/lib/python3.7/site-packages/parlai/core/params.py", line 1163, in parse_args self.add_extra_args(args) File "/root/miniconda3/envs/myconda/lib/python3.7/site-packages/parlai/core/script.py", line 175, in add_extra_args sa.choices[args[0]].add_extra_args(args) File "/root/miniconda3/envs/myconda/lib/python3.7/site-packages/parlai/core/params.py", line 946, in add_extra_args model = get_model_name(parsed) File "/root/miniconda3/envs/myconda/lib/python3.7/site-packages/parlai/core/params.py", line 136, in get_model_name model_file = modelzoo_path(opt.get('datapath'), model_file) File "/root/miniconda3/envs/myconda/lib/python3.7/site-packages/parlai/core/build_data.py", line 504, in modelzoo_path ) from exc ImportError: Could not find pretrained model in parlai.zoo.blenderbot2.blenderbot2_400M or parlai.zoo.blenderbot2.build. Please check your spelling and make sure you've pulled from master.`

    opened by LiShaoyu5 30
  • seq2seq not able to replicate results

    seq2seq not able to replicate results

    Hi

    I am trying to get running a simple seq2seq model with decent results on opensubtitles. I ran the below command on a 12GB GPU Ram Nvidia for 15 hours but the results are not as I am expecting, I was expecting results like Neural Conversational Model paper (1506.05869)

    python3.6 examples/train_model.py -e 13 -m seq2seq -mf godz7 -t opensubtitles -dt train:stream -hist 1 -bs 32 -tr 100 --dict-maxexs=10000000 --gpu 2 --batch-sort false -hs 500 -esz 500 -nl 2 -emb glove -att general -dr 0.3 -lr 0.001 -clip 5                                                                     
    

    I have tried different variants of the hidden size from [2048, 1024, 512] and similarly embedding size with tradeoff in batch size so that RAM capacity is not crossed. Also tried the default options which come with default seq2seq but results are not good. Any tips on where I may be going wrong?

    Sample results like-

    Enter Your Message: hi there buddy
    prediction:  hypothalamus
    [Seq2Seq]: hypothalamus
    Enter Your Message: ok maybe something better?
    [Seq2Seq]: dogged
    Enter Your Message: why are these 1 word
    prediction:  nineteen
    [Seq2Seq]: nineteen
    Enter Your Message: and why is it not multi
    prediction:  llttie
    [Seq2Seq]: llttie
    Enter Your Message: ok anyways
    prediction:  bunting
    [Seq2Seq]: bunting
    Enter Your Message: i missed it
    prediction:  7OO
    [Seq2Seq]: 7OO
    Enter Your Message: is this going to work
    prediction:  interviewee
    [Seq2Seq]: interviewee
    Enter Your Message: i guess its just not
    [Seq2Seq]: interviewee
    Enter Your Message: huh is that repeating
    prediction:  Simpson
    [Seq2Seq]: Simpson
    
    opened by hsgodhia 30
  • How to get the Personality-Captions dataset?

    How to get the Personality-Captions dataset?

    I want to get this Personality-Captions dataset, but I'm confused about "The Personality-Captions dataset can be accessed via ParlAI, with -t personality_captions" in https://parl.ai/projects/personality_captions/

    -t personality_captions ??? Can you tell me the whole command or link???

    Thanks a lot!

    opened by czhxiaohuihui 26
  • Is there an Fairseq interactive dialogue AMT example?

    Is there an Fairseq interactive dialogue AMT example?

    I use Fairseq to train a seq2seq dialogue model. I'm wondering whether I can use ParlAI to let the turkers do multi-turn dialogue with my model on AMT. Is there some example that comes close to this? Thanks!

    opened by cloudygoose 25
  • Installing blenderbot 2 on a cloud server such as AWS Sagemaker g4dn.12xlarge

    Installing blenderbot 2 on a cloud server such as AWS Sagemaker g4dn.12xlarge

    Use this to open other questions or issues, and provide context here. Do you have any docs on how to install blenderbot 2 on a cloud server such as AWS Sagemaker g4dn.12xlarge

    opened by justlearntutors 0
  • Bump json5, style-loader, url-loader and webpack-cli in /parlai/crowdsourcing/tasks/acute_eval/webapp

    Bump json5, style-loader, url-loader and webpack-cli in /parlai/crowdsourcing/tasks/acute_eval/webapp

    Bumps json5 to 2.2.3 and updates ancestor dependencies json5, style-loader, url-loader and webpack-cli. These dependencies need to be updated together.

    Updates json5 from 2.2.0 to 2.2.3

    Release notes

    Sourced from json5's releases.

    v2.2.3

    v2.2.2

    • Fix: Properties with the name __proto__ are added to objects and arrays. (#199) This also fixes a prototype pollution vulnerability reported by Jonathan Gregson! (#295).

    v2.2.1

    • Fix: Removed dependence on minimist to patch CVE-2021-44906. (#266)
    Changelog

    Sourced from json5's changelog.

    v2.2.3 [code, diff]

    v2.2.2 [code, diff]

    • Fix: Properties with the name __proto__ are added to objects and arrays. (#199) This also fixes a prototype pollution vulnerability reported by Jonathan Gregson! (#295).

    v2.2.1 [code, diff]

    • Fix: Removed dependence on minimist to patch CVE-2021-44906. (#266)
    Commits
    • c3a7524 2.2.3
    • 94fd06d docs: update CHANGELOG for v2.2.3
    • 3b8cebf docs(security): use GitHub security advisories
    • f0fd9e1 docs: publish a security policy
    • 6a91a05 docs(template): bug -> bug report
    • 14f8cb1 2.2.2
    • 10cc7ca docs: update CHANGELOG for v2.2.2
    • 7774c10 fix: add proto to objects and arrays
    • edde30a Readme: slight tweak to intro
    • 97286f8 Improve example in readme
    • Additional commits viewable in compare view

    Updates style-loader from 0.23.1 to 3.3.1

    Release notes

    Sourced from style-loader's releases.

    v3.3.1

    3.3.1 (2021-10-21)

    Bug Fixes

    v3.3.0

    3.3.0 (2021-09-21)

    Features

    • added support for supports(), layer() and media from @import at-rules (b9a600c)
    • allow to pass options to insert function through style.use() (#535) (f8ef63b)

    v3.2.1

    3.2.1 (2021-07-20)

    Bug Fixes

    • added the styletagtransform option when it is a module to addBuildDependency (#528) (270513f)

    v3.2.0

    3.2.0 (2021-07-20)

    Features

    Bug Fixes

    • added the insert option when it is a module to addBuildDependency (#527) (3963c0b)

    v3.1.0

    3.1.0 (2021-07-12)

    Features

    • allow to specify the insert option from file, we strongly recommend do it, using the insert option from file will reduce your bundle size, example (#521) (56fc8f0)
    • allow to specify the styleTagTransform option from file, we strongly recommend do it, using the styleTagTransform option from file will reduce your bundle size, example

    Bug Fixes

    ... (truncated)

    Changelog

    Sourced from style-loader's changelog.

    3.3.1 (2021-10-21)

    Bug Fixes

    3.3.0 (2021-09-21)

    Features

    • added support for supports(), layer() and media from @import at-rules (b9a600c)
    • allow to pass options to insert function through style.use() (#535) (f8ef63b)

    3.2.1 (2021-07-20)

    Bug Fixes

    • added the styletagtransform option when it is a module to addBuildDependency (#528) (270513f)

    3.2.0 (2021-07-20)

    Features

    Bug Fixes

    • added the insert option when it is a module to addBuildDependency (#527) (3963c0b)

    3.1.0 (2021-07-12)

    Features

    • allow to specify the insert option from file, we strongly recommend do it, using the insert option from file will reduce your bundle size, example (#521) (56fc8f0)
    • allow to specify the styleTagTransform option from file, we strongly recommend do it, using the styleTagTransform option from file will reduce your bundle size, example

    Bug Fixes

    3.0.0 (2021-06-24)

    ... (truncated)

    Commits
    Maintainer changes

    This version was pushed to npm by evilebottnawi, a new releaser for style-loader since your current version.


    Updates url-loader from 2.3.0 to 4.1.1

    Release notes

    Sourced from url-loader's releases.

    v4.1.1

    4.1.1 (2020-10-09)

    Chore

    • update schema-utils

    v4.1.0

    4.1.0 (2020-04-08)

    Features

    • the mimetype option can be Boolean
    • added the encoding option
    • added the generator option

    v4.0.0

    4.0.0 (2020-03-17)

    ⚠ BREAKING CHANGES

    • deps: migrate on mime-types package, some rare types may have other mimetype

    v3.0.0

    3.0.0 (2019-11-26)

    BREAKING CHANGES

    • minimum required nodejs version is 10.13.0
    • rename the esModules option to esModule
    • switch to ES modules by default (the option esModule is true by default)
    Changelog

    Sourced from url-loader's changelog.

    4.1.1 (2020-10-09)

    Chore

    • update schema-utils

    4.1.0 (2020-04-08)

    Features

    • the mimetype option can be Boolean
    • added the encoding option
    • added the generator option

    4.0.0 (2020-03-17)

    ⚠ BREAKING CHANGES

    • deps: migrate on mime-types package, some rare types may have other mimetype

    Bug Fixes

    3.0.0 (2019-11-26)

    BREAKING CHANGES

    • minimum required nodejs version is 10.13.0
    • rename the esModules option to esModule
    • switch to ES modules by default (the option esModule is true by default)
    Commits

    Updates webpack-cli from 3.3.12 to 5.0.1

    Release notes

    Sourced from webpack-cli's releases.

    v5.0.1

    5.0.1 (2022-12-05)

    Bug Fixes

    • make define-process-env-node-env alias node-env (#3514) (346a518)

    v5.0.0

    5.0.0 (2022-11-17)

    Bug Fixes

    • improve description of the --disable-interpret option (#3364) (bdb7e20)
    • remove the redundant utils export (#3343) (a9ce5d0)
    • respect NODE_PATH env variable (#3411) (83d1f58)
    • show all CLI specific flags in the minimum help output (#3354) (35843e8)

    Features

    • failOnWarnings option (#3317) (c48c848)
    • update commander to v9 (#3460) (6621c02)
    • added the --define-process-env-node-env option
    • update interpret to v3 and rechoir to v0.8
    • add an option for preventing interpret (#3329) (c737383)

    BREAKING CHANGES

    • the minimum supported webpack version is v5.0.0 (#3342) (b1af0dc), closes #3342
    • webpack-cli no longer supports webpack v4, the minimum supported version is webpack v5.0.0
    • webpack-cli no longer supports webpack-dev-server v3, the minimum supported version is webpack-dev-server v4.0.0
    • remove the migrate command (#3291) (56b43e4), closes #3291
    • remove the --prefetch option in favor the PrefetchPlugin plugin
    • remove the --node-env option in favor --define-process-env-node-env
    • remove the --hot option in favor of directly using the HotModuleReplacement plugin (only for build command, for serve it will work)
    • the behavior logic of the --entry option has been changed - previously it replaced your entries, now the option adds a specified entry, if you want to return the previous behavior please use webpack --entry-reset --entry './src/my-entry.js'

    v4.10.0

    4.10.0 (2022-06-13)

    Bug Fixes

    Features

    v4.9.2

    4.9.2 (2022-01-24)

    ... (truncated)

    Changelog

    Sourced from webpack-cli's changelog.

    5.0.1 (2022-12-05)

    Bug Fixes

    • make define-process-env-node-env alias node-env (#3514) (346a518)

    5.0.0 (2022-11-17)

    Bug Fixes

    • improve description of the --disable-interpret option (#3364) (bdb7e20)
    • remove the redundant utils export (#3343) (a9ce5d0)
    • respect NODE_PATH env variable (#3411) (83d1f58)
    • show all CLI specific flags in the minimum help output (#3354) (35843e8)

    Features

    • failOnWarnings option (#3317) (c48c848)
    • update commander to v9 (#3460) (6621c02)
    • added the --define-process-env-node-env option
    • update interpret to v3 and rechoir to v0.8
    • add an option for preventing interpret (#3329) (c737383)

    BREAKING CHANGES

    • the minimum supported webpack version is v5.0.0 (#3342) (b1af0dc), closes #3342
    • webpack-cli no longer supports webpack v4, the minimum supported version is webpack v5.0.0
    • webpack-cli no longer supports webpack-dev-server v3, the minimum supported version is webpack-dev-server v4.0.0
    • remove the migrate command (#3291) (56b43e4), closes #3291
    • remove the --prefetch option in favor the PrefetchPlugin plugin
    • remove the --node-env option in favor --define-process-env-node-env
    • remove the --hot option in favor of directly using the HotModuleReplacement plugin (only for build command, for serve it will work)
    • the behavior logic of the --entry option has been changed - previously it replaced your entries, now the option adds a specified entry, if you want to return the previous behavior please use webpack --entry-reset --entry './src/my-entry.js'

    4.10.0 (2022-06-13)

    Bug Fixes

    Features

    4.9.2 (2022-01-24)

    Bug Fixes

    • respect negatedDescription for flags from schema (#3102) (463b731)

    ... (truncated)

    Commits
    • 4a0f893 chore(release): publish new version
    • 9de982c chore: fix cspell
    • 32d26c8 chore(deps-dev): bump cspell from 6.15.1 to 6.16.0 (#3517)
    • 2788bf9 chore(deps-dev): bump eslint from 8.28.0 to 8.29.0 (#3516)
    • ac88ee4 chore(deps-dev): bump lint-staged from 13.0.4 to 13.1.0 (#3515)
    • 346a518 fix: make define-process-env-node-env alias node-env (#3514)
    • 3ec7b16 chore(deps): bump yeoman-environment from 3.12.1 to 3.13.0 (#3508)
    • c8adfa6 chore(deps-dev): bump @​types/node from 18.11.9 to 18.11.10 (#3513)
    • 0ad8cc2 chore(deps-dev): bump cspell from 6.15.0 to 6.15.1 (#3512)
    • d30f261 chore(deps-dev): bump ts-loader from 9.4.1 to 9.4.2 (#3511)
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    CLA Signed dependencies javascript 
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  • (Question) BB2 Set custom persona at start without adding it to history

    (Question) BB2 Set custom persona at start without adding it to history

    Hey, I've been exploring the blenderbot2, and I was wondering if it was possible to set a custom persona with name, age, job for the bot without any bot history. As I searched online, I found a previous post, so I'm currently using the following code: turn = "your persona: My name is Andrew, I'm 16 years old and I'm a student" blender_agent.observe({'text': turn, 'episode_done': False})

    ...and than I start a while True with inputs and responses like this: blender_agent.observe({'text': input, "episode_done": False}) response = blender_agent.act() print(response)

    Basecly, this is working, but I didn't want any history about the persona, just the persona loaded, sorry if i'm explaining this badly, but on the 2nd line of the example, where the bot just observes the "turn", that "turn" goes into it's history, and the outputs come a bit strange, so I was just asking if I could just set the persona at the beginning of the chat without any previous history. Thank :)

    opened by callippo 0
  • ROSCOE: What is the correspondence between the metrics returned in the code and defined in the paper?

    ROSCOE: What is the correspondence between the metrics returned in the code and defined in the paper?

    @Golovneva The code returns 20 scores (namely faithfulness, informativeness_step, informativeness_chain, faithfulness_ww, repetition_word, repetition_step, reasoning_alignment, external_hallucination, redundancy, common_sense_error, missing_step, semantic_coverage_step, semantic_coverage_chain, discourse_representation, coherence_step_vs_step, perplexity_step, perplexity_chain, perplexity_step_max, grammar_step, grammar_step_max), and while some of these correspond exactly with the scores defined in the paper, some of them don't (such as discourse_representation, coherence_step_vs_step etc.).

    (1) Can you let me know which score in the code corresponds to which definition in the paper? (2) For almost all the scores, it looks like the higher the score is, the better the model's reasoning is. However, it looks like it is the opposite case for scores such as repetition_step. Can you also clarify what is the best score (i.e., 0 or 1), for each of these 20 scores?

    opened by SahanaRamnath 0
  • How Could I download prior version of Personachat dataset?

    How Could I download prior version of Personachat dataset?

    thanks for implementation of ParlAI.

    i want to download old version of personachat dataset. (train set have 10,981 dialogues, 164,356 utterances, writted in [https://arxiv.org/pdf/1801.07243v3.pdf ] .)

    i tried parlai display_data -t personachat but Only Newly version could be downloaded. (equal Convai2 train dataset distribution)

    i can't find it anywhere.

    help me please.

    opened by JHjang223 1
  • BlenderBot - ModuleNotFoundError: No module named 'torch.distributed.algorithms.join'

    BlenderBot - ModuleNotFoundError: No module named 'torch.distributed.algorithms.join'

    Giving me this error when I try to run the following command: interactive.py -t blended_skill_talk -mf zoo:blender/blender_400Mdistill/model (I placed a copy of the interactive script in the project's "main" folder (ParlAI)

    opened by eclipt69 1
Releases(1.7.1)
  • 1.7.1(Sep 16, 2022)

    This release is mainly to address build errors resulting from functionality introduced in 1.7.0, i.e., n-gram blocking on the GPU. Full release notes below:

    General Fixes/Improvements

    • Protect loading of n-gram blocking on GPU (#4779)
    • General lint fixes (#4771)
    • Increase CI parallelism (#4702)
    • Update DialCrowd to mephisto 2.0.1

    Agent Improvements/Fixes

    • [BB3] General fixes (#4786, #4789)
    • [BB3] Memory usage heuristics (#4770)
    • [BB3] README Updates (#4784)
    • [DIRECTOR] Added shared embedding option to director model. (#4763)
    Source code(tar.gz)
    Source code(zip)
  • 1.7.0(Aug 23, 2022)

    New Releases

    New Features

    • The Decoder-Only Transformer agent is now available in ParlAI! (#4329)
    • Beam N-Gram blocking is now supported on the GPU (#4633, #4721)
    • The model chat mephisto crowdsourced task now supports emojis! (#4666)

    Agent Fixes + Improvements

    • Updates to Reranker, Pacer (#4469, #4473, #4488)
    • Updates to RagAgent, FidAgent, and Search (#4470, #4503, #4631, #4765)
    • Updates to HuggingFace agents (#4508)
    • Updates to T5Agent (#4505)
    • Updates to BertClassifierAgent (#4553)
    • Updates to SeeKeR (#4634)
    • Updates to TorchAgent, TorchGeneratorAgent,TorchClassifierAgent` (#4654, #4650, #4700, #4727, #4754, #4720)
    • Updates to models from the WhoAmI project (#4742)

    Bug fixes + Performance Improvements

    • Script fixes script (#4054, #4482, #4496, #4572)
    • [TorchScript] fixes (#4489, #4499, #4554), add torchscriptable classifier + BPE tokenizer (#4566),
    • Train model supports setting seed (#4662)
    • ParlaiParser Fix (#4507)
    • Various crowdsourcing fixes + enhancements (#4551, #4560, #4577, #4625)
    • Fix downloads of TOD models (#4647)
    • Test fixes (#4749)

    Datasets & Teachers & Mutators

    • Added datasets:
      • SPOLIN Dataset (#4540)
      • Friends Dataset (#4568, #4678, #4693)
    • Deprecate Auxiliary BST Teachers (#4513)
    • Updates to HuggingFace dataset integration (#4516)
    • Update LCCC Download Link (#4542)
    • MultiWoz V22 Updates (#4565, #4656, #4695, #4752, #4757, #4761, #4762, #4736, #4764)
    • Wizard of Internet Updates (#4576)
    • SaferDialogues updates (#4623)
    • Various mutators bugs (#4730)
    • BAD Teacher updates (#4732)
    • GoogleSGD updates (#4698)

    Logging & Metrics

    • Improvements to Weights & Biases integration (#4484, #4548, #4708)
    • Include tensorboard logging in eval_model (#4497)
    • TimerMetric fixes (#4536)
    • Expose precision + recall metrics (#4670)

    Developers & Documentation

    • Various documentation updates (#4487, #4509, #4609, #4613, #4612, #4624, #4632, #4687, #4688, #4690, #4691, #4686, #4733)
    • Various dependency + CI updates (#4481, #4506, #4514, #4483, #4524, #4523, #4522, #4521, #4529, #4532, #4562, #4564, #4590, #4608, #4593, #4615, #4671, #4677, #4759)
    • Various linting, syntactic updates (#4684, #4718, #4728, #4731)
    Source code(tar.gz)
    Source code(zip)
  • 1.6.0(Mar 30, 2022)

    New Releases

    • SeeKeR project code and models release (#4447, #4458, #4449, #4453, #4448)
    • User Simulators and Task Oriented Dialogue support (#4437, #4438, #4188, #4187, #4189, #4186, #4185, #4184, #4183, #4249, #4174, #4181, #4182, #4180, #4178, #4233)
    • Per Turn evaluation project code release (#4304, #4323, #4333, #4362)
    • SaFeRDialogues dataset and model release (#4229, #4300)
    • Am I Me or You project code release (#4239, #4252, #4250)
    • K2R Project release(#4251)

    New Features

    • Updating to Mephisto 1.0 (#4426)
    • [TGA]
      • More flexible token metadata logging (#4169, #4427)
      • Record avg generation length (#4295)
      • change tga default to not sort (#4138)
    • Add a small example Flask server (#4433)
    • Add support for WorldLoggers in training (#4369)
    • [T5] Support Distributed Training (#4434)
    • [HuggingFace] Add support for any GPT-2 model hosted in Huggingface (#4360), and ranking (#4326)
    • [Crowdsourcing]
      • [ACUTE-Eval] Add support for knowledgeable question (#4416), interestingness question (#4113)
      • [ACUTE-Eval] Record start and end times (#4208)
      • [Model chat] allow multiple final ratings (#4276)
      • [Model chat] allow spacing out of annotation buckets (#4275)
      • Allow Use of external database in crowdsourcing code (#4272)
      • Allow specification of blueprints from command line (#4254)
      • Unify turn annotation tasks (model chat and turn annotations static tasks) (#4162)
      • [ACUTE-Eval] Save worker name in Acute-Eval analysis script (#4126)
    • [RAG/FiD/BB2]
      • [All] Incremental Decoding (#4088)
      • [BB2] Allow hybrid mode (skip search when needed) (#4221)
      • [FiD] Add specialized chunking to search engine retrievers (#4227)
      • [BB2] Support for gold docs training (#4163)
      • [FiD] Gold retrieved documents FiD Agent. (#4123)
      • Export memories to the observation output (#4040)
    • [Style-Controlled Generation] OSS Second Classifier (#4380)
    • [Re-ranker] Support for a classifier re-ranker agent (#4291)
    • [TCA] return candidates (#4286)
    • Curated response generators (#4197)
    • [Chat Services] add option for host specification (#4335)

    Bug fixes

    • [TCA] Various updates and fixes (#4287, #4406, #4270)
    • [BlenderBot2] Various updates and fixes (#4379, #4428, #4419, #4331, #4377, #4366, #4289, #4259, #4238, #4212, #4198, #4156)
    • [TorchAgent] Fix an issue with warmup updates not working properly (introduced after 1.5.1) (#4384, #4242, #4196)
    • [RAG/FiD] various updates and fixes (#4436, #4361, #4389, #4207, #4199, #4146)
    • [GPT2] misc. Fixes (#4395)
    • [Train Model] Fixes train_model worldlogging for multitask with mutators. (#4414)
    • [Crowdsourcing] various updates and fixes (#4413, #4273, #4274, #4089)
    • [Re-ranker] Bubble up all batch fields (#4296)
    • Fix clobbering issues with WandB & Tensorboard requeueing (#4175, #4093)
    • Fix interactive web (#4140)
    • Several misc. fixes (#4459, #4403, #4386, #4439, #4425, #4021, #4218, #4164)

    Datasets & Teachers & Mutators

    • Relicense several parlai datasets as commercially friendly (#4269, #4213, #4126)
    • LLLC, a large chinese dataset (#4325)
    • Casino dataset (#4129)
    • Upgrade internals of several teachers: WoW (#4284), Empathetic Dialogues (#4405), Natural Questions (#4205)
    • WoW and WoI mutators (#4418, #4204, #4168, #4124, #4125, #4122, #4114)
    • Speed up the json teachers (#4404)
    • XPersona Dataset (#4314)
    • ConversationTeacher parent class is now ParlAIDialogTeacher (#4256)
    • [WizInt] Additional knowledge-related eval metrics (#4193); turn dicts to Messages (#4144)

    Developers

    • Various documentation improvements (#4423, #4352, #4375, #4074, #4172, #4423, #4100, #4385. #4349, #4298, #4297, #4217, #4173, #4133, #4120, #4028, #4104, #4102)
    • Various test improvements and fixes (#4442, #4375, #4311, #4271, #4435, #4343, #4236, #4261, #4223, #4224, #4096, #4315, #4253, #4190)
    • Various dependency bumps (#4464, #4463, #4420, #4351, #4348, #4346, #4337, #4317, #4302, #4299, #4301) Other QOL Improvements (#4095)
    Source code(tar.gz)
    Source code(zip)
  • v1.5.1(Oct 12, 2021)

    v1.5.1

    Project Releases

    Hi, my name is Martha - New reduced-bias dialogue models! (#3981)

    Minor features

    • Allow the style classifier to save output probabilities (#4026)
    • Add gpu option to torchscript BART models (#3979)

    Crowdsourcing

    • Upgrade to Mephisto 0.4.0 (#3982, #4043)
    • Save model chat data in the Mephisto database (#4005)
    • Add Last Turn Annotation Only option to turn annotations static task (#3436)
    • Crowdsourcing data compiler class for using Mephisto abstractions (#4029, #4034)
    • Force model chats starting with "Hi!" to use BST-style context (#4004)

    Datasets

    • [LIGHT] Jericho World dataset (#3957)

    Bugfixes

    • [RAG] Fix ReGReT Cuda Issue (#4022)
    • [BlenderBot2] Handle distributed (#4023)
    • [mutators] Prevent name collisions in mutators (#4006)
    • [crowdsourcing] Fix model chat frame height by (#4030)

    Other

    • Various error message improvements (#3987, #4018, #4007)
    • Various typos and documentation clarifications (#4053, #4052, #4008, #4002, #4064)
    • Various project-specific small additions and mutators (#3997, #3996, #3999, #4000, #3966, #4062)

    Developer changes

    • [Modular] Update Transformer Layer __init__s by @klshuster in #4061
    • Migrate to the main branch by @stephenroller (#3998, #4010)
    • Allow more subclassing of self-chat world (#3955)
    • Moving Wizard of Internet task to crowdsourcing/projects directory. by @mojtaba-komeili in #3978
    • Improve internal facebook compatibility (#3964, #3994, #4032, #3991)
    • Various dependency bumps (#3995, #4072, #4017, #4077)
    Source code(tar.gz)
    Source code(zip)
  • v1.5.0(Aug 25, 2021)

    v1.5.0

    Major Features

    Model Cards have now been added to ParlAI. We support automatically generating cards for different models. See an example of BlenderBot2's model card. (#3857, #3865, #3899, #3884, #3915, #3965, #3860, #3863)

    Minor Features

    • Add support for an extra final evaluation in training scripts with custom opts (#3883)
    • Add --checkpoint-activations to lower memory usage of training transformers (#3864)

    Crowdsourcing

    • Open source the Wizard of Internet crowdsourcing tooling (#3924)
    • Open source the Personal Knowledge crowdsourcing tooling (#3945)
    • More customization for the [Static Turn Annotations] task. (#3926)
    • More flexibility in model-chat analysis code (#3844, #3958, #3935)

    Bug Fixes

    • [world logs] Fix a bug where dynamic batching didn't use episode boundaries in world logs (#3867)
    • [self chat] Fix the order of openers so output is deterministic (#3923)
    • [parser] Fix bug where parse_kwargs couldn't handle mutator args (#3900)
    • [parser] Fix bug where nargs=+ wasn't working with parse_kwargs (#3930)
    • [teachers] Fixed an issue where some preprocessing was missing from labels field (#3874)
    • [blenderbot2] Fix a crash when not using internet search (#3950)
    • [regret] Fix a regression in Regret (#3934)
    • [rag] Fix a bug when receiving NaN scores

    Teachers

    • Auxillary data added in the Wizard of Internet Task (#3897)

    Documentation changes

    • Updates/improvements to some project documentations in Hallucination/RAG/etc (#3869, #3888, #3917, #3873)
    • Remove a false statement in chat services tutorial
    • Update a link to datasets in Contradiction (#3878)
    • Repo-wide spelling corrections (#3894, #3960)

    Developer changes

    • Minor refactors (#3892)
    • CI fixes and improvements (#3954, #3837, #3889)
    • Small extensibilities to the torchscript functionality (#3851)
    • Enable self_chat to seed messages from tasks in parlai_internal (#3852)
    • Avoid exception in core/agents.py when arg is missing from dict (#3893)
    • Allow customization of the AcceptabilityChecker (#3846)
    Source code(tar.gz)
    Source code(zip)
  • 1.4.1(Jul 23, 2021)

    Includes a fix to make sure that BlenderBot2 can be used with a pip install (#3848)

    Also includes a teacher for training a Wikipedia Page Title Generator from the Wizard of Wikipedia Dataset (#3845)

    Source code(tar.gz)
    Source code(zip)
  • 1.4.0(Jul 22, 2021)

    v1.4.0 Changelog

    Major Features/Paper Releases

    BlenderBot 2.0 Models, Code, Datasets

    This release of ParlAI includes all the code, models, and datasets used to build BlenderBot 2.0 - please see the project page for more information, including how to access and use the models themselves (#3790, #3793, #3794, #3795, #3796, #3797, #3798, #3801, #3802, #3805, #3803, #3815, #3817)

    Internet-Augmented Dialogue Generation

    Build and release a crowd-sourced dataset of humans searching the internet and talking in depth about a vast array of topics; search-engine-augmented dialogue models are trained on the dataset, and are shown to be more knowledgeable than their non-search-augmented counterparts. (#3792, #3800, #3814)

    Multi-Session Chat

    Build and release a dataset of multi-session chats for the purpose of studying long-term open-domain conversation. Models trained on the dataset prove to perform better at recalling information from the distant past in the chats. (#3791, #3799, #3814)

    Safety Benchmark Tests

    With the release of Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling, ParlAI now supports running safety unit tests for conversational models. Check out the project page to see how to run the safety benchmarks. (#3767, #3768, #3769, #3784)

    Convenience Functions for Agents

    With a recent update to ParlAI's agent API, you can now bypass the act/observe loop for interacting with agents. (#3775)

    In [1]: from parlai.core.agents import create_agent
    
    In [2]: from parlai.core.params import ParlaiParser
    
    In [3]: opt = ParlaiParser(True, True).parse_args(['--model_file', 'zoo:blender/blender_90M/model'])
    
    In [4]: agent = create_agent(opt)
    
    In [5]: agent.respond("Hi! How's it going?")
    Out[5]: "it ' s going well . i ' m getting ready to go to work . how about you ?"
    

    Minor Features

    [Metrics] AUC Metrics added to parlai eval_model (#3751)

    Bug Fixes

    [Crowdsourcing] Crowdsourcing Fixes concerning Left Pane Text and Model Chat (#3773, #3780, #3789, #3831) [RAG] Fix some issues with RAG/FiD agents (#3787, #3818, #3834, #3833, #3836) Fix JSON serialization in interactive_web.py script (#3821) Fix CI test issues (#3825, #3823) Misc. README typos (#3807, #3839, #3841)

    Developer Changes

    Stripping before processing Conversations to allow leniency (#3772) [ACUTE-Eval] Dev improvements to running ACUTE-Eval (#3781, #3782, #3783) Allow self-chat in nested folders (#3785) Allow opt presets from parlai_internal folders (#3819)

    Source code(tar.gz)
    Source code(zip)
  • v1.3.0(Jul 7, 2021)

    v1.3.0 Changelog

    Major Features

    Fully Sharded Data Parallel

    Implementation of DeepSpeed/FairScale's Zero2 sharding. Improves training speed and reduces memory usage over vanilla DistributedDataParallel. Switch to the new mode with --ddp-backend zero2 to see free improvements in your training! (#3740)

    Swappable Transformer Components

    We've added support for overriding internal components within Transformers. It is now easy to swap only an attention module, or customize your layers, without having to fully override all classes. (#3567, #3703, #3708, #3715, #3638)

    ChunkTeacher no longer requires num_examples/num_episodes to be correct

    For as long as we've had ChunkTeacher, the value of num_examples/num_episodes must be exactly correct, or your training would hang. Furthermore, that calculation would need to be done outside of ParlAI. We've relaxed this restriction: these methods can now return arbitrary values, and you will correctly iterate through all of your data. However, using the wrong value of num_examples can cause the "epoch" counter (used in parlai train) to be wrong relative to your dataset. (#3681, #3745)

    Eliminate dummy batches and init_cuda_buffer

    You are no longer required to implement dummy batches in your Generator agents, when using custom batch formats. Additionally, you will no longer see a dummy batch as the first batch when debugging. Instead, the first batch your agent sees will be reserved as the future dummy batch. (#3732, #3744)

    Paper Releases

    Reducing Hallucination

    Exploratory architectures that add retrieval mechanisms to dialogue models, reducing hallucination while maintaining conversational ability. (#3611, #3657, #3693, #3688, #3668)

    Hash Layers & Ladder Transformers

    More Parameters or More Compute? Answer: Both! Two new methods that explore this question: Hash Layers for more parameters, and Staircase Attention for more power per parameter. (#3697, #3699, #3700, #3746, #3747)

    Minor Features

    • [TGA] Substantial speedups during generation on GPUs (#3730, #3729, #3669)
    • [Datasets] Add GLUE teachers, and support for HuggingFace datasets (#3570, #3624)
    • [Datasets] [Safety] Release the Non Adversarial Data (#3684)
    • [TA] Support temp history via special field in observation (#3617)
    • [TGA] Allow setting prefix tokens (#3760)
    • [TCA] Classifier on generator for TGA (#3716)
    • [ChunkTeacher] Remove exception for specifying non-streaming data (#3653)
    • [Transformer] Better initiaization for segment embeddings (#3680)
    • [Message] Add a new json_safe_payload method for serialization (#3643, #3726, #3686)
    • [JIT] Support special tokens in torchscript module. (#3644)
    • [JIT] Fix a parsing error with parlai torchscript in Python 3.8 (#3641)
    • [ACUTE] Support randomize_conversations (#3636, #3642)

    Bugfixes

    • [train] Fix bugs with loading validation impatience. (#3713)
    • [train] Fix LR scheduler cooldown (#3719)
    • [train] Dynamic Batching doesn't choke with really small datasets (#3721)
    • [Logging] Fix a bug with world logging and multitasking (#3718)
    • [Mutators] Ensure mutations do not persist across epochs (#3649)
    • [BART] Do not add start/end tokens multiple times (#3714)
    • [TCA] weighted_f1 no longer assumes binary classification (#3728)
    • [Safety] Fix a Static Task bug and Safety README (#3612)
    • [logging] Fix an issue where --loglevel debug was ignored (#3658)
    • [Tensorboard] Fix an exception in some versions of Tensorboard (#3637)
    • [vacuum] Add support for PathManager in vacuum (#3635)
    • [Crowdsourcing] Slightly improve the analysis script to make it more robust (#3683, #3629)
    • Various locations where the change to is_padding caused issues (#3704, #3634, #3674)
    • Various typos/lint (#3621, #3622, #3646)

    Developer changes

    • Helper functions for building deterministic data splits (#3676)
    • Teacher URL updates (#3749, #3627, #3678)
    • CI bugfixes & version bumps (#3754, #3724, #3672, #3652, #3710, #3628, #3452, #3720)
    • Documentation updates (#3748, #3690, #3742, #3671)
    • Mutators and Scripts support for parlai_internal (#3623, #3625)
    • [Crowdsourcing] Small refactor in Model-Chat
    Source code(tar.gz)
    Source code(zip)
  • v1.2.0(Apr 23, 2021)

    This Saturday marks the 4 year anniversary since the initial release of ParlAI. I'd like to offer my sincere gratitude to our users, our contributors, and all of the core development team. ParlAI wouldn't be what it is without all of you. -@stephenroller

    Major new features

    Background Preprocessing

    Improve your training speeds by 1.25x-5.0x by switching from --num-workers 0 to --num-workers N. See our Speeding up training docs for details. (#3527, #3586, #3575, #3533, #3389)

    (Beta) Support for torch.jit Deploy faster models by exporting models with TorchScript. Currently limited to BART models only. (#3459)

    Support for T5 We now have agents for Google's T5 models (#3519)

    Opt Presets Opt presets. Easily use prepackaged opt files as shorthand for long command line arguments (#3564)

    Log/validate/stop based on number of steps Get up to a 10% speedup of distributed training by switching from -vtim or -veps to -vstep (#3379, #3555)

    Backwards-incompatible changes

    • DictionaryAgent.text2vec now requires input to be a string (#3472)
    • A number of older projects have been archived: DrQA (#3559), Controllable Dialogue (#3557), and Self-Feeding Chatbot (#3557).

    Minor improvements

    • Performance speedup in generation using Transformer Generators (#3550)
    • Improvements to the Transformer API, making Transformer models more easily extensible. More to come soon. (#3486, #3545, #3466, #3501)
    • Various performance improvements when loading ParlAI or performing some activities (#3544, #3482)
    • Metrics:
      • New truncation metrics show you how much context/label you're losing (#3458, #3508)
      • Additional metrics in the Wizard of Wikipedia teacher (#3566, #3592, #3503)
      • New token_em metric, an equivalent to accuracy with --skip-generation true (#3497)
    • Self-chat can now use seed messages (#3580)
    • New "normalized" ConvAI2 teachers for the non-standard variants (#3509)
    • Update FusedAdam support to use FairScale (#3522)
    • Add --wandb-entity flag to the logger (#3562)
    • Tensorboard now provides nicer names of metrics (#3534)

    Bugfixes

    • [core] Fix a bug when resuming with the cosine LR scheduler after preemption (#3599)
    • [core] Improve robustness to serialization of Observations (#3591)
    • [core] ParlaiDialogTeacher now parses the rewards field as a number (#3517)
    • [core] Fix recently introduced ChunkTeacher bugs (#3549, #3542, #3543)
    • [core] Minor FP16 fixes when converting old checkpoints (#3514)
    • [core] Fix annoying ambiguity issues with commandline parsing in Python 3.8 (#3598)
    • [core] Fix a rare situation in case a dictionary contained tokens with leading whitespace (#3613)
    • [mutators] Fix a bug with the flatten mutator providing the wrong history (#3578, #3584)
    • [metrics] Fix a bug with computation of fairseq metrics (#3518)
    • [task] Fix a bug with Wizard of Wikipedia teacher causing some data to be omitted (#3585)
    • [task] Fix a crash in Wizard of Wikipedia end2end agent when given zero documents (#3602)
    • [task] Update a dead dataset to a new link (#3520)
    • [task] Fix an issue with CCPE (#3487)
    • [tga] Fix a case where TGA used as a ranking model could crash (#3541)
    • [agent] Fix a crash in BertDictionaryAgent (#3560)
    • [other] Various rare issues (#3505) and quality improvements (#3496)

    Crowdsourcing improvements

    • Add new option to avoid randomizing pairs in ACUTE-Eval (#3528)
    • ACUTE-Eval provides additional warnings when options are not set to recommended values (#3536, #3524)

    New Datasets

    • MetaLWoZ (#3583)
    • CMU_DoG (#3593, #3615)

    Doc improvements

    • New tutorial: How to write a PR contributing (moving to a fork) tutorial (#3490)
    • New reference manual of standard ParlAI metrics (#3498)
    • Fix a bug keeping some tasks from being listed in our docs (#3495)
    • Various minor doc changes (#3513, #3561, #3596)

    Developer improvements

    • Update to pytorch 1.8. No changes necessary. (#3607)
    • Various reliability improvements and speed ups to our CI and tests (#3603, #3597, #3604, #3606, #3605, #3587, #3588, #3590, #3539, #3535, #3526, #3521)
    • Various dependency bumps (#3553, #3537, #3515)
    • Switched logging.warn to logging.warning (#3569)
    • TorchAgent.history prettier debug printing (#3510)
    • Small other improvements (#3506)
    Source code(tar.gz)
    Source code(zip)
  • v1.1.1(Mar 17, 2021)

    Bug fix release

    Fix a bug introduced in v1.1.0 caused by the removal of APEX, which increased the numerical instability of training with fp16. See #3532 for details.

    Source code(tar.gz)
    Source code(zip)
  • v1.1.0(Mar 1, 2021)

    Breaking changes

    • Removed dependence on APEX. --fp16-impl safe is the new standard (#3469)
    • Change DialoGPT default to medium as that's the best results and most common setup (#3401)

    Major new features

    • Mutators are a new way to perform transformations on arbitrary datasets (#3448)
    • Support for WandB (#3417)
    • display_model now displays teacher-metrics, and world loggers store them (#3388, #3419)

    Minor new features

    • Make convenience script for dumping out chat to conversations format (#3354)
    • Allow a variable number of transformer heads in distillation, and improved loss normalization (#3424, #3447, #3430)
    • Better error messages when incorrectly providing a model zoo file (#3445)
    • Add --no-backup option to vacuum. (#3431)
    • Release BST human annotations (#3405)

    Crowdsourcing changes

    • Abstract class for compiling annotation results (#3422, #3423, #3464)
    • Improvements to output format for some tasks (#3400, #3425)
    • Configuration option for setting soft blocks (#3435)

    Bug fixes

    • [security] RCE fixed in chat services (#3402, #3429)
    • Speedups when using conversation openers in self-chat (#3461)
    • Speedups in metrics accumulation (#3474)
    • Fix an error bounds error when manually applying vec2txt with --dict-tokenizer bytelevelbpe (#3437)
    • Add pathmanager support to BERT agent (#3439)
    • Fixes to Natural Questions (#3440, #3438)
    • Remove a warning in --fp16-impl mem_efficient (#3443)
    • Fix an issue with windows compatibility (#3428)
    • Update data urls for Taskmaster-1 (-t taskmaster) (#3475)
    • Fix a bug with terminal chat where the socket would close early (#3457)

    Developer features

    • New abstract method for ranking candidates in TorchGeneratorAgent (#3455)
    • Improved type annotations and code cleanup (#3413, #3462, #3420)
    • Various documentation immprovements (#3398, #3399, #3349, #3384, #3385, #3427, #3446, #3441)
    • Test fixes (#3442, #3467)
    Source code(tar.gz)
    Source code(zip)
  • v1.0.0(Jan 19, 2021)

    This marks a major release for ParlAI worthy of celebration. Thank you to the team, our numerous external contributors, and all of our users.

    Major changes

    MTurk is dead, long live Crowdsourcing

    As the primary impetus for the release of v1.0.0, we have officially removed parlai.mturk from our repo, fully migrating to the newer, Mephisto-based parlai.crowdsourcing. If you have any questions about upgrading, please make sure to check the new tutorial and feel free to ask questions in our new Discussions forum

    New discussions forum

    We've enabled GitHub Discussions as a new place for individuals to ask more long-lived questions. We still encourage using issues for bug reports, but many "How do I...?" questions are better for Discussions now.

    Distilled models

    We have released several distilled BlenderBot models (#3313, #3314), as well as code for distilling your own models. See project page.

    DECODE model releases

    New project on addressing contradictions in dialogue models (#3324, #3325, #3327, #3334, #3309). See project page for more information.

    Backwards incompatible changes

    • parlai.mturk has been removed in favor of parlai.crowdsourcing (#3362, #3371)
    • The API for add_cmdline_args has changed. Please see the PR for information on upgrading. This enables things like defaults that depend on other values, or arguments that depend on other arguments. (#3328)
    • Improvements to world logger arguments (#3380)

    New features in core

    • New distinct metrics (including intra-distinct and inter-distinct). (#3347)
    • 40% Speedups in --model-parallel true generations and training (#3326)
    • Updated README, autodoc descriptions, PR templates (#3359, #3342, #3345, #3322))
    • [developer] Many more task regression tests (#3240)

    New features in crowdsourcing

    • General improvements to ACUTE-Eval implementation, docs, and introduction of analysis framework (#3374, #3333, #3344, #3305, #3323)
    • Conversion of turn annotations to Mephisto (#3262, #3356)
    • Mephisto QA data collection (#3318, #3330)
    • Mephisto image-chat task (#3320)
    • Documentation improvements (#3319, #3373)
    • Fixing flaky tests (#3363, #3372, #3321, #3355)

    Smaller bugfixes

    • Allow differing arguments for dynamic batching in eval/train (#3382)
    • fix: deprecated argument when calling transformers>4.0.0 (#3393)
    • Small bugs with crowdsourcing (#3346, #3386, #3387)
    • Fix a misparse of -o (#3347)
    • Fix bert models in distributed. (#3351)
    • Suppress PermissionErrors in windows deletions. (#3340)
    • Fix for Interactive Web with TF-IDF models (#3381)
    • Fix a small bug in Wizard of Wikipedia task (#3100)
    • Fix minor idx not-existing issue in world_logging (#3317)
    Source code(tar.gz)
    Source code(zip)
  • v0.10.0(Dec 16, 2020)

    Backwards compatibility breakages:

    • TorchClassifierAgent changed use_reply default from 'label' to 'none' (#3128)
    • [BERT] Deprecate Adam with Decay (#3235)

    Major features

    • [safety] Open source Sensitive Topics classifier and data (#3253, #3259, #3260, #3258, #3230, #3227, #3252)
    • Support for model distillation (#3274)
    • [docs] Link to request Multi-Modal BlenderBot weights (#3281)

    Minor features

    • DialogTeacher provides verbose warning if opt['datafile'] is not set (#3140)
    • [bpe] Support BPE dropout (#3232)
    • Support special tokens in non-HF BPE dictionaries. (#3213)
    • Unify verbose & display_verbose, enable verbose during interactive (#3205, #3248)
    • BART Supports incremental decoding (#3231)
    • Use more modern metrics reporting with data_stats. (#2854)
    • Ease-of-use improvements to wrapper teacher (#3247)
    • Add classifier for style-controlled generation (#2829)
    • Add support for frozen encoders (only train head) in TorchClassifierAgent (#3215)

    Mephisto Migrations & Upgrades

    • [CrowdSourcing] Turn annotation edits (#3234)
    • Fast ACUTE in Mephisto (#3297)
    • Mephisto API upgrades (#3275, #3285)
    • Remove two old MTurk tasks (#3225)
    • Port static turn annotations to Hydra (#3149)
    • Add command for viewing all Hydra parameters (#3210)
    • Analysis script for static turn annotations (#3263)
    • Make the log rate an adjustable parameter (#3189)

    Bug Fixes:

    • Fix argparse issues in python 3.8 (#3284)
    • Torch 1.8 Compatibility (#3228)
    • Fix dialogpt dual usage of END_IDX (#3256), broken by adding support by adding batchsize > 1
    • Fix minor bugs with GPT2 (#3261, #3207, #3208)
    • Fix an issue where ChunkTeacher would sometimes repeat examples (#3244, #3301)
    • make dir at start of dict.save (#3250)
    • Fix a bug in distributed sync when metrics dicts become large (#3291)
    • [BART] Some smaller bug fixes (#3272, #3236)
    • Data parallel is now false in Offensive Language Classifier (#3212)
    • Fix a bug with LR scheduler loading from disk in TCA (#3229)

    Developer changes:

    • Task regression testing (#3223)
    • Stabilized distributed gpt2 test (#3219)
    • CI for Mephisto tasks (#3206, #3238, #3246, #3254)
    • CircleCI refactor (#3245)
    • Documentation improvements (#3226, #3251)
    • Deprecated some dead code (#3257)
    • Various CI fixes (#3310, #3264)
    Source code(tar.gz)
    Source code(zip)
  • v0.9.4(Oct 16, 2020)

    v0.9.4 release

    Known issues

    • Short options like -m and -t do fail in Python 3.8. Use --model and --task

    New project/paper releases

    • Safety recipes project (#3190, #3199)
    • Gender bias project (#3171, #3146, #3131))
    • Multimodal Blender Bot (#3152, #3151, #3144)
    • LIGHT Quests project (#3153, #3156)

    Major MTurk changes

    • [Removal] Deleting 2/3 of MTurk (#3161)
    • [Upgrade] Porting ACUTE-Eval task to Hydra (#3103)
    • [Task] Adding option for file with annotation indices per conversation and other features to turn annotations static (#3154, #3142)
    • [Docs] AcceptabilityChecker doc (#3124)

    New Features

    • [ParlAI] Adding tensorboard_logdir argument to TensorboardLogger. (#3184)
    • [ParlAI] [TGA] Return text for all beams (#3123, #3179)
    • [ParlAI] Using the parlai color (#3137)
    • [ParlAI] Add a --version flag to the parlai command #3163 (#3164)
    • [Task] Improvements to Taskmaster-2 (#3135, #3134, #3129)
    • [Task] Flag to enable polarity categories in ImageChat (#3132)
    • [Model] Allow Polyencoder to resize token embs (#3194)

    Bug Fixes

    • [Model] Fix GPT-2 generation when using batchsize >1
    • [ParlAI] Show subcommand help error messages on parse error in supercommand. (#3196)
    • [ParlAI] Fixes to --init-model options and --init-opt. (#3162, #3112)
    • [ParlAI] Update requests version (#3155)
    • [HuggingFace/GPT2] Check directory depending on size param for gpt2 files (#3158)
    • [Docs] Correct swapped README links (#3166)
    • [Task] ConvAI2: Bug fix in convai2:normalized NormalizedTeacher (#3168)
    • [Task] COCO: Make sure folder is always created when unzipping COCO (#3143)

    Developer notes & Tests

    • [Tests] New/fixed tests (#3167, #3117, #3114, #3082)
    • [Feature] Add ability for Metrics to add metrics from another Metrics object (#3145)
    • [Docs] Comments in AbstractWrapperTeacher.act() (#3160)
    • [Docs] Documentation improvements to poly-encoder (#3159)
    • [Quality] distributed_eval now mimics distributed_train (#3157)
    • [Quality] Add "fb" option to autoformat script for parlai_fb (#3165)
    Source code(tar.gz)
    Source code(zip)
  • v0.9.3(Sep 28, 2020)

    Known issues

    • Short options like -m and -t do fail in Python 3.8. Use --model and --task

    Breaking Changes

    • A number of old MTurk tasks have been archived and removed from the code (#3085)

    New Features

    • [image] Detectron feature extraction (#3083)
    • [data] Natural questions (#3070)
    • [data] TaskMaster-2 (#2678)
    • [data] New versions of multiwoz (#3072)
    • [distributed] Allow non-tcp based distributed setup (#3095)
    • [core] Move torch.load/torch.save to PathManager. (#3094, #3077)
    • [mturk] New task on static turn annotations (#3053)
    • [mturk] New features in human+model annotation (#3006)
    • [core] TorchClassifierAgent now prints its number of prameters (#3086)

    Doc Changes:

    • New Worlds tutorial (#3049)
    • Tutorial on using -t jsonfile (#3061)
    • Better help message for --init-model (#3090)
    • Additions to FAQ (#3073)
    • Updated model zoo descriptions for BlenderBot (#3096)

    Bug Fixes

    • Distributed evaluation now writes to world logs earlier (#3122)
    • An argument was updated from store_true to bool (#3113)
    • Self-chat now fails loudly with unexpected batchsize (#3081)
    • Update drqa default tokenizer away from removed (#3069)
    • Using wizard of wikipedia in interactive mode downloads data (#3079)

    Developer notes:

    • New pre-commit git-secrets (#3106)
    • Code coverage improvements (#3110, #3091)
    • More reliable tests. (#3108, #3097, #3055)
    • Mephisto task dependencies have been updates due to security bugs (#3111, #3101, #3104)
    • MTurk config folders are exempt from init.py requirements (#3105)
    Source code(tar.gz)
    Source code(zip)
  • v0.9.2(Sep 10, 2020)

    v0.9.2 release notes

    Breaking changes:

    • Fix no-op mask fill in some of the the transformer/ranker models (#3068). We believe this to be fine, but it may change the performance of some ranking models. If you are training a transformer/ranker or polyencoder model and you notice your model no longer gets the same performance, please file an issue on GitHub.

    Bugfixes:

    • Fix a bug where using tensorboard in training caused a crash (#3067)
    • Fix a bug where BART failed to load from checkpoint properly (#3060)
    • Fix an issue where some arguments could not be overridden in BART (#3065)

    Other:

    • fromfile now emits a warning about using valid/test (#3063)
    Source code(tar.gz)
    Source code(zip)
  • v0.9.1(Sep 8, 2020)

    Version 0.9.1 Changelog:

    ParlAI now supports pytorch 1.6.

    Breaking changes:

    • Change the arguments for JsonFile teacher, and fix some bugs (#3054)
    • ParlAI now expects HuggingFace tokenizers >=0.8.0 (#2967)

    New features/Improvements:

    • Release of LIGHT-WILD project (#2992)
    • HRED has now been added as a standard model (#2989)
    • DialoGPT has been added as a standard model (#3007)
    • Allow colored logging in jupyter notebooks. (#3024)
    • [Squad2] Add option to change label for impossible answers (#3020)
    • ChunkTeacher has support to prevent auto enqueuing (#2993)
    • Add support for PathManager. (#3011)
    • DistilGPT2 has been added as an option of GPT2 model (#2997)
    • tfidf_retriever now reports doc ids (#3008)

    Lots of new/updated documentation

    • Custom metrics tutorial (#2975)
    • Chat Services tutorial clarification (#3048)
    • Release of Mephisto ACUTE-Evals (#3002)
    • Writing custom scripts and integration with parlai command (#3046)
    • Writing tests for ParlAI (#3044)
    • Contributor guide (#3047)
    • Mark deprecation of ParlAI MTurk for Mephisto (#2988)
    • Updates to docs on how to build docs (#3041)
    • Update Link and Commands Display format (#2952)
    • Small modifications (#3036, #2994, #3031, #2916)

    Bugfixes:

    • Upgrade to pytorch 1.6 (#3022)
    • Linear/Cosine LR schedulers don't crash in distributed (#3000)
    • Fix unexpected crashes in convo_render (#3052)
    • Context block segfault fix (#3019)
    • Fix crash in loading from checkpoint in Cosine/Linear LR schedulers (#3025)
    • Upgrade schedulers to be Pytorch 1.6 friendly (#3025)
    • Fix bug where "restart conversation" didn't work in chat_services browser (#3050)
    • Faster amazon QA teacher (#2851)
    • Fix crashes to Reward Unlikelihood agent (#3034)
    • Fix a misalignment in BART agent between generation and training (#3021)
    • Prevent mixing model parallel and multiprocessing. (#2964)
    • [ACUTE][Mephisto] Fix extend that should append (#3029)
    • Adding option to load pretrained model from directory for gpt2 (#3027)
    • Fix an obscure crash with dict_file and GPT2 (#3038)

    Developer:

    • Improve coverage of some base agents (#3026)
    • CircleCI now produces a build of website as an artifact (#3035)
    • Rework sphinx docs and upgrade docs to MarkDown (#2972, #2999, #3003)
    • Minor refactor of transformer decoder forward (#3009)
    Source code(tar.gz)
    Source code(zip)
  • v0.9.0(Aug 18, 2020)

    v0.9.0 ChangeLog

    Breaking Changes

    • Removed support for HogWild and ExecutableWorld (#2919)
    • Archived a number of older projects (Mastering the dungeon, TalkTheWalk, Memnn_feed) (#2919)

    New Features

    • [Dynamic Batching] Add world logging capability (#2941)
    • [Torch Generator Agent] Option to block full context (#2928)
    • [Safety] can supply custom offensive language file (#2968)
    • [Safety] Add new model file argument to safety classifiers (#2955)
    • Script for comparing two different opts (#2932)
    • [Image S2S] Standardize Image Seq2Seq Image Processing (#2911)

    Bug fixes

    • [Chunk teacher] Bug with distributed evaluation (#2935)
    • Add encoding to "with open"s in teachers.py (#2946)
    • Fix an issue where parlai suppercommand wasn't handling set_params appropriately (#2956)
    • Fix a bug where Git was trying to be called regard (#2961)
    • Project specific: Personality Captions interactive mode fix (#2963)
    • Project specific: fix openers loading opt (#2965)
    • Fix underscore opt not being handled by parlai supercommand (#2938)
    • [Style] Add style-controlled generation agent (#2913)
    • Add return in report of wrapper agents (#2907)

    Doc updates

    • Fixed a mistake in documentation for creating tasks based on ParlAIDialogTeacher. (#2973)
    • Updated link for LICENSE file (#2970)
    • Added pip installation guide to Readme.md (#2959)
    • Mention colab tutorial in our quickstart tutorial (#2936)

    Other

    • Tweak colors of logs. (#2940)
    • Add printing of opts into scripts. (#2933)
    • [Dodeca] Split Dodeca tar file (#2934)
    • [BART/TGA] BART and TGA API Updates (#2840)
    • Show all stdout on GPU tests (#2929)
    Source code(tar.gz)
    Source code(zip)
  • v0.8.0(Aug 4, 2020)

    Tying off a "pieces of 8" release, with an arbitrary version number to switch to semantic versioning.

    Notable additions:

    • Fix a bug in distributed launching (#2850)
    • Add support for reversed history in TorchAgent (--history-reversed true), which reverses text_vec. (#2786, #2888 )
    • A new parlai super command, with a script registry. This replaces all the usage of "examples/train_model.py" etc. (#2859, #2845, #2860, #2887, #2889)
    • Some improvements to model parallelization (#2839)
    • Add some timing metrics, including tps (tokens per second), etc. (#2878)
    • Self-chat can set up two models talking to each other with different options (#2803)
    • An mturk task with per-turn annotations (#2877, #2886)
    • An abstract class for writing "wrapper" teachers, which contain some transformation of data (#2842)
    • Support writing to a log in an interactive script (#2881)

    Bug fixes:

    • Fix a type error in valid_step (#2890)
    • Improve the output when listing differences between an init model and specified options (#2880)
    • Upgrade TGA to be compatible with pytorch 1.6 (#2902)
    • Fix a bug in seq2seq that broke with pytorch 1.6 (#2910)

    Breaking changes:

    • Switch --load-from-checkpoint to True by default in train_model
    • Upgrade dependency to pillow 7.2.0 for a security reason (#2896)
    • Switch to using a suffix on the model file, instead of a NamedTemporaryFile, for atomic save (#2898)
    • Removed some old deprecated pytorch data teacher text (#2883)
    Source code(tar.gz)
    Source code(zip)
  • v0.1.20200716(Jul 16, 2020)

    Notable additions since 2020-07-13:

    • Support for adding special to tokenizers (#2828)
    • Distributed Evaluation, to help scale generations/evaluations across many GPUs (#2775)
    • Google SGD dataset (#2738).

    Other notable features since 2020-06-16:

    • Multi-turn chunk teacher (#2805)
    • Fromfile jsonl teacher; works directly from files dumped by self_chat, ACUTE logs, etc. (#2717)
    • BART model now part of parlai (-m bart) (#2781)
    • Atomic saves to be more robust to preemption (#2760)

    Recent bugfixes:

    • #2789: crash when printing an empty report
    • #2788: multi-tasking failed to sample appropriately with --datatype train:stream.
    Source code(tar.gz)
    Source code(zip)
  • v0.1.20200416(Apr 17, 2020)

  • v0.1.20200409(Apr 9, 2020)

Owner
Facebook Research
Facebook Research
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