Search is not available for this dataset
repo stringlengths 2 152 ⌀ | file stringlengths 15 239 | code stringlengths 0 58.4M | file_length int64 0 58.4M | avg_line_length float64 0 1.81M | max_line_length int64 0 12.7M | extension_type stringclasses 364
values |
|---|---|---|---|---|---|---|
tb3py | tb3py-master/setup.py | #!/usr/bin/python3
import os
import sys
import subprocess
# import requests
import glob
import os
from setuptools import setup, find_packages
base_dir = os.path.dirname(__file__)
with open(os.path.join(base_dir, "README.md")) as f:
long_d = f.read()
def precompile(julia=None):
"""Precompile Julia"""
p... | 3,636 | 26.976923 | 206 | py |
tb3py | tb3py-master/.github/workflows/main.yml | name: tb3py-action
on: [push, pull_request]
jobs:
build:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: [3.8]
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${... | 1,366 | 30.790698 | 149 | yml |
tb3py | tb3py-master/tb3py/__init__.py | """Version number."""
__version__ = "2021.11.11"
| 49 | 15.666667 | 26 | py |
tb3py | tb3py-master/tb3py/main.py | """Module to run tb3py."""
import sys
import os
import numpy as np
from julia.api import Julia
from jarvis.core.kpoints import Kpoints3D as Kpoints
# from jarvis.core.kpoints import generate_kgrid
import matplotlib.pyplot as plt
from jarvis.db.figshare import get_jid_data
from jarvis.core.atoms import Atoms
import a... | 7,914 | 29.678295 | 166 | py |
tb3py | tb3py-master/tb3py/pred.py | """Predict properties of a db."""
from jarvis.db.figshare import data
from jarvis.db.jsonutils import dumpjson
from sklearn.metrics import mean_absolute_error
import matplotlib.pyplot as plt
from jarvis.core.atoms import Atoms
from tb3py.main import get_energy
plt.switch_backend("agg")
def predict_for_db(
datas... | 2,251 | 27.506329 | 64 | py |
tb3py | tb3py-master/tb3py/Bandgaps/gap_auto_multi.py | """Module for vacancy formation energy."""
# from jarvis.analysis.defects.vacancy import Vacancy
from jarvis.db.jsonutils import dumpjson
from jarvis.core.atoms import Atoms
from jarvis.db.figshare import data
from tb3py.main import get_energy
# from jarvis.analysis.thermodynamics.energetics import get_optb88vdw_ener... | 2,321 | 20.109091 | 76 | py |
tb3py | tb3py-master/tb3py/Surf/surf_auto_multi.py | # from jarvis.analysis.defects.vacancy import Vacancy
from jarvis.db.jsonutils import dumpjson
from jarvis.core.atoms import Atoms
from jarvis.db.figshare import get_jid_data, data
from tb3py.main import get_energy
# from jarvis.analysis.thermodynamics.energetics import get_optb88vdw_energy
from jarvis.analysis.structu... | 4,740 | 21.258216 | 79 | py |
tb3py | tb3py-master/tb3py/Surf/surf_auto_multiv1.py | from jarvis.db.jsonutils import dumpjson
from jarvis.core.atoms import Atoms
from jarvis.db.figshare import get_jid_data, data
from tb3py.main import get_energy
# from jarvis.analysis.thermodynamics.energetics import get_optb88vdw_energy
from jarvis.analysis.structure.spacegroup import (
Spacegroup3D,
symmetric... | 5,236 | 22.59009 | 174 | py |
tb3py | tb3py-master/tb3py/Vacancy/chempot_maker1.py | """Module for making chemical potentials."""
# from jarvis.analysis.defects.vacancy import Vacancy
from jarvis.db.jsonutils import dumpjson
from jarvis.core.atoms import Atoms
from jarvis.db.figshare import data
from tb3py.main import get_energy
from collections import defaultdict
# from jarvis.analysis.thermodynamic... | 4,792 | 18.019841 | 76 | py |
tb3py | tb3py-master/tb3py/Vacancy/defects_comparison.py | """Compare vacancy and surface energy plots."""
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
import pandas as pd
plt.switch_backend("agg")
df = pd.read_csv("defects_comparison.csv")
V_DFT = df["V_DFT"].dropna().values
V_TB = df["V_TB"].dropna().values
Gamma_DFT = df["Gamma_DFT"].dropna().v... | 1,001 | 21.772727 | 47 | py |
tb3py | tb3py-master/tb3py/Vacancy/vac_auto_multi.py | from jarvis.analysis.defects.vacancy import Vacancy
from jarvis.db.jsonutils import loadjson, dumpjson
from jarvis.core.atoms import Atoms
from jarvis.db.figshare import data
from tb3py.main import get_energy
# from jarvis.analysis.thermodynamics.energetics import get_optb88vdw_energy
dat = data("dft_3d")
# x = get_... | 4,865 | 22.061611 | 76 | py |
tb3py | tb3py-master/tb3py/Vacancy/vac_auto_multiv1.py | from jarvis.analysis.defects.vacancy import Vacancy
from jarvis.db.jsonutils import loadjson, dumpjson
from jarvis.core.atoms import Atoms
from jarvis.db.figshare import data
from tb3py.main import get_energy
# from jarvis.analysis.thermodynamics.energetics import get_optb88vdw_energy
dat = data("dft_3d")
# x = get_... | 4,747 | 22.50495 | 76 | py |
tb3py | tb3py-master/tb3py/examples/example_using_julia_functions_directly.py | import tb3py.main as tb3
import numpy as np
#this example shows how to use the julia commands directly in python.
#it is also possible to access some of these commands with a more pythonic
#interface using functions defined in main.py
#make crystal object from POSCAR
#c = tb3.TB.makecrys("POSCAR")
c = tb3.TB.makecr... | 846 | 23.2 | 74 | py |
tb3py | tb3py-master/tb3py/tests/__init__.py | 0 | 0 | 0 | py | |
tb3py | tb3py-master/tb3py/tests/test_ptop.py | from tb3py.main import example, get_energy_bandstructure
def test_example():
energy, tbc, flag = example()
print(energy)
assert round(energy, 5) == round(-0.43160184930052803, 5)
def test_jarvis_dat():
from jarvis.db.figshare import get_jid_data
from jarvis.core.atoms import Atoms
atoms = A... | 468 | 21.333333 | 64 | py |
null | ParlAI-main/.pre-commit-config.yaml | repos:
- repo: https://github.com/psf/black
rev: 22.3.0
hooks:
- id: black
language_version: python3
- repo: local
hooks:
- id: git-secrets
language: script
entry: .github/scripts/git-secrets --pre_commit_hook
name: git-secrets
require_serial: true
| 317 | 21.714286 | 60 | yaml |
null | ParlAI-main/CODE_OF_CONDUCT.md | # Code of Conduct
## Our Pledge
In the interest of fostering an open and welcoming environment, we as
contributors and maintainers pledge to make participation in our project and
our community a harassment-free experience for everyone, regardless of age, body
size, disability, ethnicity, sex characteristics, gender i... | 3,355 | 42.584416 | 87 | md |
null | ParlAI-main/CONTRIBUTING.md | # Contributing to ParlAI
While we are seeding this project with an initial set of popular tasks and a few
models and examples, ongoing contributions from the research community are
desired to increase the pool of tasks, models, and baselines.
## Pull Requests
We actively welcome your pull requests.
1. Fork the repo... | 3,038 | 42.414286 | 157 | md |
null | ParlAI-main/NEWS.md | ## News
**Archive Information**
We are now making most of our major announcements on [Twitter](https://twitter.com/parlai_parley) and in our
[Release Notes](https://github.com/facebookresearch/ParlAI/releases).
### Older news
2020-07-21: We have added a new `parlai` super command, complete with [autocompletion](http... | 10,628 | 86.122951 | 911 | md |
null | ParlAI-main/README.md | <p align="center">
<img width="70%" src="docs/source/\_static/img/parlai.png" />
</p>
<p align="center">
<a href="https://github.com/facebookresearch/ParlAI/blob/main/LICENSE">
<img src="https://img.shields.io/badge/license-MIT-blue.svg" alt="CircleCI" />
</a>
<a href="https://pypi.org/project/parlai/">
... | 11,675 | 56.80198 | 1,098 | md |
null | ParlAI-main/autoformat.sh | #!/bin/bash
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# exit on errors
set -e
# configuration options for our doc formatting
DOCOPTS="--pre-summary-newline --wrap-descriptions 88 --wra... | 4,824 | 25.222826 | 112 | sh |
null | ParlAI-main/codecov.yml | coverage:
status:
project: off
patch: off
changes: off
ignore:
- parlai/tasks/*/build.py
| 105 | 12.25 | 27 | yml |
null | ParlAI-main/conftest.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
This is used to configure markers on tests based on filename.
We use this to split up tests into different circlec... | 4,125 | 31.746032 | 87 | py |
null | ParlAI-main/setup.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import sys
from setuptools import setup, find_packages
VERSION = '1.7.2' # if you update, update parlai/__init__.py ... | 1,660 | 30.942308 | 86 | py |
null | ParlAI-main/.circleci/config.yml | version: 2.1
# -------------------------------------------------------------------------------------
# environments where we run our jobs
# -------------------------------------------------------------------------------------
executors:
standard_cpu39:
docker:
- image: cimg/python:3.9.16
environment:
... | 15,467 | 32.051282 | 228 | yml |
null | ParlAI-main/.github/pull_request_template.md | **Patch description**
<!--Please enter a clear and concise description of what your pull request does, and why
it is necessary. If your patch fixes an issue, please reference that issue here. -->
**Testing steps**
<!-- Enter steps to test your pull request. Give a clear and concise description of
what you expected to ... | 586 | 47.916667 | 97 | md |
null | ParlAI-main/.github/ISSUE_TEMPLATE/agent-bug.md | ---
name: "[Agent Bug]"
about: Reporting problems or unexpected behavior with an Agent or pretrained model.
---
**Bug description**
Please enter a clear and concise description of what the bug is.
**Reproduction steps**
Enter steps to reproduce the behavior.
**Expected behavior**
Give a clear and concise descriptio... | 556 | 21.28 | 103 | md |
null | ParlAI-main/.github/ISSUE_TEMPLATE/feature-request.md | ---
name: "[Feature Request]"
about: Suggest an idea for this project
---
**Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
**Describe the solution you'd like**
A clear and concise description of what you wa... | 564 | 30.388889 | 92 | md |
null | ParlAI-main/.github/ISSUE_TEMPLATE/mturk-bug.md | ---
name: "[MTurk]"
about: Reporting problems or unexpected behavior with MTurk
---
**Bug description**
Please enter a clear and concise description of what the bug is.
**Reproduction steps**
Enter steps to reproduce the behavior:
1. Go to '...'
2. Click on '....'
3. Scroll down to '....'
4. See error
**Expected be... | 1,173 | 29.894737 | 82 | md |
null | ParlAI-main/.github/ISSUE_TEMPLATE/other.md | ---
name: "[Other]"
about: For anything else you want an issue for
---
Use this to open other questions or issues, and provide context here.
| 143 | 17 | 69 | md |
null | ParlAI-main/.github/workflows/lint.yml | name: Lint
on:
push:
branches:
- main
pull_request:
jobs:
pre-commit:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- uses: actions/setup-python@v2
- uses: pre-commit/action@v2.0.0
lint:
runs-on: ubuntu-latest
steps:
- name: Setup Python
uses: act... | 5,552 | 32.859756 | 130 | yml |
null | ParlAI-main/.github/workflows/stale.yml | name: Mark stale issues and pull requests
on:
schedule:
- cron: "0 0 * * *"
permissions:
contents: read
jobs:
stale:
permissions:
issues: write # for actions/stale to close stale issues
pull-requests: write # for actions/stale to close stale PRs
runs-on: ubuntu-latest
steps:
- us... | 903 | 33.769231 | 194 | yml |
null | ParlAI-main/docs/README.md | # Updating the documentation
First, if you haven't already, run:
```bash
cd ~/ParlAI; python setup.py develop
```
Then use make to build the html:
```
make html
```
NOTE: Autodocs imports many agents, so you may run into `ImportError`s when running `make`. Just `pip install` as needed to continue.
Then, make any ch... | 702 | 40.352941 | 185 | md |
null | ParlAI-main/docs/sample_model_cards/blenderbot_90M/model_card.md | # Blender 90M
90M-parameter generative model finetuned on blended_skill_talk tasks.
- Developed by Facebook AI Research using [ParlAI](https://parl.ai/)
- Model started training on February 10, 2007.
- Type of model: Transformer Generative Model
### Quick Usage
```
python parlai/scripts/safe_interactive.py -m... | 10,399 | 41.975207 | 547 | md |
null | ParlAI-main/docs/sample_model_cards/safety_multi/model_card.md | # BERT Classifier Multi-turn Dialogue Safety Model
Classifier trained on the multi-turn adversarial safety task in addition to both the single-turn standard and adversarial safety tasks and Wikipedia Toxic Comments.
- Developed by Facebook AI Research using [ParlAI](https://parl.ai/)
- Model started training on Se... | 6,475 | 29.985646 | 252 | md |
null | ParlAI-main/docs/source/agents_list.md | # Standard Agents
ParlAI comes with a wide variety of standardized agents. Some of these are
common baselines made available for quicker research; some can be made
state-of-the-art with careful tuning and experimentation. Each of these contains
a README with examples of usage and description of the agent.
```{toctree... | 385 | 24.733333 | 80 | md |
null | ParlAI-main/docs/source/chat_service.md | # parlai.chat_service
ParlAI's chat service functionality.
## Chat Service Core
### parlai.chat_service.core.agents
```{eval-rst}
.. automodule:: parlai.chat_service.core.agents
:members:
```
### parlai.chat_service.core.core.chat_service_manager
```{eval-rst}
.. automodule:: parlai.chat_service.core.chat_servic... | 3,113 | 20.776224 | 75 | md |
null | ParlAI-main/docs/source/cli_advanced.md | # Advanced Scripts
These are the more obscure and advanced scripts in parlai.
```{include} cli_advanced.inc
```
| 114 | 15.428571 | 58 | md |
null | ParlAI-main/docs/source/cli_custom.md | # Writing Your Own Script
Author: Kurt Shuster
## Custom ParlAI Script
If you have accustomed yourself with the `parlai` command and would like to write your own ParlAI-based script, this tutorial is meant for you. Writing and using a script today in ParlAI is a smooth experience, thanks to recent work in standardiz... | 3,210 | 32.447917 | 324 | md |
null | ParlAI-main/docs/source/cli_usage.md | # Command Line Usage
This contains the command line usage for each of the standard scripts we
release. These are each included in `parlai/scripts`, and all may
be invoked with the "parlai" supercommand.
The parlai supercommand may be invoked from the command line by running
`parlai` after installing ParlAI. Its defau... | 1,166 | 28.923077 | 84 | md |
null | ParlAI-main/docs/source/conf.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
#
# ParlAI documentation build configuration file, created by
# sphinx-quickstart on Wed Apr 19 ... | 6,624 | 30.25 | 109 | py |
null | ParlAI-main/docs/source/core.md | # parlai.core
This contains the full, comprehensive docstrings of all of `parlai.core`,
which powers the vast majority of ParlAI.
```{toctree}
:maxdepth: 1
:glob:
core/*
```
| 177 | 13.833333 | 73 | md |
null | ParlAI-main/docs/source/faq.md | # Frequently Asked Questions
This document contains a number of questions that are regularly asked on GitHub Issues.
## Why is my model not generating a response?
For a generative model, check that `--skip-generation` is set to `False`.
## Why can't I reproduce the results of an evaluation on a task with a pretrain... | 1,953 | 38.877551 | 88 | md |
null | ParlAI-main/docs/source/generate_agent_list.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.abs
import parlai.core.agents
import parlai.agents
from parlai.core.params import ParlaiParser
import argparse
import os
... | 5,144 | 33.3 | 88 | py |
null | ParlAI-main/docs/source/generate_cli.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import importlib
import inspect
import argparse
import parlai.core.script as pcs
def render_script(fout, key, registra... | 3,507 | 32.730769 | 86 | py |
null | ParlAI-main/docs/source/generate_metric_list.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from parlai.core.metrics import METRICS_DISPLAY_DATA
fout = open('metric_list.inc', 'w')
fout.write('| Metric | Expla... | 509 | 27.333333 | 65 | py |
null | ParlAI-main/docs/source/generate_mutator_list.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import textwrap
import argparse
from parlai.core.params import ParlaiParser
from parlai.core.mutators import setup_mutato... | 4,213 | 35.643478 | 88 | py |
null | ParlAI-main/docs/source/generate_opt_presets.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import json
import pkg_resources
from parlai.opt_presets.docs import PRESET_DESCRIPTIONS
fout = open('opt_presets_list... | 1,047 | 36.428571 | 82 | py |
null | ParlAI-main/docs/source/generate_task_READMEs.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from parlai.tasks.task_list import task_list
import os
tasks = {}
for task_dict in task_list:
id = task_dict.get('i... | 1,443 | 29.723404 | 69 | py |
null | ParlAI-main/docs/source/generate_task_list.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from parlai.tasks.task_list import task_list
MAIN = "https://github.com/facebookresearch/ParlAI/tree/main"
categories =... | 2,277 | 33.515152 | 74 | py |
null | ParlAI-main/docs/source/generate_zoo_list.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from parlai.zoo.model_list import model_list
category_zoo_list = {}
for model_dict in model_list:
task = model_dict... | 2,262 | 28.38961 | 82 | py |
null | ParlAI-main/docs/source/index.md | # ParlAI Documentation
ParlAI is a one-stop-shop for dialog research.
```{toctree}
:maxdepth: 1
:caption: Tutorials & Explanations
tutorial_quick
tutorial_basic
tutorial_task
tutorial_worlds
tutorial_torch_generator_agent
tutorial_torch_ranker_agent
tutorial_metrics
tutorial_fast
tutorial_mutators
tutorial_crowdsour... | 796 | 11.854839 | 46 | md |
null | ParlAI-main/docs/source/mutators.md | # Mutators
List of ParlAI mutators. Mutators are teacher-independent transformations, and
are useful for writing transformations you want to apply to multiple datasets.
Mutators are available any time teachers are used, i.e. when there is a `--task`
argument. Mutators may also be stacked, e.g. `--mutators flatten,wor... | 500 | 32.4 | 80 | md |
null | ParlAI-main/docs/source/opt_presets.md | # Opt Presets
Opt presets are a way to provide multiple options on the command line as
shorthand. Opt presets are bundled with ParlAI and may be used by simply
invoking the `-o preset_name` option within any ParlAI command.
You may also define your own options by placing them in `~/.parlai/opt_presets/`.
For example,... | 727 | 27 | 81 | md |
null | ParlAI-main/docs/source/tasks.md | # Tasks
List of ParlAI tasks defined in the file [task_list.py](https://github.com/facebookresearch/ParlAI/tree/main/parlai/tasks/task_list.py).
```{include} task_list.inc
```
| 179 | 21.5 | 136 | md |
null | ParlAI-main/docs/source/tutorial_basic.md | Intro to ParlAI
===============
__Authors__: Alexander Holden Miller, Margaret Li, Jason Weston
What is ParlAI?
---------------
ParlAI is a python-based platform for enabling dialog AI research.
Its goal is to provide researchers:
- a unified framework for sharing, training and testing dialog models
- many pop... | 16,039 | 36.652582 | 158 | md |
null | ParlAI-main/docs/source/tutorial_chat_service.md | # Using Chat Services
This is a tutorial for connecting your trained ParlAI agents to various chat services in order to allow your models to talk to humans. Humans using chat services (like Facebook Messenger) can be viewed as another type of agent in ParlAI and communicate in the standard observation/act dict format.... | 12,200 | 58.228155 | 402 | md |
null | ParlAI-main/docs/source/tutorial_crowdsourcing.md | Running crowdsourcing tasks
=====================
__Authors__: Jack Urbanek, Emily Dinan, Will Feng, Eric Smith
:::{warning}
ParlAI's MTurk functionality has expanded out of this project to become [Mephisto](https://github.com/facebookresearch/Mephisto), and the ParlAI crowdsourcing code has moved from `parlai.mturk` ... | 17,078 | 64.436782 | 652 | md |
null | ParlAI-main/docs/source/tutorial_docker.md | ParlAI Docker image
==================
**Authors**: Mojtaba Komeili
We offer a Docker image that provides a ready to use environment for ParlAI.
This image comes with pre-installed ParlAI, along with some extra packages often required for using it.
You can find it under Packages in our main Github repository ([link](... | 4,618 | 53.341176 | 183 | md |
null | ParlAI-main/docs/source/tutorial_fast.md | # Speeding up training
Author: Stephen Roller
This tutorial walks you through a few ways to massively speed up your training
runs in ParlAI. These tricks tend to work best with generative models, but some
can also be used with others.
:::{warning} Retuning-hyperparameters
Many of these options are effectively tricks... | 9,767 | 47.356436 | 85 | md |
null | ParlAI-main/docs/source/tutorial_metrics.md | # Understanding and adding metrics
Author: Stephen Roller
## Introduction and Standard Metrics
:::{tip} List of metrics
If you're not sure what a metric means, refer to our [List of metrics](#list-of-metrics).
:::
ParlAI contains a number of built-in metrics that are automatically computed when
we train and evaluat... | 18,697 | 43.308057 | 151 | md |
null | ParlAI-main/docs/source/tutorial_model_cards.md | # Generating Model Cards
**Author**: Wendy Zhang
## What is a model card?
Think of model cards as a condensed medical card for models. It is a great way for people who might not have the time to read a paper in detail to get the gist of what a model is doing, the datasets involved, how it is performing, and any con... | 9,448 | 49.801075 | 400 | md |
null | ParlAI-main/docs/source/tutorial_mutators.md | # Mutators
**Author**: Stephen Roller
Mutators are task-independent data transformations, which are applicable to
_any_ dataset. Examples of mutators include:
- Reversing all the turns in a conversation
- Down-sampling the dataset
- Shuffling the words in a turn
- and much more
Mutators are particularly useful when... | 4,447 | 34.870968 | 172 | md |
null | ParlAI-main/docs/source/tutorial_quick.md | ParlAI Quick-start
==================
**Authors**: Alexander Holden Miller, Margaret Li
Colab Tutorial
--------------
As an alternative to this quick start tutorial, you may also consider our
[Google Colab tutorial](https://colab.research.google.com/drive/1bRMvN0lGXaTF5fuTidgvlAl-Lb41F7AD#scrollTo=KtVz5dCUmFkN),
whi... | 6,375 | 30.254902 | 199 | md |
null | ParlAI-main/docs/source/tutorial_swap_components.md | # Swapping Out Transformer Subcomponents
__Author__: Spencer Poff
Sometimes you find yourself wanting to experiment with an architecture that looks a lot like another, but with one component modified. If that component is buried deep within the model, this is not easily accomplished with subclassing without copying a... | 2,388 | 36.328125 | 299 | md |
null | ParlAI-main/docs/source/tutorial_task.md | # Tasks and Datasets in ParlAI
__Authors__: Alexander Holden Miller, Filipe de Avila Belbute Peres, Jason Weston, Emily Dinan
ParlAI can support fixed dialogue data for supervised learning (which we
call a dataset) or even dynamic tasks involving an environment, agents
and possibly rewards (we refer to the general ca... | 25,438 | 39.964573 | 306 | md |
null | ParlAI-main/docs/source/tutorial_tests.md | # Tests in ParlAI
Author: Kurt Shuster
## Running a Test
To run tests in ParlAI, we use [pytest](https://docs.pytest.org/en/stable/). The following commands are taken from the `tests` directory [README](https://github.com/facebookresearch/ParlAI/tree/main/tests).
*To run all tests in your current directory, simply ... | 16,592 | 52.01278 | 875 | md |
null | ParlAI-main/docs/source/tutorial_tipsntricks.md | Tips and Tricks
===============
Here we list other miscellaneous useful tips of things you can do in
ParlAI not listed elsewhere.
Command line tool
-----------------
ParlAI comes with a "super" command, that has all the other commands
built in:
```bash
$ parlai help
ParlAI - Dialogue Research Platform
usage: parlai... | 8,285 | 45.033333 | 414 | md |
null | ParlAI-main/docs/source/tutorial_torch_generator_agent.md | # Using Torch Generator Agent
**Authors**: Eric Smith
`parlai.core.torch_generator_agent.TorchGeneratorAgent` is an abstract parent class that provides functionality for building autoregressive generative models. Extending `TorchGeneratorAgent` requires your model conform to a strict interface, but then provides you ... | 7,558 | 47.146497 | 670 | md |
null | ParlAI-main/docs/source/tutorial_torch_ranker_agent.md | Using Torch Ranker Agent
========================
__Authors__: Emily Dinan
TorchRankerAgent is an abstract parent class for PyTorch models that
rank possible responses from a set of possible candidates. It inherits
from TorchAgent and contains boilerplate code for training and
evaluating ranking models.
Example Mode... | 4,788 | 31.80137 | 186 | md |
null | ParlAI-main/docs/source/tutorial_worlds.md | Worlds, Sharing & Batching
==========================
__Authors__: Alexander Holden Miller, Kurt Shuster, Stephen Roller
:::{important} Before you begin
If you are unfamiliar with the basics of displaying data or calling train or
evaluate on a model, please first see the [getting started](tutorial_basic)
section. If ... | 16,531 | 41.718346 | 285 | md |
null | ParlAI-main/docs/source/utils.md | # parlai.utils
ParlAI has very many utilities, roughly organized by function.
## parlai.utils.bpe
```{eval-rst}
.. automodule:: parlai.utils.bpe
:members:
```
## parlai.utils.conversations
```{eval-rst}
.. automodule:: parlai.utils.conversations
:members:
```
## parlai.utils.data
```{eval-rst}
.. automodule... | 1,393 | 12.533981 | 62 | md |
null | ParlAI-main/docs/source/zoo.md | Model Zoo
=========
This is a list of pretrained ParlAI models. They are listed by task, or
else in a pretraining section (at the end) when meant to be used as
initialization for fine-tuning on a task.
```{include} zoo_list.inc
```
Pretrained Word Embeddings
--------------------------
Some models support using Pret... | 1,315 | 30.333333 | 142 | md |
null | ParlAI-main/docs/source/_static/css/parlai_theme.css | /*
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
*/
body {
font-family: "Lato","proxima-nova","Helvetica Neue",Arial,sans-serif;
}
/* Default header fonts are ugly */
h1, h2, .rst-content .to... | 3,168 | 18.090361 | 84 | css |
null | ParlAI-main/docs/source/core/agents.md | # parlai.core.agents
```{eval-rst}
.. automodule:: parlai.core.agents
:members:
```
| 86 | 13.5 | 34 | md |
null | ParlAI-main/docs/source/core/build_data.md | # parlai.core.build_data
```{eval-rst}
.. automodule:: parlai.core.build_data
:members:
```
| 94 | 14.833333 | 38 | md |
null | ParlAI-main/docs/source/core/dict.md | # parlai.core.dict
```{eval-rst}
.. automodule:: parlai.core.dict
:members:
```
| 82 | 12.833333 | 32 | md |
null | ParlAI-main/docs/source/core/loader.md | # parlai.core.loader
```{eval-rst}
.. automodule:: parlai.core.loader
:members:
```
| 86 | 13.5 | 34 | md |
null | ParlAI-main/docs/source/core/messages.md | # parlai.core.message
```{eval-rst}
.. automodule:: parlai.core.message
:members:
```
<img src="/docs/_static/img/act-obs-dict.png" width="60%"/>
The primary medium for information flow (messages between agents and the environment)
in ParlAI is a Message, a subclass of a python `dict` containing the actions of an a... | 8,653 | 33.616 | 121 | md |
null | ParlAI-main/docs/source/core/metrics_api.md | # parlai.core.metrics
```{eval-rst}
.. automodule:: parlai.core.metrics
:members:
```
| 88 | 13.833333 | 35 | md |
null | ParlAI-main/docs/source/core/mutators.md | # parlai.core.mutators
```{eval-rst}
.. automodule:: parlai.core.mutators
:members:
```
| 90 | 14.166667 | 36 | md |
null | ParlAI-main/docs/source/core/params.md | # parlai.core.opt
```{eval-rst}
.. automodule:: parlai.core.opt
:members:
```
# parlai.core.params
```{eval-rst}
.. automodule:: parlai.core.params
:members:
```
| 167 | 13 | 34 | md |
null | ParlAI-main/docs/source/core/script.md | # parlai.core.script
```{eval-rst}
.. automodule:: parlai.core.script
:members:
```
| 86 | 13.5 | 34 | md |
null | ParlAI-main/docs/source/core/teachers.md | # parlai.core.teachers
```{eval-rst}
.. automodule:: parlai.core.teachers
:members:
```
| 90 | 14.166667 | 36 | md |
null | ParlAI-main/docs/source/core/torch_agent.md | # parlai.core.torch_agent
Torch Agent implements much of the boilerplate necessary for creating
a neural dialogue agent, so you can focus on modeling. Torch Agent limits its
functionality to maintaining dialogue history, transforming text into vectors of
indices, and loading/saving models. The user is required to impl... | 1,352 | 27.1875 | 80 | md |
null | ParlAI-main/docs/source/core/worlds.md | # parlai.core.worlds
```{eval-rst}
.. automodule:: parlai.core.worlds
:members:
```
| 86 | 13.5 | 34 | md |
null | ParlAI-main/example_parlai_internal/README.md | # Internal subfolder
By creating an internal subfolder, you can set up your own custom agents and tasks,
create your own model zoo, and manage it all with a separate git repository.
We've set it up so you can now work inside the ParlAI folder without the risk of accidentally pushing your work to the public ParlAI repo... | 2,734 | 40.439394 | 138 | md |
null | ParlAI-main/example_parlai_internal/__init__.py | 0 | 0 | 0 | py | |
null | ParlAI-main/example_parlai_internal/agents/parrot/parrot.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from parlai.core.torch_agent import TorchAgent, Output
class ParrotAgent(TorchAgent):
def train_step(self, batch):
... | 640 | 29.52381 | 73 | py |
null | ParlAI-main/parlai/README.md | ParlAI 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 examples of different loops (building dictionary, train/eval, displaying data)
- **tas... | 749 | 61.5 | 104 | md |
null | ParlAI-main/parlai/__init__.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
__version__ = '1.7.2'
| 222 | 26.875 | 65 | py |
null | ParlAI-main/parlai/__main__.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from parlai.core.script import superscript_main
def main():
# indirect call so that console_entry (see setup.py) d... | 547 | 27.842105 | 79 | py |
null | ParlAI-main/parlai/agents/README.md | # Agents
This directory contains a variety of different agents which use ParlAI's interface.
## Utility
- **local_human**: receives human input from the terminal. used for interactive mode, e.g. `parlai/scripts/interactive.py`.
- **legacy_agents**: contains deprecated agent code for posterity
- **random_candidate**:... | 1,385 | 45.2 | 126 | md |
null | ParlAI-main/parlai/agents/__init__.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
| 199 | 32.333333 | 65 | py |
null | ParlAI-main/parlai/agents/alice/README.md | # ALICE Bot
This is an agent that takes an observation, gets the ALICE bot's response the observation, and wraps it into an action's reply.
The ALICE bot is a strong rule-based bot uing AIML.
The Python implementation of the bot was taken from https://github.com/paulovn/python-aiml.
https://www.pandorabots.com/pandora/... | 555 | 41.769231 | 127 | md |
null | ParlAI-main/parlai/agents/alice/__init__.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
| 198 | 38.8 | 65 | py |
null | ParlAI-main/parlai/agents/alice/alice.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Agent uses the Free ALICE AIML interpreter to generate replies to observations.
More information can be found at:
ht... | 2,114 | 24.792683 | 79 | py |
null | ParlAI-main/parlai/agents/bart/README.md | # BART
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
See https://arxiv.org/abs/1910.13461.
The BART agent can be instantiated as simply `-m bart`, however it is recommended to specify `--init-model zoo:bart/bart_large/model` or `-mf zoo:bart/bart_la... | 847 | 29.285714 | 210 | md |
null | ParlAI-main/parlai/agents/bart/__init__.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
| 198 | 38.8 | 65 | py |
null | ParlAI-main/parlai/agents/bart/bart.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
BART: Denoising Sequence-to-Sequence Pre-training for
Natural Language Generation, Translation, and Comprehension
Se... | 6,036 | 31.283422 | 79 | py |