repo_id stringlengths 15 89 | file_path stringlengths 27 180 | content stringlengths 1 2.23M | __index_level_0__ int64 0 0 |
|---|---|---|---|
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/checkpoint_saver.py | """ Checkpoint Saver
Track top-n training checkpoints and maintain recovery checkpoints on specified intervals.
Hacked together by / Copyright 2020 Ross Wightman
"""
import glob
import operator
import os
import logging
import torch
from .model import unwrap_model, get_state_dict
_logger = logging.getLogger(__nam... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/cuda.py | """ CUDA / AMP utils
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch
try:
from apex import amp
has_apex = True
except ImportError:
amp = None
has_apex = False
from .clip_grad import dispatch_clip_grad
class ApexScaler:
state_dict_key = "amp"
def __call__(
sel... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/random.py | import random
import numpy as np
import torch
def random_seed(seed=42, rank=0):
torch.manual_seed(seed + rank)
np.random.seed(seed + rank)
random.seed(seed + rank)
| 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/loss/asymmetric_loss.py | import torch
import torch.nn as nn
class AsymmetricLossMultiLabel(nn.Module):
def __init__(self, gamma_neg=4, gamma_pos=1, clip=0.05, eps=1e-8, disable_torch_grad_focal_loss=False):
super(AsymmetricLossMultiLabel, self).__init__()
self.gamma_neg = gamma_neg
self.gamma_pos = gamma_pos
... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/loss/cross_entropy.py | """ Cross Entropy w/ smoothing or soft targets
Hacked together by / Copyright 2021 Ross Wightman
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
class LabelSmoothingCrossEntropy(nn.Module):
""" NLL loss with label smoothing.
"""
def __init__(self, smoothing=0.1):
super(Lab... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/loss/jsd.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from .cross_entropy import LabelSmoothingCrossEntropy
class JsdCrossEntropy(nn.Module):
""" Jensen-Shannon Divergence + Cross-Entropy Loss
Based on impl here: https://github.com/google-research/augmix/blob/master/imagenet.py
From paper: ... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/loss/__init__.py | from .asymmetric_loss import AsymmetricLossMultiLabel, AsymmetricLossSingleLabel
from .binary_cross_entropy import BinaryCrossEntropy
from .cross_entropy import LabelSmoothingCrossEntropy, SoftTargetCrossEntropy
from .jsd import JsdCrossEntropy
| 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/loss/binary_cross_entropy.py | """ Binary Cross Entropy w/ a few extras
Hacked together by / Copyright 2021 Ross Wightman
"""
from typing import Optional
import torch
import torch.nn as nn
import torch.nn.functional as F
class BinaryCrossEntropy(nn.Module):
""" BCE with optional one-hot from dense targets, label smoothing, thresholding
N... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/lion.py | """ Lion Optimizer
Paper: `Symbolic Discovery of Optimization Algorithms` - https://arxiv.org/abs/2302.06675
Original Impl: https://github.com/google/automl/tree/master/lion
"""
# Copyright 2023 Google Research. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use t... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/adahessian.py | """ AdaHessian Optimizer
Lifted from https://github.com/davda54/ada-hessian/blob/master/ada_hessian.py
Originally licensed MIT, Copyright 2020, David Samuel
"""
import torch
class Adahessian(torch.optim.Optimizer):
"""
Implements the AdaHessian algorithm from "ADAHESSIAN: An Adaptive Second OrderOptimizer fo... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/nadam.py | import math
import torch
from torch.optim.optimizer import Optimizer
class Nadam(Optimizer):
"""Implements Nadam algorithm (a variant of Adam based on Nesterov momentum).
It has been proposed in `Incorporating Nesterov Momentum into Adam`__.
Arguments:
params (iterable): iterable of parameters ... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/lookahead.py | """ Lookahead Optimizer Wrapper.
Implementation modified from: https://github.com/alphadl/lookahead.pytorch
Paper: `Lookahead Optimizer: k steps forward, 1 step back` - https://arxiv.org/abs/1907.08610
Hacked together by / Copyright 2020 Ross Wightman
"""
from collections import OrderedDict
from typing import Callable... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/rmsprop_tf.py | """ RMSProp modified to behave like Tensorflow impl
Originally cut & paste from PyTorch RMSProp
https://github.com/pytorch/pytorch/blob/063946d2b3f3f1e953a2a3b54e0b34f1393de295/torch/optim/rmsprop.py
Licensed under BSD-Clause 3 (ish), https://github.com/pytorch/pytorch/blob/master/LICENSE
Modifications Copyright 2021... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/lars.py | """ PyTorch LARS / LARC Optimizer
An implementation of LARS (SGD) + LARC in PyTorch
Based on:
* PyTorch SGD: https://github.com/pytorch/pytorch/blob/1.7/torch/optim/sgd.py#L100
* NVIDIA APEX LARC: https://github.com/NVIDIA/apex/blob/master/apex/parallel/LARC.py
Additional cleanup and modifications to properly su... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/madgrad.py | """ PyTorch MADGRAD optimizer
MADGRAD: https://arxiv.org/abs/2101.11075
Code from: https://github.com/facebookresearch/madgrad
"""
# 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 ma... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/sgdp.py | """
SGDP Optimizer Implementation copied from https://github.com/clovaai/AdamP/blob/master/adamp/sgdp.py
Paper: `Slowing Down the Weight Norm Increase in Momentum-based Optimizers` - https://arxiv.org/abs/2006.08217
Code: https://github.com/clovaai/AdamP
Copyright (c) 2020-present NAVER Corp.
MIT license
"""
import ... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/adamw.py | """ AdamW Optimizer
Impl copied from PyTorch master
NOTE: Builtin optim.AdamW is used by the factory, this impl only serves as a Python based reference, will be removed
someday
"""
import math
import torch
from torch.optim.optimizer import Optimizer
class AdamW(Optimizer):
r"""Implements AdamW algorithm.
Th... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/nvnovograd.py | """ Nvidia NovoGrad Optimizer.
Original impl by Nvidia from Jasper example:
- https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/SpeechRecognition/Jasper
Paper: `Stochastic Gradient Methods with Layer-wise Adaptive Moments for Training of Deep Networks`
- https://arxiv.org/abs/1905.11286
"""
im... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/adamp.py | """
AdamP Optimizer Implementation copied from https://github.com/clovaai/AdamP/blob/master/adamp/adamp.py
Paper: `Slowing Down the Weight Norm Increase in Momentum-based Optimizers` - https://arxiv.org/abs/2006.08217
Code: https://github.com/clovaai/AdamP
Copyright (c) 2020-present NAVER Corp.
MIT license
"""
impor... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/lamb.py | """ PyTorch Lamb optimizer w/ behaviour similar to NVIDIA FusedLamb
This optimizer code was adapted from the following (starting with latest)
* https://github.com/HabanaAI/Model-References/blob/2b435114fe8e31f159b1d3063b8280ae37af7423/PyTorch/nlp/bert/pretraining/lamb.py
* https://github.com/NVIDIA/DeepLearningExample... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/nadamw.py | """ NAdamW Optimizer
Based on simplified algorithm in https://github.com/mlcommons/algorithmic-efficiency/tree/main/baselines/nadamw
Added multi-tensor (foreach) path.
"""
import math
from typing import List, Optional
import torch
from torch import Tensor
# Modified from github.com/pytorch/pytorch/blob/v1.12.1/tor... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/radam.py | """RAdam Optimizer.
Implementation lifted from: https://github.com/LiyuanLucasLiu/RAdam
Paper: `On the Variance of the Adaptive Learning Rate and Beyond` - https://arxiv.org/abs/1908.03265
"""
import math
import torch
from torch.optim.optimizer import Optimizer
class RAdam(Optimizer):
def __init__(self, params, ... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/__init__.py | from .adabelief import AdaBelief
from .adafactor import Adafactor
from .adahessian import Adahessian
from .adamp import AdamP
from .adamw import AdamW
from .adan import Adan
from .lamb import Lamb
from .lars import Lars
from .lookahead import Lookahead
from .madgrad import MADGRAD
from .nadam import Nadam
from .nvnovog... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/adabelief.py | import math
import torch
from torch.optim.optimizer import Optimizer
class AdaBelief(Optimizer):
r"""Implements AdaBelief algorithm. Modified from Adam in PyTorch
Arguments:
params (iterable): iterable of parameters to optimize or dicts defining
parameter groups
lr (float, optiona... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/adafactor.py | """ Adafactor Optimizer
Lifted from https://github.com/pytorch/fairseq/blob/master/fairseq/optim/adafactor.py
Original header/copyright below.
"""
# 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... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/optim_factory.py | """ Optimizer Factory w/ Custom Weight Decay
Hacked together by / Copyright 2021 Ross Wightman
"""
import logging
from itertools import islice
from typing import Optional, Callable, Tuple
import torch
import torch.nn as nn
import torch.optim as optim
from timm.models import group_parameters
from .adabelief import Ad... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/optim/adan.py | """ Adan Optimizer
Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models[J]. arXiv preprint arXiv:2208.06677, 2022.
https://arxiv.org/abs/2208.06677
Implementation adapted from https://github.com/sail-sg/Adan
"""
import math
import torch
from torch.optim import Optimizer
class Adan(Opt... | 0 |
hf_public_repos/pytorch-image-models | hf_public_repos/pytorch-image-models/convert/convert_from_mxnet.py | import argparse
import hashlib
import os
import mxnet as mx
import gluoncv
import torch
from timm import create_model
parser = argparse.ArgumentParser(description='Convert from MXNet')
parser.add_argument('--model', default='all', type=str, metavar='MODEL',
help='Name of model to train (default: "... | 0 |
hf_public_repos/pytorch-image-models | hf_public_repos/pytorch-image-models/convert/convert_nest_flax.py | """
Convert weights from https://github.com/google-research/nested-transformer
NOTE: You'll need https://github.com/google/CommonLoopUtils, not included in requirements.txt
"""
import sys
import numpy as np
import torch
from clu import checkpoint
arch_depths = {
'nest_base': [2, 2, 20],
'nest_small': [2, 2... | 0 |
hf_public_repos | hf_public_repos/trl/Makefile | .PHONY: test precommit benchmark_core benchmark_aux
check_dirs := examples tests trl
test:
python -m pytest -n auto --dist=loadfile -s -v ./tests/
precommit:
pre-commit run --all-files
benchmark_core:
bash ./benchmark/benchmark_core.sh
benchmark_aux:
bash ./benchmark/benchmark_aux.sh
| 0 |
hf_public_repos | hf_public_repos/trl/MANIFEST.in | include settings.ini
include LICENSE
include CONTRIBUTING.md
include README.md
recursive-exclude * __pycache__
| 0 |
hf_public_repos | hf_public_repos/trl/LICENSE | Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
... | 0 |
hf_public_repos | hf_public_repos/trl/README.md | <div style="text-align: center">
<img src="https://huggingface.co/datasets/trl-internal-testing/example-images/resolve/main/images/trl_banner_dark.png">
</div>
# TRL - Transformer Reinforcement Learning
> Full stack transformer language models with reinforcement learning.
<p align="center">
<a href="https://githu... | 0 |
hf_public_repos | hf_public_repos/trl/CONTRIBUTING.md | # How to contribute
## How to get started
Before you start contributing make sure you installed all the dev tools:
```bash
pip install -e ".[dev]"
```
## Did you find a bug?
* Ensure the bug was not already reported by searching on GitHub under Issues.
* If you're unable to find an open issue addressing the proble... | 0 |
hf_public_repos | hf_public_repos/trl/.pre-commit-config.yaml | repos:
- repo: https://github.com/PyCQA/isort
rev: 5.12.0
hooks:
- id: isort
args:
- --profile=black
- --skip-glob=wandb/**/*
- --thirdparty=wandb
- repo: https://github.com/myint/autoflake
rev: v1.4
hooks:
- id: autoflake
args:
- -... | 0 |
hf_public_repos | hf_public_repos/trl/setup.py | """ trl is an open library for RL with transformer models.
Note:
VERSION needs to be formatted following the MAJOR.MINOR.PATCH convention
(we need to follow this convention to be able to retrieve versioned scripts)
Simple check list for release from AllenNLP repo: https://github.com/allenai/allennlp/blob/maste... | 0 |
hf_public_repos | hf_public_repos/trl/requirements.txt | datasets>=1.17.0
torch>=1.4.0
tqdm
transformers
accelerate
peft>=0.3.0
tyro>=0.5.7 | 0 |
hf_public_repos | hf_public_repos/trl/setup.cfg | [metadata]
license_file = LICENSE
[isort]
ensure_newline_before_comments = True
force_grid_wrap = 0
include_trailing_comma = True
line_length = 119
lines_after_imports = 2
multi_line_output = 3
use_parentheses = True
| 0 |
hf_public_repos | hf_public_repos/trl/CITATION.cff | cff-version: 1.2.0
title: 'TRL: Transformer Reinforcement Learning'
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Leandro
family-names: von Werra
- given-names: Younes
family-names: Belkada
- given-names: Lewis
family... | 0 |
hf_public_repos | hf_public_repos/trl/pyproject.toml | [tool.black]
line-length = 119
target-version = ['py38']
[tool.ruff]
ignore = ["E501", "E741", "W605"]
select = ["E", "F", "I", "W"]
line-length = 119
# Ignore import violations in all `__init__.py` files.
[tool.ruff.per-file-ignores]
"__init__.py" = ["E402", "F401", "F403", "F811"]
[tool.ruff.isort]
lines-after-imp... | 0 |
hf_public_repos/trl | hf_public_repos/trl/trl/import_utils.py | # Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/trl/__init__.py | # flake8: noqa
__version__ = "0.7.5.dev0"
from .core import set_seed
from .environment import TextEnvironment, TextHistory
from .extras import BestOfNSampler
from .import_utils import is_diffusers_available, is_peft_available, is_wandb_available, is_xpu_available
from .models import (
AutoModelForCausalLMWithValu... | 0 |
hf_public_repos/trl | hf_public_repos/trl/trl/core.py | # Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/models/modeling_sd_base.py | # Copyright 2023 DDPO-pytorch authors (Kevin Black), The HuggingFace Team, metric-space. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/lic... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/models/modeling_base.py | # Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/models/modeling_value_head.py | # Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/models/__init__.py | # flake8: noqa
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/trainer/training_configs.py | # coding=utf-8
# coding=utf-8
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/trainer/reward_trainer.py | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/trainer/ppo_trainer.py | # Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/trainer/iterative_sft_trainer.py | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/trainer/utils.py | # Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/trainer/ddpo_trainer.py | # Copyright 2023 DDPO-pytorch authors (Kevin Black), metric-space, The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/lic... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/trainer/ppo_config.py | # Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/trainer/base.py | # Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/trainer/ddpo_config.py | import os
import sys
import warnings
from dataclasses import dataclass, field
from typing import Literal, Optional
from ..core import flatten_dict
from ..import_utils import is_bitsandbytes_available, is_torchvision_available
@dataclass
class DDPOConfig:
"""
Configuration class for DDPOTrainer
"""
#... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/trainer/sft_trainer.py | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/trainer/__init__.py | # flake8: noqa
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/trainer/dpo_trainer.py | # DPO Authors: Rafael Rafailov, Archit Sharma, Eric Mitchell, Stefano Ermon, Christopher D. Manning, and Chelsea Finn 2023
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# ... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/environment/__init__.py | # flake8: noqa
from .base_environment import TextEnvironment, TextHistory
| 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/environment/base_environment.py | # Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/extras/best_of_n_sampler.py | from typing import Any, Callable, List, Optional, Union
import torch
from transformers import GenerationConfig, PreTrainedTokenizer, PreTrainedTokenizerFast
from ..core import set_seed
from ..models import SUPPORTED_ARCHITECTURES, PreTrainedModelWrapper
class BestOfNSampler(object):
def __init__(
self,
... | 0 |
hf_public_repos/trl/trl | hf_public_repos/trl/trl/extras/__init__.py | # flake8: noqa
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/benchmark_level3.sh | ## w/ and w/o gradient accumulation
python benchmark/benchmark.py \
--command "python examples/scripts/ppo.py --ppo_config.exp_name ppo_step_grad_accu --ppo_config.mini_batch_size 1 --ppo_config.gradient_accumulation_steps 128 --ppo_config.log_with wandb" \
--num-seeds 3 \
--start-seed 1 \
--workers 10 ... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/benchmark_level1_plot.sh | # pip install openrlbenchmark==0.2.1a5
# see https://github.com/openrlbenchmark/openrlbenchmark#get-started for documentation
echo "we deal with $TAGS_STRING"
python -m openrlbenchmark.rlops_multi_metrics \
--filters '?we=huggingface&wpn=trl&xaxis=_step&ceik=trl_ppo_trainer_config.value.reward_model&cen=trl_ppo_tr... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/plot.sh | # pip install openrlbenchmark==0.2.1a5
# see https://github.com/openrlbenchmark/openrlbenchmark#get-started for documentation
BASELINE_PR_TAG=v0.4.7-55-g110e672
BASELINE_PR_NAME=PR-662
python -m openrlbenchmark.rlops_multi_metrics \
--filters '?we=huggingface&wpn=trl&xaxis=_step&ceik=trl_ppo_trainer_config.value.r... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/benchmark.py | import argparse
import math
import os
import shlex
import subprocess
import uuid
from distutils.util import strtobool
import requests
def parse_args():
# fmt: off
parser = argparse.ArgumentParser()
parser.add_argument("--command", type=str, default="",
help="the command to run")
parser.add_ar... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/upload_benchmark.py | from dataclasses import dataclass
import tyro
from huggingface_hub import HfApi
@dataclass
class Args:
folder_path: str = "benchmark/trl"
path_in_repo: str = "images/benchmark"
repo_id: str = "trl-internal-testing/example-images"
repo_type: str = "dataset"
args = tyro.cli(Args)
api = HfApi()
api.u... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/post_github_comment.py | import json
import os
from ghapi.all import GhApi
FOLDER_STRING = os.environ.get("FOLDER_STRING", "")
folder = f"benchmark/trl/{FOLDER_STRING}"
host_url = f"https://huggingface.co/datasets/trl-internal-testing/example-images/resolve/main/images/benchmark/{FOLDER_STRING}"
# Create a GitHub API instance
github_contex... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/benchmark_level1.sh | # hello world experiment
python benchmark/benchmark.py \
--command "python examples/scripts/ppo.py --ppo_config.log_with wandb" \
--num-seeds 3 \
--start-seed 1 \
--workers 10 \
--slurm-nodes 1 \
--slurm-gpus-per-task 1 \
--slurm-ntasks 1 \
--slurm-total-cpus 12 \
--slurm-template-pa... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/benchmark_level2.sh | # compound experiments: gpt2xl + grad_accu
python benchmark/benchmark.py \
--command "python examples/scripts/ppo.py --ppo_config.exp_name ppo_gpt2xl_grad_accu --ppo_config.model_name gpt2-xl --ppo_config.mini_batch_size 16 --ppo_config.gradient_accumulation_steps 8 --ppo_config.log_with wandb" \
--num-seeds 3 ... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/trl.slurm_template | #!/bin/bash
#SBATCH --job-name=trl
#SBATCH --partition=production-cluster
#SBATCH --gpus-per-task={{gpus_per_task}}
#SBATCH --cpus-per-gpu={{cpus_per_gpu}}
#SBATCH --ntasks={{ntasks}}
#SBATCH --output=slurm/logs/%x_%j.out
#SBATCH --array={{array}}
#SBATCH --exclude=ip-26-0-156-239,ip-26-0-148-151,ip-26-0-146-212,ip-26-... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/post_github_comment.sbatch | #!/bin/bash
#SBATCH --job-name=trl
#SBATCH --partition=production-cluster
#SBATCH --ntasks=1
#SBATCH --output=slurm/logs/%x_%j.out
sleep 2m
bash $BENCHMARK_PLOT_SCRIPT
srun python benchmark/post_github_comment.py
| 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/benchmark_and_report.sh | #### Step 1: create a work directory:
# this is necessary because another github action job will remove
# the entire directory, which slurm depends on.
# https://stackoverflow.com/questions/4632028/how-to-create-a-temporary-directory
MY_SLURM_TMP_DIR=/fsx/costa/slurm_tmpdir
mkdir -p $MY_SLURM_TMP_DIR
WORK_DIR=`mktemp -... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/benchmark_level2_plot.sh | # pip install openrlbenchmark==0.2.1a5
# see https://github.com/openrlbenchmark/openrlbenchmark#get-started for documentation
echo "we deal with $TAGS_STRING"
python -m openrlbenchmark.rlops_multi_metrics \
--filters '?we=huggingface&wpn=trl&xaxis=_step&ceik=trl_ppo_trainer_config.value.reward_model&cen=trl_ppo_tr... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/test_ddpo_trainer.py | # Copyright 2023 metric-space, The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/test_modeling_value_head.py | # Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/testing_constants.py | # Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/test_best_of_n_sampler.py | import unittest
import torch
from transformers import AutoTokenizer, GenerationConfig
from trl import AutoModelForCausalLMWithValueHead
from trl.core import LengthSampler
from trl.extras import BestOfNSampler
def queries_to_scores(list_of_strings):
return [torch.rand(1).item() for _ in list_of_strings]
class ... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/test_sft_trainer.py | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/test_reward_trainer.py | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/test_peft_models.py | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/test_core.py | # Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/test_data_collator_completion_only.py | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/test_no_peft.py | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/test_dpo_trainer.py | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/test_environments.py | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/test_e2e.py | import subprocess
def test_hello_world():
subprocess.run(
"python examples/hello_world.py",
shell=True,
check=True,
)
| 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/testing_utils.py | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/test_iterative_sft_trainer.py | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/tests/test_ppo_trainer.py | # Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/trl/docs | hf_public_repos/trl/docs/source/quickstart.mdx | # Quickstart
## How does it work?
Fine-tuning a language model via PPO consists of roughly three steps:
1. **Rollout**: The language model generates a response or continuation based on a query which could be the start of a sentence.
2. **Evaluation**: The query and response are evaluated with a function, model, huma... | 0 |
hf_public_repos/trl/docs | hf_public_repos/trl/docs/source/how_to_train.md | # Training FAQ
## What Metrics Should I Look at?
When performing classical supervised fine-tuning of language models, the loss (especially the validation loss) serves as a good indicator of the training progress. However, in Reinforcement Learning (RL), the loss becomes less informative about the model's performance,... | 0 |
hf_public_repos/trl/docs | hf_public_repos/trl/docs/source/ddpo_trainer.mdx | # Denoising Diffusion Policy Optimization
## The why
| Before | After DDPO finetuning |
| --- | --- |
| <div style="text-align: center"><img src="https://huggingface.co/datasets/trl-internal-testing/example-images/resolve/main/images/pre_squirrel.png"/></div> | <div style="text-align: center"><img src="https://huggin... | 0 |
hf_public_repos/trl/docs | hf_public_repos/trl/docs/source/sentiment_tuning.mdx | # Sentiment Tuning Examples
The notebooks and scripts in this examples show how to fine-tune a model with a sentiment classifier (such as `lvwerra/distilbert-imdb`).
Here's an overview of the notebooks and scripts in the [trl repository](https://github.com/huggingface/trl/tree/main/examples):
| File ... | 0 |
hf_public_repos/trl/docs | hf_public_repos/trl/docs/source/_toctree.yml | - sections:
- local: index
title: TRL
- local: quickstart
title: Quickstart
- local: installation
title: Installation
- local: how_to_train
title: PPO Training FAQ
- local: use_model
title: Use Trained Models
- local: customization
title: Customize the Training
- local: logging
... | 0 |
hf_public_repos/trl/docs | hf_public_repos/trl/docs/source/sft_trainer.mdx | # Supervised Fine-tuning Trainer
Supervised fine-tuning (or SFT for short) is a crucial step in RLHF. In TRL we provide an easy-to-use API to create your SFT models and train them with few lines of code on your dataset.
Check out a complete flexible example at [`examples/scripts/sft.py`](https://github.com/huggingfa... | 0 |
hf_public_repos/trl/docs | hf_public_repos/trl/docs/source/text_environments.md | # Text Environments
Text environments provide a learning ground for language agents. It allows a language model to use tools to accomplish a task such as using a Python interpreter to answer math questions or using a search index for trivia questions. Having access to tools allows language models to solve tasks that w... | 0 |
hf_public_repos/trl/docs | hf_public_repos/trl/docs/source/dpo_trainer.mdx | # DPO Trainer
TRL supports the DPO Trainer for training language models from preference data, as described in the paper [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://arxiv.org/abs/2305.18290) by Rafailov et al., 2023. For a full example have a look at [`examples/scripts/dpo.... | 0 |
hf_public_repos/trl/docs | hf_public_repos/trl/docs/source/using_llama_models.mdx | # Using LLaMA models with TRL
We've begun rolling out examples to use Meta's LLaMA models in `trl` (see [Meta's LLaMA release](https://ai.facebook.com/blog/large-language-model-llama-meta-ai/) for the original LLaMA model).
## Efficient training strategies
Even training the smallest LLaMA model requires an enormous ... | 0 |
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