repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
value |
|---|---|---|---|---|---|---|
fine-grained-evals | fine-grained-evals-main/models/BLIP/train_caption.py | '''
* Copyright (c) 2022, salesforce.com, inc.
* All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
* For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
* By Junnan Li
'''
import argparse
import os
import ruamel_yaml as yaml
import numpy as np
imp... | 8,388 | 39.723301 | 128 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/predict.py | """
Download the weights in ./checkpoints beforehand for fast inference
wget https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model*_base_caption.pth
wget https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model*_vqa.pth
wget https://storage.googleapis.com/sfr-vision-language... | 3,796 | 37.353535 | 114 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/SVO.py | import argparse
import os
import ruamel.yaml as yaml
import time
import datetime
import json
import jsonlines
from pathlib import Path
from tqdm import tqdm
import torch
import torch.nn.functional as F
from torchvision import transforms
from PIL import Image
from data.utils import pre_caption
from models.blip_pretr... | 5,796 | 41.625 | 135 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/models/blip_pretrain.py | '''
* Copyright (c) 2022, salesforce.com, inc.
* All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
* For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
* By Junnan Li
'''
from models.med import BertConfig, BertModel, BertLMHeadModel
from transfor... | 16,066 | 46.255882 | 184 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/models/blip_vqa.py | from models.med import BertConfig, BertModel, BertLMHeadModel
from models.blip import create_vit, init_tokenizer, load_checkpoint
import torch
from torch import nn
import torch.nn.functional as F
from transformers import BertTokenizer
import numpy as np
class BLIP_VQA(nn.Module):
def __init__(self, ... | 8,969 | 47.225806 | 122 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/models/blip_retrieval.py | from models.med import BertConfig, BertModel
from transformers import BertTokenizer
import torch
from torch import nn
import torch.nn.functional as F
from models.blip import create_vit, init_tokenizer, load_checkpoint
class BLIP_Retrieval(nn.Module):
def __init__(self,
med_confi... | 13,759 | 42 | 123 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/models/vit.py | '''
* Copyright (c) 2022, salesforce.com, inc.
* All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
* For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
* By Junnan Li
* Based on timm code base
* https://github.com/rwightman/pytorch-image-models... | 14,240 | 45.691803 | 118 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/models/blip_itm.py | from models.med import BertConfig, BertModel
from transformers import BertTokenizer
import torch
from torch import nn
import torch.nn.functional as F
from models.blip import create_vit, init_tokenizer, load_checkpoint
class BLIP_ITM(nn.Module):
def __init__(self,
med_config = 'c... | 3,160 | 40.592105 | 119 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/models/blip_nlvr.py | from models.med import BertConfig
from models.nlvr_encoder import BertModel
from models.vit import interpolate_pos_embed
from models.blip import create_vit, init_tokenizer, is_url
from timm.models.hub import download_cached_file
import torch
from torch import nn
import torch.nn.functional as F
from transformers impor... | 4,398 | 41.708738 | 128 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/models/med.py | '''
* Copyright (c) 2022, salesforce.com, inc.
* All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
* For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
* By Junnan Li
* Based on huggingface code base
* https://github.com/huggingface/transformer... | 41,786 | 42.710251 | 213 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/models/nlvr_encoder.py | import math
import os
import warnings
from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import Tensor, device, dtype, nn
import torch.utils.checkpoint
from torch import nn
from torch.nn import CrossEntropyLoss
import torch.nn.functional as F
from transformers.activations imp... | 36,738 | 42.529621 | 213 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/models/blip.py | '''
* Copyright (c) 2022, salesforce.com, inc.
* All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
* For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
* By Junnan Li
'''
import warnings
warnings.filterwarnings("ignore")
from models.vit import V... | 10,946 | 44.803347 | 128 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/data/custom_itr_dataset.py | import os
import json
from torch.utils.data import Dataset
from PIL import Image
from data.utils import pre_caption
class custom_itr_retrieval_eval(Dataset):
def __init__(self, transform, image_root, filename, max_words=30):
'''
image_root (string): Root directory of images (e.g. flickr30... | 1,463 | 29.5 | 91 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/data/nlvr_dataset.py | import os
import json
import random
from torch.utils.data import Dataset
from torchvision.datasets.utils import download_url
from PIL import Image
from data.utils import pre_caption
class nlvr_dataset(Dataset):
def __init__(self, transform, image_root, ann_root, split):
'''
image_root (string)... | 2,722 | 33.910256 | 111 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/data/pretrain_dataset.py | import json
import os
import random
from torch.utils.data import Dataset
from PIL import Image
from PIL import ImageFile
ImageFile.LOAD_TRUNCATED_IMAGES = True
Image.MAX_IMAGE_PIXELS = None
from data.utils import pre_caption
import os,glob
class pretrain_dataset(Dataset):
def __init__(self, ann_file, laion_path... | 1,632 | 26.677966 | 75 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/data/coco_karpathy_dataset.py | import os
import json
from torch.utils.data import Dataset
from torchvision.datasets.utils import download_url
from PIL import Image
from data.utils import pre_caption
class coco_karpathy_train(Dataset):
def __init__(self, transform, image_root, ann_root, max_words=30, prompt=''):
'''
im... | 4,711 | 36.396825 | 118 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/data/utils.py | import re
import json
import os
import torch
import torch.distributed as dist
import utils
def pre_caption(caption,max_words=50):
caption = re.sub(
r"([.!\"()*#:;~])",
' ',
caption.lower(),
)
caption = re.sub(
r"\s{2,}",
' ',
caption,
)
capti... | 3,449 | 29.803571 | 117 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/data/vqa_dataset.py | import os
import json
import random
from PIL import Image
import torch
from torch.utils.data import Dataset
from data.utils import pre_question
from torchvision.datasets.utils import download_url
class vqa_dataset(Dataset):
def __init__(self, transform, ann_root, vqa_root, vg_root, train_files=[], split="train")... | 3,454 | 38.261364 | 122 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/data/nocaps_dataset.py | import os
import json
from torch.utils.data import Dataset
from torchvision.datasets.utils import download_url
from PIL import Image
class nocaps_eval(Dataset):
def __init__(self, transform, image_root, ann_root, split):
urls = {'val':'https://storage.googleapis.com/sfr-vision-language-research/datase... | 1,139 | 34.625 | 111 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/data/video_dataset.py | from torch.utils.data import Dataset
from torchvision.datasets.utils import download_url
from PIL import Image
import torch
import numpy as np
import random
import decord
from decord import VideoReader
import json
import os
from data.utils import pre_caption
decord.bridge.set_bridge("torch")
class ImageNorm(object):... | 4,005 | 35.09009 | 122 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/data/__init__.py | import torch
from torch.utils.data import DataLoader
from torchvision import transforms
from torchvision.transforms.functional import InterpolationMode
from data.coco_karpathy_dataset import coco_karpathy_train, coco_karpathy_caption_eval, coco_karpathy_retrieval_eval
from data.custom_itr_dataset import custom_itr_ret... | 5,678 | 51.583333 | 127 | py |
fine-grained-evals | fine-grained-evals-main/models/BLIP/data/flickr30k_dataset.py | import os
import json
from torch.utils.data import Dataset
from torchvision.datasets.utils import download_url
from PIL import Image
from data.utils import pre_caption
class flickr30k_train(Dataset):
def __init__(self, transform, image_root, ann_root, max_words=30, prompt=''):
'''
image_... | 3,346 | 34.989247 | 114 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/Retrieval.py | import argparse
import os
import ruamel.yaml as yaml
import numpy as np
import random
import time
import datetime
import json
from pathlib import Path
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.backends.cudnn as cudnn
import torch.distributed as dist
from torchvision import transfo... | 17,004 | 41.5125 | 149 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/Winoground.py | import argparse
import os
import ruamel.yaml as yaml
import time
import datetime
import json
from pathlib import Path
from tqdm import tqdm
import torch
import torch.nn.functional as F
from torchvision import transforms
from PIL import Image
from dataset.utils import pre_caption
from datasets import load_dataset
f... | 7,311 | 44.7 | 143 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/utils.py | import numpy as np
import io
import os
import time
from collections import defaultdict, deque
import datetime
import torch
import torch.distributed as dist
class SmoothedValue(object):
"""Track a series of values and provide access to smoothed values over a
window or the global series average.
"""
de... | 7,621 | 28.542636 | 94 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/run_grounding_train.py | '''
* Copyright (c) 2021, salesforce.com, inc.
* All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
* For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
'''
import os
import utils
import argparse
import random
import time
import datetime
import j... | 20,851 | 46.935632 | 169 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/VSR.py | import argparse
import os
import ruamel.yaml as yaml
import time
import datetime
import json
import jsonlines
from pathlib import Path
from tqdm import tqdm
import torch
import torch.nn.functional as F
from torchvision import transforms
from PIL import Image
from dataset.utils import pre_caption
from models.model_p... | 5,389 | 37.5 | 123 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/run_pretrain.py | '''
* Copyright (c) 2021, salesforce.com, inc.
* All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
* For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
'''
import argparse
import os
import random
import time
import datetime
import json
import uti... | 12,110 | 42.722022 | 184 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/VALSE.py | import argparse
import os
import ruamel.yaml as yaml
import time
import datetime
import json
from pathlib import Path
from tqdm import tqdm
import torch
import torch.nn.functional as F
from torchvision import transforms
from PIL import Image
from dataset.utils import pre_caption
from models.model_pretrain import PE... | 6,871 | 40.902439 | 148 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/SVO.py | import argparse
import os
import ruamel.yaml as yaml
import time
import datetime
import json
import jsonlines
from pathlib import Path
from tqdm import tqdm
import torch
import torch.nn.functional as F
from torchvision import transforms
from PIL import Image
from dataset.utils import pre_caption
from models.model_p... | 6,270 | 40.806667 | 123 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/run_vrd_train.py | '''
* Copyright (c) 2021, salesforce.com, inc.
* All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
* For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
'''
import argparse
import os
import utils
import ruamel_yaml as yaml
import numpy as np
impor... | 21,217 | 45.735683 | 152 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/scheduler/plateau_lr.py | """ Plateau Scheduler
Adapts PyTorch plateau scheduler and allows application of noise, warmup.
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch
from .scheduler import Scheduler
class PlateauLRScheduler(Scheduler):
"""Decay the LR by a factor every time the validation loss plateaus."""
d... | 4,140 | 35.324561 | 97 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/scheduler/tanh_lr.py | """ TanH Scheduler
TanH schedule with warmup, cycle/restarts, noise.
Hacked together by / Copyright 2020 Ross Wightman
"""
import logging
import math
import numpy as np
import torch
from .scheduler import Scheduler
_logger = logging.getLogger(__name__)
class TanhLRScheduler(Scheduler):
"""
Hyberbolic-Tan... | 4,045 | 32.438017 | 106 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/scheduler/cosine_lr.py | """ Cosine Scheduler
Cosine LR schedule with warmup, cycle/restarts, noise.
Hacked together by / Copyright 2020 Ross Wightman
"""
import logging
import math
import numpy as np
import torch
from .scheduler import Scheduler
from pdb import set_trace as breakpoint
_logger = logging.getLogger(__name__)
class CosineL... | 4,027 | 33.135593 | 121 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/scheduler/scheduler.py | from typing import Dict, Any
import torch
class Scheduler:
""" Parameter Scheduler Base Class
A scheduler base class that can be used to schedule any optimizer parameter groups.
Unlike the builtin PyTorch schedulers, this is intended to be consistently called
* At the END of each epoch, before incre... | 4,750 | 43.820755 | 112 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/scheduler/step_lr.py | """ Step Scheduler
Basic step LR schedule with warmup, noise.
Hacked together by / Copyright 2020 Ross Wightman
"""
import math
import torch
from .scheduler import Scheduler
class StepLRScheduler(Scheduler):
"""
"""
def __init__(self,
optimizer: torch.optim.Optimizer,
... | 1,902 | 28.734375 | 105 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/dataset/grounding_dataset.py | import os
import re
import PIL
import json
import torch
import random
import numpy as np
from PIL import Image
from PIL import ImageFile
from torch.utils.data import Dataset
from torchvision import transforms
import torchvision.transforms as T
import torchvision.transforms.functional as F
ImageFile.LOAD_TRUNCATED_IMAGE... | 14,077 | 38.105556 | 146 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/dataset/vcr_dataset.py | import json
import os
import random
import numpy as np
from torch.utils.data import Dataset
from torchvision import transforms
import PIL
from PIL import Image
from PIL import ImageFile
ImageFile.LOAD_TRUNCATED_IMAGES = True
Image.MAX_IMAGE_PIXELS = None
import re
import cv2 as cv
import torch
import torchvision.transf... | 26,271 | 40.901116 | 146 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/dataset/utils.py | import re
def pre_question(question,max_ques_words):
question = re.sub(
r"([,.'!?\"()*#:;~])",
'',
question.lower(),
).replace('-', ' ').replace('/', ' ')
question = question.rstrip(' ')
#truncate question
question_words = question.split(' ')
if len(question_words... | 6,853 | 31.330189 | 116 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/dataset/caption_dataset.py | import json
import os
import random
from collections import defaultdict
from torch.utils.data import Dataset
from PIL import Image
from PIL import ImageFile
ImageFile.LOAD_TRUNCATED_IMAGES = True
Image.MAX_IMAGE_PIXELS = None
from dataset.utils import pre_caption
from models.tokenization_bert import BertTokenizer
... | 2,472 | 29.158537 | 84 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/dataset/vrd_dataset.py | import os
import re
import PIL
import json
import pickle
import torch
import random
import numpy as np
from PIL import Image
from PIL import ImageFile
from torch.utils.data import Dataset
from torchvision import transforms
import torchvision.transforms as T
import torchvision.transforms.functional as F
ImageFile.LOAD_T... | 16,163 | 40.767442 | 146 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/dataset/__init__.py | import torch
from torch.utils.data import DataLoader
from torchvision import transforms
from PIL import Image
from dataset.randaugment import RandomAugment
from dataset.caption_dataset import re_train_dataset, re_eval_dataset
def create_dataset(dataset, config):
normalize = transforms.Normalize((0.48145466, 0.4... | 3,628 | 42.722892 | 127 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/models/xbert.py | import math
import os
import warnings
from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import Tensor, device, dtype, nn
import torch.utils.checkpoint
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
import torch.nn.functional as F
from transformers.activa... | 80,299 | 41.735498 | 213 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/models/vit.py |
import torch
import torch.nn as nn
import torch.nn.functional as F
from functools import partial
from timm.models.vision_transformer import _cfg, PatchEmbed
from timm.models.registry import register_model
from timm.models.layers import trunc_normal_, DropPath
class Mlp(nn.Module):
""" MLP as used in Vision Tran... | 8,558 | 41.162562 | 118 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/models/model_vrd.py | '''
* Copyright (c) 2021, salesforce.com, inc.
* All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
* For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
'''
from functools import partial
from models.vit import VisionTransformer, interpolate_pos_em... | 19,322 | 49.451697 | 157 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/models/model_grounding.py | import torch
from torch import nn
import torch.nn.functional as F
import numpy as np
from functools import partial
from models.vit import VisionTransformer, interpolate_pos_embed
from models.xbert import BertConfig, BertForMaskedLM
class PEVL_Grounding(nn.Module):
def __init__(self,
tokenize... | 16,317 | 49.055215 | 157 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/models/model_pretrain.py | '''
* Copyright (c) 2021, salesforce.com, inc.
* All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
* For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
'''
from functools import partial
from models.vit import VisionTransformer, interpolate_pos_em... | 23,053 | 51.997701 | 161 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/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... | 6,535 | 40.630573 | 129 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/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, required
class RAdam(Optimizer):
def __init__(self... | 5,924 | 37.72549 | 111 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/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... | 4,795 | 39.302521 | 99 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/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... | 3,689 | 33.166667 | 123 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/optim/nadam.py | import torch
from torch.optim 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 to optimize or dicts de... | 3,758 | 41.235955 | 108 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/optim/adamw.py | """ AdamW Optimizer
Impl copied from PyTorch master
"""
import math
import torch
from torch.optim.optimizer import Optimizer
class AdamW(Optimizer):
r"""Implements AdamW algorithm.
The original Adam algorithm was proposed in `Adam: A Method for Stochastic Optimization`_.
The AdamW variant was proposed in... | 4,965 | 41.084746 | 116 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/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... | 8,126 | 45.706897 | 114 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/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 2020... | 6,127 | 43.729927 | 117 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/optim/novograd.py | """NovoGrad Optimizer.
Original impl by Masashi Kimura (Convergence Lab): https://github.com/convergence-lab/novograd
Paper: `Stochastic Gradient Methods with Layer-wise Adaptive Moments for Training of Deep Networks`
- https://arxiv.org/abs/1905.11286
"""
import torch
from torch.optim.optimizer import Optimizer
i... | 2,925 | 36.512821 | 107 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/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 ... | 3,231 | 32.319588 | 115 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/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
"""
import torch
from torch.optim.optimizer import Optimizer
from c... | 3,815 | 40.032258 | 93 | py |
fine-grained-evals | fine-grained-evals-main/models/PEVL/optim/optim_factory.py | """ Optimizer Factory w/ Custom Weight Decay
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch
from torch import optim as optim
from .adafactor import Adafactor
from .adahessian import Adahessian
from .adamp import AdamP
from .lookahead import Lookahead
from .nadam import Nadam
from .novograd import N... | 4,764 | 37.739837 | 100 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/VE.py | import argparse
import os
import ruamel_yaml as yaml
import numpy as np
import random
import time
import datetime
import json
from pathlib import Path
import json
import pickle
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader
import torch.backends.cudnn as cudn... | 9,911 | 38.177866 | 128 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/NLVR.py | import argparse
import os
import ruamel_yaml as yaml
import numpy as np
import random
import time
import datetime
import json
from pathlib import Path
import json
import pickle
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader
import torch.backends.cudnn as cudn... | 8,709 | 37.034934 | 125 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/Grounding.py | import argparse
import os
import ruamel_yaml as yaml
import numpy as np
import random
import time
import datetime
import json
from pathlib import Path
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.backends.cudnn as cudnn
import torch.distributed as dist
from torch.utils.data import Da... | 12,733 | 42.166102 | 139 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/Retrieval.py | import argparse
import os
import ruamel.yaml as yaml
import numpy as np
import random
import time
import datetime
import json
from pathlib import Path
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.backends.cudnn as cudnn
import torch.distributed as dist
from torch.utils.data import Da... | 17,123 | 41.81 | 149 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/Winoground.py | import argparse
import os
import ruamel.yaml as yaml
import time
import datetime
import json
from pathlib import Path
from tqdm import tqdm
import torch
import torch.nn.functional as F
from torchvision import transforms
from PIL import Image
from dataset.utils import pre_caption
from datasets import load_dataset
f... | 7,895 | 47.740741 | 164 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/utils.py | import numpy as np
import io
import os
import time
from collections import defaultdict, deque
import datetime
import torch
import torch.distributed as dist
import wandb
def generate_wandb_id():
return wandb.util.generate_id()
class SmoothedValue(object):
"""Track a series of values and provide access to s... | 8,226 | 28.916364 | 94 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/VSR.py | import argparse
import os
import ruamel.yaml as yaml
import time
import datetime
import json
import jsonlines
from pathlib import Path
from tqdm import tqdm
import torch
import torch.nn.functional as F
from torchvision import transforms
from PIL import Image
from dataset.utils import pre_caption
from models.model_p... | 4,748 | 38.247934 | 123 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/VALSE.py | import argparse
import os
import ruamel.yaml as yaml
import time
import datetime
import json
from pathlib import Path
from tqdm import tqdm
import torch
import torch.nn.functional as F
from torchvision import transforms
from PIL import Image
from dataset.utils import pre_caption
from models.model_pretrain import AL... | 6,212 | 41.848276 | 148 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/predict.py | import re
import tempfile
from functools import partial
import cv2
from PIL import Image
import numpy as np
from cog import BasePredictor, Path, Input
from skimage import transform as skimage_transform
from scipy.ndimage import filters
from matplotlib import pyplot as plt
import torch
from torch import nn
from torchv... | 6,335 | 29.171429 | 90 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/Pretrain.py | '''
* Copyright (c) 2021, salesforce.com, inc.
* All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
* For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
'''
import argparse
import os
import ruamel_yaml as yaml
import numpy as np
import random
impo... | 7,767 | 37.26601 | 142 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/Pretrain_nlvr.py | import argparse
import os
import ruamel_yaml as yaml
import numpy as np
import random
import time
import datetime
import json
from pathlib import Path
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader
import torch.backends.cudnn as cudnn
import torch.distributed... | 7,557 | 36.60199 | 142 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/SVO.py | import argparse
import os
import ruamel.yaml as yaml
import time
import datetime
import json
import jsonlines
from pathlib import Path
from tqdm import tqdm
import torch
import torch.nn.functional as F
from torchvision import transforms
from PIL import Image
from dataset.utils import pre_caption
from models.model_p... | 5,687 | 42.090909 | 123 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/VQA.py | import argparse
import os
import ruamel_yaml as yaml
import numpy as np
import random
import time
import datetime
import json
from pathlib import Path
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader
import torch.backends.cudnn as cudnn
import torch.distributed... | 10,488 | 39.342308 | 128 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/scheduler/plateau_lr.py | """ Plateau Scheduler
Adapts PyTorch plateau scheduler and allows application of noise, warmup.
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch
from .scheduler import Scheduler
class PlateauLRScheduler(Scheduler):
"""Decay the LR by a factor every time the validation loss plateaus."""
d... | 4,140 | 35.324561 | 97 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/scheduler/tanh_lr.py | """ TanH Scheduler
TanH schedule with warmup, cycle/restarts, noise.
Hacked together by / Copyright 2020 Ross Wightman
"""
import logging
import math
import numpy as np
import torch
from .scheduler import Scheduler
_logger = logging.getLogger(__name__)
class TanhLRScheduler(Scheduler):
"""
Hyberbolic-Tan... | 4,045 | 32.438017 | 106 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/scheduler/cosine_lr.py | """ Cosine Scheduler
Cosine LR schedule with warmup, cycle/restarts, noise.
Hacked together by / Copyright 2020 Ross Wightman
"""
import logging
import math
import numpy as np
import torch
from .scheduler import Scheduler
from pdb import set_trace as breakpoint
_logger = logging.getLogger(__name__)
class CosineL... | 4,027 | 33.135593 | 121 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/scheduler/scheduler.py | from typing import Dict, Any
import torch
class Scheduler:
""" Parameter Scheduler Base Class
A scheduler base class that can be used to schedule any optimizer parameter groups.
Unlike the builtin PyTorch schedulers, this is intended to be consistently called
* At the END of each epoch, before incre... | 4,750 | 43.820755 | 112 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/scheduler/step_lr.py | """ Step Scheduler
Basic step LR schedule with warmup, noise.
Hacked together by / Copyright 2020 Ross Wightman
"""
import math
import torch
from .scheduler import Scheduler
class StepLRScheduler(Scheduler):
"""
"""
def __init__(self,
optimizer: torch.optim.Optimizer,
... | 1,902 | 28.734375 | 105 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/dataset/nlvr_dataset.py | import json
import os
from torch.utils.data import Dataset
from PIL import Image
from dataset.utils import pre_caption
class nlvr_dataset(Dataset):
def __init__(self, ann_file, transform, image_root):
self.ann = []
for f in ann_file:
self.ann += json.load(open(f,'r'))
s... | 1,158 | 27.975 | 82 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/dataset/grounding_dataset.py | import json
import os
from torch.utils.data import Dataset
from PIL import Image
from dataset.utils import pre_caption
class grounding_dataset(Dataset):
def __init__(self, ann_file, transform, image_root, max_words=30, mode='train'):
self.ann = []
for f in ann_file:
self.ann += ... | 1,390 | 29.911111 | 92 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/dataset/utils.py | import re
def pre_question(question,max_ques_words):
question = re.sub(
r"([,.'!?\"()*#:;~])",
'',
question.lower(),
).replace('-', ' ').replace('/', ' ')
question = question.rstrip(' ')
#truncate question
question_words = question.split(' ')
if len(question_words... | 6,839 | 31.571429 | 116 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/dataset/vqa_dataset.py | import os
import json
import random
from PIL import Image
from torch.utils.data import Dataset
from dataset.utils import pre_question
class vqa_dataset(Dataset):
def __init__(self, ann_file, transform, vqa_root, vg_root, eos='[SEP]', split="train", max_ques_words=30, answer_list=''):
self.split = split ... | 2,367 | 32.828571 | 126 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/dataset/ve_dataset.py | import json
import os
from torch.utils.data import Dataset
from PIL import Image
from dataset.utils import pre_caption
class ve_dataset(Dataset):
def __init__(self, ann_file, transform, image_root, max_words=30):
self.ann = json.load(open(ann_file,'r'))
self.transform = transform
s... | 919 | 28.677419 | 80 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/dataset/caption_dataset.py | import json
import os
import random
from torch.utils.data import Dataset
from PIL import Image
from PIL import ImageFile
ImageFile.LOAD_TRUNCATED_IMAGES = True
Image.MAX_IMAGE_PIXELS = None
from dataset.utils import pre_caption
class re_train_dataset(Dataset):
def __init__(self, ann_file, transform, image_root... | 3,150 | 28.726415 | 84 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/dataset/__init__.py | import torch
from torch.utils.data import DataLoader
from torchvision import transforms
from PIL import Image
from dataset.caption_dataset import re_train_dataset, re_eval_dataset, pretrain_dataset
from dataset.nlvr_dataset import nlvr_dataset
from dataset.ve_dataset import ve_dataset
from dataset.vqa_dataset import v... | 5,959 | 47.852459 | 170 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/models/model_vqa.py | from functools import partial
from models.vit import VisionTransformer
from models.xbert import BertConfig, BertModel, BertLMHeadModel
import torch
from torch import nn
import torch.nn.functional as F
import numpy as np
class ALBEF(nn.Module):
def __init__(self,
text_encoder = N... | 11,062 | 50.938967 | 125 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/models/model_pretrain_nlvr.py | from functools import partial
from models.vit import VisionTransformer
from models.xbert import BertConfig, BertModel
import torch
from torch import nn
import torch.nn.functional as F
class ALBEF(nn.Module):
def __init__(self,
text_encoder = None,
tokenizer = Non... | 4,158 | 41.010101 | 118 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/models/xbert.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 82,210 | 41.885237 | 213 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/models/vit.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from functools import partial
from timm.models.vision_transformer import _cfg, PatchEmbed
from timm.models.registry import register_model
from timm.models.layers import trunc_normal_, DropPath
class Mlp(nn.Module):
""" MLP as used in Vision Trans... | 8,558 | 41.162562 | 118 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/models/model_nlvr.py | from functools import partial
from models.vit import VisionTransformer
from models.xbert import BertConfig, BertModel
import torch
from torch import nn
import torch.nn.functional as F
class ALBEF(nn.Module):
def __init__(self,
text_encoder = None,
tokenizer = Non... | 6,146 | 47.023438 | 121 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/models/model_retrieval.py | from functools import partial
from models.vit import VisionTransformer
from models.xbert import BertConfig, BertModel
import torch
from torch import nn
import torch.nn.functional as F
class ALBEF(nn.Module):
def __init__(self,
text_encoder = None,
tokenizer = Non... | 10,231 | 45.93578 | 139 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/models/model_ve.py | from functools import partial
from models.vit import VisionTransformer
from models.xbert import BertConfig, BertModel
import torch
from torch import nn
import torch.nn.functional as F
class ALBEF(nn.Module):
def __init__(self,
text_encoder = None,
tokenizer = Non... | 5,253 | 46.333333 | 124 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/models/model_pretrain.py | '''
* Copyright (c) 2021, salesforce.com, inc.
* All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
* For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
'''
from functools import partial
from models.vit import VisionTransformer, interpolate_pos_em... | 13,825 | 46.349315 | 139 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/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... | 6,535 | 40.630573 | 129 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/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, required
class RAdam(Optimizer):
def __init__(self... | 5,924 | 37.72549 | 111 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/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... | 4,795 | 39.302521 | 99 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/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... | 3,689 | 33.166667 | 123 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/optim/nadam.py | import torch
from torch.optim 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 to optimize or dicts de... | 3,758 | 41.235955 | 108 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/optim/adamw.py | """ AdamW Optimizer
Impl copied from PyTorch master
"""
import math
import torch
from torch.optim.optimizer import Optimizer
class AdamW(Optimizer):
r"""Implements AdamW algorithm.
The original Adam algorithm was proposed in `Adam: A Method for Stochastic Optimization`_.
The AdamW variant was proposed in... | 4,965 | 41.084746 | 116 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/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... | 8,126 | 45.706897 | 114 | py |
fine-grained-evals | fine-grained-evals-main/models/ALBEF/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 2020... | 6,127 | 43.729927 | 117 | py |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.