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
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DOCRED-FE | DOCRED-FE-main/code/JEREX/jerex/sampling/sampling_classify.py | import torch
from jerex.sampling.sampling_common import create_positive_mentions, create_entities, \
create_pos_relations, \
create_rel_mention_pairs, create_neg_relations, create_mention_tensors, \
create_entity_tensors, create_rel_global_tensors, create_rel_mi_tensors, create_entity_pairs, \
create_n... | 14,734 | 55.026616 | 127 | py |
DOCRED-FE | DOCRED-FE-main/code/JEREX/jerex/sampling/sampling_common.py | import random
import torch
from jerex import util
def create_positive_mentions(doc, context_size, include_orig_spans=False):
""" Creates positive samples of entity mentions according to ground truth annotations """
pos_mention_spans, pos_mention_masks, pos_mention_sizes, pos_mention_orig_spans = [], [], []... | 22,634 | 42.196565 | 120 | py |
end-to-end-driving | end-to-end-driving-main/geometric_fusion/predict_expert.py | import pandas as pd
import os
from tqdm import tqdm
from collections import OrderedDict
import time
import numpy as np
from torch import torch
import torch.optim as optim
from torch.utils.data import DataLoader
import torch.nn.functional as F
torch.backends.cudnn.benchmark = True
from model import GeometricFusion
from... | 5,015 | 33.122449 | 154 | py |
end-to-end-driving | end-to-end-driving-main/geometric_fusion/model.py | from collections import deque
import numpy as np
import torch
from torch import nn
import torch.nn.functional as F
from torchvision import models
class ImageCNN(nn.Module):
"""
Encoder network for image input list.
Args:
c_dim (int): output dimension of the latent embedding
normalize (b... | 20,483 | 50.082294 | 166 | py |
end-to-end-driving | end-to-end-driving-main/geometric_fusion/data.py | import os
import json
from PIL import Image
import numpy as np
import random
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.seq_len = config.seq_len
self.pred_len = config.pred_len
self.ignore_sides = config.i... | 17,454 | 39.78271 | 128 | py |
end-to-end-driving | end-to-end-driving-main/geometric_fusion/train.py | import argparse
import json
import os
from tqdm import tqdm
import numpy as np
import torch
import torch.optim as optim
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
import torch.nn.functional as F
torch.backends.cudnn.benchmark = True
from model import GeometricFusion
from... | 8,822 | 34.011905 | 153 | py |
end-to-end-driving | end-to-end-driving-main/transfuser/predict_expert.py | import pandas as pd
import os
from tqdm import tqdm
from collections import OrderedDict
import time
import numpy as np
from torch import torch
import torch.optim as optim
from torch.utils.data import DataLoader
import torch.nn.functional as F
torch.backends.cudnn.benchmark = True
from model import TransFuser
from data... | 4,813 | 32.2 | 154 | py |
end-to-end-driving | end-to-end-driving-main/transfuser/model.py | import math
from collections import deque
import numpy as np
import torch
from torch import nn
import torch.nn.functional as F
from torchvision import models
class ImageCNN(nn.Module):
"""
Encoder network for image input list.
Args:
c_dim (int): output dimension of the latent embedding
... | 21,659 | 41.304688 | 144 | py |
end-to-end-driving | end-to-end-driving-main/transfuser/data.py | import os
import json
from PIL import Image
import numpy as np
import torch
from torch.utils.data import Dataset
from tqdm import tqdm
import sys
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.seq_len = config.seq_len
self.pred_len = config.pred_len
self.ignor... | 13,839 | 40.939394 | 128 | py |
end-to-end-driving | end-to-end-driving-main/transfuser/train.py | import argparse
import json
import os
from tqdm import tqdm
import numpy as np
import torch
import torch.optim as optim
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
import torch.nn.functional as F
torch.backends.cudnn.benchmark = True
from config import GlobalConfig
from m... | 8,583 | 33.199203 | 153 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/x13_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from x13.model import x13
from x13.config import Global... | 13,835 | 38.418803 | 170 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/geometric_fusion_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from geometric_fusion.model import GeometricFusion
from geometric_fusion.config ... | 10,106 | 34.09375 | 143 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/transfuser_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from transfuser.model import TransFuser
from transfuser.config import GlobalConf... | 10,510 | 34.630508 | 145 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/aim_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from aim.model import AIM
from aim.config import GlobalConfig
from aim.data impo... | 8,340 | 32.633065 | 168 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/late_fusion_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from late_fusion.model import LateFusion
from late_fusion.config import GlobalCo... | 10,025 | 34.679715 | 168 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/cilrs_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from cilrs.model import CILRS
from cilrs.data import scale_and_crop_image
from c... | 7,074 | 30.030702 | 108 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/s13_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from s13.model import s13
from s13.config import Global... | 13,897 | 38.482955 | 171 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/geometric_fusion/model.py | from collections import deque
import numpy as np
import torch
from torch import nn
import torch.nn.functional as F
from torchvision import models
class ImageCNN(nn.Module):
"""
Encoder network for image input list.
Args:
c_dim (int): output dimension of the latent embedding
normalize (b... | 20,483 | 50.082294 | 166 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/geometric_fusion/data.py | import os
import json
from PIL import Image
import numpy as np
import random
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.seq_len = config.seq_len
self.pred_len = config.pred_len
self.ignore_sides = config.i... | 17,453 | 39.780374 | 128 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/transfuser/model.py | import math
from collections import deque
import numpy as np
import torch
from torch import nn
import torch.nn.functional as F
from torchvision import models
class ImageCNN(nn.Module):
"""
Encoder network for image input list.
Args:
c_dim (int): output dimension of the latent embedding
... | 21,792 | 41.316505 | 144 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/transfuser/data.py | import os
import json
from PIL import Image
import numpy as np
import torch
from torch.utils.data import Dataset
from tqdm import tqdm
import sys
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.seq_len = config.seq_len
self.pred_len = config.pred_len
self.ignor... | 13,838 | 40.936364 | 128 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x14_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from x14.model import x14
from x14.config import Global... | 13,895 | 38.477273 | 179 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s8_B3_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from s8_B3.model import s8_B3
from s8_B3.config import ... | 13,651 | 38.571014 | 172 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x12_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from x12.model import x12
from x12.config import Global... | 13,731 | 38.45977 | 179 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x8_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from x8.model import x8
from x8.config import GlobalCon... | 13,521 | 37.9683 | 170 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x8_B3_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from x8_B3.model import x8_B3
from x8_B3.config import ... | 13,610 | 38.224784 | 170 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x9_B3_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from x9_B3.model import x9_B3
from x9_B3.config import ... | 13,542 | 38.028818 | 170 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x11_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from x11.model import x11
from x11.config import Global... | 13,622 | 38.259366 | 170 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s8_R34_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from s8_R34.model import s8_R34
from s8_R34.config impo... | 13,594 | 38.405797 | 172 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s8_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from s8.model import s8
from s8.config import GlobalCon... | 13,566 | 38.324638 | 172 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s10_B3_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from s10_B3.model import s10_B3
from s10_B3.config impo... | 13,711 | 38.402299 | 172 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x8_R34_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from x8_R34.model import x8_R34
from x8_R34.config impo... | 13,549 | 38.048991 | 170 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x10_B3_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from x10_B3.model import x10_B3
from x10_B3.config impo... | 13,643 | 38.319885 | 170 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/v8_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from v8.model import v8
from v8.config import GlobalCon... | 12,865 | 37.291667 | 170 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s9_B3_agent.py | import os
import json
import datetime
import pathlib
import time
import cv2
import carla
from collections import deque
from torch import torch
import torch
import carla
import numpy as np
from PIL import Image
from leaderboard.autoagents import autonomous_agent
from s9_B3.model import s9_B3
from s9_B3.config import ... | 13,587 | 38.385507 | 172 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x12/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 24,005 | 51.186957 | 183 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x12/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 15,602 | 41.056604 | 157 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s8_B3/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 14,803 | 47.221498 | 179 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s8_B3/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 14,928 | 41.053521 | 157 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x14/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 23,734 | 51.279736 | 190 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x14/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 15,831 | 41.218667 | 157 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x14/config.py | import os
class GlobalConfig:
gpu_id = '0'
model = 'x14'
logdir = 'log/'+model+'_w1'
init_stop_counter = 15
n_class = 23
batch_size = 20
coverage_area = 64 #untuk top view SC, HXW sama dalam meter
#parameter untuk MGN
MGN = True
loss_weights = [1, 1, 1, 1, 1, 1, 1]
lw_alph... | 4,360 | 39.757009 | 126 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s8_R34/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 13,982 | 46.723549 | 181 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s8_R34/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 14,928 | 41.053521 | 157 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x8_R34/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 21,032 | 51.191067 | 181 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x8_R34/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 14,902 | 40.980282 | 157 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x8_B3/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 21,900 | 51.394737 | 183 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x8_B3/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 14,902 | 40.980282 | 157 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x10_B3/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 24,176 | 50.993548 | 183 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x10_B3/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 15,602 | 41.056604 | 157 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x8/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 21,398 | 51.320293 | 183 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x8/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 14,902 | 40.980282 | 157 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x9_B3/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 20,930 | 51.3275 | 183 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x9_B3/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 14,902 | 40.980282 | 157 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x11/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 24,246 | 51.144086 | 183 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/x11/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 15,602 | 41.056604 | 157 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s10_B3/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 16,802 | 46.600567 | 179 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s10_B3/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 14,133 | 39.968116 | 136 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s9_B3/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 13,656 | 46.420139 | 137 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s9_B3/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 14,928 | 41.053521 | 157 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s8/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 14,300 | 47.151515 | 179 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/s8/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 14,928 | 41.053521 | 157 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/v8/model.py | from collections import deque
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaiming_w_init... | 24,753 | 51.893162 | 192 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/old_models/v8/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 14,928 | 41.053521 | 157 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/x13/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 23,007 | 51.891954 | 190 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/x13/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 15,831 | 41.218667 | 157 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/x13/config.py | import os
class GlobalConfig:
gpu_id = '0'
model = 'x13'
logdir = 'log/'+model#+'_w1'
init_stop_counter = 15
n_class = 23
batch_size = 20
coverage_area = 64 #untuk top view SC, HXW sama dalam meter
#parameter untuk MGN
MGN = True
loss_weights = [1, 1, 1, 1, 1, 1, 1]
lw_alp... | 5,308 | 43.991525 | 274 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/late_fusion/model.py | from collections import deque
import numpy as np
import torch
from torch import nn
import torch.nn.functional as F
from torchvision import models
class ImageCNN(nn.Module):
""" Encoder network for image input list.
Args:
c_dim (int): output dimension of the latent embedding
normalize (bool):... | 6,219 | 32.085106 | 126 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/late_fusion/data.py | import os
import json
from PIL import Image
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.seq_len = config.seq_len
self.pred_len = config.pred_len
self.ignore_sides = config.ignore_sides
... | 13,826 | 40.9 | 128 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/aim/model.py | from collections import deque
import numpy as np
import torch
from torch import nn
import torch.nn.functional as F
from torchvision import models
class ImageCNN(nn.Module):
""" Encoder network for image input list.
Args:
c_dim (int): output dimension of the latent embedding
normalize (bool):... | 5,350 | 32.030864 | 126 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/aim/data.py | import os
import json
from PIL import Image
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
self.pred_len = config.pred_len
self.front = []
... | 11,019 | 41.061069 | 130 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/s13/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 18,829 | 48.94695 | 137 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/s13/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 14,354 | 40.131805 | 136 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/s13/config.py | import os
class GlobalConfig:
gpu_id = '0'
model = 's13'
logdir = 'log/'+model+'_w1'
init_stop_counter = 15
n_class = 23
batch_size = 20
coverage_area = 64 #untuk top view SC, HXW sama dalam meter
#parameter untuk MGN
MGN = True
loss_weights = [1, 1, 1, 1, 1, 1, 1]
lw_alph... | 5,123 | 42.423729 | 274 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/cilrs/model.py | import torch
from torch import nn
import torch.nn.functional as F
from torchvision import models
class ImageCNN(nn.Module):
""" Encoder network for image input list.
Args:
c_dim (int): output dimension of the latent embedding
normalize (bool): whether the input images should be normalized
... | 4,562 | 33.568182 | 101 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/team_code/cilrs/data.py | import os
import json
from PIL import Image
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
self.pred_len = config.pred_len
self.front = []
... | 11,014 | 41.041985 | 130 | py |
end-to-end-driving | end-to-end-driving-main/leaderboard/leaderboard/leaderboard_evaluator.py | #!/usr/bin/env python
# Copyright (c) 2018-2019 Intel Corporation.
# authors: German Ros (german.ros@intel.com), Felipe Codevilla (felipe.alcm@gmail.com)
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""
CARLA Challenge Evaluator Routes
Provisio... | 19,930 | 38.467327 | 199 | py |
end-to-end-driving | end-to-end-driving-main/x13/predict_expert.py | import pandas as pd
import os
from tqdm import tqdm
from collections import OrderedDict
import time
import numpy as np
from torch import torch
from torch.utils.data import DataLoader
import torch.nn.functional as F
torch.backends.cudnn.benchmark = True
from model import x13
from data import CARLA_Data
from config impo... | 7,926 | 39.860825 | 154 | py |
end-to-end-driving | end-to-end-driving-main/x13/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
def kaiming_init_layer(layer):
nn.init.kaiming_normal_(layer.weight, nonlinearity='relu')
def kaiming... | 16,764 | 48.600592 | 163 | py |
end-to-end-driving | end-to-end-driving-main/x13/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
self.pred_len = config.pred_len
... | 13,602 | 41.642633 | 156 | py |
end-to-end-driving | end-to-end-driving-main/x13/train.py | import pandas as pd
import os
from tqdm import tqdm
from collections import OrderedDict
import time
import numpy as np
from torch import torch, nn
import torch.optim as optim
from torch.utils.data import DataLoader
import torch.nn.functional as F
torch.backends.cudnn.benchmark = True
from model import x13
from data im... | 20,073 | 41.350211 | 325 | py |
end-to-end-driving | end-to-end-driving-main/late_fusion/predict_expert.py | import pandas as pd
import os
from tqdm import tqdm
from collections import OrderedDict
import time
import numpy as np
from torch import torch
import torch.optim as optim
from torch.utils.data import DataLoader
import torch.nn.functional as F
torch.backends.cudnn.benchmark = True
from model import LateFusion
from data... | 4,831 | 32.09589 | 154 | py |
end-to-end-driving | end-to-end-driving-main/late_fusion/model.py | from collections import deque
import numpy as np
import torch
from torch import nn
import torch.nn.functional as F
from torchvision import models
class ImageCNN(nn.Module):
""" Encoder network for image input list.
Args:
c_dim (int): output dimension of the latent embedding
normalize (bool):... | 6,219 | 32.085106 | 126 | py |
end-to-end-driving | end-to-end-driving-main/late_fusion/data.py | import os
import json
from PIL import Image
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.seq_len = config.seq_len
self.pred_len = config.pred_len
self.ignore_sides = config.ignore_sides
... | 13,827 | 40.90303 | 128 | py |
end-to-end-driving | end-to-end-driving-main/late_fusion/train.py | import argparse
import json
import os
from tqdm import tqdm
import numpy as np
import torch
import torch.optim as optim
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
import torch.nn.functional as F
torch.backends.cudnn.benchmark = True
from model import LateFusion
from data... | 9,031 | 32.576208 | 153 | py |
end-to-end-driving | end-to-end-driving-main/aim/predict_expert.py | import pandas as pd
import os
from tqdm import tqdm
from collections import OrderedDict
import time
import numpy as np
from torch import torch
import torch.optim as optim
from torch.utils.data import DataLoader
import torch.nn.functional as F
torch.backends.cudnn.benchmark = True
from model import AIM
from data import... | 4,657 | 31.573427 | 154 | py |
end-to-end-driving | end-to-end-driving-main/aim/model.py | from collections import deque
import numpy as np
import torch
from torch import nn
import torch.nn.functional as F
from torchvision import models
class ImageCNN(nn.Module):
""" Encoder network for image input list.
Args:
c_dim (int): output dimension of the latent embedding
normalize (bool):... | 5,473 | 32.790123 | 126 | py |
end-to-end-driving | end-to-end-driving-main/aim/data.py | import os
import json
from PIL import Image
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
self.pred_len = config.pred_len
self.front = []
... | 11,019 | 41.061069 | 130 | py |
end-to-end-driving | end-to-end-driving-main/aim/train.py | import argparse
import json
import os
from tqdm import tqdm
import numpy as np
import torch
import torch.optim as optim
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
import torch.nn.functional as F
torch.backends.cudnn.benchmark = True
from model import AIM
from data import... | 8,638 | 32.746094 | 153 | py |
end-to-end-driving | end-to-end-driving-main/s13/predict_expert.py | import pandas as pd
import os
from tqdm import tqdm
from collections import OrderedDict
import time
import numpy as np
from torch import torch
import torch.optim as optim
from torch.utils.data import DataLoader
import torch.nn.functional as F
torch.backends.cudnn.benchmark = True
from model import s13
from data import... | 9,347 | 41.490909 | 154 | py |
end-to-end-driving | end-to-end-driving-main/s13/model.py | from collections import deque
import sys
import numpy as np
from torch import torch, cat, add, nn
import torch.nn.functional as F
import torchvision.models as models
import torchvision.transforms as transforms
#FUNGSI INISIALISASI WEIGHTS MODEL
#baca https://pytorch.org/docs/stable/nn.init.html
#kaiming he
def kaim... | 18,828 | 49.077128 | 137 | py |
end-to-end-driving | end-to-end-driving-main/s13/data.py | import os
import json
import cv2
from PIL import Image, ImageFile
# ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
... | 14,354 | 40.131805 | 136 | py |
end-to-end-driving | end-to-end-driving-main/s13/config.py | import os
class GlobalConfig:
gpu_id = '1'
model = 's13'
logdir = 'log/'+model+'_w1'
init_stop_counter = 15
n_class = 23
batch_size = 20
coverage_area = 64 #untuk top view SC, HXW sama dalam meter
#parameter untuk MGN
MGN = True
loss_weights = [1, 1, 1, 1, 1, 1, 1]
lw_alph... | 5,123 | 42.423729 | 274 | py |
end-to-end-driving | end-to-end-driving-main/s13/train.py | import pandas as pd
import os
from tqdm import tqdm
from collections import OrderedDict
import time
import numpy as np
from torch import torch, nn
import torch.optim as optim
from torch.utils.data import DataLoader
import torch.nn.functional as F
torch.backends.cudnn.benchmark = True
from model import s13
from data im... | 23,577 | 41.25448 | 325 | py |
end-to-end-driving | end-to-end-driving-main/cilrs/predict_expert.py | import pandas as pd
import os
from tqdm import tqdm
from collections import OrderedDict
import time
import numpy as np
from torch import torch
import torch.optim as optim
from torch.utils.data import DataLoader
import torch.nn.functional as F
torch.backends.cudnn.benchmark = True
from model import CILRS
from data impo... | 5,619 | 33.906832 | 113 | py |
end-to-end-driving | end-to-end-driving-main/cilrs/model.py | import torch
from torch import nn
import torch.nn.functional as F
from torchvision import models
class ImageCNN(nn.Module):
""" Encoder network for image input list.
Args:
c_dim (int): output dimension of the latent embedding
normalize (bool): whether the input images should be normalized
... | 4,562 | 33.568182 | 101 | py |
end-to-end-driving | end-to-end-driving-main/cilrs/data.py | import os
import json
from PIL import Image
import numpy as np
import torch
from torch.utils.data import Dataset
class CARLA_Data(Dataset):
def __init__(self, root, config):
self.config = config
self.seq_len = config.seq_len
self.pred_len = config.pred_len
self.front = []
... | 11,014 | 41.041985 | 130 | py |
end-to-end-driving | end-to-end-driving-main/cilrs/train.py | import argparse
import json
import os
from tqdm import tqdm
import numpy as np
import torch
import torch.optim as optim
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
import torch.nn.functional as F
torch.backends.cudnn.benchmark = True
from model import CILRS
from data impo... | 8,497 | 32.588933 | 114 | py |
FusedChat | FusedChat-main/cross_base.py | '''Bert-based cross encoder used for sentence pair classification'''
import torch.nn as nn
import numpy as np
import torch
from pytorch_pretrained_bert import BertModel
import math
from tqdm import tqdm
from sklearn import metrics
class BertEncoder(nn.Module):
def __init__(self, embd_dim, num_classes, option, le... | 2,936 | 37.644737 | 116 | py |
FusedChat | FusedChat-main/generate.py |
''' generate dialogue turns'''
import torch
from tqdm import tqdm
import os
import sys
import re
import csv
from argparse import ArgumentParser
filepath = os.path.realpath(__file__)
dirpath = os.path.dirname(filepath)
from Transformer import Transformer
APPEND_TEST_ODD_IDS = ['MUL1598','MUL2290','PMUL2636','MUL2499'... | 5,305 | 45.955752 | 449 | py |
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