earakely
commented
1 year ago It was due to using python version < 3.9.
Getting this repo to work is like pulling one's teeth out. There is a lot of documentation on prerequisites that is missing.
I'm now getting the below error using the xl model:
DepthEstimation loaded
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ in <module>:1 │
│ │
│ ❱ 1 from main_simple_lib import * │
│ 2 │
│ │
│ /home/ec2-user/viper2/main_simple_lib.py:32 in <module> │
│ │
│ 29 cache = Memory('cache/' if config.use_cache else None, verbose=0) │
│ 30 │
│ 31 mp.set_start_method('spawn', force=True) │
│ ❱ 32 from vision_processes import forward, finish_all_consumers # This import loads all the │
│ 33 from image_patch import * │
│ 34 from video_segment import * │
│ 35 from datasets.dataset import MyDataset │
│ │
│ /home/ec2-user/viper2/vision_processes.py:177 in <module> │
│ │
│ 174 │ for model_class_ in list_models: │
│ 175 │ │ for process_name_ in model_class_.list_processes(): │
│ 176 │ │ │ if process_name_ in config.load_models and config.load_models[process_name_] │
│ ❱ 177 │ │ │ │ consumers[process_name_] = make_fn(model_class_, process_name_, counter_ │
│ 178 │ │ │ │ counter_ += 1 │
│ 179 │ │
│ 180 │ queues_in = None │
│ │
│ /home/ec2-user/viper2/vision_processes.py:43 in make_fn │
│ │
│ 40 │ num_gpus = torch.cuda.device_count() │
│ 41 │ gpu_number = counter % num_gpus │
│ 42 │ │
│ ❱ 43 │ model_instance = model_class(gpu_number=gpu_number) │
│ 44 │ │
│ 45 │ def _function(*args, **kwargs): │
│ 46 │ │ if process_name != model_class.name: │
│ │
│ /home/ec2-user/viper2/vision_models.py:416 in __init__ │
│ │
│ 413 │ │ BaseModel.__init__(self, gpu_number) │
│ 414 │ │ │
│ 415 │ │ with contextlib.redirect_stderr(open(os.devnull, "w")): # Do not print nltk_dat │
│ ❱ 416 │ │ │ from maskrcnn_benchmark.engine.predictor_glip import GLIPDemo, to_image_list │
│ 417 │ │ │ │ create_positive_map_label_to_token_from_positive_map │
│ 418 │ │ │
│ 419 │ │ working_dir = f'{config.path_pretrained_models}/GLIP/' │
│ │
│ /home/ec2-user/viper2/GLIP/maskrcnn_benchmark/engine/predictor_glip.py:11 in <module> │
│ │
│ 8 from transformers import AutoTokenizer │
│ 9 from torchvision import transforms as T │
│ 10 import pdb │
│ ❱ 11 from maskrcnn_benchmark.modeling.detector import build_detection_model │
│ 12 from maskrcnn_benchmark.utils.checkpoint import DetectronCheckpointer │
│ 13 from maskrcnn_benchmark.structures.image_list import to_image_list │
│ 14 from maskrcnn_benchmark.structures.boxlist_ops import boxlist_iou │
│ │
│ /home/ec2-user/viper2/GLIP/maskrcnn_benchmark/modeling/detector/__init__.py:1 in <module> │
│ │
│ ❱ 1 from .generalized_rcnn import GeneralizedRCNN │
│ 2 from .generalized_vl_rcnn import GeneralizedVLRCNN │
│ 3 │
│ 4 _DETECTION_META_ARCHITECTURES = {"GeneralizedRCNN": GeneralizedRCNN, │
│ │
│ /home/ec2-user/viper2/GLIP/maskrcnn_benchmark/modeling/detector/generalized_rcnn.py:11 in │
│ <module> │
│ │
│ 8 │
│ 9 from maskrcnn_benchmark.structures.image_list import to_image_list │
│ 10 │
│ ❱ 11 from ..backbone import build_backbone │
│ 12 from ..rpn import build_rpn │
│ 13 from ..roi_heads import build_roi_heads │
│ 14 │
│ │
│ /home/ec2-user/viper2/GLIP/maskrcnn_benchmark/modeling/backbone/__init__.py:6 in <module> │
│ │
│ 3 from torch import nn │
│ 4 │
│ 5 from maskrcnn_benchmark.modeling import registry │
│ ❱ 6 from maskrcnn_benchmark.modeling.make_layers import conv_with_kaiming_uniform │
│ 7 from maskrcnn_benchmark.layers import DropBlock2D, DyHead │
│ 8 from . import fpn as fpn_module │
│ 9 from . import bifpn │
│ │
│ /home/ec2-user/viper2/GLIP/maskrcnn_benchmark/modeling/make_layers.py:10 in <module> │
│ │
│ 7 from torch import nn │
│ 8 from torch.nn import functional as F │
│ 9 from maskrcnn_benchmark.config import cfg │
│ ❱ 10 from maskrcnn_benchmark.layers import Conv2d, DYReLU │
│ 11 from maskrcnn_benchmark.modeling.poolers import Pooler │
│ 12 │
│ 13 │
│ │
│ /home/ec2-user/viper2/GLIP/maskrcnn_benchmark/layers/__init__.py:10 in <module> │
│ │
│ 7 from .misc import DFConv2d │
│ 8 from .misc import interpolate │
│ 9 from .misc import Scale │
│ ❱ 10 from .nms import nms │
│ 11 from .nms import ml_nms │
│ 12 from .nms import soft_nms │
│ 13 from .roi_align import ROIAlign │
│ │
│ /home/ec2-user/viper2/GLIP/maskrcnn_benchmark/layers/nms.py:3 in <module> │
│ │
│ 1 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. │
│ 2 import torch │
│ ❱ 3 from maskrcnn_benchmark import _C │
│ 4 │
│ 5 try: │
│ 6 │ import torchvision │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ImportError: /home/ec2-user/viper2/GLIP/maskrcnn_benchmark/_C.cpython-310-x86_64-linux-gnu.so: undefined symbol:
_ZN3c104cuda20CUDACachingAllocator9allocatorE
Tony363
surisdi
Hi,
I followed the setup in the README.md. I am getting the following error when running the first cell of the main_simple.ipynb notebook: