英文:
How to fix error "Module is not callable"
问题
你遇到了一个错误，错误信息是 "'module' object is not callable"。这个错误可能是由于模块和类之间的混淆引起的。要解决这个问题，你可以检查以下几点：
-
确保导入了正确的库和模块，特别是
pytorchvideo和pytorch_lightning。 -
检查
pytorchvideo.data.ucf101和pytorchvideo.data.make_clip_sampler是否被正确使用。可能需要查看这些函数的文档或示例以确保正确的调用方式。 -
确保
dataset_root_path和train_transform、val_transform变量已经定义并且可用。 -
可以尝试在导入模块时使用别名，以避免与类名混淆。例如，使用
import pytorchvideo.data as pvdata，然后在代码中使用pvdata.ucf101和pvdata.make_clip_sampler。
请检查这些方面，看看是否可以解决这个错误。如果问题仍然存在，可能需要更多的上下文信息来帮助进一步调试。
英文:
I am getting error "Module is not callable" at the function val_dataloader step. I already saw that this error may be caused by pyhton confusion between module and class, but still I am not able to resolve it.
class UCFDataModule(pytorch_lightning.LightningDataModule):
_CLIP_DURATION = 2 # Duration of sampled clip for each video
_BATCH_SIZE = 8
_NUM_WORKERS = 8 # Number of parallel processes fetching data
def train_dataloader(self):
train_dataset = pytorchvideo.data.ucf101(
data_path = os.path.join(dataset_root_path, "train"),
clip_sampler = pytorchvideo.data.make_clip_sampler("random", self._CLIP_DURATION),
transform = train_transform
)
return torch.utils.data.DataLoader(
train_dataset,
batch_size = self._BATCH_SIZE,
num_workers = self._NUM_WORKERS,
)
def val_dataloader(self):
val_dataset = pytorchvideo.data.ucf101(
data_path = os.path.join(dataset_root_path, "val"),
clip_sampler = pytorchvideo.data.make_clip_sampler("uniform", self._CLIP_DURATION),
decode_audio = False,
transform = val_transform
)
return torch.utils.data.DataLoader(
val_dataset,
batch_size = self._BATCH_SIZE,
num_workers = self._NUM_WORKERS
)
def test_dataloader(self):
test_dataset = pytorchvideo.data.ucf101(
data_path = os.path.join(dataset_root_path, "test"),
clip_sampler = pytorchvideo.data.make_clip_sampler("uniform", self._CLIP_DURATION),
decode_audio = False,
transform = val_transform
)
return torch.utils.data.DataLoader(
test_dataset,
batch_size = self._BATCH_SIZE,
num_workers = self._NUM_WORKERS
)
def train():
classification_module = VideoClassificationLightningModule()
data_module = UCFDataModule()
trainer = pytorch_lightning.Trainer()
trainer.fit(classification_module, data_module)
pdb.set_trace()
train()
INFO:pytorch_lightning.utilities.rank_zero:GPU available: False, used: False
INFO:pytorch_lightning.utilities.rank_zero:TPU available: False, using: 0 TPU cores
INFO:pytorch_lightning.utilities.rank_zero:IPU available: False, using: 0 IPUs
INFO:pytorch_lightning.utilities.rank_zero:HPU available: False, using: 0 HPUs
/usr/local/lib/python3.10/dist-packages/pytorch_lightning/loops/utilities.py:70: PossibleUserWarning: `max_epochs` was not set. Setting it to 1000 epochs. To train without an epoch limit, set `max_epochs=-1`.
rank_zero_warn(
WARNING:pytorch_lightning.loggers.tensorboard:Missing logger folder: /content/lightning_logs
INFO:pytorch_lightning.callbacks.model_summary:
| Name | Type | Params
-------------------------------
0 | model | Net | 31.7 M
-------------------------------
31.7 M Trainable params
0 Non-trainable params
31.7 M Total params
126.695 Total estimated model params size (MB)
Sanity Checking:
0/? [00:00<?, ?it/s]
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-15-ff9f91c35b9e> in <cell line: 1>()
----> 1 train_results = train()
13 frames
<ipython-input-11-c166a5edf011> in val_dataloader(self)
22 def val_dataloader(self):
23
---> 24 val_dataset = pytorchvideo.data.ucf101(
25 data_path = os.path.join(dataset_root_path, "val"),
26 clip_sampler = pytorchvideo.data.make_clip_sampler("uniform", self._CLIP_DURATION),
TypeError: 'module' object is not callable
答案1
得分: 2
ucf101 是一个模块，我认为你想要使用Ucf101类，你可以直接从pytorchvideo.data中使用它，或者你可以从pytorchvideo.data.ucf101中导入它。
因此，你的最终代码将如下所示：
test_dataset = pytorchvideo.data.Ucf101(
data_path = os.path.join(dataset_root_path, "test"),
clip_sampler = pytorchvideo.data.make_clip_sampler(
"uniform", self._CLIP_DURATION
),
decode_audio = False,
transform = val_transform
)
英文:
ucf101 is a module I think you want to use Ucf101 class you can directly use it from pytorchvideo.data or you can import it from pytorchvideo.data.ucf101.
So your final code will look like this
test_dataset = pytorchvideo.data.Ucf101(
data_path = os.path.join(dataset_root_path, "test"),
clip_sampler = pytorchvideo.data.make_clip_sampler(
"uniform", self._CLIP_DURATION
),
decode_audio = False,
transform = val_transform
)
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