Very slow dataloader

(Rohit Singh) #1

I am creating an ObjectItemList and running into very slow loading of each batch.
x,y = next(iter(dl))
takes upwards of 1 minute for each batch, even when the batch size is small (16).

This slowness shows up in calls such as show_batch(), show_results() and training in each epoch. Am I missing something? Using 64GB RAM, i7 Extreme processor and GP100 GPU.

1 Like

(Rohit Singh) #2

Digging further, it looks like it might be related to (Windows issue). However, in the fastai code num_workers is set to 0 before a batch is fetched:

Why is num_workers being set to 0?


(Rohit Singh) #3

I have a workaround for this issue. In num_workers needs to be set to 0 in the intercept_args function.



I have the same issue.
It takes about a 40 sec in my case to fetch a batch.
But I do not understand what have you done to solve it.
num_workers=0 is already there

Would you have a minute to share how exactly I need to modify


(Rohit Singh) #5

In fastai\, add the line setting “num_workers = 0” to the intercept_args() method, to workaround this problem:

def intercept_args(self, dataset, batch_size=1, shuffle=False, sampler=None, batch_sampler=None,

             num_workers=0, collate_f=default_collate, pin_memory=True, drop_last=False,

             timeout=0, worker_init_f=None):

num_workers = 0 # add this line

self.init_kwargs = {'batch_size':batch_size, 'shuffle':shuffle, 'sampler':sampler, 'batch_sampler':batch_sampler,

                    'num_workers':num_workers, 'collate_fn':collate_fn, 'pin_memory':pin_memory,

                    'drop_last': drop_last, 'timeout':timeout, 'worker_init_fn':worker_init_fn}

old_dl_init(self, dataset, **self.init_kwargs)