Fix --data from_HUB.zip (#4732)

@kalenmike

train.py

@@ -36,7 +36,7 @@
 from utils.datasets import create_dataloader
 from utils.general import labels_to_class_weights, increment_path, labels_to_image_weights, init_seeds, \
     strip_optimizer, get_latest_run, check_dataset, check_git_status, check_img_size, check_requirements, \
-    check_yaml, check_suffix, print_mutation, set_logging, one_cycle, colorstr, methods
+    check_file, check_yaml, check_suffix, print_mutation, set_logging, one_cycle, colorstr, methods
 from utils.downloads import attempt_download
 from utils.loss import ComputeLoss
 from utils.plots import plot_labels, plot_evolve
@@ -105,6 +105,7 @@ def train(hyp,  # path/to/hyp.yaml or hyp dictionary
     is_coco = data.endswith('coco.yaml') and nc == 80  # COCO dataset
 
     # Model
+    check_suffix(weights, '.pt')  # check weights
     pretrained = weights.endswith('.pt')
     if pretrained:
         with torch_distributed_zero_first(RANK):
@@ -484,8 +485,7 @@ def main(opt, callbacks=Callbacks()):
         opt.cfg, opt.weights, opt.resume = '', ckpt, True  # reinstate
         LOGGER.info(f'Resuming training from {ckpt}')
     else:
-        check_suffix(opt.weights, '.pt')  # check weights
-        opt.data, opt.cfg, opt.hyp = check_yaml(opt.data), check_yaml(opt.cfg), check_yaml(opt.hyp)  # check YAMLs
+        opt.data, opt.cfg, opt.hyp = check_file(opt.data), check_yaml(opt.cfg), check_yaml(opt.hyp)  # check YAMLs
         assert len(opt.cfg) or len(opt.weights), 'either --cfg or --weights must be specified'
         if opt.evolve:
             opt.project = 'runs/evolve'