Loaded pretrained weights for efficientnet-b0
AttributeError Traceback (most recent call last)
Cell In[19], line 1
----> 1 model = CrossEfficientViT(config=config)
2 model.eval()
Cell In[14], line 267, in CrossEfficientViT.init(self, config)
262 dropout = config['model']['dropout']
263 emb_dropout = config['model']['emb-dropout']
--> 267 self.sm_image_embedder = ImageEmbedder(dim = sm_dim, image_size = image_size, patch_size = sm_patch_size, dropout = emb_dropout, efficient_block = 16, channels=sm_channels)
268 self.lg_image_embedder = ImageEmbedder(dim = lg_dim, image_size = image_size, patch_size = lg_patch_size, dropout = emb_dropout, efficient_block = 1, channels=lg_channels)
270 self.multi_scale_encoder = MultiScaleEncoder(
271 depth = depth,
272 sm_dim = sm_dim,
(...)
289 dropout = dropout
290 )
Cell In[14], line 186, in ImageEmbedder.init(self, dim, image_size, patch_size, dropout, efficient_block, channels)
184 assert image_size % patch_size == 0, 'Image dimensions must be divisible by the patch size.'
185 self.efficient_net = EfficientNet.from_pretrained('efficientnet-b0')
--> 186 self.efficient_net.delete_blocks(efficient_block)
187 self.efficient_block = efficient_block
189 for index, (name, param) in enumerate(self.efficient_net.named_parameters()):
File ~/.local/lib/python3.10/site-packages/torch/nn/modules/module.py:1614, in Module.getattr(self, name)
1612 if name in modules:
1613 return modules[name]
-> 1614 raise AttributeError("'{}' object has no attribute '{}'".format(
1615 type(self).name, name))
AttributeError: 'EfficientNet' object has no attribute 'delete_blocks'
Loaded pretrained weights for efficientnet-b0
AttributeError Traceback (most recent call last)
Cell In[19], line 1
----> 1 model = CrossEfficientViT(config=config)
2 model.eval()
Cell In[14], line 267, in CrossEfficientViT.init(self, config)
262 dropout = config['model']['dropout']
263 emb_dropout = config['model']['emb-dropout']
--> 267 self.sm_image_embedder = ImageEmbedder(dim = sm_dim, image_size = image_size, patch_size = sm_patch_size, dropout = emb_dropout, efficient_block = 16, channels=sm_channels)
268 self.lg_image_embedder = ImageEmbedder(dim = lg_dim, image_size = image_size, patch_size = lg_patch_size, dropout = emb_dropout, efficient_block = 1, channels=lg_channels)
270 self.multi_scale_encoder = MultiScaleEncoder(
271 depth = depth,
272 sm_dim = sm_dim,
(...)
289 dropout = dropout
290 )
Cell In[14], line 186, in ImageEmbedder.init(self, dim, image_size, patch_size, dropout, efficient_block, channels)
184 assert image_size % patch_size == 0, 'Image dimensions must be divisible by the patch size.'
185 self.efficient_net = EfficientNet.from_pretrained('efficientnet-b0')
--> 186 self.efficient_net.delete_blocks(efficient_block)
187 self.efficient_block = efficient_block
189 for index, (name, param) in enumerate(self.efficient_net.named_parameters()):
File ~/.local/lib/python3.10/site-packages/torch/nn/modules/module.py:1614, in Module.getattr(self, name)
1612 if name in modules:
1613 return modules[name]
-> 1614 raise AttributeError("'{}' object has no attribute '{}'".format(
1615 type(self).name, name))
AttributeError: 'EfficientNet' object has no attribute 'delete_blocks'