collab notebook error

[barbara42]

Under loading a pre-trained model

# This is an MAE model trained with pixels as targets for visualization (ViT-Large, training mask ratio=0.75)

# download checkpoint if not exist
!wget -nc https://dl.fbaipublicfiles.com/mae/visualize/mae_visualize_vit_large.pth

chkpt_dir = 'mae_visualize_vit_large.pth'
model_mae = prepare_model(chkpt_dir, 'mae_vit_large_patch16')
print('Model loaded.')

Results in the following error

--2024-03-12 18:31:48--  https://dl.fbaipublicfiles.com/mae/visualize/mae_visualize_vit_large.pth
Resolving dl.fbaipublicfiles.com (dl.fbaipublicfiles.com)... 13.35.7.50, 13.35.7.38, 13.35.7.82, ...
Connecting to dl.fbaipublicfiles.com (dl.fbaipublicfiles.com)|13.35.7.50|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 1318315181 (1.2G) [binary/octet-stream]
Saving to: ‘mae_visualize_vit_large.pth’

mae_visualize_vit_l 100%[===================>]   1.23G   138MB/s    in 11s     

2024-03-12 18:31:59 (115 MB/s) - ‘mae_visualize_vit_large.pth’ saved [1318315181/1318315181]

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
[<ipython-input-4-062e15d3f32e>](https://localhost:8080/#) in <cell line: 7>()
      5 
      6 chkpt_dir = 'mae_visualize_vit_large.pth'
----> 7 model_mae = prepare_model(chkpt_dir, 'mae_vit_large_patch16')
      8 print('Model loaded.')

7 frames
[<ipython-input-2-4a1bff3e6bef>](https://localhost:8080/#) in prepare_model(chkpt_dir, arch)
     14 def prepare_model(chkpt_dir, arch='mae_vit_large_patch16'):
     15     # build model
---> 16     model = getattr(models_mae, arch)()
     17     # load model
     18     checkpoint = torch.load(chkpt_dir, map_location='cpu')

[/content/./mae/models_mae.py](https://localhost:8080/#) in mae_vit_large_patch16_dec512d8b(**kwargs)
    230 
    231 def mae_vit_large_patch16_dec512d8b(**kwargs):
--> 232     model = MaskedAutoencoderViT(
    233         patch_size=16, embed_dim=1024, depth=24, num_heads=16,
    234         decoder_embed_dim=512, decoder_depth=8, decoder_num_heads=16,

[/content/./mae/models_mae.py](https://localhost:8080/#) in __init__(self, img_size, patch_size, in_chans, embed_dim, depth, num_heads, decoder_embed_dim, decoder_depth, decoder_num_heads, mlp_ratio, norm_layer, norm_pix_loss)
     61         self.norm_pix_loss = norm_pix_loss
     62 
---> 63         self.initialize_weights()
     64 
     65     def initialize_weights(self):

[/content/./mae/models_mae.py](https://localhost:8080/#) in initialize_weights(self)
     66         # initialization
     67         # initialize (and freeze) pos_embed by sin-cos embedding
---> 68         pos_embed = get_2d_sincos_pos_embed(self.pos_embed.shape[-1], int(self.patch_embed.num_patches**.5), cls_token=True)
     69         self.pos_embed.data.copy_(torch.from_numpy(pos_embed).float().unsqueeze(0))
     70 

[/content/./mae/util/pos_embed.py](https://localhost:8080/#) in get_2d_sincos_pos_embed(embed_dim, grid_size, cls_token)
     30 
     31     grid = grid.reshape([2, 1, grid_size, grid_size])
---> 32     pos_embed = get_2d_sincos_pos_embed_from_grid(embed_dim, grid)
     33     if cls_token:
     34         pos_embed = np.concatenate([np.zeros([1, embed_dim]), pos_embed], axis=0)

[/content/./mae/util/pos_embed.py](https://localhost:8080/#) in get_2d_sincos_pos_embed_from_grid(embed_dim, grid)
     40 
     41     # use half of dimensions to encode grid_h
---> 42     emb_h = get_1d_sincos_pos_embed_from_grid(embed_dim // 2, grid[0])  # (H*W, D/2)
     43     emb_w = get_1d_sincos_pos_embed_from_grid(embed_dim // 2, grid[1])  # (H*W, D/2)
     44 

[/content/./mae/util/pos_embed.py](https://localhost:8080/#) in get_1d_sincos_pos_embed_from_grid(embed_dim, pos)
     54     """
     55     assert embed_dim % 2 == 0
---> 56     omega = np.arange(embed_dim // 2, dtype=np.float)
     57     omega /= embed_dim / 2.
     58     omega = 1. / 10000**omega  # (D/2,)

[/usr/local/lib/python3.10/dist-packages/numpy/__init__.py](https://localhost:8080/#) in __getattr__(attr)
    317 
    318         if attr in __former_attrs__:
--> 319             raise AttributeError(__former_attrs__[attr])
    320 
    321         if attr == 'testing':

AttributeError: module 'numpy' has no attribute 'float'.
`np.float` was a deprecated alias for the builtin `float`. To avoid this error in existing code, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
    https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations

[DannaShavit]

I had the same issue, and this solved it for me:
Add these lines before your imports:
%load_ext autoreload
%autoreload 2

Taken from here:
https://stackoverflow.com/questions/75397364/google-colab-not-detecting-changes-in-py-files

[hzy-del]

!pip install numpy==1.23.3