运行fastai样例代码报错 AttributeError: module ‘numpy‘ has no attribute ‘int‘

使用fastai库时，numpy报错没有int属性。完整报错如下：

Could not do one pass in your dataloader, there is something wrong in it. Please see the stack trace below:
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[12], line 2
      1 def is_cat(x): return x[0].isupper()
----> 2 dls = ImageDataLoaders.from_name_func(
      3     path, get_image_files(path), valid_pct=0.2, seed=42,
      4     label_func=is_cat, item_tfms=Resize(224))
      6 learn = vision_learner(dls, resnet34, metrics=error_rate)
      7 learn.fine_tune(1)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastai\vision\data.py:149, in ImageDataLoaders.from_name_func(cls, path, fnames, label_func, **kwargs)
    147     raise ValueError("label_func couldn't be lambda function on Windows")
    148 f = using_attr(label_func, 'name')
--> 149 return cls.from_path_func(path, fnames, f, **kwargs)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastai\vision\data.py:135, in ImageDataLoaders.from_path_func(cls, path, fnames, label_func, valid_pct, seed, item_tfms, batch_tfms, img_cls, **kwargs)
    129 "Create from list of `fnames` in `path`s with `label_func`"
    130 dblock = DataBlock(blocks=(ImageBlock(img_cls), CategoryBlock),
    131                    splitter=RandomSplitter(valid_pct, seed=seed),
    132                    get_y=label_func,
    133                    item_tfms=item_tfms,
    134                    batch_tfms=batch_tfms)
--> 135 return cls.from_dblock(dblock, fnames, path=path, **kwargs)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastai\data\core.py:281, in DataLoaders.from_dblock(cls, dblock, source, path, bs, val_bs, shuffle, device, **kwargs)
    270 @classmethod
    271 def from_dblock(cls, 
    272     dblock, # `DataBlock` object
   (...)
    279     **kwargs
    280 ):
--> 281     return dblock.dataloaders(source, path=path, bs=bs, val_bs=val_bs, shuffle=shuffle, device=device, **kwargs)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastai\data\block.py:157, in DataBlock.dataloaders(self, source, path, verbose, **kwargs)
    155 dsets = self.datasets(source, verbose=verbose)
    156 kwargs = {**self.dls_kwargs, **kwargs, 'verbose': verbose}
--> 157 return dsets.dataloaders(path=path, after_item=self.item_tfms, after_batch=self.batch_tfms, **kwargs)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastai\data\core.py:334, in FilteredBase.dataloaders(self, bs, shuffle_train, shuffle, val_shuffle, n, path, dl_type, dl_kwargs, device, drop_last, val_bs, **kwargs)
    332 dl = dl_type(self.subset(0), **merge(kwargs,def_kwargs, dl_kwargs[0]))
    333 def_kwargs = {'bs':bs if val_bs is None else val_bs,'shuffle':val_shuffle,'n':None,'drop_last':False}
--> 334 dls = [dl] + [dl.new(self.subset(i), **merge(kwargs,def_kwargs,val_kwargs,dl_kwargs[i]))
    335               for i in range(1, self.n_subsets)]
    336 return self._dbunch_type(*dls, path=path, device=device)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastai\data\core.py:334, in (.0)
    332 dl = dl_type(self.subset(0), **merge(kwargs,def_kwargs, dl_kwargs[0]))
    333 def_kwargs = {'bs':bs if val_bs is None else val_bs,'shuffle':val_shuffle,'n':None,'drop_last':False}
--> 334 dls = [dl] + [dl.new(self.subset(i), **merge(kwargs,def_kwargs,val_kwargs,dl_kwargs[i]))
    335               for i in range(1, self.n_subsets)]
    336 return self._dbunch_type(*dls, path=path, device=device)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastai\data\core.py:97, in TfmdDL.new(self, dataset, cls, **kwargs)
     95 if not hasattr(self, '_n_inp') or not hasattr(self, '_types'):
     96     try:
---> 97         self._one_pass()
     98         res._n_inp,res._types = self._n_inp,self._types
     99     except Exception as e: 

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastai\data\core.py:78, in TfmdDL._one_pass(self)
     77 def _one_pass(self):
---> 78     b = self.do_batch([self.do_item(None)])
     79     if self.device is not None: b = to_device(b, self.device)
     80     its = self.after_batch(b)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastai\data\load.py:153, in DataLoader.do_item(self, s)
    152 def do_item(self, s):
--> 153     try: return self.after_item(self.create_item(s))
    154     except SkipItemException: return None

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastcore\transform.py:208, in Pipeline.__call__(self, o)
--> 208 def __call__(self, o): return compose_tfms(o, tfms=self.fs, split_idx=self.split_idx)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastcore\transform.py:158, in compose_tfms(x, tfms, is_enc, reverse, **kwargs)
    156 for f in tfms:
    157     if not is_enc: f = f.decode
--> 158     x = f(x, **kwargs)
    159 return x

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastcore\transform.py:81, in Transform.__call__(self, x, **kwargs)
     79 @property
     80 def name(self): return getattr(self, '_name', _get_name(self))
---> 81 def __call__(self, x, **kwargs): return self._call('encodes', x, **kwargs)
     82 def decode  (self, x, **kwargs): return self._call('decodes', x, **kwargs)
     83 def __repr__(self): return f'{self.name}:\nencodes: {self.encodes}decodes: {self.decodes}'

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastcore\transform.py:91, in Transform._call(self, fn, x, split_idx, **kwargs)
     89 def _call(self, fn, x, split_idx=None, **kwargs):
     90     if split_idx!=self.split_idx and self.split_idx is not None: return x
---> 91     return self._do_call(getattr(self, fn), x, **kwargs)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastcore\transform.py:98, in Transform._do_call(self, f, x, **kwargs)
     96     ret = f.returns(x) if hasattr(f,'returns') else None
     97     return retain_type(f(x, **kwargs), x, ret)
---> 98 res = tuple(self._do_call(f, x_, **kwargs) for x_ in x)
     99 return retain_type(res, x)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastcore\transform.py:98, in (.0)
     96     ret = f.returns(x) if hasattr(f,'returns') else None
     97     return retain_type(f(x, **kwargs), x, ret)
---> 98 res = tuple(self._do_call(f, x_, **kwargs) for x_ in x)
     99 return retain_type(res, x)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastcore\transform.py:97, in Transform._do_call(self, f, x, **kwargs)
     95     if f is None: return x
     96     ret = f.returns(x) if hasattr(f,'returns') else None
---> 97     return retain_type(f(x, **kwargs), x, ret)
     98 res = tuple(self._do_call(f, x_, **kwargs) for x_ in x)
     99 return retain_type(res, x)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastcore\dispatch.py:120, in TypeDispatch.__call__(self, *args, **kwargs)
    118 elif self.inst is not None: f = MethodType(f, self.inst)
    119 elif self.owner is not None: f = MethodType(f, self.owner)
--> 120 return f(*args, **kwargs)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastai\vision\core.py:236, in encodes(self, o)
    235 ToTensor
--> 236 def encodes(self, o:PILBase): return o._tensor_cls(image2tensor(o))

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastai\vision\core.py:106, in image2tensor(img)
    104 def image2tensor(img):
    105     "Transform image to byte tensor in `c*h*w` dim order."
--> 106     res = tensor(img)
    107     if res.dim()==2: res = res.unsqueeze(-1)
    108     return res.permute(2,0,1)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastai\torch_core.py:154, in tensor(x, *rest, **kwargs)
    146     if len(rest): x = (x,)+rest
    147     # There was a Pytorch bug in dataloader using num_workers>0. Haven't confirmed if fixed
    148     # if isinstance(x, (tuple,list)) and len(x)==0: return tensor(0)
    149     res = (x if isinstance(x, Tensor)
    150            else torch.tensor(x, **kwargs) if isinstance(x, (tuple,list,numbers.Number))
    151            else _array2tensor(x, **kwargs) if isinstance(x, ndarray)
    152            else as_tensor(x.values, **kwargs) if isinstance(x, (pd.Series, pd.DataFrame))
    153 #            else as_tensor(array(x, **kwargs)) if hasattr(x, '__array__') or is_iter(x)
--> 154            else _array2tensor(array(x), **kwargs))
    155     if res.dtype is torch.float64: return res.float()
    156     return res

File D:\Program Files\anaconda\envs\torch\lib\site-packages\fastai\torch_core.py:136, in _array2tensor(x, requires_grad, pin_memory, **kwargs)
    133 if x.dtype==np.uint16: x = x.astype(np.float32)
    134 # windows default numpy int dtype is int32, while torch tensor default int dtype is int64
    135 # https://github.com/numpy/numpy/issues/9464
--> 136 if sys.platform == "win32" and x.dtype==np.int: x = x.astype(np.int64)
    137 t = torch.as_tensor(x, **kwargs)
    138 t.requires_grad_(requires_grad)

File D:\Program Files\anaconda\envs\torch\lib\site-packages\numpy\__init__.py:284, in __getattr__(attr)
    281     from .testing import Tester
    282     return Tester
--> 284 raise AttributeError("module {!r} has no attribute "
    285                      "{!r}".format(__name__, attr))

AttributeError: module 'numpy' has no attribute 'int'

解决方法：
参考How to Fix AttributeError: module ‘numpy’ has no attribute ‘float’：

As of numpy v1.20, numpy.float as well as similar aliases (including numpy.int) were deprecated.

可知，自1.20版本后，np.int已经废弃，所以安装旧版本的numpy即可：

pip install numpy==1.19

安装时报错很长，有以下字段:

No module named ‘numpy.distutils._msvccompiler’ in numpy.distutils; trying from distutils

参考git issue可知，是python版本太高了。重装环境使用python3.6后解决问题。

总结

要顺利运行fastai，建议使用以下配置：

• python 3.7
• numpy 1.19 更高的版本可能导致numpy找不到int属性

这样的配置能更顺利地运行fastai代码，减少不必要的报错debug时间。