Hi, I am trying to run the following import instructions in a jupyter notebook but torchvision is giving me a problem
from __future__ import print_function, division
! python --version
! python2 --version
! python3 --version
import os
import torch
import pandas as pd
from skimage import io, transform
import numpy as np
import matplotlib.pyplot as plt
from torch.utils.data import Dataset, DataLoader
import sys
print(sys.version)
import torchvision
# from torchvision import transforms, utils
The output is the following
Python 3.5.2
Python 2.7.12
Python 3.5.2
3.5.2 (default, Apr 16 2020, 17:47:17)
[GCC 5.4.0 20160609]
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-1-3a8a37d1acbb> in <module>
12 import sys
13 print(sys.version)
---> 14 import torchvision
15 # from torchvision import transforms, utils
~/virtualenvs/testenv1/lib/python3.5/site-packages/torchvision/__init__.py in <module>
1 import warnings
2
----> 3 from torchvision import models
4 from torchvision import datasets
5 from torchvision import ops
~/virtualenvs/testenv1/lib/python3.5/site-packages/torchvision/models/__init__.py in <module>
10 from .shufflenetv2 import *
11 from . import segmentation
---> 12 from . import detection
13 from . import video
14 from . import quantization
~/virtualenvs/testenv1/lib/python3.5/site-packages/torchvision/models/detection/__init__.py in <module>
----> 1 from .faster_rcnn import *
2 from .mask_rcnn import *
3 from .keypoint_rcnn import *
~/virtualenvs/testenv1/lib/python3.5/site-packages/torchvision/models/detection/faster_rcnn.py in <module>
12 from .generalized_rcnn import GeneralizedRCNN
13 from .rpn import AnchorGenerator, RPNHead, RegionProposalNetwork
---> 14 from .roi_heads import RoIHeads
15 from .transform import GeneralizedRCNNTransform
16 from .backbone_utils import resnet_fpn_backbone
~/virtualenvs/testenv1/lib/python3.5/site-packages/torchvision/models/detection/roi_heads.py in <module>
208
209
--> 210 @torch.jit.script
211 def _onnx_heatmaps_to_keypoints_loop(maps, rois, widths_ceil, heights_ceil,
212 widths, heights, offset_x, offset_y, num_keypoints):
~/virtualenvs/testenv1/lib/python3.5/site-packages/torch/jit/__init__.py in script(obj, optimize, _frames_up, _rcb)
1288 if _rcb is None:
1289 _rcb = _jit_internal.createResolutionCallbackFromClosure(obj)
-> 1290 fn = torch._C._jit_script_compile(qualified_name, ast, _rcb, get_default_args(obj))
1291 # Forward docstrings
1292 fn.__doc__ = obj.__doc__
~/virtualenvs/testenv1/lib/python3.5/site-packages/torch/jit/_recursive.py in try_compile_fn(fn, loc)
566 # object
567 rcb = _jit_internal.createResolutionCallbackFromClosure(fn)
--> 568 return torch.jit.script(fn, _rcb=rcb)
569
570 def wrap_cpp_module(cpp_module):
~/virtualenvs/testenv1/lib/python3.5/site-packages/torch/jit/__init__.py in script(obj, optimize, _frames_up, _rcb)
1288 if _rcb is None:
1289 _rcb = _jit_internal.createResolutionCallbackFromClosure(obj)
-> 1290 fn = torch._C._jit_script_compile(qualified_name, ast, _rcb, get_default_args(obj))
1291 # Forward docstrings
1292 fn.__doc__ = obj.__doc__
~/virtualenvs/testenv1/lib/python3.5/site-packages/torch/jit/__init__.py in _get_overloads(obj)
2028 compiled_fns = []
2029 for overload_fn in uncompiled_overloads:
-> 2030 compiled_fns.append(_compile_function_with_overload(overload_fn, qual_name, obj))
2031
2032 if existing_compiled_fns:
~/virtualenvs/testenv1/lib/python3.5/site-packages/torch/jit/__init__.py in _compile_function_with_overload(overload_fn, qual_name, impl_fn)
2008 def _compile_function_with_overload(overload_fn, qual_name, impl_fn):
2009 overload_decl = torch.jit.get_jit_def(overload_fn).decl()
-> 2010 overload_signature = torch.jit.annotations.get_signature(overload_fn, None, None, inspect.ismethod(overload_fn))
2011 impl_ast = torch.jit.get_jit_def(impl_fn)
2012 overload_defaults = get_default_args(overload_fn)
~/virtualenvs/testenv1/lib/python3.5/site-packages/torch/jit/annotations.py in get_signature(fn, rcb, loc, is_method)
77 # because it didn't have any annotations.
78 if type_line is not None:
---> 79 signature = parse_type_line(type_line, rcb, loc)
80
81 return signature
~/virtualenvs/testenv1/lib/python3.5/site-packages/torch/jit/annotations.py in parse_type_line(type_line, rcb, loc)
163 raise RuntimeError("Failed to parse the return type of a type annotation: {}".format(str(e)))
164
--> 165 arg_types = [ann_to_type(ann, loc) for ann in arg_ann]
166 return arg_types, ann_to_type(ret_ann, loc)
167
~/virtualenvs/testenv1/lib/python3.5/site-packages/torch/jit/annotations.py in <listcomp>(.0)
163 raise RuntimeError("Failed to parse the return type of a type annotation: {}".format(str(e)))
164
--> 165 arg_types = [ann_to_type(ann, loc) for ann in arg_ann]
166 return arg_types, ann_to_type(ret_ann, loc)
167
~/virtualenvs/testenv1/lib/python3.5/site-packages/torch/jit/annotations.py in ann_to_type(ann, loc)
301
302 def ann_to_type(ann, loc):
--> 303 the_type = try_ann_to_type(ann, loc)
304 if the_type is not None:
305 return the_type
~/virtualenvs/testenv1/lib/python3.5/site-packages/torch/jit/annotations.py in try_ann_to_type(ann, loc)
294 def fake_rcb(key):
295 return None
--> 296 the_type = torch._C._resolve_type_from_object(ann, loc, fake_rcb)
297 if the_type is not None:
298 return the_type
TypeError: _resolve_type_from_object(): incompatible function arguments. The following argument types are supported:
1. (arg0: object, arg1: torch._C._jit_tree_views.SourceRange, arg2: Callable[[str], function]) -> torch._C.Type
Invoked with: typing.Union[int, NoneType], None, <function try_ann_to_type.<locals>.fake_rcb at 0x7f8aa1ad2e18>
I tried to search on the internet but I could not find anything. Any ideas on how to solve this problem?
Thanks!