TypeError: requires_grad_() takes 1 positional argument but 2 were given

[randywreed]

Here's the code I'm using

from fastai.text.all import *  
from fastinference.inference import *   
learn_class=load_learner('/content/gdrive/MyDrive/TuesdayChatbot/classifier_model-'+ver+'.pkl')   
test=["In the article there were several things left out."]   
learn_class.predict(test)   
learn_class.intrinsic_attention(test[0])   

TypeError                                 Traceback (most recent call last)
<ipython-input-76-ba2c19ef8949> in <module>()
----> 1 learn_class.intrinsic_attention(test[0])

1 frames
/usr/local/lib/python3.6/dist-packages/fastinference/inference/text.py in _intrinsic_attention(learn, text, class_id)
    149     dl = learn.dls.test_dl([text])
    150     batch = next(iter(dl))[0]
--> 151     emb = learn.model[0].module.encoder(batch).detach().requires_grad_(True)
    152     lstm = learn.model[0].module(emb, True)
    153     learn.model.eval()

TypeError: requires_grad_() takes 1 positional argument but 2 were given

[muellerzr]

Can you please post the entire stack trace wrapped around the code ticks?

I'm pretty sure this has been fixed in the master version of fastai, but I can't tell without that.

[randywreed]

edited above comment accordingly

[muellerzr]

Yes, this has been fixed in master of fastai. However I'm also relooking the intrinsic attention implementation right now, so you may want to wait a day or two

[randywreed]

So I was loading fastai through fastbook. I should load fastai directly from github?

[muellerzr]

Yes, this is what I mean by master

[xspellsteal]

Hello, I've faced the same issue while i was trying to set up a tensorboard with the fastai v2. I have posted the issue here:

Anyway i ll duplicate it here :)

TypeError Traceback (most recent call last) in

1 from fastai.callback.tensorboard import *
2 cbs = [TensorBoardCallback(log_dir=‘logs’, projector=True)]
----> 3 learn.fit_one_cycle(3, cbs=cbs)

/opt/conda/lib/python3.7/site-packages/fastai/callback/schedule.py in fit_one_cycle(self, n_epoch, lr_max, div, div_final, pct_start, wd, moms, cbs, reset_opt)
110 scheds = {‘lr’: combined_cos(pct_start, lr_max/div, lr_max, lr_max/div_final),
111 ‘mom’: combined_cos(pct_start, *(self.moms if moms is None else moms))}
–> 112 self.fit(n_epoch, cbs=ParamScheduler(scheds)+L(cbs), reset_opt=reset_opt, wd=wd)
113
114 # Cell

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in fit(self, n_epoch, lr, wd, cbs, reset_opt)
209 self.opt.set_hypers(lr=self.lr if lr is None else lr)
210 self.n_epoch = n_epoch
–> 211 self._with_events(self._do_fit, ‘fit’, CancelFitException, self._end_cleanup)
212
213 def _end_cleanup(self): self.dl,self.xb,self.yb,self.pred,self.loss = None,(None,),(None,),None,None

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in with_events(self, f, event_type, ex, final)
158
159 def with_events(self, f, event_type, ex, final=noop):
–> 160 try: self(f’before{event_type}’); f()
161 except ex: self(f’after_cancel{event_type}’)
162 self(f’after_{event_type}’); final()

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in call(self, event_name)
139
140 def ordered_cbs(self, event): return [cb for cb in self.cbs.sorted(‘order’) if hasattr(cb, event)]
–> 141 def call(self, event_name): L(event_name).map(self._call_one)
142
143 def _call_one(self, event_name):

/opt/conda/lib/python3.7/site-packages/fastcore/foundation.py in map(self, f, gen, *args, **kwargs)
152 def range(cls, a, b=None, step=None): return cls(range_of(a, b=b, step=step))
153
–> 154 def map(self, f, *args, gen=False, **kwargs): return self._new(map_ex(self, f, *args, gen=gen, **kwargs))
155 def argwhere(self, f, negate=False, **kwargs): return self._new(argwhere(self, f, negate, **kwargs))
156 def filter(self, f=noop, negate=False, gen=False, **kwargs):

/opt/conda/lib/python3.7/site-packages/fastcore/basics.py in map_ex(iterable, f, gen, *args, **kwargs)
664 res = map(g, iterable)
665 if gen: return res
–> 666 return list(res)
667
668 # Cell

/opt/conda/lib/python3.7/site-packages/fastcore/basics.py in call(self, *args, **kwargs)
649 if isinstance(v,_Arg): kwargs[k] = args.pop(v.i)
650 fargs = [args[x.i] if isinstance(x, _Arg) else x for x in self.pargs] + args[self.maxi+1:]
–> 651 return self.func(*fargs, **kwargs)
652
653 # Cell

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in _call_one(self, event_name)
143 def _call_one(self, event_name):
144 if not hasattr(event, event_name): raise Exception(f’missing {event_name}’)
–> 145 for cb in self.cbs.sorted(‘order’): cb(event_name)
146
147 def _bn_bias_state(self, with_bias): return norm_bias_params(self.model, with_bias).map(self.opt.state)

/opt/conda/lib/python3.7/site-packages/fastai/callback/core.py in call(self, event_name)
42 (self.run_valid and not getattr(self, ‘training’, False)))
43 res = None
—> 44 if self.run and _run: res = getattr(self, event_name, noop)()
45 if event_name==‘after_fit’: self.run=True #Reset self.run to True at each end of fit
46 return res

/opt/conda/lib/python3.7/site-packages/fastai/callback/tensorboard.py in before_fit(self)
57 b = self.dls.one_batch()
58 self.learn._split(b)
—> 59 self.writer.add_graph(self.model, *self.xb)
60
61 def after_batch(self):

/opt/conda/lib/python3.7/site-packages/torch/utils/tensorboard/writer.py in add_graph(self, model, input_to_model, verbose)
722 if hasattr(model, ‘forward’):
723 # A valid PyTorch model should have a ‘forward’ method
–> 724 self._get_file_writer().add_graph(graph(model, input_to_model, verbose))
725 else:
726 # Caffe2 models do not have the ‘forward’ method

/opt/conda/lib/python3.7/site-packages/torch/utils/tensorboard/_pytorch_graph.py in graph(model, args, verbose)
284 with torch.onnx.select_model_mode_for_export(model, torch.onnx.TrainingMode.EVAL): # TODO: move outside of torch.onnx?
285 try:
–> 286 trace = torch.jit.trace(model, args)
287 graph = trace.graph
288 torch._C._jit_pass_inline(graph)

/opt/conda/lib/python3.7/site-packages/torch/jit/_trace.py in trace(func, example_inputs, optimize, check_trace, check_inputs, check_tolerance, strict, _force_outplace, _module_class, _compilation_unit)
740 strict,
741 _force_outplace,
–> 742 _module_class,
743 )
744

/opt/conda/lib/python3.7/site-packages/torch/jit/_trace.py in trace_module(mod, inputs, optimize, check_trace, check_inputs, check_tolerance, strict, _force_outplace, _module_class, _compilation_unit)
964 _force_outplace,
965 True,
–> 966 _module_class,
967 )
968 finally:

/opt/conda/lib/python3.7/site-packages/torch/autograd/grad_mode.py in decorate_context(*args, **kwargs)
24 def decorate_context(*args, **kwargs):
25 with self.class():
—> 26 return func(*args, **kwargs)
27 return cast(F, decorate_context)
28

/opt/conda/lib/python3.7/site-packages/torch/jit/_trace.py in _check_trace(check_inputs, func, traced_func, check_tolerance, strict, force_outplace, is_trace_module, _module_class)
325 copied_dict = {}
326 for name, data in inputs.items():
–> 327 copied_dict[name] = _clone_inputs(data)
328 check_mod = torch.jit.trace_module(
329 func.self if hasattr(func, “self”) else func,

/opt/conda/lib/python3.7/site-packages/torch/jit/_trace.py in _clone_inputs(args)
158 return function._nested_map(
159 lambda x: isinstance(x, torch.Tensor), clone_input, condition_msg=“tensors”
–> 160 )(args)
161
162

/opt/conda/lib/python3.7/site-packages/torch/autograd/function.py in _map(obj)
272 def _map(obj):
273 if condition(obj):
–> 274 return fn(obj)
275 elif obj is None:
276 return None

/opt/conda/lib/python3.7/site-packages/torch/jit/trace.py in clone_input(a)
148 a.detach()
149 .clone(memory_format=torch.preserve_format)
–> 150 .requires_grad(a.requires_grad)
151 )
152 if a.grad is not None:

TypeError: requires_grad_() takes 1 positional argument but 2 were given

[muellerzr]

Same solution. Load with github until the latest release.

[xspellsteal]

Could you please tell me how to do that? My issue is not related to fastinference, but the error is same using fastai when i was trying to activate tensorboard callbacks

[muellerzr]

pip install git+https://github.com/fastai/fastai
pip install git+https://github.com/fastai/fastcore

[xspellsteal]

pip install git+https://github.com/fastai/fastai
pip install git+https://github.com/fastai/fastcore

I did as you said, but im still facing that error.

Collecting git+https://github.com/fastai/fastai
  Cloning https://github.com/fastai/fastai to /tmp/pip-req-build-cvi2wka1
Requirement already satisfied (use --upgrade to upgrade): fastai==2.2.5 from git+https://github.com/fastai/fastai in /opt/conda/lib/python3.7/site-packages
Requirement already satisfied: pip in /opt/conda/lib/python3.7/site-packages (from fastai==2.2.5) (20.2.2)
Requirement already satisfied: packaging in /opt/conda/lib/python3.7/site-packages (from fastai==2.2.5) (20.1)
Requirement already satisfied: fastcore<1.4,>=1.3.8 in /opt/conda/lib/python3.7/site-packages (from fastai==2.2.5) (1.3.19)
Requirement already satisfied: torchvision<0.9,>=0.8 in /opt/conda/lib/python3.7/site-packages (from fastai==2.2.5) (0.8.2)
Requirement already satisfied: matplotlib in /opt/conda/lib/python3.7/site-packages (from fastai==2.2.5) (3.2.1)
Requirement already satisfied: pandas in /opt/conda/lib/python3.7/site-packages (from fastai==2.2.5) (1.1.1)
Requirement already satisfied: requests in /opt/conda/lib/python3.7/site-packages (from fastai==2.2.5) (2.23.0)
Requirement already satisfied: pyyaml in /opt/conda/lib/python3.7/site-packages (from fastai==2.2.5) (5.3.1)
Requirement already satisfied: fastprogress>=0.2.4 in /opt/conda/lib/python3.7/site-packages (from fastai==2.2.5) (1.0.0)
Requirement already satisfied: pillow>6.0.0 in /opt/conda/lib/python3.7/site-packages (from fastai==2.2.5) (7.2.0)
Requirement already satisfied: scikit-learn in /opt/conda/lib/python3.7/site-packages (from fastai==2.2.5) (0.23.2)
Requirement already satisfied: scipy in /opt/conda/lib/python3.7/site-packages (from fastai==2.2.5) (1.4.1)
Requirement already satisfied: spacy<3 in /opt/conda/lib/python3.7/site-packages (from fastai==2.2.5) (2.2.4)
Requirement already satisfied: torch<1.8,>=1.7.0 in /opt/conda/lib/python3.7/site-packages (from fastai==2.2.5) (1.7.1)
Requirement already satisfied: six in /opt/conda/lib/python3.7/site-packages (from packaging->fastai==2.2.5) (1.14.0)
Requirement already satisfied: pyparsing>=2.0.2 in /opt/conda/lib/python3.7/site-packages (from packaging->fastai==2.2.5) (2.4.7)
Requirement already satisfied: numpy in /opt/conda/lib/python3.7/site-packages (from torchvision<0.9,>=0.8->fastai==2.2.5) (1.18.5)
Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.7/site-packages (from matplotlib->fastai==2.2.5) (0.10.0)
Requirement already satisfied: python-dateutil>=2.1 in /opt/conda/lib/python3.7/site-packages (from matplotlib->fastai==2.2.5) (2.8.1)
Requirement already satisfied: kiwisolver>=1.0.1 in /opt/conda/lib/python3.7/site-packages (from matplotlib->fastai==2.2.5) (1.2.0)
Requirement already satisfied: pytz>=2017.2 in /opt/conda/lib/python3.7/site-packages (from pandas->fastai==2.2.5) (2019.3)
Requirement already satisfied: chardet<4,>=3.0.2 in /opt/conda/lib/python3.7/site-packages (from requests->fastai==2.2.5) (3.0.4)
Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /opt/conda/lib/python3.7/site-packages (from requests->fastai==2.2.5) (1.24.3)
Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.7/site-packages (from requests->fastai==2.2.5) (2020.6.20)
Requirement already satisfied: idna<3,>=2.5 in /opt/conda/lib/python3.7/site-packages (from requests->fastai==2.2.5) (2.9)
Requirement already satisfied: joblib>=0.11 in /opt/conda/lib/python3.7/site-packages (from scikit-learn->fastai==2.2.5) (0.14.1)
Requirement already satisfied: threadpoolctl>=2.0.0 in /opt/conda/lib/python3.7/site-packages (from scikit-learn->fastai==2.2.5) (2.1.0)
Requirement already satisfied: thinc==7.4.0 in /opt/conda/lib/python3.7/site-packages (from spacy<3->fastai==2.2.5) (7.4.0)
Requirement already satisfied: cymem<2.1.0,>=2.0.2 in /opt/conda/lib/python3.7/site-packages (from spacy<3->fastai==2.2.5) (2.0.3)
Requirement already satisfied: tqdm<5.0.0,>=4.38.0 in /opt/conda/lib/python3.7/site-packages (from spacy<3->fastai==2.2.5) (4.45.0)
Requirement already satisfied: blis<0.5.0,>=0.4.0 in /opt/conda/lib/python3.7/site-packages (from spacy<3->fastai==2.2.5) (0.4.1)
Requirement already satisfied: murmurhash<1.1.0,>=0.28.0 in /opt/conda/lib/python3.7/site-packages (from spacy<3->fastai==2.2.5) (1.0.2)
Requirement already satisfied: setuptools in /opt/conda/lib/python3.7/site-packages (from spacy<3->fastai==2.2.5) (46.1.3.post20200325)
Requirement already satisfied: plac<1.2.0,>=0.9.6 in /opt/conda/lib/python3.7/site-packages (from spacy<3->fastai==2.2.5) (1.1.3)
Requirement already satisfied: srsly<1.1.0,>=1.0.2 in /opt/conda/lib/python3.7/site-packages (from spacy<3->fastai==2.2.5) (1.0.2)
Requirement already satisfied: wasabi<1.1.0,>=0.4.0 in /opt/conda/lib/python3.7/site-packages (from spacy<3->fastai==2.2.5) (0.7.1)
Requirement already satisfied: catalogue<1.1.0,>=0.0.7 in /opt/conda/lib/python3.7/site-packages (from spacy<3->fastai==2.2.5) (1.0.0)
Requirement already satisfied: preshed<3.1.0,>=3.0.2 in /opt/conda/lib/python3.7/site-packages (from spacy<3->fastai==2.2.5) (3.0.2)
Requirement already satisfied: typing-extensions in /opt/conda/lib/python3.7/site-packages (from torch<1.8,>=1.7.0->fastai==2.2.5) (3.7.4.1)
Requirement already satisfied: importlib-metadata>=0.20; python_version < "3.8" in /opt/conda/lib/python3.7/site-packages (from catalogue<1.1.0,>=0.0.7->spacy<3->fastai==2.2.5) (1.6.0)
Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.7/site-packages (from importlib-metadata>=0.20; python_version < "3.8"->catalogue<1.1.0,>=0.0.7->spacy<3->fastai==2.2.5) (3.1.0)
Building wheels for collected packages: fastai
  Building wheel for fastai (setup.py) ... done
  Created wheel for fastai: filename=fastai-2.2.5-py3-none-any.whl size=192192 sha256=59360ca5832e9c61b43f57e42770410b0b6745c692c9e64d465403a98fafc076
  Stored in directory: /tmp/pip-ephem-wheel-cache-q7qywaxj/wheels/40/be/4f/b7f2aec4df5712626ceed9f20a8996eb05e31244e57e58d632
Successfully built fastai
WARNING: You are using pip version 20.2.2; however, version 21.0.1 is available.
You should consider upgrading via the '/opt/conda/bin/python3.7 -m pip install --upgrade pip' command.
Collecting git+https://github.com/fastai/fastcore
  Cloning https://github.com/fastai/fastcore to /tmp/pip-req-build-36paufmg
Requirement already satisfied: pip in /opt/conda/lib/python3.7/site-packages (from fastcore==1.3.20) (20.2.2)
Requirement already satisfied: packaging in /opt/conda/lib/python3.7/site-packages (from fastcore==1.3.20) (20.1)
Requirement already satisfied: pyparsing>=2.0.2 in /opt/conda/lib/python3.7/site-packages (from packaging->fastcore==1.3.20) (2.4.7)
Requirement already satisfied: six in /opt/conda/lib/python3.7/site-packages (from packaging->fastcore==1.3.20) (1.14.0)
Building wheels for collected packages: fastcore
  Building wheel for fastcore (setup.py) ... done
  Created wheel for fastcore: filename=fastcore-1.3.20-py3-none-any.whl size=52134 sha256=b416c69fbce3a247b3812df59eaffaec9ac6a36a9d45329db9a4b371e78f91d8
  Stored in directory: /tmp/pip-ephem-wheel-cache-zgt35c_2/wheels/74/46/b7/0d3dddeb22ca1b6f226a3d5b096df11a632951327002d86f1f
Successfully built fastcore
Installing collected packages: fastcore
  Attempting uninstall: fastcore
    Found existing installation: fastcore 1.3.19
    Uninstalling fastcore-1.3.19:
      Successfully uninstalled fastcore-1.3.19
Successfully installed fastcore-1.3.20
WARNING: You are using pip version 20.2.2; however, version 21.0.1 is available.
You should consider upgrading via the '/opt/conda/bin/python3.7 -m pip install --upgrade pip' command.

The error:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-25-4b7157f74a3c> in <module>
      1 from fastai.callback.tensorboard import *
      2 cbs = [TensorBoardCallback(log_dir='logs', projector=True)]
----> 3 learn.fit_one_cycle(3, cbs=cbs)

/opt/conda/lib/python3.7/site-packages/fastai/callback/schedule.py in fit_one_cycle(self, n_epoch, lr_max, div, div_final, pct_start, wd, moms, cbs, reset_opt)
    110     scheds = {'lr': combined_cos(pct_start, lr_max/div, lr_max, lr_max/div_final),
    111               'mom': combined_cos(pct_start, *(self.moms if moms is None else moms))}
--> 112     self.fit(n_epoch, cbs=ParamScheduler(scheds)+L(cbs), reset_opt=reset_opt, wd=wd)
    113 
    114 # Cell

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in fit(self, n_epoch, lr, wd, cbs, reset_opt)
    209             self.opt.set_hypers(lr=self.lr if lr is None else lr)
    210             self.n_epoch = n_epoch
--> 211             self._with_events(self._do_fit, 'fit', CancelFitException, self._end_cleanup)
    212 
    213     def _end_cleanup(self): self.dl,self.xb,self.yb,self.pred,self.loss = None,(None,),(None,),None,None

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in _with_events(self, f, event_type, ex, final)
    158 
    159     def _with_events(self, f, event_type, ex, final=noop):
--> 160         try: self(f'before_{event_type}');  f()
    161         except ex: self(f'after_cancel_{event_type}')
    162         self(f'after_{event_type}');  final()

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in __call__(self, event_name)
    139 
    140     def ordered_cbs(self, event): return [cb for cb in self.cbs.sorted('order') if hasattr(cb, event)]
--> 141     def __call__(self, event_name): L(event_name).map(self._call_one)
    142 
    143     def _call_one(self, event_name):

/opt/conda/lib/python3.7/site-packages/fastcore/foundation.py in map(self, f, gen, *args, **kwargs)
    152     def range(cls, a, b=None, step=None): return cls(range_of(a, b=b, step=step))
    153 
--> 154     def map(self, f, *args, gen=False, **kwargs): return self._new(map_ex(self, f, *args, gen=gen, **kwargs))
    155     def argwhere(self, f, negate=False, **kwargs): return self._new(argwhere(self, f, negate, **kwargs))
    156     def filter(self, f=noop, negate=False, gen=False, **kwargs):

/opt/conda/lib/python3.7/site-packages/fastcore/basics.py in map_ex(iterable, f, gen, *args, **kwargs)
    664     res = map(g, iterable)
    665     if gen: return res
--> 666     return list(res)
    667 
    668 # Cell

/opt/conda/lib/python3.7/site-packages/fastcore/basics.py in __call__(self, *args, **kwargs)
    649             if isinstance(v,_Arg): kwargs[k] = args.pop(v.i)
    650         fargs = [args[x.i] if isinstance(x, _Arg) else x for x in self.pargs] + args[self.maxi+1:]
--> 651         return self.func(*fargs, **kwargs)
    652 
    653 # Cell

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in _call_one(self, event_name)
    143     def _call_one(self, event_name):
    144         if not hasattr(event, event_name): raise Exception(f'missing {event_name}')
--> 145         for cb in self.cbs.sorted('order'): cb(event_name)
    146 
    147     def _bn_bias_state(self, with_bias): return norm_bias_params(self.model, with_bias).map(self.opt.state)

/opt/conda/lib/python3.7/site-packages/fastai/callback/core.py in __call__(self, event_name)
     42                (self.run_valid and not getattr(self, 'training', False)))
     43         res = None
---> 44         if self.run and _run: res = getattr(self, event_name, noop)()
     45         if event_name=='after_fit': self.run=True #Reset self.run to True at each end of fit
     46         return res

/opt/conda/lib/python3.7/site-packages/fastai/callback/tensorboard.py in before_fit(self)
     57             b = self.dls.one_batch()
     58             self.learn._split(b)
---> 59             self.writer.add_graph(self.model, *self.xb)
     60 
     61     def after_batch(self):

/opt/conda/lib/python3.7/site-packages/torch/utils/tensorboard/writer.py in add_graph(self, model, input_to_model, verbose)
    722         if hasattr(model, 'forward'):
    723             # A valid PyTorch model should have a 'forward' method
--> 724             self._get_file_writer().add_graph(graph(model, input_to_model, verbose))
    725         else:
    726             # Caffe2 models do not have the 'forward' method

/opt/conda/lib/python3.7/site-packages/torch/utils/tensorboard/_pytorch_graph.py in graph(model, args, verbose)
    284     with torch.onnx.select_model_mode_for_export(model, torch.onnx.TrainingMode.EVAL):  # TODO: move outside of torch.onnx?
    285         try:
--> 286             trace = torch.jit.trace(model, args)
    287             graph = trace.graph
    288             torch._C._jit_pass_inline(graph)

/opt/conda/lib/python3.7/site-packages/torch/jit/_trace.py in trace(func, example_inputs, optimize, check_trace, check_inputs, check_tolerance, strict, _force_outplace, _module_class, _compilation_unit)
    740             strict,
    741             _force_outplace,
--> 742             _module_class,
    743         )
    744 

/opt/conda/lib/python3.7/site-packages/torch/jit/_trace.py in trace_module(mod, inputs, optimize, check_trace, check_inputs, check_tolerance, strict, _force_outplace, _module_class, _compilation_unit)
    964                         _force_outplace,
    965                         True,
--> 966                         _module_class,
    967                     )
    968     finally:

/opt/conda/lib/python3.7/site-packages/torch/autograd/grad_mode.py in decorate_context(*args, **kwargs)
     24         def decorate_context(*args, **kwargs):
     25             with self.__class__():
---> 26                 return func(*args, **kwargs)
     27         return cast(F, decorate_context)
     28 

/opt/conda/lib/python3.7/site-packages/torch/jit/_trace.py in _check_trace(check_inputs, func, traced_func, check_tolerance, strict, force_outplace, is_trace_module, _module_class)
    325             copied_dict = {}
    326             for name, data in inputs.items():
--> 327                 copied_dict[name] = _clone_inputs(data)
    328             check_mod = torch.jit.trace_module(
    329                 func.__self__ if hasattr(func, "__self__") else func,

/opt/conda/lib/python3.7/site-packages/torch/jit/_trace.py in _clone_inputs(args)
    158     return function._nested_map(
    159         lambda x: isinstance(x, torch.Tensor), clone_input, condition_msg="tensors"
--> 160     )(args)
    161 
    162 

/opt/conda/lib/python3.7/site-packages/torch/autograd/function.py in _map(obj)
    272     def _map(obj):
    273         if condition(obj):
--> 274             return fn(obj)
    275         elif obj is None:
    276             return None

/opt/conda/lib/python3.7/site-packages/torch/jit/_trace.py in clone_input(a)
    148                 a.detach()
    149                 .clone(memory_format=torch.preserve_format)
--> 150                 .requires_grad_(a.requires_grad)
    151             )
    152             if a.grad is not None:

TypeError: requires_grad_() takes 1 positional argument but 2 were given

[muellerzr]

Given this is a fastai issue open an issue there. This repo isn't meant for fastai issues. And please include a complete reproducer as well when you do.