Integration of Tensorboard

[oguiza]

Discussed in https://github.com/timeseriesAI/tsai/discussions/633

^{Originally posted by **Samcro5C** November 30, 2022} When I tried to use the fastai callback [TensorBoardCallback](https://docs.fast.ai/callback.tensorboard.html#tensorboardprojectorcallback) for a TSForecaster (minimal example from Readme), I ran into a RuntimeError (_RuntimeError: Exception occured in `TensorBoardCallback` when calling event `after_epoch`: Can't call numpy() on Tensor that requires grad. Use tensor.detach().numpy() instead._), so I was wondering if tsai supports tensorboard at all or if this is a bug. Thank you in advance.

Code to reproduce the issue:

X, y, splits = get_UCR_data('LSST', split_data=False)
tfms = [None, TSClassification()]
batch_tfms = TSStandardize(by_sample=True)
dls = get_ts_dls(X, y, splits=splits, tfms=tfms, batch_tfms=batch_tfms)
cbs = [TensorBoardCallback()]
learn = ts_learner(dls, InceptionTimePlus, metrics=accuracy, cbs=cbs)
learn.fit_one_cycle(10, 1e-2)

Here's the full traceback:

---------------------------------------------------------------------------

TypeError                                 Traceback (most recent call last)

[<ipython-input-36-af203e69f537>](https://localhost:8080/#) in <module>
      5 cbs = [TensorBoardCallback()]
      6 learn = ts_learner(dls, InceptionTimePlus, metrics=accuracy, cbs=cbs)
----> 7 learn.fit_one_cycle(10, 1e-2)

18 frames

[/usr/local/lib/python3.8/dist-packages/fastai/callback/schedule.py](https://localhost:8080/#) in fit_one_cycle(self, n_epoch, lr_max, div, div_final, pct_start, wd, moms, cbs, reset_opt, start_epoch)
    117     scheds = {'lr': combined_cos(pct_start, lr_max/div, lr_max, lr_max/div_final),
    118               'mom': combined_cos(pct_start, *(self.moms if moms is None else moms))}
--> 119     self.fit(n_epoch, cbs=ParamScheduler(scheds)+L(cbs), reset_opt=reset_opt, wd=wd, start_epoch=start_epoch)
    120 
    121 # %% ../../nbs/14_callback.schedule.ipynb 50

[/usr/local/lib/python3.8/dist-packages/fastai/learner.py](https://localhost:8080/#) in fit(self, n_epoch, lr, wd, cbs, reset_opt, start_epoch)
    254             self.opt.set_hypers(lr=self.lr if lr is None else lr)
    255             self.n_epoch = n_epoch
--> 256             self._with_events(self._do_fit, 'fit', CancelFitException, self._end_cleanup)
    257 
    258     def _end_cleanup(self): self.dl,self.xb,self.yb,self.pred,self.loss = None,(None,),(None,),None,None

[/usr/local/lib/python3.8/dist-packages/fastai/learner.py](https://localhost:8080/#) in _with_events(self, f, event_type, ex, final)
    191 
    192     def _with_events(self, f, event_type, ex, final=noop):
--> 193         try: self(f'before_{event_type}');  f()
    194         except ex: self(f'after_cancel_{event_type}')
    195         self(f'after_{event_type}');  final()

[/usr/local/lib/python3.8/dist-packages/fastai/learner.py](https://localhost:8080/#) in _do_fit(self)
    243         for epoch in range(self.n_epoch):
    244             self.epoch=epoch
--> 245             self._with_events(self._do_epoch, 'epoch', CancelEpochException)
    246 
    247     def fit(self, n_epoch, lr=None, wd=None, cbs=None, reset_opt=False, start_epoch=0):

[/usr/local/lib/python3.8/dist-packages/fastai/learner.py](https://localhost:8080/#) in _with_events(self, f, event_type, ex, final)
    193         try: self(f'before_{event_type}');  f()
    194         except ex: self(f'after_cancel_{event_type}')
--> 195         self(f'after_{event_type}');  final()
    196 
    197     def all_batches(self):

[/usr/local/lib/python3.8/dist-packages/fastai/learner.py](https://localhost:8080/#) in __call__(self, event_name)
    169 
    170     def ordered_cbs(self, event): return [cb for cb in self.cbs.sorted('order') if hasattr(cb, event)]
--> 171     def __call__(self, event_name): L(event_name).map(self._call_one)
    172 
    173     def _call_one(self, event_name):

[/usr/local/lib/python3.8/dist-packages/fastcore/foundation.py](https://localhost:8080/#) in map(self, f, gen, *args, **kwargs)
    154     def range(cls, a, b=None, step=None): return cls(range_of(a, b=b, step=step))
    155 
--> 156     def map(self, f, *args, gen=False, **kwargs): return self._new(map_ex(self, f, *args, gen=gen, **kwargs))
    157     def argwhere(self, f, negate=False, **kwargs): return self._new(argwhere(self, f, negate, **kwargs))
    158     def argfirst(self, f, negate=False): return first(i for i,o in self.enumerate() if f(o))

[/usr/local/lib/python3.8/dist-packages/fastcore/basics.py](https://localhost:8080/#) in map_ex(iterable, f, gen, *args, **kwargs)
    838     res = map(g, iterable)
    839     if gen: return res
--> 840     return list(res)
    841 
    842 # %% ../nbs/01_basics.ipynb 336

[/usr/local/lib/python3.8/dist-packages/fastcore/basics.py](https://localhost:8080/#) in __call__(self, *args, **kwargs)
    823             if isinstance(v,_Arg): kwargs[k] = args.pop(v.i)
    824         fargs = [args[x.i] if isinstance(x, _Arg) else x for x in self.pargs] + args[self.maxi+1:]
--> 825         return self.func(*fargs, **kwargs)
    826 
    827 # %% ../nbs/01_basics.ipynb 326

[/usr/local/lib/python3.8/dist-packages/fastai/learner.py](https://localhost:8080/#) in _call_one(self, event_name)
    173     def _call_one(self, event_name):
    174         if not hasattr(event, event_name): raise Exception(f'missing {event_name}')
--> 175         for cb in self.cbs.sorted('order'): cb(event_name)
    176 
    177     def _bn_bias_state(self, with_bias): return norm_bias_params(self.model, with_bias).map(self.opt.state)

[/usr/local/lib/python3.8/dist-packages/fastai/callback/core.py](https://localhost:8080/#) in __call__(self, event_name)
     60             try: res = getcallable(self, event_name)()
     61             except (CancelBatchException, CancelBackwardException, CancelEpochException, CancelFitException, CancelStepException, CancelTrainException, CancelValidException): raise
---> 62             except Exception as e: raise modify_exception(e, f'Exception occured in `{self.__class__.__name__}` when calling event `{event_name}`:\n\t{e.args[0]}', replace=True)
     63         if event_name=='after_fit': self.run=True #Reset self.run to True at each end of fit
     64         return res

[/usr/local/lib/python3.8/dist-packages/fastai/callback/core.py](https://localhost:8080/#) in __call__(self, event_name)
     58         res = None
     59         if self.run and _run:
---> 60             try: res = getcallable(self, event_name)()
     61             except (CancelBatchException, CancelBackwardException, CancelEpochException, CancelFitException, CancelStepException, CancelTrainException, CancelValidException): raise
     62             except Exception as e: raise modify_exception(e, f'Exception occured in `{self.__class__.__name__}` when calling event `{event_name}`:\n\t{e.args[0]}', replace=True)

[/usr/local/lib/python3.8/dist-packages/fastai/callback/tensorboard.py](https://localhost:8080/#) in after_epoch(self)
     74             preds = getcallable(self.loss_func, 'activation')(self.pred)
     75             out = getcallable(self.loss_func, 'decodes')(preds)
---> 76             x,y,its,outs = self.dls.valid.show_results(b, out, show=False, max_n=self.n_preds)
     77             tensorboard_log(x, y, its, outs, self.writer, self.train_iter)
     78 

[/usr/local/lib/python3.8/dist-packages/tsai/data/core.py](https://localhost:8080/#) in show_results(self, b, preds, ctxs, max_n, nrows, ncols, figsize, **kwargs)
    643         p = self.decode_batch((b[0],preds), max_n=max_n)
    644         if figsize is None: figsize = (ncols*6, max_n//ncols*4)
--> 645         if ctxs is None: ctxs = get_grid(min(len(t), nrows*ncols), nrows=None, ncols=ncols, figsize=figsize, **kwargs)
    646         for i,ctx in enumerate(ctxs):
    647             title = f'True: {t[i][1]}\nPred: {p[i][1]}'

[/usr/local/lib/python3.8/dist-packages/fastai/vision/data.py](https://localhost:8080/#) in get_grid(n, nrows, ncols, figsize, double, title, return_fig, flatten, **kwargs)
     34         ncols = int(np.ceil(n/nrows))
     35     if double: ncols*=2 ; n*=2
---> 36     fig,axs = subplots(nrows, ncols, figsize=figsize, **kwargs)
     37     if flatten: axs = [ax if i<n else ax.set_axis_off() for i, ax in enumerate(axs.flatten())][:n]
     38     if title is not None: fig.suptitle(title, weight='bold', size=14)

[/usr/local/lib/python3.8/dist-packages/fastai/torch_core.py](https://localhost:8080/#) in subplots(nrows, ncols, figsize, imsize, suptitle, **kwargs)
     51         h=nrows*imsize if suptitle is None or imsize>2 else nrows*imsize+0.6 #https://github.com/matplotlib/matplotlib/issues/5355
     52         figsize=(ncols*imsize, h)
---> 53     fig,ax = plt.subplots(nrows, ncols, figsize=figsize, **kwargs)
     54     if suptitle is not None: fig.suptitle(suptitle)
     55     if nrows*ncols==1: ax = array([ax])

[/usr/local/lib/python3.8/dist-packages/matplotlib/pyplot.py](https://localhost:8080/#) in subplots(nrows, ncols, sharex, sharey, squeeze, subplot_kw, gridspec_kw, **fig_kw)
   1175 
   1176     """
-> 1177     fig = figure(**fig_kw)
   1178     axs = fig.subplots(nrows=nrows, ncols=ncols, sharex=sharex, sharey=sharey,
   1179                        squeeze=squeeze, subplot_kw=subplot_kw,

[/usr/local/lib/python3.8/dist-packages/matplotlib/pyplot.py](https://localhost:8080/#) in figure(num, figsize, dpi, facecolor, edgecolor, frameon, FigureClass, clear, **kwargs)
    538             dpi = 72
    539 
--> 540         figManager = new_figure_manager(num, figsize=figsize,
    541                                         dpi=dpi,
    542                                         facecolor=facecolor,

[/usr/local/lib/python3.8/dist-packages/matplotlib/backend_bases.py](https://localhost:8080/#) in new_figure_manager(cls, num, *args, **kwargs)
   3355         from matplotlib.figure import Figure
   3356         fig_cls = kwargs.pop('FigureClass', Figure)
-> 3357         fig = fig_cls(*args, **kwargs)
   3358         return cls.new_figure_manager_given_figure(num, fig)
   3359 

TypeError: Exception occured in `TensorBoardCallback` when calling event `after_epoch`:
    __init__() got an unexpected keyword argument 'show'