(This is using the DataBlock API with a couple custom TransformBlocks)
I even tried just overwriting the default “catch all” show_batch as such:
@typedispatch
def show_batch(x, y, samples, ctxs=None, max_n=10, trunc_at=100, **kwargs):
pdb.set_trace()
pass
Never gets called. Instead, when I do a dls.show_batch I get an error like this:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-77-90634fcc3c9e> in <module>
----> 1 dls.show_batch()
~/development/_training/ml/nlp-playground/_libs/fastai2/fastai2/data/core.py in show_batch(self, b, max_n, ctxs, show, **kwargs)
90 if b is None: b = self.one_batch()
91 if not show: return self._pre_show_batch(b, max_n=max_n)
---> 92 show_batch(*self._pre_show_batch(b, max_n=max_n), ctxs=ctxs, max_n=max_n, **kwargs)
93
94 def show_results(self, b, out, max_n=9, ctxs=None, show=True, **kwargs):
~/development/_training/ml/nlp-playground/_libs/fastai2/fastai2/data/core.py in _pre_show_batch(self, b, max_n)
83 b = self.decode(b)
84 if hasattr(b, 'show'): return b,None,None
---> 85 its = self._decode_batch(b, max_n, full=False)
86 if not is_listy(b): b,its = [b],L((o,) for o in its)
87 return detuplify(b[:self.n_inp]),detuplify(b[self.n_inp:]),its
~/development/_training/ml/nlp-playground/_libs/fastai2/fastai2/data/core.py in _decode_batch(self, b, max_n, full)
77 f = self.after_item.decode
78 f = compose(f, partial(getattr(self.dataset,'decode',noop), full = full))
---> 79 return L(batch_to_samples(b, max_n=max_n)).map(f)
80
81 def _pre_show_batch(self, b, max_n=9):
~/development/_training/ml/nlp-playground/_libs/fastcore/fastcore/foundation.py in map(self, f, *args, **kwargs)
360 else f.format if isinstance(f,str)
361 else f.__getitem__)
--> 362 return self._new(map(g, self))
363
364 def filter(self, f, negate=False, **kwargs):
~/development/_training/ml/nlp-playground/_libs/fastcore/fastcore/foundation.py in _new(self, items, *args, **kwargs)
313 @property
314 def _xtra(self): return None
--> 315 def _new(self, items, *args, **kwargs): return type(self)(items, *args, use_list=None, **kwargs)
316 def __getitem__(self, idx): return self._get(idx) if is_indexer(idx) else L(self._get(idx), use_list=None)
317 def copy(self): return self._new(self.items.copy())
~/development/_training/ml/nlp-playground/_libs/fastcore/fastcore/foundation.py in __call__(cls, x, *args, **kwargs)
39 return x
40
---> 41 res = super().__call__(*((x,) + args), **kwargs)
42 res._newchk = 0
43 return res
~/development/_training/ml/nlp-playground/_libs/fastcore/fastcore/foundation.py in __init__(self, items, use_list, match, *rest)
304 if items is None: items = []
305 if (use_list is not None) or not _is_array(items):
--> 306 items = list(items) if use_list else _listify(items)
307 if match is not None:
308 if is_coll(match): match = len(match)
~/development/_training/ml/nlp-playground/_libs/fastcore/fastcore/foundation.py in _listify(o)
240 if isinstance(o, list): return o
241 if isinstance(o, str) or _is_array(o): return [o]
--> 242 if is_iter(o): return list(o)
243 return [o]
244
~/development/_training/ml/nlp-playground/_libs/fastcore/fastcore/foundation.py in __call__(self, *args, **kwargs)
206 if isinstance(v,_Arg): kwargs[k] = args.pop(v.i)
207 fargs = [args[x.i] if isinstance(x, _Arg) else x for x in self.pargs] + args[self.maxi+1:]
--> 208 return self.fn(*fargs, **kwargs)
209
210 # Cell
~/development/_training/ml/nlp-playground/_libs/fastcore/fastcore/utils.py in _inner(x, *args, **kwargs)
339 if order is not None: funcs = funcs.sorted(order)
340 def _inner(x, *args, **kwargs):
--> 341 for f in L(funcs): x = f(x, *args, **kwargs)
342 return x
343 return _inner
~/development/_training/ml/nlp-playground/_libs/fastai2/fastai2/data/core.py in decode(self, o, full)
283 def __iter__(self): return (self[i] for i in range(len(self)))
284 def __repr__(self): return coll_repr(self)
--> 285 def decode(self, o, full=True): return tuple(tl.decode(o_, full=full) for o_,tl in zip(o,tuplify(self.tls, match=o)))
286 def subset(self, i): return type(self)(tls=L(tl.subset(i) for tl in self.tls), n_inp=self.n_inp)
287 def _new(self, items, *args, **kwargs): return super()._new(items, tfms=self.tfms, do_setup=False, **kwargs)
~/development/_training/ml/nlp-playground/_libs/fastai2/fastai2/data/core.py in <genexpr>(.0)
283 def __iter__(self): return (self[i] for i in range(len(self)))
284 def __repr__(self): return coll_repr(self)
--> 285 def decode(self, o, full=True): return tuple(tl.decode(o_, full=full) for o_,tl in zip(o,tuplify(self.tls, match=o)))
286 def subset(self, i): return type(self)(tls=L(tl.subset(i) for tl in self.tls), n_inp=self.n_inp)
287 def _new(self, items, *args, **kwargs): return super()._new(items, tfms=self.tfms, do_setup=False, **kwargs)
~/development/_training/ml/nlp-playground/_libs/fastai2/fastai2/data/core.py in decode(self, o, **kwargs)
219 def __iter__(self): return (self[i] for i in range(len(self)))
220 def show(self, o, **kwargs): return self.tfms.show(o, **kwargs)
--> 221 def decode(self, o, **kwargs): return self.tfms.decode(o, **kwargs)
222 def __call__(self, o, **kwargs): return self.tfms.__call__(o, **kwargs)
223 def overlapping_splits(self): return L(Counter(self.splits.concat()).values()).filter(gt(1))
~/development/_training/ml/nlp-playground/_libs/fastcore/fastcore/transform.py in decode(self, o, full)
195 for f in reversed(self.fs):
196 if self._is_showable(o): return o
--> 197 o = f.decode(o, split_idx=self.split_idx)
198 return o
199
~/development/_training/ml/nlp-playground/_libs/fastcore/fastcore/transform.py in decode(self, x, **kwargs)
71 def name(self): return getattr(self, '_name', _get_name(self))
72 def __call__(self, x, **kwargs): return self._call('encodes', x, **kwargs)
---> 73 def decode (self, x, **kwargs): return self._call('decodes', x, **kwargs)
74 def __repr__(self): return f'{self.name}: {self.encodes} {self.decodes}'
75
~/development/_training/ml/nlp-playground/_libs/fastcore/fastcore/transform.py in _call(self, fn, x, split_idx, **kwargs)
80 def _call(self, fn, x, split_idx=None, **kwargs):
81 if split_idx!=self.split_idx and self.split_idx is not None: return x
---> 82 return self._do_call(getattr(self, fn), x, **kwargs)
83
84 def _do_call(self, f, x, **kwargs):
~/development/_training/ml/nlp-playground/_libs/fastcore/fastcore/transform.py in _do_call(self, f, x, **kwargs)
85 if not _is_tuple(x):
86 return x if f is None else retain_type(f(x, **kwargs), x, f.returns_none(x))
---> 87 res = tuple(self._do_call(f, x_, **kwargs) for x_ in x)
88 return retain_type(res, x)
89
~/development/_training/ml/nlp-playground/_libs/fastcore/fastcore/transform.py in <genexpr>(.0)
85 if not _is_tuple(x):
86 return x if f is None else retain_type(f(x, **kwargs), x, f.returns_none(x))
---> 87 res = tuple(self._do_call(f, x_, **kwargs) for x_ in x)
88 return retain_type(res, x)
89
~/development/_training/ml/nlp-playground/_libs/fastcore/fastcore/transform.py in _do_call(self, f, x, **kwargs)
84 def _do_call(self, f, x, **kwargs):
85 if not _is_tuple(x):
---> 86 return x if f is None else retain_type(f(x, **kwargs), x, f.returns_none(x))
87 res = tuple(self._do_call(f, x_, **kwargs) for x_ in x)
88 return retain_type(res, x)
~/development/_training/ml/nlp-playground/_libs/fastcore/fastcore/dispatch.py in __call__(self, *args, **kwargs)
96 if not f: return args[0]
97 if self.inst is not None: f = MethodType(f, self.inst)
---> 98 return f(*args, **kwargs)
99
100 def __get__(self, inst, owner):
~/development/_training/ml/nlp-playground/_libs/fastai2/fastai2/text/core.py in decodes(self, o)
300 except: return None
301
--> 302 def decodes(self, o): return TitledStr(self.sep.join(o))
303
304 # Cell
TypeError: sequence item 0: expected str instance, Tensor found
This only happens with the DataBlock API. If I use the mid-level API, it works as expected. I can see what it’s doing … but again, I just want my custom show_batch method called where things are properly handled for showing.