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@ -76,6 +76,7 @@ class Learner(Process):
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# sel.max_epoc
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self.logger = None
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if 'logger' in self.store :
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# self.store['logger']['context'] = 'write'
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self.logger = transport.factory.instance(**self.store['logger'])
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self.autopilot = False #-- to be set by caller
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self._initStateSpace()
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@ -243,7 +244,7 @@ class Trainer(Learner):
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#
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# @TODO Log that the dataset was empty or not statistically relevant
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return
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_space,_matrix = self._encoder.convert()
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_space,_matrix = self._encoder._convert()
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_args = self.network_args
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if self.gpu :
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@ -341,7 +342,7 @@ class Generator (Learner):
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# The values will be returned because we have provided _map information from the constructor
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#
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values,_matrix = self._encoder.convert()
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values,_matrix = self._encoder._convert()
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_args = self.network_args
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_args['map'] = self._map
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_args['values'] = np.array(values)
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@ -353,7 +354,7 @@ class Generator (Learner):
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gHandler = gan.Predict(**_args)
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gHandler.load_meta(columns=None)
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_iomatrix = gHandler.apply()
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_candidates= [ self._encoder.revert(matrix=_item) for _item in _iomatrix]
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_candidates= [ self._encoder._revert(matrix=_item) for _item in _iomatrix]
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_size = np.sum([len(_item) for _item in _iomatrix])
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_log = {'action':'io-data','input':{'candidates':len(_candidates),'rows':int(_size)}}
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