diff --git a/Project/simple_approach/Continous_Learner.ipynb b/Project/simple_approach/Continous_Learner.ipynb index 09ed913..8514c2c 100644 --- a/Project/simple_approach/Continous_Learner.ipynb +++ b/Project/simple_approach/Continous_Learner.ipynb @@ -144,7 +144,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d018a59d95fe45f2ae7be013a49b5900", + "model_id": "a4899ee1720f4db4a136a96657f3283a", "version_major": 2, "version_minor": 0 }, @@ -495,7 +495,7 @@ " p = progress_indicator()\n", " \n", " tr = stl.trainer(sdm=sdm, pm=pm)\n", - " tr.fit(progress_callback=p.update, batch_size=batch_size, n_epochs=n_epochs)\n", + " tr.fit(progress_callback=p.update, batch_size=batch_size if batch_size > 0 else None, n_epochs=n_epochs)\n", " \n", "\n", "# linking:\n", diff --git a/Project/simple_approach/simple_twitter_learning.py b/Project/simple_approach/simple_twitter_learning.py index ee69669..73ebd5e 100644 --- a/Project/simple_approach/simple_twitter_learning.py +++ b/Project/simple_approach/simple_twitter_learning.py @@ -633,14 +633,15 @@ class trainer(object): named_steps[s].fit = lambda self, X, y=None: self named_steps[s].fit_transform = named_steps[s].transform - for k in keras_batch_fitting_layer: - # forcing batch fitting on keras - disabled_keras_fits[k]=named_steps[k].fit + if batch_size is not None: + for k in keras_batch_fitting_layer: + # forcing batch fitting on keras + disabled_keras_fits[k]=named_steps[k].fit - named_steps[k].fit = lambda X, y: named_steps[k].train_on_batch(to_dense_if_sparse(X), y) # ← why has keras no sparse support on batch progressing!?!?! - + named_steps[k].fit = lambda X, y: named_steps[k].train_on_batch(to_dense_if_sparse(X), y) # ← why has keras no sparse support on batch progressing!?!?! + if batch_size is None: - self.pm.fit(X = self.sdm.X[:max_size], y = self.sdm.y[:max_size]) + self.pm.fit(X = self.sdm.X[:max_size], y = self.sdm.y[:max_size], validation_split=0.1, epochs=n_epochs) else: n = len(self.sdm.X) // batch_size for i in range(n_epochs): @@ -658,8 +659,9 @@ class trainer(object): named_steps[s].fit = disabled_fits[s] named_steps[s].fit_transform = disabled_fit_transforms[s] - for k in keras_batch_fitting_layer: - named_steps[k].fit = disabled_keras_fits[k] + if batch_size is not None: + for k in keras_batch_fitting_layer: + named_steps[k].fit = disabled_keras_fits[k] def test(self): '''