Open sgbaird opened 1 year ago
I'm noticing the following convention for Dataset:
Dataset
https://github.com/aspuru-guzik-group/olympus/blob/bbeb991c4c1929474a0b1a4435a5eed566d30542/src/olympus/datasets/dataset.py#L42
(i.e., plural target_ids)
target_ids
When trying to pass multiple list entries to target_ids, I get:
--------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In[44], line 1 ----> 1 emulator.train() File c:\Users\sterg\Miniconda3\envs\sdl-demo\lib\site-packages\olympus\emulators\emulator.py:354, in Emulator.train(self, plot, retrain) 347 # Train 348 Logger.log( 349 ">>> Training model on {0:.0%} of the dataset, testing on {1:.0%}...".format( 350 (1 - self.dataset.test_frac), self.dataset.test_frac 351 ), 352 "INFO", 353 ) --> 354 mdl_train_r2, mdl_test_r2, mdl_train_rmsd, mdl_test_rmsd = self.model.train( 355 train_features=train_features_scaled, 356 train_targets=train_targets_scaled, 357 valid_features=test_features_scaled, 358 valid_targets=test_targets_scaled, 359 model_path=model_path, 360 plot=plot, 361 ) 363 # write file to indicate training is complete and add R2 in there 364 with open(f"{model_path}/training_completed.info", "w") as content: File c:\Users\sterg\Miniconda3\envs\sdl-demo\lib\site-packages\olympus\models\wrapper_tensorflow_model\wrapper_tensorflow_model.py:159, in WrapperTensorflowModel.train(self, train_features, train_targets, valid_features, valid_targets, model_path, plot) 154 losses.append(loss) 156 if epoch % self.pred_int == 0: 157 158 # make a prediction on the validation set --> 159 valid_pred = self.predict( 160 features=valid_features[valid_indices], num_samples=10 161 ) 162 valid_r2 = r2_score(valid_targets[valid_indices], valid_pred) 163 valid_rmsd = np.sqrt( 164 mean_squared_error(valid_targets[valid_indices], valid_pred) 165 ) File c:\Users\sterg\Miniconda3\envs\sdl-demo\lib\site-packages\olympus\models\wrapper_tensorflow_model\wrapper_tensorflow_model.py:282, in WrapperTensorflowModel.predict(self, features, num_samples) 278 for _ in range(num_samples): 279 predic = self.sess.run( 280 self.y_pred, feed_dict={self.tf_x: X_test_batch} 281 ) --> 282 pred[_, start:stop] = predic[:size] 284 pred = np.mean(pred, axis=0) 285 return pred ValueError: could not broadcast input array from shape (50,8) into shape (50,1)
Just noticed the new manuscript. I'm guessing the changes mentioned in the manuscript will be incorporated here soon https://chemrxiv.org/engage/chemrxiv/article-details/6464ae0afb40f6b3eebaab70.
I'm noticing the following convention for
Dataset
:https://github.com/aspuru-guzik-group/olympus/blob/bbeb991c4c1929474a0b1a4435a5eed566d30542/src/olympus/datasets/dataset.py#L42
(i.e., plural
target_ids
)When trying to pass multiple list entries to
target_ids
, I get: