057: Code cleaning

3 files changed, 13 insertions, 26 deletions

diff --git a/transquest/algo/sentence_level/siamesetransquest/evaluation/embedding_similarity_evaluator.py b/transquest/algo/sentence_level/siamesetransquest/evaluation/embedding_similarity_evaluator.py
index b9b6657..74985b8 100644
--- a/transquest/algo/sentence_level/siamesetransquest/evaluation/embedding_similarity_evaluator.py
+++ b/transquest/algo/sentence_level/siamesetransquest/evaluation/embedding_similarity_evaluator.py
@@ -51,7 +51,7 @@ class EmbeddingSimilarityEvaluator(SentenceEvaluator):
         self.batch_size = batch_size
         if show_progress_bar is None:
             show_progress_bar = (
-                        logger.getEffectiveLevel() == logging.INFO or logger.getEffectiveLevel() == logging.DEBUG)
+                    logger.getEffectiveLevel() == logging.INFO or logger.getEffectiveLevel() == logging.DEBUG)
         self.show_progress_bar = show_progress_bar
 
         self.csv_file = "similarity_evaluation" + ("_" + name if name else '') + "_results.csv"
diff --git a/transquest/algo/sentence_level/siamesetransquest/models.py b/transquest/algo/sentence_level/siamesetransquest/models.py
index ab70622..a6a3e6c 100644
--- a/transquest/algo/sentence_level/siamesetransquest/models.py
+++ b/transquest/algo/sentence_level/siamesetransquest/models.py
@@ -1,4 +1,3 @@
-from transformers import AutoModel, AutoTokenizer, AutoConfig
 import json
 import logging
 import math
@@ -17,10 +16,11 @@ from torch import nn, Tensor, device
 from torch.optim.optimizer import Optimizer
 from torch.utils.data import DataLoader
 from tqdm.autonotebook import trange
+from transformers import AutoModel, AutoTokenizer, AutoConfig
 
+from transquest.algo.sentence_level.siamesetransquest.evaluation.sentence_evaluator import SentenceEvaluator
 from transquest.algo.sentence_level.siamesetransquest.model_args import SiameseTransQuestArgs
 from transquest.algo.sentence_level.siamesetransquest.util import batch_to_device
-from transquest.algo.sentence_level.siamesetransquest.evaluation.sentence_evaluator import SentenceEvaluator
 
 logger = logging.getLogger(__name__)
 
@@ -557,7 +557,6 @@ class SiameseTransformer(nn.Sequential):
         else:
             return sum([len(t) for t in text])  # Sum of length of individual strings
 
-
     def fit(self,
             train_objectives: Iterable[Tuple[DataLoader, nn.Module]],
             evaluator: SentenceEvaluator = None,
@@ -818,4 +817,3 @@ class SiameseTransformer(nn.Sequential):
         Property to set the maximal input sequence length for the model. Longer inputs will be truncated.
         """
         self._first_module().max_seq_length = value
-
diff --git a/transquest/algo/sentence_level/siamesetransquest/run_model.py b/transquest/algo/sentence_level/siamesetransquest/run_model.py
index 91fccb7..246bf4b 100644
--- a/transquest/algo/sentence_level/siamesetransquest/run_model.py
+++ b/transquest/algo/sentence_level/siamesetransquest/run_model.py
@@ -1,26 +1,19 @@
 import logging
 import math
-import os
 import random
 
-
 import numpy as np
 import torch
 from sklearn.metrics.pairwise import paired_cosine_distances
-
-
 from torch.utils.data import DataLoader
 
-
 from transquest.algo.sentence_level.siamesetransquest.evaluation.embedding_similarity_evaluator import \
     EmbeddingSimilarityEvaluator
 from transquest.algo.sentence_level.siamesetransquest.losses.cosine_similarity_loss import CosineSimilarityLoss
 from transquest.algo.sentence_level.siamesetransquest.model_args import SiameseTransQuestArgs
 from transquest.algo.sentence_level.siamesetransquest.models import SiameseTransformer
-
 from transquest.algo.sentence_level.siamesetransquest.readers.input_example import InputExample
 
-
 logger = logging.getLogger(__name__)
 
 
@@ -89,17 +82,13 @@ class SiameseTransQuestModel:
         warmup_steps = math.ceil(len(train_dataloader) * self.args.num_train_epochs * 0.1)
 
         self.model.fit(train_objectives=[(train_dataloader, train_loss)],
-                 evaluator=evaluator,
-                 epochs=self.args.num_train_epochs,
-                 evaluation_steps=self.args.evaluate_during_training_steps,
-                 optimizer_params={'lr': self.args.learning_rate,
-                                   'eps': self.args.adam_epsilon,
-                                   'correct_bias': False},
-                 warmup_steps=warmup_steps,
-                 weight_decay=self.args.weight_decay,
-                 max_grad_norm=self.args.max_grad_norm,
-                 output_path=self.args.best_model_dir)
-
-
-
-
+                       evaluator=evaluator,
+                       epochs=self.args.num_train_epochs,
+                       evaluation_steps=self.args.evaluate_during_training_steps,
+                       optimizer_params={'lr': self.args.learning_rate,
+                                         'eps': self.args.adam_epsilon,
+                                         'correct_bias': False},
+                       warmup_steps=warmup_steps,
+                       weight_decay=self.args.weight_decay,
+                       max_grad_norm=self.args.max_grad_norm,
+                       output_path=self.args.best_model_dir)