Rename MLP to LogisticRegression (#44)

castorini · Nov 2, 2019 · c602b82 · c602b82
1 parent d2dba11
commit c602b82
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Showing 4 changed files with 5 additions and 6 deletions.
diff --git a/models/mlp/__init__.py → models/lr/__init__.py b/models/mlp/__init__.py → models/lr/__init__.py
diff --git a/models/mlp/__main__.py → models/lr/__main__.py b/models/mlp/__main__.py → models/lr/__main__.py
@@ -13,11 +13,10 @@
 from datasets.bow_processors.imdb_processor import IMDBProcessor
 from datasets.bow_processors.reuters_processor import ReutersProcessor
 from datasets.bow_processors.yelp2014_processor import Yelp2014Processor
-from models.mlp.args import get_args
-from models.mlp.model import MLP
+from models.lr.args import get_args
+from models.lr.model import LogisticRegression
 
 # String templates for logging results
-
 LOG_HEADER = 'Split  Dev/Acc.  Dev/Pr.  Dev/Re.   Dev/F1   Dev/Loss'
 LOG_TEMPLATE = ' '.join('{:>5s},{:>9.4f},{:>8.4f},{:8.4f},{:8.4f},{:10.4f}'.split(','))
 
@@ -72,7 +71,7 @@ def evaluate_split(model, vectorizer, processor, args, split='dev'):
         save_path = os.path.join(args.save_path, dataset_map[args.dataset].NAME)
         os.makedirs(save_path, exist_ok=True)
 
-    model = MLP(args)
+    model = LogisticRegression(args)
     model.to(device)
 
     if n_gpu > 1:

diff --git a/models/mlp/args.py → models/lr/args.py b/models/mlp/args.py → models/lr/args.py
@@ -12,7 +12,7 @@ def get_args():
     parser.add_argument('--epoch-decay', type=int, default=15)
     parser.add_argument('--weight-decay', type=float, default=0)
 
-    parser.add_argument('--save-path', type=str, default=os.path.join('model_checkpoints', 'mlp'))
+    parser.add_argument('--save-path', type=str, default=os.path.join('model_checkpoints', 'lr'))
     parser.add_argument('--resume-snapshot', type=str)
     parser.add_argument('--trained-model', type=str)
 

diff --git a/models/mlp/model.py → models/lr/model.py b/models/mlp/model.py → models/lr/model.py
@@ -2,7 +2,7 @@
 import torch.nn as nn
 
 
-class MLP(nn.Module):
+class LogisticRegression(nn.Module):
 
     def __init__(self, config):
         super().__init__()