add model architecture parametrization

config.yaml

@@ -30,10 +30,11 @@ dataloader:
   batch_size: 64
 
 model:
+  architecture: BiLSTM
   embedding:
     embedding_dim: 128
   rnn:
-    rnn_unit: nn.LSTM
+    rnn_unit: LSTM  # GRU, RNN
     hidden_size: 256
     num_layers: 1
     dropout: 0

main.py

@@ -8,7 +8,6 @@
 from torch.utils.data import DataLoader
 
 from pytorch_ner.dataset import NERCollator, NERDataset
-from pytorch_ner.nn_modules.architecture import BiLSTM
 from pytorch_ner.nn_modules.embedding import Embedding
 from pytorch_ner.nn_modules.linear import LinearHead
 from pytorch_ner.nn_modules.rnn import DynamicRNN
@@ -19,6 +18,7 @@
 )
 from pytorch_ner.save import save_model
 from pytorch_ner.train import train
+from pytorch_ner.utils import str_to_class
 
 
 def main(path_to_config: str):
@@ -148,10 +148,11 @@ def main(path_to_config: str):
     )
 
     rnn_layer = DynamicRNN(
-        rnn_unit=eval(config["model"]["rnn"]["rnn_unit"]),  # TODO: fix eval
-        input_size=config["model"]["embedding"][
-            "embedding_dim"
-        ],  # reference to embedding_dim
+        rnn_unit=str_to_class(
+            module_name="torch.nn",
+            class_name=config["model"]["rnn"]["rnn_unit"],
+        ),
+        input_size=config["model"]["embedding"]["embedding_dim"],  # ref to emb_dim
         hidden_size=config["model"]["rnn"]["hidden_size"],
         num_layers=config["model"]["rnn"]["num_layers"],
         dropout=config["model"]["rnn"]["dropout"],
@@ -169,9 +170,12 @@ def main(path_to_config: str):
         ),
     )
 
-    # TODO: add model architecture in config
     # TODO: add attention if needed
-    model = BiLSTM(
+    model_class = str_to_class(
+        module_name="pytorch_ner.nn_modules.architecture",
+        class_name=config["model"]["architecture"],
+    )
+    model = model_class(
         embedding_layer=embedding_layer,
         rnn_layer=rnn_layer,
         linear_head=linear_head,

pytorch_ner/utils.py

@@ -1,3 +1,4 @@
+import importlib
 import os
 import random
 import shutil
@@ -44,3 +45,16 @@ def rmdir(path: str):
 
     if os.path.exists(path):
         shutil.rmtree(path)
+
+
+def str_to_class(module_name, class_name):
+    """
+    Convert string to Python class object.
+    https://stackoverflow.com/questions/1176136/convert-string-to-python-class-object
+    """
+
+    # load the module, will raise ImportError if module cannot be loaded
+    module = importlib.import_module(module_name)
+    # get the class, will raise AttributeError if class cannot be found
+    cls = getattr(module, class_name)
+    return cls

tests/test_onnx.py

@@ -1,6 +1,7 @@
+from test_nn_modules.test_architecture import model_bilstm as model
+
 from pytorch_ner.onnx import onnx_export_and_check
 from pytorch_ner.utils import mkdir
-from tests.test_nn_modules.test_architecture import model_bilstm as model
 
 path_to_save = "models/model.onnx"
 mkdir("models")