diff --git a/embedding_converter/src/dataset.py b/embedding_converter/src/dataset.py
index 79c25a4..21057a4 100644
--- a/embedding_converter/src/dataset.py
+++ b/embedding_converter/src/dataset.py
@@ -9,10 +9,10 @@ from .types import Batch
 
 
 class StaticDataset(Dataset[Tensor]):
-	def __init__(self, config : ConfigParser) -> None:
+	def __init__(self, config_parser : ConfigParser) -> None:
 		self.config =\
 		{
-			'file_pattern': config.get('training.dataset', 'file_pattern')
+			'file_pattern': config_parser.get('training.dataset', 'file_pattern')
 		}
 		self.file_paths = glob.glob(self.config.get('file_pattern'))
 		self.transforms = self.compose_transforms()
diff --git a/embedding_converter/src/exporting.py b/embedding_converter/src/exporting.py
index 4222295..3c76a4f 100644
--- a/embedding_converter/src/exporting.py
+++ b/embedding_converter/src/exporting.py
@@ -1,11 +1,11 @@
-import configparser
-from os import makedirs
+import os
+from configparser import ConfigParser
 
 import torch
 
 from .training import EmbeddingConverterTrainer
 
-CONFIG_PARSER = configparser.ConfigParser()
+CONFIG_PARSER = ConfigParser()
 CONFIG_PARSER.read('config.ini')
 
 
@@ -19,7 +19,7 @@ def export() -> None:
 		'opset_version': CONFIG_PARSER.getint('exporting', 'opset_version')
 	}
 
-	makedirs(config.get('directory_path'), exist_ok = True) # type:ignore[arg-type]
+	os.makedirs(config.get('directory_path'), exist_ok = True) # type:ignore[arg-type]
 	model = EmbeddingConverterTrainer.load_from_checkpoint(config.get('source_path'), map_location = 'cpu')
 	model.eval()
 	model.ir_version = torch.tensor(config.get('ir_version'))