Fix inference and test with new tokenizer

src/modes/inference.py

@@ -17,7 +17,6 @@
 def perform_inference(config: Config,
                       model: tf.keras.Model,
                       inference_dataset: tf.data.Dataset,
-                      charlist: List[str],
                       data_manager: DataManager) -> None:
     """
     Performs inference on a given dataset using a specified model and writes
@@ -33,8 +32,6 @@ def perform_inference(config: Config,
         The Keras model to be used for inference.
     inference_dataset : tf.data.Dataset
         The dataset on which inference is to be performed.
-    charlist : List[str]
-        A list of characters used in the model, for decoding predictions.
     data_manager : DataManager
         A data manager object used for retrieving additional information needed
         during inference (e.g., filenames).
@@ -48,7 +45,7 @@ def perform_inference(config: Config,
     results.
     """
 
-    tokenizer = Tokenizer(charlist)
+    tokenizer = data_manager.tokenizer
 
     with open(config["results_file"], "w", encoding="utf-8") as results_file:
         for batch_no, batch in enumerate(inference_dataset):
@@ -62,7 +59,7 @@ def perform_inference(config: Config,
             # Print the predictions and process the CER
             for index, (confidence, prediction) in enumerate(y_pred):
                 # Remove the special characters from the prediction
-                prediction = prediction.strip().replace('', '')
+                prediction = prediction.strip().replace('[MASK]', '')
 
                 # Format the filename
                 filename = data_manager.get_filename('inference',

src/modes/test.py

@@ -21,9 +21,7 @@ def process_batch(batch: Tuple[tf.Tensor, tf.Tensor],
                   prediction_model: tf.keras.Model,
                   tokenizer: Tokenizer,
                   config: Config,
-                  wbs: Optional[Any],
-                  data_manager: DataManager,
-                  chars: List[str]) -> Dict[str, int]:
+                  wbs: Optional[Any]) -> Dict[str, int]:
     """
     Processes a batch of data by predicting, calculating Character Error Rate
     (CER), and handling Word Beam Search (WBS) if enabled.
@@ -43,11 +41,6 @@ def process_batch(batch: Tuple[tf.Tensor, tf.Tensor],
     wbs : Optional[Any]
         An optional Word Beam Search object for advanced decoding, if
         applicable.
-    data_manager : DataManager
-        A data data_manager object for additional operations like
-        normalization.
-    chars : List[str]
-        A list of characters used in the model.
 
     Returns
     -------
@@ -68,7 +61,7 @@ def process_batch(batch: Tuple[tf.Tensor, tf.Tensor],
     # Transpose the predictions for WordBeamSearch
     if wbs:
         predsbeam = tf.transpose(predictions, perm=[1, 0, 2])
-        char_str = handle_wbs_results(predsbeam, wbs, chars)
+        char_str = handle_wbs_results(predsbeam, wbs, tokenizer.token_list)
     else:
         char_str = None
 
@@ -113,7 +106,6 @@ def process_batch(batch: Tuple[tf.Tensor, tf.Tensor],
 def perform_test(config: Config,
                  model: tf.keras.Model,
                  test_dataset: tf.data.Dataset,
-                 charlist: List[str],
                  data_manager: DataManager) -> None:
     """
     Performs test run on a dataset using a given model and calculates various
@@ -128,8 +120,6 @@ def perform_test(config: Config,
         The Keras model to be validated.
     test_dataset : tf.data.Dataset
         The dataset to be used for testing.
-    charlist : List[str]
-        A list of characters used in the model.
     data_manager : DataManager
         A data data_manager object for additional operations like normalization
         and Word Beam Search setup.
@@ -143,11 +133,10 @@ def perform_test(config: Config,
     """
 
     logging.info("Performing test...")
-
-    tokenizer = Tokenizer(charlist)
+    tokenizer = data_manager.tokenizer
 
     # Setup WordBeamSearch if needed
-    wbs = setup_word_beam_search(config, charlist) \
+    wbs = setup_word_beam_search(config, tokenizer.token_list) \
         if config["corpus_file"] else None
 
     # Initialize the counters
@@ -160,7 +149,7 @@ def perform_test(config: Config,
 
         logging.info("Batch %s/%s", batch_no + 1, len(test_dataset))
         batch_counter = process_batch((X, y_true), model, tokenizer,
-                                      config, wbs, data_manager, charlist)
+                                      config, wbs)
 
         # Update the total counter
         for key, value in batch_counter.items():