Rename teacher_forcing_scheduler to label_noise_scheduler

dan/manager/training.py

@@ -1116,26 +1116,26 @@ class Manager(OCRManager):
         ):
             error_rate = self.params["training_params"]["teacher_forcing_error_rate"]
             simulated_y_pred, y_len = self.add_label_noise(y, y_len, error_rate)
-        elif "teacher_forcing_scheduler" in self.params["training_params"]:
+        elif "label_noise_scheduler" in self.params["training_params"]:
             error_rate = (
-                self.params["training_params"]["teacher_forcing_scheduler"][
+                self.params["training_params"]["label_noise_scheduler"][
                     "min_error_rate"
                 ]
                 + min(
                     self.latest_step,
-                    self.params["training_params"]["teacher_forcing_scheduler"][
+                    self.params["training_params"]["label_noise_scheduler"][
                         "total_num_steps"
                     ],
                 )
                 * (
-                    self.params["training_params"]["teacher_forcing_scheduler"][
+                    self.params["training_params"]["label_noise_scheduler"][
                         "max_error_rate"
                     ]
-                    - self.params["training_params"]["teacher_forcing_scheduler"][
+                    - self.params["training_params"]["label_noise_scheduler"][
                         "min_error_rate"
                     ]
                 )
-                / self.params["training_params"]["teacher_forcing_scheduler"][
+                / self.params["training_params"]["label_noise_scheduler"][
                     "total_num_steps"
                 ]
             )

dan/ocr/document/train.py

@@ -223,7 +223,7 @@ def get_config():
             "force_cpu": False,  # True for debug purposes
             "max_char_prediction": 1000,  # max number of token prediction
             # Keep teacher forcing rate to 20% during whole training
-            "teacher_forcing_scheduler": {
+            "label_noise_scheduler": {
                 "min_error_rate": 0.2,
                 "max_error_rate": 0.2,
                 "total_num_steps": 5e4,

docs/usage/train/parameters.md

@@ -270,9 +270,9 @@ The following configuration can be used by default. It must be defined in `datas
 | `training_params.train_metrics`                             | List of metrics to compute during validation.                               | `list`       | `["cer", "wer", "wer_no_punct"]`            |
 | `training_params.force_cpu`                                 | Whether to train on CPU (for debugging).                                    | `bool`       | `False`                                     |
 | `training_params.max_char_prediction`                       | Maximum number of characters to predict.                                    | `int`        | `1000`                                      |
-| `training_params.teacher_forcing_scheduler.min_error_rate`  | Minimum ratio of teacher forcing.                                           | `float`      | `0.2`                                       |
-| `training_params.teacher_forcing_scheduler.max_error_rate`  | Maximum ratio of teacher forcing.                                           | `float`      | `0.2`                                       |
-| `training_params.teacher_forcing_scheduler.total_num_steps` | Number of steps before stopping teacher forcing.                            | `float`      | `5e4`                                       |
+| `training_params.label_noise_scheduler.min_error_rate`  | Minimum ratio of teacher forcing.                                           | `float`      | `0.2`                                       |
+| `training_params.label_noise_scheduler.max_error_rate`  | Maximum ratio of teacher forcing.                                           | `float`      | `0.2`                                       |
+| `training_params.label_noise_scheduler.total_num_steps` | Number of steps before stopping teacher forcing.                            | `float`      | `5e4`                                       |
 
 
 ## MLFlow logging

tests/conftest.py

@@ -158,7 +158,7 @@ def training_config():
             "force_cpu": True,  # True for debug purposes
             "max_char_prediction": 30,  # max number of token prediction
             # Keep teacher forcing rate to 20% during whole training
-            "teacher_forcing_scheduler": {
+            "label_noise_scheduler": {
                 "min_error_rate": 0.2,
                 "max_error_rate": 0.2,
                 "total_num_steps": 5e4,