different weight for masked/unmasked region

egs/librispeech/ASR/pruned_transducer_stateless6/model.py

@@ -23,7 +23,7 @@ from scaling import ScaledLinear
 
 from icefall.utils import add_sos
 
-from quantization.prediction import JointCodebookLoss
+from multi_quantization.prediction import JointCodebookLoss
 
 
 class Transducer(nn.Module):
@@ -41,6 +41,8 @@ class Transducer(nn.Module):
         joiner_dim: int,
         vocab_size: int,
         num_codebooks: int = 0,
+        masked_scale: float = 1.0,
+        unmasked_scale: float = 1.0,
     ):
         """
         Args:
@@ -60,6 +62,10 @@ class Transducer(nn.Module):
             contains unnormalized probs, i.e., not processed by log-softmax.
           num_codebooks:
             Used by distillation loss.
+          masked_scale:
+            scale of codebook loss of masked area.
+          unmasked_scale:
+            scale of codebook loss of unmasked area.
         """
         super().__init__()
         assert isinstance(encoder, EncoderInterface), type(encoder)
@@ -79,6 +85,8 @@ class Transducer(nn.Module):
                 num_codebooks=num_codebooks,
                 reduction="none",
             )
+        self.masked_scale = masked_scale
+        self.unmasked_scale = unmasked_scale
 
     def forward(
         self,
@@ -91,7 +99,6 @@ class Transducer(nn.Module):
         warmup: float = 1.0,
         codebook_indexes: torch.Tensor = None,
         time_masked_area: torch.Tensor = None,
-        masked_scale: float = 1.0,
     ) -> torch.Tensor:
         """
         Args:
@@ -119,9 +126,6 @@ class Transducer(nn.Module):
             codebook_indexes extracted from a teacher model.
           time_masked_area:
             masked area by SpecAugment, 1 represents masked.
-          masked_scale:
-            scale of codebook loss of masked area.
-            the unmasked_scale = 1 - masked_scale
         Returns:
           Return the transducer loss.
 
@@ -162,7 +166,8 @@ class Transducer(nn.Module):
             masked_loss = (time_masked_area * codebook_loss).sum()
             unmasked_loss = (~time_masked_area * codebook_loss).sum()
             codebook_loss = (
-                masked_scale * masked_loss + (1 - masked_scale) * unmasked_loss
+                self.masked_scale * masked_loss
+                + self.unmasked_scale * unmasked_loss
             )
         else:
             # when codebook index is not available.

egs/librispeech/ASR/pruned_transducer_stateless6/train.py

@@ -177,6 +177,18 @@ def get_parser():
         changed.""",
     )
 
+    parser.add_argument(
+        "--masked-scale",
+        type=float,
+        default=1.0,
+    )
+
+    parser.add_argument(
+        "--unmasked-scale",
+        type=float,
+        default=1.0,
+    )
+
     parser.add_argument(
         "--lr-batches",
         type=float,
@@ -378,6 +390,8 @@ def get_params() -> AttributeDict:
             # two successive codebook_index are concatenated together.
             # Detailed in function Transducer::concat_sucessive_codebook_indexes.
             "num_codebooks": 16,  # used to construct distillation loss
+            "masked_scale": 1.0,
+            "unmasked_scale": 1.0,
         }
     )
 
@@ -436,6 +450,8 @@ def get_transducer_model(params: AttributeDict) -> nn.Module:
         num_codebooks=params.num_codebooks
         if params.enable_distiallation
         else 0,
+        masked_scale=params.masked_scale,
+        unmasked_scale=params.unmasked_scale,
     )
     return model
 
@@ -1090,7 +1106,9 @@ def main():
     parser = get_parser()
     LibriSpeechAsrDataModule.add_arguments(parser)
     args = parser.parse_args()
-    args.exp_dir = Path(args.exp_dir)
+    args.exp_dir = Path(
+        f"{args.exp_dir}-masked_scale-{args.masked_scale}-un-{args.unmasked_scale}-{args.spec_aug_max_frames_mask_fraction}"
+    )
 
     world_size = args.world_size
     assert world_size >= 1