fairseq/models/fairseq_encoder.py

Survived

Mutant 2097

--- fairseq/models/fairseq_encoder.py
+++ fairseq/models/fairseq_encoder.py
@@ -9,7 +9,7 @@
 from torch import Tensor
 
 EncoderOut = NamedTuple(
-    "EncoderOut",
+    "XXEncoderOutXX",
     [
         ("encoder_out", Tensor),  # T x B x C
         ("encoder_padding_mask", Optional[Tensor]),  # B x T

Mutant 2098

--- fairseq/models/fairseq_encoder.py
+++ fairseq/models/fairseq_encoder.py
@@ -11,7 +11,7 @@
 EncoderOut = NamedTuple(
     "EncoderOut",
     [
-        ("encoder_out", Tensor),  # T x B x C
+        ("XXencoder_outXX", Tensor),  # T x B x C
         ("encoder_padding_mask", Optional[Tensor]),  # B x T
         ("encoder_embedding", Optional[Tensor]),  # B x T x C
         ("encoder_states", Optional[List[Tensor]]),  # List[T x B x C]

Mutant 2099

--- fairseq/models/fairseq_encoder.py
+++ fairseq/models/fairseq_encoder.py
@@ -12,7 +12,7 @@
     "EncoderOut",
     [
         ("encoder_out", Tensor),  # T x B x C
-        ("encoder_padding_mask", Optional[Tensor]),  # B x T
+        ("XXencoder_padding_maskXX", Optional[Tensor]),  # B x T
         ("encoder_embedding", Optional[Tensor]),  # B x T x C
         ("encoder_states", Optional[List[Tensor]]),  # List[T x B x C]
         ("src_tokens", Optional[Tensor]),  # B x T

Mutant 2100

--- fairseq/models/fairseq_encoder.py
+++ fairseq/models/fairseq_encoder.py
@@ -13,7 +13,7 @@
     [
         ("encoder_out", Tensor),  # T x B x C
         ("encoder_padding_mask", Optional[Tensor]),  # B x T
-        ("encoder_embedding", Optional[Tensor]),  # B x T x C
+        ("XXencoder_embeddingXX", Optional[Tensor]),  # B x T x C
         ("encoder_states", Optional[List[Tensor]]),  # List[T x B x C]
         ("src_tokens", Optional[Tensor]),  # B x T
         ("src_lengths", Optional[Tensor]),  # B x 1

Mutant 2101

--- fairseq/models/fairseq_encoder.py
+++ fairseq/models/fairseq_encoder.py
@@ -14,7 +14,7 @@
         ("encoder_out", Tensor),  # T x B x C
         ("encoder_padding_mask", Optional[Tensor]),  # B x T
         ("encoder_embedding", Optional[Tensor]),  # B x T x C
-        ("encoder_states", Optional[List[Tensor]]),  # List[T x B x C]
+        ("XXencoder_statesXX", Optional[List[Tensor]]),  # List[T x B x C]
         ("src_tokens", Optional[Tensor]),  # B x T
         ("src_lengths", Optional[Tensor]),  # B x 1
     ],

Mutant 2102

--- fairseq/models/fairseq_encoder.py
+++ fairseq/models/fairseq_encoder.py
@@ -15,7 +15,7 @@
         ("encoder_padding_mask", Optional[Tensor]),  # B x T
         ("encoder_embedding", Optional[Tensor]),  # B x T x C
         ("encoder_states", Optional[List[Tensor]]),  # List[T x B x C]
-        ("src_tokens", Optional[Tensor]),  # B x T
+        ("XXsrc_tokensXX", Optional[Tensor]),  # B x T
         ("src_lengths", Optional[Tensor]),  # B x 1
     ],
 )

Mutant 2103

--- fairseq/models/fairseq_encoder.py
+++ fairseq/models/fairseq_encoder.py
@@ -16,7 +16,7 @@
         ("encoder_embedding", Optional[Tensor]),  # B x T x C
         ("encoder_states", Optional[List[Tensor]]),  # List[T x B x C]
         ("src_tokens", Optional[Tensor]),  # B x T
-        ("src_lengths", Optional[Tensor]),  # B x 1
+        ("XXsrc_lengthsXX", Optional[Tensor]),  # B x 1
     ],
 )
 

Mutant 2104

--- fairseq/models/fairseq_encoder.py
+++ fairseq/models/fairseq_encoder.py
@@ -26,7 +26,7 @@
 
     def __init__(self, dictionary):
         super().__init__()
-        self.dictionary = dictionary
+        self.dictionary = None
 
     def forward(self, src_tokens, src_lengths=None, **kwargs):
         """

Mutant 2105

--- fairseq/models/fairseq_encoder.py
+++ fairseq/models/fairseq_encoder.py
@@ -52,7 +52,6 @@
         else:
             return self.forward_non_torchscript(net_input)
 
-    @torch.jit.unused
     def forward_non_torchscript(self, net_input: Dict[str, Tensor]):
         encoder_input = {
             k: v