fairseq/models/nat/iterative_nonautoregressive_transformer.py

Killed 4 out of 13 mutants

Survived

Survived mutation testing. These mutants show holes in your test suite.

Mutant 2213

--- fairseq/models/nat/iterative_nonautoregressive_transformer.py
+++ fairseq/models/nat/iterative_nonautoregressive_transformer.py
@@ -9,7 +9,7 @@
 from fairseq.models.nat import NATransformerModel
 
 
-def _sequential_poisoning(s, V, beta=0.33, bos=2, eos=3, pad=1):
+def _sequential_poisoning(s, V, beta=1.33, bos=2, eos=3, pad=1):
     # s: input batch
     # V: vocabulary size
     rand_words = torch.randint(low=4, high=V, size=s.size(), device=s.device)

Mutant 2214

--- fairseq/models/nat/iterative_nonautoregressive_transformer.py
+++ fairseq/models/nat/iterative_nonautoregressive_transformer.py
@@ -9,7 +9,7 @@
 from fairseq.models.nat import NATransformerModel
 
 
-def _sequential_poisoning(s, V, beta=0.33, bos=2, eos=3, pad=1):
+def _sequential_poisoning(s, V, beta=0.33, bos=3, eos=3, pad=1):
     # s: input batch
     # V: vocabulary size
     rand_words = torch.randint(low=4, high=V, size=s.size(), device=s.device)

Mutant 2215

--- fairseq/models/nat/iterative_nonautoregressive_transformer.py
+++ fairseq/models/nat/iterative_nonautoregressive_transformer.py
@@ -9,7 +9,7 @@
 from fairseq.models.nat import NATransformerModel
 
 
-def _sequential_poisoning(s, V, beta=0.33, bos=2, eos=3, pad=1):
+def _sequential_poisoning(s, V, beta=0.33, bos=2, eos=4, pad=1):
     # s: input batch
     # V: vocabulary size
     rand_words = torch.randint(low=4, high=V, size=s.size(), device=s.device)

Mutant 2216

--- fairseq/models/nat/iterative_nonautoregressive_transformer.py
+++ fairseq/models/nat/iterative_nonautoregressive_transformer.py
@@ -9,7 +9,7 @@
 from fairseq.models.nat import NATransformerModel
 
 
-def _sequential_poisoning(s, V, beta=0.33, bos=2, eos=3, pad=1):
+def _sequential_poisoning(s, V, beta=0.33, bos=2, eos=3, pad=2):
     # s: input batch
     # V: vocabulary size
     rand_words = torch.randint(low=4, high=V, size=s.size(), device=s.device)

Mutant 2217

--- fairseq/models/nat/iterative_nonautoregressive_transformer.py
+++ fairseq/models/nat/iterative_nonautoregressive_transformer.py
@@ -43,7 +43,7 @@
     return s
 
 
-def gumbel_noise(input, TINY=1e-8):
+def gumbel_noise(input, TINY=1.00000001):
     return input.new_zeros(*input.size()).uniform_().add_(
         TINY).log_().neg_().add_(TINY).log_().neg_()

Mutant 2220

--- fairseq/models/nat/iterative_nonautoregressive_transformer.py
+++ fairseq/models/nat/iterative_nonautoregressive_transformer.py
@@ -50,7 +50,7 @@
 
 @register_model("iterative_nonautoregressive_transformer")
 class IterNATransformerModel(NATransformerModel):
-    @staticmethod
+
     def add_args(parser):
         NATransformerModel.add_args(parser)
         parser.add_argument("--train-step", type=int,

Mutant 2221

--- fairseq/models/nat/iterative_nonautoregressive_transformer.py
+++ fairseq/models/nat/iterative_nonautoregressive_transformer.py
@@ -60,7 +60,6 @@
         parser.add_argument("--stochastic-approx", action="store_true",
                             help="sampling from the decoder as the inputs for next iteration")
 
-    @classmethod
     def build_model(cls, args, task):
         model = super().build_model(args, task)
         model.train_step = getattr(args, "train_step", 4)

Mutant 2223

--- fairseq/models/nat/iterative_nonautoregressive_transformer.py
+++ fairseq/models/nat/iterative_nonautoregressive_transformer.py
@@ -145,7 +145,7 @@
 
 
 @register_model_architecture(
-    "iterative_nonautoregressive_transformer", "iterative_nonautoregressive_transformer"
+    "iterative_nonautoregressive_transformer", "XXiterative_nonautoregressive_transformerXX"
 )
 def inat_base_architecture(args):
     args.encoder_embed_path = getattr(args, "encoder_embed_path", None)

Mutant 2225

--- fairseq/models/nat/iterative_nonautoregressive_transformer.py
+++ fairseq/models/nat/iterative_nonautoregressive_transformer.py
@@ -199,7 +199,7 @@
 
 @register_model_architecture(
     "iterative_nonautoregressive_transformer",
-    "iterative_nonautoregressive_transformer_wmt_en_de",
+    "XXiterative_nonautoregressive_transformer_wmt_en_deXX",
 )
 def iter_nat_wmt_en_de(args):
     inat_base_architecture(args)