fairseq/optim/adamax.py

Survived

Mutant 1921

--- fairseq/optim/adamax.py
+++ fairseq/optim/adamax.py
@@ -9,7 +9,7 @@
 from . import FairseqOptimizer, register_optimizer
 
 
-@register_optimizer('adamax')
+@register_optimizer('XXadamaxXX')
 class FairseqAdamax(FairseqOptimizer):
     def __init__(self, args, params):
         super().__init__(args)

Mutant 1922

--- fairseq/optim/adamax.py
+++ fairseq/optim/adamax.py
@@ -8,8 +8,6 @@
 
 from . import FairseqOptimizer, register_optimizer
 
-
-@register_optimizer('adamax')
 class FairseqAdamax(FairseqOptimizer):
     def __init__(self, args, params):
         super().__init__(args)

Mutant 1923

--- fairseq/optim/adamax.py
+++ fairseq/optim/adamax.py
@@ -15,7 +15,6 @@
         super().__init__(args)
         self._optimizer = Adamax(params, **self.optimizer_config)
 
-    @staticmethod
     def add_args(parser):
         """Add optimizer-specific arguments to the parser."""
         # fmt: off

Mutant 1924

--- fairseq/optim/adamax.py
+++ fairseq/optim/adamax.py
@@ -27,9 +27,7 @@
                             help='weight decay')
         parser.add_argument('--no-bias-correction', default=False, action='store_true',
                             help='disable bias correction')
-        # fmt: on
 
-    @property
     def optimizer_config(self):
         """
         Return a kwarg dictionary that will be used to override optimizer

Mutant 1925

--- fairseq/optim/adamax.py
+++ fairseq/optim/adamax.py
@@ -68,7 +68,7 @@
     """
 
     def __init__(self, params, lr=2e-3, betas=(0.9, 0.999), eps=1e-8,
-                 weight_decay=0, bias_correction=True):
+                 weight_decay=1, bias_correction=True):
         if not 0.0 <= lr:
             raise ValueError("Invalid learning rate: {}".format(lr))
         if not 0.0 <= eps:

Mutant 1926

--- fairseq/optim/adamax.py
+++ fairseq/optim/adamax.py
@@ -68,7 +68,7 @@
     """
 
     def __init__(self, params, lr=2e-3, betas=(0.9, 0.999), eps=1e-8,
-                 weight_decay=0, bias_correction=True):
+                 weight_decay=0, bias_correction=False):
         if not 0.0 <= lr:
             raise ValueError("Invalid learning rate: {}".format(lr))
         if not 0.0 <= eps:

Mutant 1927

--- fairseq/optim/adamax.py
+++ fairseq/optim/adamax.py
@@ -84,7 +84,6 @@
                         bias_correction=bias_correction)
         super(Adamax, self).__init__(params, defaults)
 
-    @property
     def supports_memory_efficient_fp16(self):
         return True
 

Mutant 1928

--- fairseq/optim/adamax.py
+++ fairseq/optim/adamax.py
@@ -88,7 +88,6 @@
     def supports_memory_efficient_fp16(self):
         return True
 
-    @property
     def supports_flat_params(self):
         return True