Add support for Python3.11

fairseq/dataclass/configs.py

@@ -1126,16 +1126,16 @@ class EMAConfig(FairseqDataclass):
 
 @dataclass
 class FairseqConfig(FairseqDataclass):
-    common: CommonConfig = CommonConfig()
-    common_eval: CommonEvalConfig = CommonEvalConfig()
-    distributed_training: DistributedTrainingConfig = DistributedTrainingConfig()
-    dataset: DatasetConfig = DatasetConfig()
-    optimization: OptimizationConfig = OptimizationConfig()
-    checkpoint: CheckpointConfig = CheckpointConfig()
-    bmuf: FairseqBMUFConfig = FairseqBMUFConfig()
-    generation: GenerationConfig = GenerationConfig()
-    eval_lm: EvalLMConfig = EvalLMConfig()
-    interactive: InteractiveConfig = InteractiveConfig()
+    common: CommonConfig = field(default_factory=CommonConfig)
+    common_eval: CommonEvalConfig = field(default_factory=CommonEvalConfig)
+    distributed_training: DistributedTrainingConfig = field(default_factory=DistributedTrainingConfig)
+    dataset: DatasetConfig = field(default_factory=DatasetConfig)
+    optimization: OptimizationConfig = field(default_factory=OptimizationConfig)
+    checkpoint: CheckpointConfig = field(default_factory=CheckpointConfig)
+    bmuf: FairseqBMUFConfig = field(default_factory=FairseqBMUFConfig)
+    generation: GenerationConfig = field(default_factory=GenerationConfig)
+    eval_lm: EvalLMConfig = field(default_factory=EvalLMConfig)
+    interactive: InteractiveConfig = field(default_factory=InteractiveConfig)
     model: Any = MISSING
     task: Any = None
     criterion: Any = None
@@ -1144,4 +1144,4 @@ class FairseqConfig(FairseqDataclass):
     scoring: Any = None
     bpe: Any = None
     tokenizer: Any = None
-    ema: EMAConfig = EMAConfig()
+    ema: EMAConfig = field(default_factory=EMAConfig) 

fairseq/models/transformer/transformer_config.py

@@ -111,13 +111,13 @@ class TransformerConfig(FairseqDataclass):
         },
     )
     adaptive_input: bool = False
-    encoder: EncDecBaseConfig = EncDecBaseConfig()
+    encoder: EncDecBaseConfig = field(default_factory=EncDecBaseConfig)
     # TODO should really be in the encoder config
     max_source_positions: int = field(
         default=DEFAULT_MAX_SOURCE_POSITIONS,
         metadata={"help": "Maximum input length supported by the encoder"},
     )
-    decoder: DecoderConfig = DecoderConfig()
+    decoder: DecoderConfig = field(default_factory=EncDecBaseConfig)
     # TODO should really be in the decoder config
     max_target_positions: int = field(
         default=DEFAULT_MAX_TARGET_POSITIONS,
@@ -197,7 +197,7 @@ class TransformerConfig(FairseqDataclass):
         default=False, metadata={"help": "perform cross+self-attention"}
     )
     # args for Training with Quantization Noise for Extreme Model Compression ({Fan*, Stock*} et al., 2020)
-    quant_noise: QuantNoiseConfig = field(default=QuantNoiseConfig())
+    quant_noise: QuantNoiseConfig = field(default_factory=QuantNoiseConfig)
     min_params_to_wrap: int = field(
         default=DEFAULT_MIN_PARAMS_TO_WRAP,
         metadata={

setup.py

@@ -179,8 +179,8 @@ def do_setup(package_data):
         install_requires=[
             "cffi",
             "cython",
-            "hydra-core>=1.0.7,<1.1",
-            "omegaconf<2.1",
+            "hydra-core>=1.3.2",
+            "omegaconf>2.1",
             "numpy>=1.21.3",
             "regex",
             "sacrebleu>=1.4.12",

tests/test_py_311_support.py

@@ -0,0 +1,3 @@
+from fairseq import checkpoint_utils
+
+