Fix formatting

Author: Ghost---Shadow

src/extra_metrics/base.py

@@ -6,5 +6,4 @@ def __init__(self, pipeline):
         self.pipeline = pipeline
 
     @abstractmethod
-    def generate_metric(self, batch):
-        ...
+    def generate_metric(self, batch): ...

src/generative_models/no_operation.py

@@ -1,8 +1,7 @@
 class NoOp:
     NAME = "noop"
 
-    def __init__(self, *args, **kwargs):
-        ...
+    def __init__(self, *args, **kwargs): ...
 
     def batch_evaluate(self, *args, **kwargs):
         raise NotImplementedError("Should not be invoked")

src/losses/base_loss.py

@@ -59,5 +59,4 @@ def compute_similarity_matrix(self, a, b, center_at_half=True):
         return similarities
 
     @abstractmethod
-    def forward(self, a, b):
-        ...
+    def forward(self, a, b): ...

src/semantic_search_models/base.py

@@ -15,5 +15,4 @@ def get_all_trainable_parameters(self):
         return self.model.parameters()
 
     @abstractmethod
-    def embed(self, sentences):
-        ...
+    def embed(self, sentences): ...

src/shortlist_strategies/base.py

@@ -90,9 +90,7 @@ def _populate_and_cache_index(self, cache_name, use_cache, wrapped_dataset):
             self.pipeline.dense_index.save_index(cache_name)
 
     @abstractmethod
-    def shortlist(self, use_cache=True):
-        ...
+    def shortlist(self, use_cache=True): ...
 
     @abstractmethod
-    def assemble_few_shot(self, use_cache=True):
-        ...
+    def assemble_few_shot(self, use_cache=True): ...

src/training_strategies/no_operation.py

@@ -8,8 +8,7 @@ def __init__(self, config, pipeline):
         self.pipeline = pipeline
         self.config = config
 
-    def before_each_epoch(self):
-        ...
+    def before_each_epoch(self): ...
 
     def train_step(self, batch):
         return torch.tensor(0, requires_grad=True)

src/training_strategies/quaild.py

@@ -9,8 +9,7 @@ def __init__(self, config, pipeline):
         self.config = config
         self.epsilon = 1e-7
 
-    def before_each_epoch(self):
-        ...
+    def before_each_epoch(self): ...
 
     def train_step(self, batch):
         # TODO: Gradient accumulation steps