Clean up some type annotations in caffe2/torch/quantization (#49942)

Summary:
Pull Request resolved: #49942

Upgrades type annotations from Python2 to Python3

Test Plan: Sandcastle tests

Reviewed By: vkuzo

Differential Revision: D25717551

fbshipit-source-id: d52555d701793b7c07e561df56acd82c966bdb7c

torch/quantization/_numeric_suite_fx.py

@@ -21,7 +21,7 @@
 def remove_qconfig_observer_fx(model):
     # remove activation post process
     act_post_process_removed_graph = Graph()
-    env = {}  # type: Dict[str, Any]
+    env: Dict[str, Any] = {}
 
     modules = dict(model.named_modules())
 

torch/quantization/fake_quantize.py

@@ -41,17 +41,15 @@ def calculate_qparams(self, **kwargs):
         pass
 
     @torch.jit.export
-    def enable_fake_quant(self, enabled=True):
-        # type: (bool) -> None
+    def enable_fake_quant(self, enabled: bool = True) -> None:
         self.fake_quant_enabled[0] = 1 if enabled else 0
 
     @torch.jit.export
     def disable_fake_quant(self):
         self.enable_fake_quant(False)
 
     @torch.jit.export
-    def enable_observer(self, enabled=True):
-        # type: (bool) -> None
+    def enable_observer(self, enabled: bool = True) -> None:
         self.observer_enabled[0] = 1 if enabled else 0
 
     @torch.jit.export

torch/quantization/observer.py

@@ -877,8 +877,7 @@ def _combine_histograms(self,
         orig_hist = orig_hist + interpolated_histogram.to(torch.float)
         return orig_hist
 
-    def forward(self, x_orig):
-        # type: (torch.Tensor) -> torch.Tensor
+    def forward(self, x_orig: torch.Tensor) -> torch.Tensor:
         x = x_orig.detach()
         min_val = self.min_val
         max_val = self.max_val