chore: Linter fixes

Signed-off-by: Dheeraj Peri <[email protected]>

Author: peri044

py/torch_tensorrt/ts/_compile_spec.py

@@ -38,6 +38,7 @@ def _supported_input_size_type(input_size: Any) -> bool:
             + str(type(input_size))
         )
 
+
 def _parse_op_precision(precision: Any) -> _enums.dtype:
     if isinstance(precision, torch.dtype):
         if precision == torch.int8:
@@ -192,9 +193,17 @@ def _parse_input_signature(input_signature: Any, depth: int = 0):
         if i.shape_mode == Input._ShapeMode.STATIC:
             ts_i = TSInput(shape=i.shape, dtype=i.dtype, format=i.format)
         elif i.shape_mode == Input._ShapeMode.DYNAMIC:
-            ts_i = TSInput(min_shape=i.shape["min_shape"], opt_shape=i.shape["opt_shape"], max_shape=i.shape["max_shape"], dtype=i.dtype, format=i.format)
+            ts_i = TSInput(
+                min_shape=i.shape["min_shape"],
+                opt_shape=i.shape["opt_shape"],
+                max_shape=i.shape["max_shape"],
+                dtype=i.dtype,
+                format=i.format,
+            )
         else:
-            raise ValueError("Invalid shape mode detected for input while parsing the input_signature")
+            raise ValueError(
+                "Invalid shape mode detected for input while parsing the input_signature"
+            )
 
         clone = _internal_input_to_torch_class_input(ts_i._to_internal())
         return clone
@@ -231,9 +240,21 @@ def _parse_compile_spec(compile_spec_: Dict[str, Any]) -> _ts_C.CompileSpec:
         ts_inputs = []
         for i in inputs:
             if i.shape_mode == Input._ShapeMode.STATIC:
-                ts_inputs.append(TSInput(shape=i.shape, dtype=i.dtype, format=i.format)._to_internal())
+                ts_inputs.append(
+                    TSInput(
+                        shape=i.shape, dtype=i.dtype, format=i.format
+                    )._to_internal()
+                )
             elif i.shape_mode == Input._ShapeMode.DYNAMIC:
-                ts_inputs.append(TSInput(min_shape=i.shape["min_shape"], opt_shape=i.shape["opt_shape"], max_shape=i.shape["max_shape"], dtype=i.dtype, format=i.format)._to_internal())
+                ts_inputs.append(
+                    TSInput(
+                        min_shape=i.shape["min_shape"],
+                        opt_shape=i.shape["opt_shape"],
+                        max_shape=i.shape["max_shape"],
+                        dtype=i.dtype,
+                        format=i.format,
+                    )._to_internal()
+                )
         info.inputs = ts_inputs
 
     elif compile_spec["input_signature"] is not None:

tests/py/api/test_classes.py

@@ -199,15 +199,27 @@ def test_dynamic_shape(self):
         i = torchtrt.Input(
             min_shape=min_shape, opt_shape=opt_shape, max_shape=max_shape
         )
-        ts_i = torchtrt.ts.TSInput(min_shape=i.shape["min_shape"], opt_shape=i.shape["opt_shape"], max_shape=i.shape["max_shape"], dtype=i.dtype, format=i.format)
+        ts_i = torchtrt.ts.TSInput(
+            min_shape=i.shape["min_shape"],
+            opt_shape=i.shape["opt_shape"],
+            max_shape=i.shape["max_shape"],
+            dtype=i.dtype,
+            format=i.format,
+        )
         self.assertTrue(self._verify_correctness(ts_i, target))
 
         i = torchtrt.Input(
             min_shape=tuple(min_shape),
             opt_shape=tuple(opt_shape),
             max_shape=tuple(max_shape),
         )
-        ts_i = torchtrt.ts.TSInput(min_shape=i.shape["min_shape"], opt_shape=i.shape["opt_shape"], max_shape=i.shape["max_shape"], dtype=i.dtype, format=i.format)
+        ts_i = torchtrt.ts.TSInput(
+            min_shape=i.shape["min_shape"],
+            opt_shape=i.shape["opt_shape"],
+            max_shape=i.shape["max_shape"],
+            dtype=i.dtype,
+            format=i.format,
+        )
         self.assertTrue(self._verify_correctness(ts_i, target))
 
         tensor_shape = lambda shape: torch.randn(shape).shape
@@ -216,7 +228,13 @@ def test_dynamic_shape(self):
             opt_shape=tensor_shape(opt_shape),
             max_shape=tensor_shape(max_shape),
         )
-        ts_i = torchtrt.ts.TSInput(min_shape=i.shape["min_shape"], opt_shape=i.shape["opt_shape"], max_shape=i.shape["max_shape"], dtype=i.dtype, format=i.format)
+        ts_i = torchtrt.ts.TSInput(
+            min_shape=i.shape["min_shape"],
+            opt_shape=i.shape["opt_shape"],
+            max_shape=i.shape["max_shape"],
+            dtype=i.dtype,
+            format=i.format,
+        )
         self.assertTrue(self._verify_correctness(ts_i, target))