chore: address review comments

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

Author: peri044

py/torch_tensorrt/_Input.py

@@ -391,12 +391,6 @@ def from_tensors(
             for t in ts
         ]
 
-    def set_torch_tensor(self, torch_tensor: torch.Tensor) -> None:
-        """
-        Set the user provided torch tensor for the Input class.
-        """
-        self.torch_tensor = torch_tensor
-
     def example_tensor(
         self, optimization_profile_field: Optional[str] = None
     ) -> torch.Tensor:

py/torch_tensorrt/dynamo/compile.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-import collections.abc
 import logging
 from typing import Any, List, Optional, Sequence, Set, Tuple, Union
 
@@ -87,9 +86,6 @@ def compile(
         "require_full_compilation}"
     )
 
-    if not isinstance(inputs, collections.abc.Sequence):
-        inputs = [inputs]
-
     device = to_torch_tensorrt_device(device)
 
     if (

py/torch_tensorrt/dynamo/conversion/truncate_long_and_double.py

@@ -216,8 +216,7 @@ def repair_long_or_double_inputs(
 
             # Set the 32bit inputs and their types to the submodule Inputs
             for idx in range(len(submodule_inputs)):
-                submodule_inputs[idx].set_torch_tensor(submodule_torch_inputs[idx])
+                submodule_inputs[idx].torch_tensor = submodule_torch_inputs[idx]
                 submodule_inputs[idx].torch_dtype = submodule_torch_inputs[idx].dtype
-                submodule_inputs[idx].dtype = submodule_torch_inputs[idx].dtype
 
     return submodule_inputs