Update tuple typehint

Author: sugatmahanti

src/llmcompressor/transformers/compression/helpers.py

@@ -1,5 +1,4 @@
 from collections import defaultdict
-from typing import Tuple
 
 import torch
 from accelerate.accelerator import get_state_dict_offloaded_model
@@ -104,7 +103,7 @@ def infer_sparse_targets_and_ignores(
     model: torch.nn.Module,
     sparsity_structure: str,
     sparsity_threshold: float,
-) -> Tuple[list[str], list[str]]:
+) -> tuple[list[str], list[str]]:
     """
     Infers the target and ignore layers in the given model
     to be used for sparsity compression
@@ -151,7 +150,7 @@ def is_sparse_compression_target(
 
 def _get_sparse_targets_ignore_dicts(
     module: torch.nn.Module, sparsity_structure: str, sparsity_threshold: float
-) -> Tuple[dict[str, list[str]], dict[str, list[str]]]:
+) -> tuple[dict[str, list[str]], dict[str, list[str]]]:
     """
     Get sparse targets and ignore dictionaries
 
@@ -177,7 +176,7 @@ def _get_sparse_targets_ignore_dicts(
 
 def _reduce_targets_and_ignores_into_lists(
     exhaustive_targets: dict[str, list[str]], exhaustive_ignore: dict[str, list[str]]
-) -> Tuple[list[str], list[str]]:
+) -> tuple[list[str], list[str]]:
     """
     Reduces the targets and ignores dictionaries into lists
 

src/llmcompressor/transformers/finetune/session_mixin.py

@@ -2,7 +2,7 @@
 import math
 import os
 from dataclasses import asdict
-from typing import TYPE_CHECKING, Any, Tuple
+from typing import TYPE_CHECKING, Any
 
 import torch
 from loguru import logger
@@ -277,7 +277,7 @@ def compute_loss(
         inputs: dict[str, Any],
         return_outputs: bool = False,
         num_items_in_batch: torch.Tensor | None = None,
-    ) ->torch.Tensor | Tuple[torch.Tensor, Any]:
+    ) ->torch.Tensor | tuple[torch.Tensor, Any]:
         """
         Override for the compute_loss to factor trigger callbacks and filter columns
 
@@ -509,7 +509,7 @@ def _check_super_defined(self, func: str):
                 f"The super class for SessionManagerMixIn must define a {func} function"
             )
 
-    def _calculate_checkpoint_info(self, kwargs) -> Tuple[str | None, float]:
+    def _calculate_checkpoint_info(self, kwargs) -> tuple[str | None, float]:
         """
         If resuming from checkpoint is set, get checkpoint and epoch to resume from
         """