https://docs.astral.sh/ruff/rules/redefined-while-unused/ fixes the imports, bit needs later version of ruff

src/transformers/models/gemma/modeling_gemma.py

@@ -20,6 +20,8 @@ from typing import List, Optional, Tuple, Union
 import torch
 import torch.nn.functional as F
 import torch.utils.checkpoint
+from flash_attn import flash_attn_func, flash_attn_varlen_func
+from flash_attn.bert_padding import index_first_axis, pad_input, unpad_input  # noqa
 from torch import nn
 from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
 
@@ -29,7 +31,6 @@ from ...modeling_attn_mask_utils import AttentionMaskConverter
 from ...modeling_outputs import (
     BaseModelOutputWithPast,
     CausalLMOutputWithPast,
-    QuestionAnsweringModelOutput,
     SequenceClassifierOutputWithPast,
 )
 from ...modeling_utils import PreTrainedModel
@@ -43,8 +44,6 @@ from ...utils import (
     replace_return_docstrings,
 )
 from .configuration_gemma import GemmaConfig
-from flash_attn import flash_attn_func, flash_attn_varlen_func
-from flash_attn.bert_padding import index_first_axis, pad_input, unpad_input  # noqa
 
 
 if is_flash_attn_2_available():
@@ -215,31 +214,16 @@ def repeat_kv(hidden_states: torch.Tensor, n_rep: int) -> torch.Tensor:
 
 """ PyTorch Gemma model."""
 
-import math
-from typing import List, Optional, Tuple, Union
 
 import torch
 import torch.utils.checkpoint
-from torch import nn
 
 from transformers.models.llama.modeling_llama import (
-    LlamaDecoderLayer,
-    LlamaFlashAttention2,
-    LlamaForCausalLM,
-    LlamaForSequenceClassification,
-    LlamaModel,
-    LlamaPreTrainedModel,
-    LlamaSdpaAttention,
     apply_rotary_pos_emb,
     repeat_kv,
 )
 
-from ...activations import ACT2FN
-from ...cache_utils import Cache
-from ...modeling_outputs import CausalLMOutputWithPast
-from ...pytorch_utils import ALL_LAYERNORM_LAYERS
 from ...utils import logging
-from .configuration_gemma import GemmaConfig
 
 
 logger = logging.get_logger(__name__)