Fix unnecessary single-item container checks

cyyever · cyyever · commit 671358821be8 · 2025-10-02T17:05:21.000+08:00
Signed-off-by: Yuanyuan Chen &lt;cyyever@outlook.com&gt;
diff --git a/src/transformers/audio_utils.py b/src/transformers/audio_utils.py
@@ -587,7 +587,7 @@ def window_function(
         window = np.hamming(length)
     elif name in ["hann", "hann_window"]:
         window = np.hanning(length)
-    elif name in ["povey"]:
+    elif name == "povey":
         window = np.power(np.hanning(length), 0.85)
     else:
         raise ValueError(f"Unknown window function '{name}'")
diff --git a/src/transformers/generation/utils.py b/src/transformers/generation/utils.py
@@ -883,7 +883,7 @@ def _prepare_decoder_input_ids_for_generation(
             self.config.model_type == "vision-encoder-decoder" and "donut" in self.config.encoder.model_type.lower()
         ):
             pass
-        elif self.config.model_type in ["whisper"]:
+        elif self.config.model_type == "whisper":
             pass
         # user input but doesn't start with decoder_start_token_id -> prepend decoder_start_token_id (and adjust
         # decoder_attention_mask if provided)
diff --git a/src/transformers/integrations/ggml.py b/src/transformers/integrations/ggml.py
@@ -329,11 +329,11 @@ def _gguf_parse_value(_value, data_type):
         _value = int(_value[0])
     elif data_type in [6, 12]:
         _value = float(_value[0])
-    elif data_type in [7]:
+    elif data_type == 7:
         _value = bool(_value[0])
-    elif data_type in [8]:
+    elif data_type == 8:
         _value = array("B", list(_value)).tobytes().decode()
-    elif data_type in [9]:
+    elif data_type == 9:
         _value = _gguf_parse_value(_value, array_data_type)
     return _value
 
diff --git a/src/transformers/modeling_utils.py b/src/transformers/modeling_utils.py
@@ -4001,7 +4001,7 @@ def save_pretrained(
                 if _is_dtensor_available and isinstance(state_dict[tensor], DTensor):
                     full_tensor = state_dict[tensor].full_tensor()
                     # to get the correctly ordered tensor we need to repack if packed
-                    if _get_parameter_tp_plan(tensor, self._tp_plan) in ("local_packed_rowwise",):
+                    if _get_parameter_tp_plan(tensor, self._tp_plan) == "local_packed_rowwise":
                         full_tensor = repack_weights(full_tensor, -1, self._tp_size, 2)
                     shard[tensor] = full_tensor.contiguous()  # only do contiguous after it's permuted correctly
                 else:
diff --git a/src/transformers/models/altclip/configuration_altclip.py b/src/transformers/models/altclip/configuration_altclip.py
@@ -303,7 +303,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -335,7 +335,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
             for key, value in _vision_config_dict.items():
-                if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
+                if key in vision_config and value != vision_config[key] and key != "transformers_version":
                     # If specified in `vision_config_dict`
                     if key in vision_config_dict:
                         message = (
diff --git a/src/transformers/models/chinese_clip/configuration_chinese_clip.py b/src/transformers/models/chinese_clip/configuration_chinese_clip.py
@@ -306,7 +306,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -338,7 +338,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
             for key, value in _vision_config_dict.items():
-                if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
+                if key in vision_config and value != vision_config[key] and key != "transformers_version":
                     # If specified in `vision_config_dict`
                     if key in vision_config_dict:
                         message = (
diff --git a/src/transformers/models/clip/configuration_clip.py b/src/transformers/models/clip/configuration_clip.py
@@ -295,7 +295,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -327,7 +327,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
             for key, value in _vision_config_dict.items():
-                if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
+                if key in vision_config and value != vision_config[key] and key != "transformers_version":
                     # If specified in `vision_config_dict`
                     if key in vision_config_dict:
                         message = (
diff --git a/src/transformers/models/clipseg/configuration_clipseg.py b/src/transformers/models/clipseg/configuration_clipseg.py
@@ -307,7 +307,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -339,7 +339,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
             for key, value in _vision_config_dict.items():
-                if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
+                if key in vision_config and value != vision_config[key] and key != "transformers_version":
                     # If specified in `vision_config_dict`
                     if key in vision_config_dict:
                         message = (
diff --git a/src/transformers/models/dpt/modeling_dpt.py b/src/transformers/models/dpt/modeling_dpt.py
@@ -864,7 +864,7 @@ def __init__(self, config: DPTConfig):
         self.config = config
 
         # postprocessing: only required in case of a non-hierarchical backbone (e.g. ViT, BEiT)
-        if config.backbone_config is not None and config.backbone_config.model_type in ["swinv2"]:
+        if config.backbone_config is not None and config.backbone_config.model_type == "swinv2":
             self.reassemble_stage = None
         else:
             self.reassemble_stage = DPTReassembleStage(config)
diff --git a/src/transformers/models/flava/configuration_flava.py b/src/transformers/models/flava/configuration_flava.py
@@ -516,7 +516,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -548,7 +548,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_image_config_dict` and `image_config` but being different.
             for key, value in _image_config_dict.items():
-                if key in image_config and value != image_config[key] and key not in ["transformers_version"]:
+                if key in image_config and value != image_config[key] and key != "transformers_version":
                     # If specified in `image_config_dict`
                     if key in image_config_dict:
                         message = (
@@ -579,7 +579,7 @@ def __init__(
                 if (
                     key in multimodal_config
                     and value != multimodal_config[key]
-                    and key not in ["transformers_version"]
+                    and key != "transformers_version"
                 ):
                     # If specified in `multimodal_config_dict`
                     if key in multimodal_config_dict:
@@ -611,7 +611,7 @@ def __init__(
                 if (
                     key in image_codebook_config
                     and value != image_codebook_config[key]
-                    and key not in ["transformers_version"]
+                    and key != "transformers_version"
                 ):
                     # If specified in `image_codebook_config_dict`
                     if key in image_codebook_config_dict:
diff --git a/src/transformers/models/groupvit/configuration_groupvit.py b/src/transformers/models/groupvit/configuration_groupvit.py
@@ -288,7 +288,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -320,7 +320,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
             for key, value in _vision_config_dict.items():
-                if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
+                if key in vision_config and value != vision_config[key] and key != "transformers_version":
                     # If specified in `vision_config_dict`
                     if key in vision_config_dict:
                         message = (
diff --git a/src/transformers/models/imagegpt/convert_imagegpt_original_tf2_to_pytorch.py b/src/transformers/models/imagegpt/convert_imagegpt_original_tf2_to_pytorch.py
@@ -63,12 +63,12 @@ def load_tf_weights_in_imagegpt(model, config, imagegpt_checkpoint_path):
         if any(
             n in ["adam_v", "adam_m", "AdamWeightDecayOptimizer", "AdamWeightDecayOptimizer_1", "global_step"]
             for n in name
-        ) or name[-1] in ["_step"]:
+        ) or name[-1] == "_step":
             logger.info("Skipping {}".format("/".join(name)))
             continue
 
         pointer = model
-        if name[-1] not in ["wtet"]:
+        if name[-1] != "wtet":
             pointer = getattr(pointer, "transformer")
 
         for m_name in name:
diff --git a/src/transformers/models/kosmos2_5/modeling_kosmos2_5.py b/src/transformers/models/kosmos2_5/modeling_kosmos2_5.py
@@ -274,7 +274,7 @@ class Kosmos2_5ModelOutput(ModelOutput):
 
     def to_tuple(self) -> tuple[Any]:
         return tuple(
-            (self[k] if k not in ["vision_model_output"] else getattr(self, k).to_tuple()) for k in self.keys()
+            (self[k] if k != "vision_model_output" else getattr(self, k).to_tuple()) for k in self.keys()
         )
 
 
@@ -334,7 +334,7 @@ class Kosmos2_5ForConditionalGenerationModelOutput(ModelOutput):
 
     def to_tuple(self) -> tuple[Any]:
         return tuple(
-            (self[k] if k not in ["vision_model_output"] else getattr(self, k).to_tuple()) for k in self.keys()
+            (self[k] if k != "vision_model_output" else getattr(self, k).to_tuple()) for k in self.keys()
         )
 
 
diff --git a/src/transformers/models/llama/convert_llama_weights_to_hf.py b/src/transformers/models/llama/convert_llama_weights_to_hf.py
@@ -398,7 +398,7 @@ def permute(w, n_heads, dim1=dim, dim2=dim):
             max_position_embeddings=max_position_embeddings,
             bos_token_id=bos_token_id,
             eos_token_id=eos_token_id,
-            tie_word_embeddings=llama_version in ["3.2"],
+            tie_word_embeddings=llama_version == "3.2",
         )
 
         config.save_pretrained(tmp_model_path)
@@ -451,7 +451,7 @@ def __init__(self, vocab_file, special_tokens=None, instruct=False, llama_versio
         # Prevents a null chat_template, which triggers
         # a parsing warning in the Hub.
         additional_kwargs = {}
-        if instruct or llama_version in ["Guard-3"]:
+        if instruct or llama_version == "Guard-3":
             model_id, revision = templates_for_version.get(llama_version, (None, None))
             if model_id is not None:
                 from transformers import AutoTokenizer
diff --git a/src/transformers/models/metaclip_2/configuration_metaclip_2.py b/src/transformers/models/metaclip_2/configuration_metaclip_2.py
@@ -277,7 +277,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -309,7 +309,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
             for key, value in _vision_config_dict.items():
-                if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
+                if key in vision_config and value != vision_config[key] and key != "transformers_version":
                     # If specified in `vision_config_dict`
                     if key in vision_config_dict:
                         message = (
diff --git a/src/transformers/models/perceiver/modeling_perceiver.py b/src/transformers/models/perceiver/modeling_perceiver.py
@@ -2804,7 +2804,7 @@ class PerceiverAudioPostprocessor(nn.Module):
     def __init__(self, config: PerceiverConfig, in_channels: int, postproc_type: str = "patches") -> None:
         super().__init__()
 
-        if postproc_type not in ("patches",):  # to be supported: 'conv', 'patches', 'pixels'
+        if postproc_type != "patches":  # to be supported: 'conv', 'patches', 'pixels'
             raise ValueError("Invalid postproc_type!")
 
         # Architecture parameters:
@@ -3137,7 +3137,7 @@ def __init__(
         super().__init__()
         self.config = config
 
-        if prep_type not in ("patches",):
+        if prep_type != "patches":
             raise ValueError(f"Prep_type {prep_type} is invalid, can only be 'patches'.")
 
         if concat_or_add_pos not in ["concat", "add"]:
diff --git a/src/transformers/models/phi3/configuration_phi3.py b/src/transformers/models/phi3/configuration_phi3.py
@@ -210,7 +210,7 @@ def _rope_scaling_validation(self):
         rope_scaling_type = self.rope_scaling.get("type", None)
         rope_scaling_short_factor = self.rope_scaling.get("short_factor", None)
         rope_scaling_long_factor = self.rope_scaling.get("long_factor", None)
-        if rope_scaling_type is None or rope_scaling_type not in ["longrope"]:
+        if rope_scaling_type is None or rope_scaling_type != "longrope":
             raise ValueError(f"`rope_scaling`'s type field must be one of ['longrope'], got {rope_scaling_type}")
         if not (
             isinstance(rope_scaling_short_factor, list)
diff --git a/src/transformers/models/phi4_multimodal/configuration_phi4_multimodal.py b/src/transformers/models/phi4_multimodal/configuration_phi4_multimodal.py
@@ -452,7 +452,7 @@ def _rope_scaling_validation(self):
         rope_scaling_type = self.rope_scaling.get("type", None)
         rope_scaling_short_factor = self.rope_scaling.get("short_factor", None)
         rope_scaling_long_factor = self.rope_scaling.get("long_factor", None)
-        if rope_scaling_type is None or rope_scaling_type not in ["longrope"]:
+        if rope_scaling_type is None or rope_scaling_type != "longrope":
             raise ValueError(f"`rope_scaling`'s type field must be one of ['longrope'], got {rope_scaling_type}")
         if not (
             isinstance(rope_scaling_short_factor, list)
diff --git a/src/transformers/models/qwen3_omni_moe/modeling_qwen3_omni_moe.py b/src/transformers/models/qwen3_omni_moe/modeling_qwen3_omni_moe.py
@@ -3903,7 +3903,7 @@ def generate(
                     self.config.talker_config.text_config.vocab_size - 1024,
                     self.config.talker_config.text_config.vocab_size,
                 )
-                if i not in (self.config.talker_config.codec_eos_token_id,)
+                if i != self.config.talker_config.codec_eos_token_id
             ]  # Suppress additional special tokens, should not be predicted
             talker_kwargs = {
                 "max_new_tokens": talker_max_new_tokens,
diff --git a/src/transformers/models/qwen3_omni_moe/modular_qwen3_omni_moe.py b/src/transformers/models/qwen3_omni_moe/modular_qwen3_omni_moe.py
@@ -2414,7 +2414,7 @@ def generate(
                     self.config.talker_config.text_config.vocab_size - 1024,
                     self.config.talker_config.text_config.vocab_size,
                 )
-                if i not in (self.config.talker_config.codec_eos_token_id,)
+                if i != self.config.talker_config.codec_eos_token_id
             ]  # Suppress additional special tokens, should not be predicted
             talker_kwargs = {
                 "max_new_tokens": talker_max_new_tokens,
diff --git a/src/transformers/models/tapas/convert_tapas_original_tf_checkpoint_to_pytorch.py b/src/transformers/models/tapas/convert_tapas_original_tf_checkpoint_to_pytorch.py
@@ -96,7 +96,7 @@ def load_tf_weights_in_tapas(model, config, tf_checkpoint_path):
                 continue
         # in case the model is TapasForMaskedLM, we skip the pooler
         if isinstance(model, TapasForMaskedLM):
-            if any(n in ["pooler"] for n in name):
+            if any(n == "pooler" for n in name):
                 logger.info(f"Skipping {'/'.join(name)}")
                 continue
         # if first scope name starts with "bert", change it to "tapas"
diff --git a/src/transformers/models/x_clip/configuration_x_clip.py b/src/transformers/models/x_clip/configuration_x_clip.py
@@ -294,7 +294,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
             for key, value in _text_config_dict.items():
-                if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
+                if key in text_config and value != text_config[key] and key != "transformers_version":
                     # If specified in `text_config_dict`
                     if key in text_config_dict:
                         message = (
@@ -326,7 +326,7 @@ def __init__(
 
             # Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
             for key, value in _vision_config_dict.items():
-                if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
+                if key in vision_config and value != vision_config[key] and key != "transformers_version":
                     # If specified in `vision_config_dict`
                     if key in vision_config_dict:
                         message = (
diff --git a/src/transformers/models/zoedepth/modeling_zoedepth.py b/src/transformers/models/zoedepth/modeling_zoedepth.py
@@ -294,7 +294,7 @@ def __init__(self, config: ZoeDepthConfig):
         self.config = config
 
         # postprocessing: only required in case of a non-hierarchical backbone (e.g. ViT, BEiT)
-        if config.backbone_config is not None and config.backbone_config.model_type in ["swinv2"]:
+        if config.backbone_config is not None and config.backbone_config.model_type == "swinv2":
             self.reassemble_stage = None
         else:
             self.reassemble_stage = ZoeDepthReassembleStage(config)
diff --git a/src/transformers/pipelines/base.py b/src/transformers/pipelines/base.py
@@ -169,7 +169,7 @@ def inner(items):
         # input_values, input_pixels, input_ids, ...
         padded = {}
         for key in keys:
-            if key in {"input_ids"}:
+            if key == "input_ids":
                 # ImageGPT uses a feature extractor
                 if tokenizer is None and feature_extractor is not None:
                     _padding_value = f_padding_value
diff --git a/src/transformers/pipelines/text_generation.py b/src/transformers/pipelines/text_generation.py
@@ -179,7 +179,7 @@ def _sanitize_parameters(
             generate_kwargs["prefix_length"] = prefix_inputs["input_ids"].shape[-1]
 
         if handle_long_generation is not None:
-            if handle_long_generation not in {"hole"}:
+            if handle_long_generation != "hole":
                 raise ValueError(
                     f"{handle_long_generation} is not a valid value for `handle_long_generation` parameter expected"
                     " [None, 'hole']"
@@ -234,7 +234,7 @@ def _parse_and_tokenize(self, *args, **kwargs):
         Parse arguments and tokenize
         """
         # Parse arguments
-        if self.model.__class__.__name__ in ["TransfoXLLMHeadModel"]:
+        if self.model.__class__.__name__ == "TransfoXLLMHeadModel":
             kwargs.update({"add_space_before_punct_symbol": True})
 
         return super()._parse_and_tokenize(*args, **kwargs)
diff --git a/src/transformers/testing_utils.py b/src/transformers/testing_utils.py
diff --git a/src/transformers/utils/quantization_config.py b/src/transformers/utils/quantization_config.py
diff --git a/src/transformers/video_utils.py b/src/transformers/video_utils.py
