diff --git a/vllm/model_executor/models/arctic.py b/vllm/model_executor/models/arctic.py index e2d4a8de..065715cb 100644 --- a/vllm/model_executor/models/arctic.py +++ b/vllm/model_executor/models/arctic.py @@ -370,7 +370,6 @@ class ArcticModel(nn.Module): cache_config = vllm_config.cache_config quant_config = vllm_config.quant_config - self.padding_idx = config.pad_token_id self.vocab_size = config.vocab_size self.embed_tokens = VocabParallelEmbedding( self.vocab_size, diff --git a/vllm/model_executor/models/baichuan.py b/vllm/model_executor/models/baichuan.py index 4fb68e7b..7e2b7c86 100644 --- a/vllm/model_executor/models/baichuan.py +++ b/vllm/model_executor/models/baichuan.py @@ -267,7 +267,6 @@ class BaiChuanModel(nn.Module): quant_config = vllm_config.quant_config self.config = config - self.padding_idx = config.pad_token_id self.vocab_size = config.vocab_size self.embed_tokens = VocabParallelEmbedding( diff --git a/vllm/model_executor/models/bart.py b/vllm/model_executor/models/bart.py index 82684dfa..5847c508 100644 --- a/vllm/model_executor/models/bart.py +++ b/vllm/model_executor/models/bart.py @@ -725,7 +725,6 @@ class BartModel(nn.Module): self.config = config - self.padding_idx = config.pad_token_id lora_vocab = (lora_config.lora_extra_vocab_size * (lora_config.max_loras or 1)) if lora_config else 0 self.vocab_size = config.vocab_size + lora_vocab diff --git a/vllm/model_executor/models/chameleon.py b/vllm/model_executor/models/chameleon.py index 137bfc0f..68284a01 100644 --- a/vllm/model_executor/models/chameleon.py +++ b/vllm/model_executor/models/chameleon.py @@ -851,7 +851,6 @@ class ChameleonModel(nn.Module): quant_config = vllm_config.quant_config self.config = config - self.padding_idx = config.pad_token_id self.vocab_size = config.vocab_size self.embed_tokens = VocabParallelEmbedding( self.vocab_size, diff --git a/vllm/model_executor/models/deepseek.py b/vllm/model_executor/models/deepseek.py index c04e7a02..f0212f37 100644 --- a/vllm/model_executor/models/deepseek.py +++ b/vllm/model_executor/models/deepseek.py @@ -339,7 +339,6 @@ class DeepseekModel(nn.Module): cache_config = vllm_config.cache_config quant_config = vllm_config.quant_config - self.padding_idx = config.pad_token_id self.vocab_size = config.vocab_size self.embed_tokens = VocabParallelEmbedding( diff --git a/vllm/model_executor/models/deepseek_v2.py b/vllm/model_executor/models/deepseek_v2.py index cf244ff5..548f913c 100644 --- a/vllm/model_executor/models/deepseek_v2.py +++ b/vllm/model_executor/models/deepseek_v2.py @@ -570,7 +570,6 @@ class DeepseekV2Model(nn.Module): cache_config = vllm_config.cache_config quant_config = vllm_config.quant_config - self.padding_idx = config.pad_token_id self.vocab_size = config.vocab_size if get_pp_group().is_first_rank: diff --git a/vllm/model_executor/models/exaone.py b/vllm/model_executor/models/exaone.py index 79939f6f..7d01dd37 100644 --- a/vllm/model_executor/models/exaone.py +++ b/vllm/model_executor/models/exaone.py @@ -313,7 +313,6 @@ class ExaoneModel(nn.Module): lora_config = vllm_config.lora_config self.config = config - self.padding_idx = config.pad_token_id lora_vocab = ((lora_config.lora_extra_vocab_size * (lora_config.max_loras or 1)) if lora_config else 0) self.vocab_size = config.vocab_size + lora_vocab diff --git a/vllm/model_executor/models/florence2.py b/vllm/model_executor/models/florence2.py index 7c226ea4..e892a1a4 100644 --- a/vllm/model_executor/models/florence2.py +++ b/vllm/model_executor/models/florence2.py @@ -592,7 +592,6 @@ class Florence2LanguageModel(nn.Module): self.config = config - self.padding_idx = config.pad_token_id self.vocab_size = config.vocab_size self.shared = BartScaledWordEmbedding(self.vocab_size, config.d_model) diff --git a/vllm/model_executor/models/fuyu.py b/vllm/model_executor/models/fuyu.py index 6f4b6cdd..51c79ba8 100644 --- a/vllm/model_executor/models/fuyu.py +++ b/vllm/model_executor/models/fuyu.py @@ -255,7 +255,6 @@ class FuyuForCausalLM(nn.Module, SupportsMultiModal, SupportsPP): self.config = config self.multimodal_config = multimodal_config - self.padding_idx = config.pad_token_id self.vocab_size = config.text_config.vocab_size self.image_token_id = _IMAGE_TOKEN_ID self.image_feature_size = config.patch_size**2 * config.num_channels diff --git a/vllm/model_executor/models/granite.py b/vllm/model_executor/models/granite.py index 201e15d3..eba8207d 100644 --- a/vllm/model_executor/models/granite.py +++ b/vllm/model_executor/models/granite.py @@ -260,7 +260,6 @@ class GraniteModel(nn.Module): lora_config = vllm_config.lora_config self.config = config - self.padding_idx = config.pad_token_id lora_vocab = (lora_config.lora_extra_vocab_size * (lora_config.max_loras or 1)) if lora_config else 0 self.vocab_size = config.vocab_size + lora_vocab diff --git a/vllm/model_executor/models/granitemoe.py b/vllm/model_executor/models/granitemoe.py index 9b56874a..5152539c 100644 --- a/vllm/model_executor/models/granitemoe.py +++ b/vllm/model_executor/models/granitemoe.py @@ -252,7 +252,6 @@ class GraniteMoeModel(nn.Module): quant_config = vllm_config.quant_config lora_config = vllm_config.lora_config - self.padding_idx = config.pad_token_id lora_vocab = (lora_config.lora_extra_vocab_size * (lora_config.max_loras or 1)) if lora_config else 0 self.vocab_size = config.vocab_size + lora_vocab diff --git a/vllm/model_executor/models/idefics3.py b/vllm/model_executor/models/idefics3.py index 3e0b3c76..19d5a4c2 100644 --- a/vllm/model_executor/models/idefics3.py +++ b/vllm/model_executor/models/idefics3.py @@ -404,7 +404,6 @@ class Idefics3Model(nn.Module): quant_config = vllm_config.quant_config self.config = config - self.padding_idx = self.config.text_config.pad_token_id self.vocab_size = self.config.text_config.vocab_size self.vision_model = Idefics3VisionTransformer( config.vision_config, diff --git a/vllm/model_executor/models/internlm2.py b/vllm/model_executor/models/internlm2.py index 41ca399b..520b85c0 100644 --- a/vllm/model_executor/models/internlm2.py +++ b/vllm/model_executor/models/internlm2.py @@ -261,7 +261,6 @@ class InternLM2Model(nn.Module): quant_config = vllm_config.quant_config self.config = config - self.padding_idx = config.pad_token_id self.vocab_size = config.vocab_size self.tok_embeddings = VocabParallelEmbedding( config.vocab_size, diff --git a/vllm/model_executor/models/jamba.py b/vllm/model_executor/models/jamba.py index 58eccd6a..4ac83c6e 100644 --- a/vllm/model_executor/models/jamba.py +++ b/vllm/model_executor/models/jamba.py @@ -271,7 +271,6 @@ class JambaModel(nn.Module): lora_config = vllm_config.lora_config self.config = config - self.padding_idx = config.pad_token_id lora_vocab = ((lora_config.lora_extra_vocab_size * (lora_config.max_loras or 1)) if lora_config else 0) self.vocab_size = config.vocab_size + lora_vocab diff --git a/vllm/model_executor/models/llama.py b/vllm/model_executor/models/llama.py index a0aff9e6..81b5d9bd 100644 --- a/vllm/model_executor/models/llama.py +++ b/vllm/model_executor/models/llama.py @@ -302,7 +302,6 @@ class LlamaModel(nn.Module): self.config = config self.quant_config = quant_config - self.padding_idx = config.pad_token_id lora_vocab = (lora_config.lora_extra_vocab_size * (lora_config.max_loras or 1)) if lora_config else 0 self.vocab_size = config.vocab_size + lora_vocab diff --git a/vllm/model_executor/models/mamba.py b/vllm/model_executor/models/mamba.py index 46b9182f..7a525ad8 100644 --- a/vllm/model_executor/models/mamba.py +++ b/vllm/model_executor/models/mamba.py @@ -90,7 +90,6 @@ class MambaModel(nn.Module): is_lora_enabled = bool(lora_config) self.config = config - self.padding_idx = config.pad_token_id lora_vocab = ((lora_config.lora_extra_vocab_size * (lora_config.max_loras or 1)) if lora_config else 0) self.vocab_size = config.vocab_size + lora_vocab diff --git a/vllm/model_executor/models/minicpm.py b/vllm/model_executor/models/minicpm.py index 34e1f392..cf03396a 100644 --- a/vllm/model_executor/models/minicpm.py +++ b/vllm/model_executor/models/minicpm.py @@ -365,7 +365,6 @@ class MiniCPMModel(nn.Module): self.config = config self.cache_config = cache_config self.quant_config = quant_config - self.padding_idx = config.pad_token_id lora_vocab = (lora_config.lora_extra_vocab_size * (lora_config.max_loras or 1)) if lora_config else 0 self.vocab_size = config.vocab_size + lora_vocab diff --git a/vllm/model_executor/models/mixtral.py b/vllm/model_executor/models/mixtral.py index c8dea557..b21aa601 100644 --- a/vllm/model_executor/models/mixtral.py +++ b/vllm/model_executor/models/mixtral.py @@ -254,7 +254,6 @@ class MixtralModel(nn.Module): quant_config = vllm_config.quant_config lora_config = vllm_config.lora_config - self.padding_idx = config.pad_token_id lora_vocab = (lora_config.lora_extra_vocab_size * (lora_config.max_loras or 1)) if lora_config else 0 self.vocab_size = config.vocab_size + lora_vocab diff --git a/vllm/model_executor/models/mixtral_quant.py b/vllm/model_executor/models/mixtral_quant.py index 21b52d9f..8a893b6d 100644 --- a/vllm/model_executor/models/mixtral_quant.py +++ b/vllm/model_executor/models/mixtral_quant.py @@ -302,7 +302,6 @@ class MixtralModel(nn.Module): cache_config = vllm_config.cache_config quant_config = vllm_config.quant_config - self.padding_idx = config.pad_token_id self.vocab_size = config.vocab_size self.embed_tokens = VocabParallelEmbedding( diff --git a/vllm/model_executor/models/mllama.py b/vllm/model_executor/models/mllama.py index 2a829bf0..b1ccd8e8 100644 --- a/vllm/model_executor/models/mllama.py +++ b/vllm/model_executor/models/mllama.py @@ -1031,7 +1031,6 @@ class MllamaTextModel(nn.Module): cache_config = vllm_config.cache_config quant_config = vllm_config.quant_config - self.padding_idx = config.pad_token_id self.vocab_size = config.vocab_size self.embed_tokens = VocabParallelEmbedding(config.vocab_size + 8, config.hidden_size) diff --git a/vllm/model_executor/models/nemotron.py b/vllm/model_executor/models/nemotron.py index 3b86b914..a2b49494 100644 --- a/vllm/model_executor/models/nemotron.py +++ b/vllm/model_executor/models/nemotron.py @@ -300,7 +300,6 @@ class NemotronModel(nn.Module): lora_config = vllm_config.lora_config self.config = config - self.padding_idx = config.pad_token_id lora_vocab = (lora_config.lora_extra_vocab_size * (lora_config.max_loras or 1)) if lora_config else 0 self.vocab_size = config.vocab_size + lora_vocab diff --git a/vllm/model_executor/models/olmoe.py b/vllm/model_executor/models/olmoe.py index e27ff5de..8e72b36e 100644 --- a/vllm/model_executor/models/olmoe.py +++ b/vllm/model_executor/models/olmoe.py @@ -252,7 +252,6 @@ class OlmoeModel(nn.Module): cache_config = vllm_config.cache_config quant_config = vllm_config.quant_config - self.padding_idx = config.pad_token_id self.vocab_size = config.vocab_size self.embed_tokens = VocabParallelEmbedding( diff --git a/vllm/model_executor/models/opt.py b/vllm/model_executor/models/opt.py index e4775478..d4c2b4c4 100644 --- a/vllm/model_executor/models/opt.py +++ b/vllm/model_executor/models/opt.py @@ -200,7 +200,6 @@ class OPTDecoder(nn.Module): ): super().__init__() self.config = config - self.padding_idx = config.pad_token_id self.max_target_positions = config.max_position_embeddings self.vocab_size = config.vocab_size diff --git a/vllm/model_executor/models/orion.py b/vllm/model_executor/models/orion.py index 6668ede9..0b42666e 100644 --- a/vllm/model_executor/models/orion.py +++ b/vllm/model_executor/models/orion.py @@ -217,7 +217,6 @@ class OrionModel(nn.Module): quant_config = vllm_config.quant_config self.config = config - self.padding_idx = config.pad_token_id self.vocab_size = config.vocab_size self.embed_tokens = VocabParallelEmbedding( config.vocab_size, diff --git a/vllm/model_executor/models/phimoe.py b/vllm/model_executor/models/phimoe.py index c35c7e9f..d14425f4 100644 --- a/vllm/model_executor/models/phimoe.py +++ b/vllm/model_executor/models/phimoe.py @@ -441,7 +441,6 @@ class PhiMoEModel(nn.Module): quant_config = vllm_config.quant_config lora_config = vllm_config.lora_config - self.padding_idx = config.pad_token_id lora_vocab = ((lora_config.lora_extra_vocab_size * (lora_config.max_loras or 1)) if lora_config else 0) self.vocab_size = config.vocab_size + lora_vocab diff --git a/vllm/model_executor/models/qwen2.py b/vllm/model_executor/models/qwen2.py index fe615c41..c4d02e5d 100644 --- a/vllm/model_executor/models/qwen2.py +++ b/vllm/model_executor/models/qwen2.py @@ -284,7 +284,6 @@ class Qwen2Model(nn.Module): self.config = config self.quant_config = quant_config - self.padding_idx = config.pad_token_id self.vocab_size = config.vocab_size if get_pp_group().is_first_rank or (config.tie_word_embeddings diff --git a/vllm/model_executor/models/qwen2_moe.py b/vllm/model_executor/models/qwen2_moe.py index 41536b34..92a66568 100644 --- a/vllm/model_executor/models/qwen2_moe.py +++ b/vllm/model_executor/models/qwen2_moe.py @@ -325,7 +325,6 @@ class Qwen2MoeModel(nn.Module): cache_config = vllm_config.cache_config quant_config = vllm_config.quant_config - self.padding_idx = config.pad_token_id self.vocab_size = config.vocab_size self.embed_tokens = VocabParallelEmbedding( diff --git a/vllm/model_executor/models/solar.py b/vllm/model_executor/models/solar.py index 0f9e517a..1cae0a7f 100644 --- a/vllm/model_executor/models/solar.py +++ b/vllm/model_executor/models/solar.py @@ -269,7 +269,6 @@ class SolarModel(nn.Module): lora_config = vllm_config.lora_config self.config = config - self.padding_idx = config.pad_token_id lora_vocab = ((lora_config.lora_extra_vocab_size * (lora_config.max_loras or 1)) if lora_config else 0) self.vocab_size = config.vocab_size + lora_vocab diff --git a/vllm/model_executor/models/starcoder2.py b/vllm/model_executor/models/starcoder2.py index 90098af9..3d11dfd7 100644 --- a/vllm/model_executor/models/starcoder2.py +++ b/vllm/model_executor/models/starcoder2.py @@ -212,10 +212,8 @@ class Starcoder2Model(nn.Module): quant_config = vllm_config.quant_config self.config = config - self.padding_idx = config.pad_token_id self.vocab_size = config.vocab_size - # TODO: consider padding_idx (currently removed) self.embed_tokens = VocabParallelEmbedding( config.vocab_size, config.hidden_size, diff --git a/vllm/model_executor/models/whisper.py b/vllm/model_executor/models/whisper.py index 1cb026f4..8ed68bd8 100644 --- a/vllm/model_executor/models/whisper.py +++ b/vllm/model_executor/models/whisper.py @@ -49,10 +49,7 @@ class WhisperAudioInputs(TypedDict): class WhisperPositionalEmbedding(nn.Embedding): - def __init__(self, - num_positions: int, - embedding_dim: int, - padding_idx: Optional[int] = None): + def __init__(self, num_positions: int, embedding_dim: int): super().__init__(num_positions, embedding_dim) def forward(self, position_ids): @@ -359,7 +356,6 @@ class WhisperEncoder(nn.Module): config = vllm_config.model_config.hf_config embed_dim = config.d_model self.num_mel_bins = config.num_mel_bins - self.padding_idx = config.pad_token_id self.max_source_positions = config.max_source_positions self.embed_scale = (math.sqrt(embed_dim) if config.scale_embedding else 1.0)