Datasets:
itazap
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transformers_code_embeddings_v3

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1
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24
102
embedding
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4
448
efficientloftr/modeling_efficientloftr.py:repeat_kv
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efficientloftr/modeling_efficientloftr.py:eager_attention_forward
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efficientloftr/modeling_efficientloftr.py:EfficientLoFTRAttention
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efficientloftr/modeling_efficientloftr.py:EfficientLoFTRMLP
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efficientloftr/modeling_efficientloftr.py:EfficientLoFTRAggregatedAttention
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efficientloftr/modeling_efficientloftr.py:EfficientLoFTRLocalFeatureTransformerLayer
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efficientloftr/modeling_efficientloftr.py:EfficientLoFTRLocalFeatureTransformer
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efficientloftr/modeling_efficientloftr.py:EfficientLoFTROutConvBlock
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efficientloftr/modeling_efficientloftr.py:EfficientLoFTRFineFusionLayer
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efficientloftr/modeling_efficientloftr.py:EfficientLoFTRPreTrainedModel
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efficientloftr/modeling_efficientloftr.py:EfficientLoFTRModel
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efficientloftr/modeling_efficientloftr.py:mask_border
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efficientloftr/modeling_efficientloftr.py:create_meshgrid
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efficientloftr/modeling_efficientloftr.py:spatial_expectation2d
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efficientloftr/modeling_efficientloftr.py:EfficientLoFTRForKeypointMatching
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormEmbeddings
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:eager_attention_forward
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormSelfAttention
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormCrossAttention
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormSelfOutput
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormAttention
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormIntermediate
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormOutput
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormLayer
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormEncoder
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormPooler
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormPreTrainedModel
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormModel
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormForCausalLM
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormForMaskedLM
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roberta_prelayernorm/modeling_roberta_prelayernorm.py:RobertaPreLayerNormLMHead
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:_get_feat_extract_output_lengths
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoePreTrainedModelForConditionalGeneration
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:repeat_kv
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:eager_attention_forward
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeAudioAttention
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeAudioEncoderLayer
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeAudioEncoder
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:rotate_half
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:apply_rotary_pos_emb_vision
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeVisionAttention
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeVisionRotaryEmbedding
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTextTopKRouter
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeVisionMLP
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeVisionBlock
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeVisionPatchEmbed
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeVisionEncoder
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeThinkerTextRotaryEmbedding
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeThinkerTextExperts
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeThinkerTextTopKRouter
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeThinkerTextSparseMoeBlock
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qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeThinkerTextRMSNorm
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[ "ModelThinkerTextRMSNorm", "Module", "Parameter", "True", "__init__", "class", "def", "eps", "extra_repr", "f", "float32", "forward", "hidden_size", "hidden_states", "keepdim", "mean", "nn", "ones", "pow", "return", "rsqrt", "self", "shape", "super", "to", "torch", ...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:apply_rotary_pos_emb
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[ "Model_rotary_pos_emb", "cos", "def", "k", "k_embed", "q", "q_embed", "return", "rotate_half", "sin", "unsqueeze", "unsqueeze_dim" ]
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeThinkerTextAttention
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[ "ALL_ATTENTION_FUNCTIONS", "Linear", "ModelThinkerTextAttention", "ModelThinkerTextRMSNorm", "Module", "None", "Tensor", "True", "__init__", "_attn_implementation", "apply_rotary_pos_emb", "attention_dropout", "attention_interface", "attention_mask", "attn_output", "attn_weights", "c...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeThinkerTextMLP
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[ "ACT2FN", "Linear", "ModelThinkerTextMLP", "Module", "None", "__init__", "act_fn", "class", "config", "def", "down_proj", "else", "forward", "gate_proj", "hidden_act", "hidden_size", "if", "intermediate_size", "is", "nn", "return", "self", "super", "up_proj", "x" ]
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeThinkerTextDecoderLayer
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[ "False", "GradientCheckpointingLayer", "ModelThinkerTextAttention", "ModelThinkerTextDecoderLayer", "ModelThinkerTextMLP", "ModelThinkerTextRMSNorm", "ModelThinkerTextSparseMoeBlock", "None", "Tensor", "_", "__init__", "and", "attention_mask", "cache_position", "class", "config", "de...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeThinkerTextPreTrainedModel
[ -0.000348669447703287, 0.05392754077911377, 0.00894918292760849, 0.005288153421133757, -0.0014382614754140377, 0.05276530981063843, 0.047419045120477676, -0.019757935777306557, -0.01005330216139555, -0.006450384855270386, 0.013365662656724453, -0.005288153421133757, -0.0025133255403488874, ...
[ "ModelTextConfig", "ModelThinkerTextAttention", "ModelThinkerTextDecoderLayer", "ModelThinkerTextExperts", "ModelThinkerTextPreTrainedModel", "ModelThinkerTextTopKRouter", "OutputRecorder", "PreTrainedModel", "True", "_can_compile_fullgraph", "_can_record_outputs", "_init_weights", "_no_spli...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTextRMSNorm
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[ "ModelTextRMSNorm", "Module", "Parameter", "True", "__init__", "class", "def", "eps", "extra_repr", "f", "float32", "forward", "hidden_size", "hidden_states", "keepdim", "mean", "nn", "ones", "pow", "return", "rsqrt", "self", "shape", "super", "to", "torch", "tupl...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeThinkerTextModel
[ -0.00018215877935290337, 0.05161283537745476, 0.01290320884436369, 0.00894169695675373, -0.0009762296103872359, 0.04029422998428345, 0.04482167214155197, -0.03667227551341057, 0.0004562812391668558, 0.0008099875994957983, 0.026032788679003716, 0.014261441305279732, -0.0020232005044817924, ...
[ "BaseModelOutputWithPast", "DynamicCache", "Embedding", "False", "ModelPreTrainedModel", "ModelTextConfig", "ModelTextRMSNorm", "ModelThinkerTextAttention", "ModelThinkerTextDecoderLayer", "ModelThinkerTextModel", "ModelThinkerTextRotaryEmbedding", "ModelThinkerTextSparseMoeBlock", "ModuleLi...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeThinkerCausalLMOutputWithPast
[ -0.00032916050986386836, 0.030663128942251205, 0.006319881416857243, -0.00150682358071208, -0.001558026415295899, 0.06741207093000412, 0.054772306233644485, -0.020949237048625946, 0.008660578168928623, 0.010357583872973919, 0.013927146792411804, 0.012230141088366508, -0.0019457043381407857, ...
[ "ModelThinkerCausalLMOutputWithPast", "MoeCausalLMOutputWithPast", "None", "class", "r", "rope_deltas" ]
qwen3_omni_moe/modeling_qwen3_omni_moe.py:load_balancing_loss_func
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[ "Model_balancing_loss_func", "None", "_", "attention_mask", "batch_size", "cat", "compute_device", "concatenated_gate_logits", "def", "device", "dim", "else", "expand", "expert_attention_mask", "expert_mask", "float", "for", "functional", "gate_logits", "if", "in", "is", ...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeThinkerForConditionalGeneration
[ -0.00028381531592458487, 0.05757702887058258, -0.010567212477326393, 0.01816418021917343, -0.0011138413101434708, 0.04501061141490936, 0.051408059895038605, -0.039527084678411484, -0.003327243961393833, 0.006368887610733509, 0.021362904459238052, -0.003998404834419489, -0.0010638611856848001...
[ "False", "GenerationMixin", "Image", "Linear", "ModelAudioEncoder", "ModelAudioEncoderLayer", "ModelPreTrainedModelForConditionalGeneration", "ModelThinkerCausalLMOutputWithPast", "ModelThinkerConfig", "ModelThinkerForConditionalGeneration", "ModelThinkerTextAttention", "ModelThinkerTextDecode...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerResizeMLP
[ -0.00029760412871837616, 0.037863850593566895, 0.04061758518218994, 0.012334437109529972, -0.0011760741472244263, 0.046125058084726334, 0.03396272659301758, -0.027766825631260872, -0.0055361539125442505, 0.00639669643715024, 0.0024955719709396362, -0.02145618200302124, -0.0004517846100497991...
[ "ACT2FN", "Linear", "ModelTalkerResizeMLP", "Module", "__init__", "act_fn", "class", "config", "def", "forward", "hidden_act", "hidden_size", "hidden_state", "intermediate_size", "linear_fc1", "linear_fc2", "nn", "return", "self", "super", "text_config", "thinker_hidden_siz...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerCodePredictorOutputWithPast
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[ "CausalLMOutputWithPast", "ModelTalkerCodePredictorOutputWithPast", "None", "class", "generation_steps", "r" ]
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeRMSNorm
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[ "ModelRMSNorm", "Module", "Parameter", "True", "__init__", "class", "def", "dtype", "eps", "extra_repr", "f", "float32", "forward", "hidden_size", "hidden_states", "input_dtype", "keepdim", "mean", "nn", "ones", "pow", "return", "rsqrt", "self", "shape", "super", ...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerCodePredictorAttention
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[ "ALL_ATTENTION_FUNCTIONS", "Linear", "ModelRMSNorm", "ModelTalkerCodePredictorAttention", "Module", "None", "Tensor", "True", "__init__", "_attn_implementation", "apply_rotary_pos_emb", "attention_dropout", "attention_interface", "attention_mask", "attn_output", "attn_weights", "cach...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeMLP
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[ "ACT2FN", "Linear", "ModelMLP", "Module", "__init__", "act_fn", "class", "config", "def", "down_proj", "forward", "gate_proj", "hidden_act", "hidden_size", "intermediate_size", "nn", "return", "self", "super", "up_proj", "x" ]
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerCodePredictorDecoderLayer
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[ "False", "GradientCheckpointingLayer", "ModelMLP", "ModelRMSNorm", "ModelTalkerCodePredictorAttention", "ModelTalkerCodePredictorDecoderLayer", "None", "Tensor", "_", "__init__", "attention_mask", "attention_type", "cache_position", "class", "config", "def", "eps", "forward", "hi...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeRotaryEmbedding
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[ "False", "ModelRotaryEmbedding", "Module", "None", "ROPE_INIT_FUNCTIONS", "Tensor", "__init__", "and", "arange", "attention_factor", "attention_scaling", "base", "cat", "class", "clone", "compute_default_rope_parameters", "config", "cos", "cpu", "def", "default", "device", ...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerCodePredictorModel
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[ "BaseModelOutputWithPast", "DynamicCache", "Embedding", "False", "ModelPreTrainedModel", "ModelRMSNorm", "ModelRotaryEmbedding", "ModelTalkerCodePredictorAttention", "ModelTalkerCodePredictorConfig", "ModelTalkerCodePredictorDecoderLayer", "ModelTalkerCodePredictorModel", "ModuleList", "None...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerCodePredictorModelForConditionalGeneration
[ -0.00024011720961425453, 0.012180167250335217, -0.019237834960222244, 0.007626833859831095, -0.0006830000202171504, 0.016619667410850525, 0.055323004722595215, -0.012806250713765621, -0.006915375590324402, -0.009505083784461021, 0.05828266963362694, 0.004781000316143036, -0.00409800047054886...
[ "False", "GenerationMixin", "Linear", "ModelPreTrainedModel", "ModelTalkerCodePredictorAttention", "ModelTalkerCodePredictorConfig", "ModelTalkerCodePredictorDecoderLayer", "ModelTalkerCodePredictorModel", "ModelTalkerCodePredictorModelForConditionalGeneration", "ModelTalkerCodePredictorOutputWith...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerOutputWithPast
[ -0.0002896391961257905, 0.01738554798066616, -0.013240648433566093, 0.008289797231554985, -0.0014823769452050328, 0.03661327064037323, 0.06723947077989578, -0.02118503861129284, 0.002317113569006324, 0.00984413456171751, 0.02199099026620388, 0.013528488576412201, -0.0031230661552399397, 0....
[ "ModelTalkerOutputWithPast", "MoeCausalLMOutputWithPast", "None", "class", "generation_step", "r" ]
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerRotaryEmbedding
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[ "ModelTalkerRotaryEmbedding", "ModelThinkerTextRotaryEmbedding", "class", "pass" ]
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerTextMLP
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[ "ACT2FN", "Linear", "ModelTalkerTextMLP", "Module", "None", "__init__", "act_fn", "class", "config", "def", "down_proj", "else", "forward", "gate_proj", "hidden_act", "hidden_size", "if", "intermediate_size", "is", "nn", "return", "self", "super", "up_proj", "x" ]
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerTextExperts
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[ "ACT2FN", "ModelTalkerTextExperts", "Module", "None", "Parameter", "__init__", "act_fn", "chunk", "class", "config", "continue", "current_hidden_states", "current_state", "def", "dim", "down_proj", "dtype", "empty", "expert_hit", "expert_idx", "expert_mask", "final_hidden_s...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerTextTopKRouter
[ -0.0003849716449622065, 0.042674750089645386, 0.005186986178159714, -0.007161577697843313, -0.0016430368414148688, 0.05375603958964348, 0.08252023905515671, -0.03112191893160343, -0.0036397320218384266, 0.017918679863214493, 0.0262885894626379, -0.016857706010341644, -0.0021072132512927055, ...
[ "F", "ModelTalkerTextTopKRouter", "Module", "Parameter", "True", "__init__", "class", "config", "def", "dim", "dtype", "float", "forward", "functional", "hidden_dim", "hidden_size", "hidden_states", "if", "keepdim", "linear", "nn", "norm_topk_prob", "num_experts", "num_...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerTextSparseMoeBlock
[ -0.00045640370808541775, 0.03182210028171539, 0.012823831290006638, -0.000048469701141584665, -0.0017439816147089005, 0.04725819081068039, 0.045358363538980484, -0.049158018082380295, -0.005165154114365578, -0.021254312247037888, 0.029447315260767937, -0.018523311242461205, -0.00102412537671...
[ "F", "Linear", "ModelTalkerTextExperts", "ModelTalkerTextMLP", "ModelTalkerTextSparseMoeBlock", "ModelTalkerTextTopKRouter", "Module", "_", "__init__", "batch_size", "class", "config", "def", "expert_output", "experts", "forward", "gate", "hidden_dim", "hidden_size", "hidden_st...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerDecoderLayer
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[ "False", "GradientCheckpointingLayer", "ModelTalkerDecoderLayer", "ModelTalkerTextSparseMoeBlock", "ModelThinkerTextAttention", "ModelThinkerTextMLP", "ModelThinkerTextRMSNorm", "ModelThinkerTextSparseMoeBlock", "None", "Tensor", "_", "__init__", "and", "attention_mask", "cache_position"...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerModel
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[ "BaseModelOutputWithPast", "DynamicCache", "Embedding", "False", "ModelPreTrainedModel", "ModelTalkerDecoderLayer", "ModelTalkerModel", "ModelTalkerRotaryEmbedding", "ModelTalkerTextConfig", "ModelTalkerTextSparseMoeBlock", "ModelTextConfig", "ModelTextRMSNorm", "ModelThinkerTextAttention", ...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeTalkerForConditionalGeneration
[ -0.0002997866540681571, 0.02750813402235508, -0.010113284923136234, 0.010228864848613739, -0.0010907900286838412, 0.04438287019729614, 0.06241341307759285, -0.038603853434324265, -0.007686096243560314, -0.007368250284343958, 0.051317695528268814, 0.004103104118257761, -0.004478740505874157, ...
[ "False", "GenerationMixin", "Linear", "ModelPreTrainedModelForConditionalGeneration", "ModelTalkerCodePredictorModelForConditionalGeneration", "ModelTalkerConfig", "ModelTalkerForConditionalGeneration", "ModelTalkerModel", "ModelTalkerOutputWithPast", "ModelTalkerResizeMLP", "ModelTalkerTextSpar...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeCausalConvNet
[ -0.00012881754082627594, 0.013190915808081627, 0.0142143489792943, -0.013361488468945026, -0.0001838981406763196, 0.03638873249292374, 0.0008670752868056297, -0.047987643629312515, 0.02251552976667881, 0.012053768150508404, 0.037525881081819534, -0.02342524752020836, 0.00282865553162992, 0...
[ "Conv1d", "F", "ModelCausalConvNet", "Module", "__init__", "_get_extra_padding_for_conv1d", "ceil", "class", "constant", "contiguous", "conv", "def", "dilation", "extra_padding", "forward", "groups", "hidden_state", "ideal_length", "in_channels", "kernel_size", "length", "m...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeCausalTransConvNet
[ -0.0002699531032703817, 0.035698167979717255, 0.04508037865161896, -0.02242577262222767, -0.0012442871229723096, 0.03661350533366203, 0.009553836658596992, -0.07093866914510727, 0.009954296983778477, 0.023455526679754257, 0.020709514617919922, -0.023112274706363678, -0.001280042459256947, ...
[ "ConvTranspose1d", "ModelCausalTransConvNet", "Module", "__init__", "ceil", "class", "contiguous", "conv", "def", "forward", "hidden_state", "in_channels", "kernel_size", "left_pad", "math", "nn", "out_channels", "pad", "return", "right_pad", "self", "shape", "stride", ...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeConvNeXtBlock
[ -0.0001233784860232845, 0.018519198521971703, 0.023631861433386803, -0.008861947804689407, -0.0006674864562228322, 0.02647222951054573, 0.02033703401684761, -0.027040302753448486, 0.009657250717282295, -0.0013065692037343979, 0.013406536541879177, -0.01107743475586176, 0.002570532960817218, ...
[ "GELU", "LayerNorm", "Linear", "ModelCausalConvNet", "ModelConvNeXtBlock", "Module", "Parameter", "__init__", "act", "class", "def", "dilation", "dim", "dwconv", "eps", "forward", "gamma", "groups", "hidden_states", "input", "kernel_size", "nn", "norm", "ones", "permu...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeCode2WavAttention
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[ "ALL_ATTENTION_FUNCTIONS", "Identity", "Linear", "ModelCode2WavAttention", "Module", "None", "Tensor", "True", "__init__", "_attn_implementation", "apply_rotary_pos_emb", "attention_dropout", "attention_interface", "attention_mask", "attn_output", "attn_weights", "cache_kwargs", "c...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeCode2WavMlp
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[ "ACT2FN", "Linear", "ModelCode2WavMlp", "Module", "__init__", "act_fn", "class", "config", "def", "down_proj", "forward", "gate_proj", "hidden_act", "hidden_size", "intermediate_size", "nn", "return", "self", "super", "up_proj", "x" ]
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeCode2WavRMSNorm
[ -0.00010198439849773422, 0.04546394199132919, 0.01980607397854328, 0.04793969914317131, -0.00038683737511746585, 0.01597990095615387, 0.035335835069417953, -0.028358696028590202, 0.006161264143884182, 0.01305400300770998, 0.044563665986061096, 0.02104395255446434, -0.001111278310418129, 0....
[ "ModelCode2WavRMSNorm", "Module", "Parameter", "True", "__init__", "class", "def", "dtype", "eps", "extra_repr", "f", "float32", "forward", "hidden_size", "hidden_states", "input_dtype", "keepdim", "mean", "nn", "ones", "pow", "return", "rsqrt", "self", "shape", "su...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeCode2WavLayerScale
[ -0.00009335677168564871, 0.030888762325048447, -0.003480622312054038, 0.024012066423892975, -0.0005988925113342702, 0.019277293235063553, 0.050504252314567566, -0.020630085840821266, 0.0035088055301457644, 0.014880717732012272, 0.016909906640648842, -0.019390026107430458, -0.0026210355572402...
[ "ModelCode2WavLayerScale", "Module", "Parameter", "True", "__init__", "channels", "class", "config", "def", "forward", "full", "hidden_size", "initial_scale", "layer_scale_initial_scale", "nn", "requires_grad", "return", "scale", "self", "super", "torch", "x" ]
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeCode2WavTransformerLayer
[ -0.0001233069779118523, 0.024689579382538795, 0.019052689895033836, -0.003170750802382827, -0.00042100524296984076, 0.022660300135612488, 0.04148751497268677, -0.019390903413295746, 0.001987003954127431, -0.02277303673326969, 0.03833085671067238, 0.049830112606287, -0.006679715123027563, 0...
[ "False", "GradientCheckpointingLayer", "ModelCode2WavAttention", "ModelCode2WavLayerScale", "ModelCode2WavMlp", "ModelCode2WavRMSNorm", "ModelCode2WavTransformerLayer", "None", "_", "__init__", "attention_mask", "attention_type", "cache_position", "class", "config", "def", "forward",...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeCode2WavTransformerModel
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[ "BaseModelOutputWithPast", "DynamicCache", "False", "ModelCode2WavAttention", "ModelCode2WavTransformerLayer", "ModelCode2WavTransformerModel", "ModelPreTrainedModel", "ModelRMSNorm", "ModelRotaryEmbedding", "ModuleList", "None", "ValueError", "You", "__init__", "_can_record_outputs", ...
qwen3_omni_moe/modeling_qwen3_omni_moe.py:SnakeBeta
[ -0.00026887215790338814, 0.0537886768579483, 0.05333283916115761, -0.024273280054330826, -0.0009900192962959409, 0.026210583746433258, 0.026438502594828606, 0.0217661801725626, 0.00257832370698452, 0.010484233498573303, 0.036238983273506165, -0.046951133757829666, 0.0028062418568879366, 0....
[ "ModelBeta", "Module", "Parameter", "__init__", "alpha", "beta", "class", "def", "exp", "forward", "hidden_states", "in_features", "nn", "no_div_by_zero", "pow", "return", "self", "sin", "super", "torch", "unsqueeze", "zeros" ]
qwen3_omni_moe/modeling_qwen3_omni_moe.py:Qwen3OmniMoeCode2WavDecoderResidualUnit
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[ "ModelCausalConvNet", "ModelCode2WavDecoderResidualUnit", "Module", "SnakeBeta", "__init__", "act1", "act2", "class", "conv1", "conv2", "def", "dilation", "dim", "forward", "hidden_state", "kernel_size", "nn", "residual", "return", "self", "super" ]