Datasets:
itazap
/
transformers_code_embeddings_v3

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1
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24
117
embedding
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2.56k
2.56k
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4
444
dab_detr/modeling_dab_detr.py:DabDetrConvModel
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dab_detr/modeling_dab_detr.py:DabDetrSinePositionEmbedding
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dab_detr/modeling_dab_detr.py:inverse_sigmoid
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[ "Model_sigmoid", "clamp", "def", "eps", "log", "max", "min", "return", "torch", "x", "x1", "x2" ]
dab_detr/modeling_dab_detr.py:DetrAttention
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[ "False", "Linear", "ModelAttention", "Module", "None", "ValueError", "__init__", "and", "attention_dropout", "attention_mask", "attn_output", "attn_weights", "batch_size", "be", "but", "by", "class", "config", "contiguous", "def", "dim", "divisible", "dropout", "dtype",...
dab_detr/modeling_dab_detr.py:DabDetrAttention
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dab_detr/modeling_dab_detr.py:DabDetrDecoderLayerSelfAttention
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dab_detr/modeling_dab_detr.py:DabDetrDecoderLayerCrossAttention
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[ "False", "LayerNorm", "Linear", "ModelAttention", "ModelDecoderLayerCrossAttention", "Module", "None", "True", "_", "__init__", "and", "attention_mask", "batch_size", "cat", "class", "config", "cross_attn", "cross_attn_key_content_proj", "cross_attn_key_pos_proj", "cross_attn_l...
dab_detr/modeling_dab_detr.py:DabDetrDecoderLayerFFN
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dab_detr/modeling_dab_detr.py:DabDetrEncoderLayer
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dab_detr/modeling_dab_detr.py:DabDetrDecoderLayer
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dab_detr/modeling_dab_detr.py:DabDetrMLP
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dab_detr/modeling_dab_detr.py:DabDetrPreTrainedModel
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[ "ModelConfig", "ModelConvEncoder", "ModelDecoderLayer", "ModelEncoderLayer", "ModelForObjectDetection", "ModelMHAttentionMap", "ModelPreTrainedModel", "PReLU", "PreTrainedModel", "_init_weights", "_no_split_modules", "base_model_prefix", "bbox_predictor", "bias", "bias_value", "class",...
dab_detr/modeling_dab_detr.py:DabDetrEncoder
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[ "BaseModelOutput", "False", "LayerNorm", "ModelEncoder", "ModelEncoderLayer", "ModelMLP", "ModelPreTrainedModel", "ModuleList", "None", "_", "__init__", "all_attentions", "attention_mask", "attentions", "class", "config", "create_bidirectional_mask", "def", "dropout", "else", ...
dab_detr/modeling_dab_detr.py:DabDetrDecoder
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dab_detr/modeling_dab_detr.py:DabDetrModel
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[ "BaseModelOutput", "Conv2d", "Embedding", "False", "ModelConvEncoder", "ModelConvModel", "ModelDecoder", "ModelEncoder", "ModelModel", "ModelModelOutput", "ModelPreTrainedModel", "ModelSinePositionEmbedding", "None", "True", "_", "__init__", "and", "attention_mask", "attentions",...
dab_detr/modeling_dab_detr.py:DabDetrMHAttentionMap
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dab_detr/modeling_dab_detr.py:DabDetrForObjectDetection
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[ "Linear", "ModelForObjectDetection", "ModelMLP", "ModelModel", "ModelObjectDetectionOutput", "ModelPreTrainedModel", "None", "__init__", "_set_aux_loss", "_tied_weights_keys", "a", "auto_docstring", "auxiliary_loss", "auxiliary_outputs", "b", "bbox_embed", "bbox_predictor", "bbox_w...
layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2Embeddings
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[ "Dropout", "Embedding", "False", "IndexError", "LayerNorm", "ModelEmbeddings", "Module", "__init__", "_calc_spatial_position_embeddings", "arange", "as", "bbox", "cat", "class", "config", "coordinate_size", "def", "dim", "dropout", "e", "eps", "except", "expand", "from"...
layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2SelfAttention
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[ "Dropout", "Linear", "ModelSelfAttention", "Module", "None", "Parameter", "The", "ValueError", "__init__", "_sz", "a", "all_head_size", "and", "attention", "attention_head_size", "attention_mask", "attention_probs", "attention_probs_dropout_prob", "attention_scores", "batch_siz...
layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2Attention
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layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2SelfOutput
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layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2Intermediate
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layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2Output
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layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2Layer
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[ "False", "GradientCheckpointingLayer", "ModelAttention", "ModelIntermediate", "ModelLayer", "ModelOutput", "None", "__init__", "apply_chunking_to_forward", "attention", "attention_mask", "attention_output", "chunk_size_feed_forward", "class", "config", "def", "feed_forward_chunk", ...
layoutlmv2/modeling_layoutlmv2.py:relative_position_bucket
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layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2Encoder
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[ "BaseModelOutput", "False", "Linear", "ModelEncoder", "ModelLayer", "Module", "ModuleList", "None", "_", "__init__", "_calculate_1d_position_embeddings", "_calculate_2d_position_embeddings", "attention_mask", "bbox", "class", "config", "contiguous", "def", "else", "for", "for...
layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2PreTrainedModel
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layoutlmv2/modeling_layoutlmv2.py:my_convert_sync_batchnorm
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layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2VisualBackbone
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layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2Pooler
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layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2Model
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layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2ForSequenceClassification
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layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2ForTokenClassification
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layoutlmv2/modeling_layoutlmv2.py:LayoutLMv2ForQuestionAnswering
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informer/modeling_informer.py:InformerFeatureEmbedder
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informer/modeling_informer.py:InformerStdScaler
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informer/modeling_informer.py:InformerMeanScaler
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informer/modeling_informer.py:InformerNOPScaler
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informer/modeling_informer.py:InformerSinusoidalPositionalEmbedding
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informer/modeling_informer.py:InformerValueEmbedding
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informer/modeling_informer.py:InformerPreTrainedModel
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informer/modeling_informer.py:eager_attention_forward
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informer/modeling_informer.py:InformerAttention
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informer/modeling_informer.py:InformerProbSparseAttention
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informer/modeling_informer.py:InformerConvLayer
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informer/modeling_informer.py:InformerEncoderLayer
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informer/modeling_informer.py:InformerDecoderLayer
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informer/modeling_informer.py:InformerEncoder
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informer/modeling_informer.py:InformerDecoder
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informer/modeling_informer.py:InformerModel
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informer/modeling_informer.py:weighted_average
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informer/modeling_informer.py:nll
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informer/modeling_informer.py:InformerForPrediction
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lfm2/modeling_lfm2.py:Lfm2RMSNorm
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lfm2/modeling_lfm2.py:Lfm2RotaryEmbedding
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lfm2/modeling_lfm2.py:Lfm2MLP
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lfm2/modeling_lfm2.py:rotate_half
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lfm2/modeling_lfm2.py:apply_rotary_pos_emb
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lfm2/modeling_lfm2.py:repeat_kv
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lfm2/modeling_lfm2.py:eager_attention_forward
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lfm2/modeling_lfm2.py:Lfm2Attention
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lfm2/modeling_lfm2.py:apply_mask_to_padding_states
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lfm2/modeling_lfm2.py:causal_conv1d_update
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lfm2/modeling_lfm2.py:causal_conv1d_fn
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lfm2/modeling_lfm2.py:Lfm2ShortConv
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lfm2/modeling_lfm2.py:Lfm2DecoderLayer
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lfm2/modeling_lfm2.py:Lfm2PreTrainedModel
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lfm2/modeling_lfm2.py:Lfm2Model
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lfm2/modeling_lfm2.py:Lfm2ForCausalLM
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vits/modeling_vits.py:VitsModelOutput
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vits/modeling_vits.py:VitsTextEncoderOutput
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vits/modeling_vits.py:fused_add_tanh_sigmoid_multiply
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vits/modeling_vits.py:_unconstrained_rational_quadratic_spline
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vits/modeling_vits.py:_rational_quadratic_spline
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vits/modeling_vits.py:VitsWaveNet
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vits/modeling_vits.py:VitsPosteriorEncoder
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vits/modeling_vits.py:HifiGanResidualBlock
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vits/modeling_vits.py:VitsHifiGan
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vits/modeling_vits.py:VitsResidualCouplingLayer
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vits/modeling_vits.py:VitsResidualCouplingBlock
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vits/modeling_vits.py:VitsDilatedDepthSeparableConv
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vits/modeling_vits.py:VitsConvFlow
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vits/modeling_vits.py:VitsElementwiseAffine
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vits/modeling_vits.py:VitsStochasticDurationPredictor
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vits/modeling_vits.py:VitsDurationPredictor
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vits/modeling_vits.py:VitsAttention
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vits/modeling_vits.py:VitsFeedForward
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vits/modeling_vits.py:VitsEncoderLayer
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vits/modeling_vits.py:VitsEncoder
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vits/modeling_vits.py:VitsTextEncoder
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vits/modeling_vits.py:VitsPreTrainedModel
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vits/modeling_vits.py:VitsModel
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grounding_dino/modeling_grounding_dino.py:encode_sinusoidal_position_embedding
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grounding_dino/modeling_grounding_dino.py:MultiScaleDeformableAttention
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grounding_dino/modeling_grounding_dino.py:GroundingDinoDecoderOutput
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[ "ModelDecoderOutput", "ModelOutput", "None", "attentions", "class", "hidden_states", "intermediate_hidden_states", "intermediate_reference_points", "last_hidden_state", "r" ]
grounding_dino/modeling_grounding_dino.py:GroundingDinoEncoderOutput
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grounding_dino/modeling_grounding_dino.py:GroundingDinoModelOutput
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grounding_dino/modeling_grounding_dino.py:GroundingDinoObjectDetectionOutput
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grounding_dino/modeling_grounding_dino.py:GroundingDinoFrozenBatchNorm2d
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grounding_dino/modeling_grounding_dino.py:replace_batch_norm
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[ "BatchNorm2d", "ModelFrozenBatchNorm2d", "Model_batch_norm", "_modules", "bias", "children", "copy_", "def", "device", "for", "if", "in", "isinstance", "len", "list", "meta", "model", "module", "name", "named_children", "new_module", "nn", "num_features", "r", "runnin...