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
grounding_dino/modeling_grounding_dino.py:GroundingDinoConvEncoder
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[ "ModelConvEncoder", "Module", "None", "True", "__init__", "and", "append", "backbone", "backbone_config", "backbone_model_type", "bool", "channels", "class", "config", "def", "feature_map", "feature_maps", "features", "float", "for", "forward", "functional", "if", "in",...
grounding_dino/modeling_grounding_dino.py:GroundingDinoConvModel
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[ "ModelConvModel", "Module", "__init__", "class", "conv_encoder", "def", "dtype", "feature_map", "for", "forward", "in", "mask", "nn", "out", "pixel_mask", "pixel_values", "pos", "position_embedding", "return", "self", "super", "to" ]
grounding_dino/modeling_grounding_dino.py:GroundingDinoSinePositionEmbedding
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[ "ModelSinePositionEmbedding", "Module", "None", "__init__", "arange", "cat", "class", "config", "cos", "cumsum", "d_model", "def", "device", "dim", "dim_t", "div", "dtype", "embedding_dim", "eps", "flatten", "float32", "floor", "forward", "math", "nn", "permute", ...
grounding_dino/modeling_grounding_dino.py:GroundingDinoLearnedPositionEmbedding
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[ "Embedding", "ModelLearnedPositionEmbedding", "Module", "None", "__init__", "arange", "cat", "class", "column_embeddings", "config", "d_model", "def", "device", "dim", "embedding_dim", "forward", "height", "height_values", "nn", "permute", "pixel_mask", "pixel_values", "p...
grounding_dino/modeling_grounding_dino.py:build_position_encoding
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[ "ModelLearnedPositionEmbedding", "ModelSinePositionEmbedding", "Model_position_encoding", "config", "def", "elif", "else", "if", "learned", "position_embedding", "position_embedding_type", "return", "sine" ]
grounding_dino/modeling_grounding_dino.py:GroundingDinoMultiscaleDeformableAttention
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[ "CUDA", "F", "False", "Linear", "Make", "ModelMultiscaleDeformableAttention", "Module", "MultiScaleDeformableAttention", "None", "ValueError", "You", "_", "__init__", "a", "align", "and", "attention", "attention_mask", "attention_weights", "attn", "authors", "batch_size", ...
grounding_dino/modeling_grounding_dino.py:GroundingDinoTextEnhancerLayer
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[ "ACT2FN", "LayerNorm", "Linear", "ModelMultiheadAttention", "ModelTextEnhancerLayer", "Module", "None", "True", "__init__", "activation", "activation_function", "and", "attention_mask", "attention_masks", "attention_output", "attention_weights", "class", "config", "d_model", "d...
grounding_dino/modeling_grounding_dino.py:GroundingDinoBiMultiHeadAttention
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[ "Attention", "F", "Linear", "ModelBiMultiHeadAttention", "Module", "None", "True", "ValueError", "_", "__init__", "_reshape", "and", "attn_weights", "attn_weights_transposed", "batch_size", "be", "bmm", "but", "by", "clamp", "class", "config", "contiguous", "d_model", ...
grounding_dino/modeling_grounding_dino.py:GroundingDinoDropPath
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[ "ModelDropPath", "Module", "__init__", "class", "def", "device", "div", "drop_prob", "dtype", "extra_repr", "f", "floor", "forward", "hidden_states", "if", "keep_prob", "ndim", "nn", "not", "or", "p", "rand", "random_tensor", "return", "self", "shape", "super", ...
grounding_dino/modeling_grounding_dino.py:GroundingDinoFusionLayer
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[ "Identity", "LayerNorm", "ModelBiMultiHeadAttention", "ModelDropPath", "ModelFusionLayer", "Module", "None", "Parameter", "True", "__init__", "attention_mask_text", "attention_mask_vision", "attn", "class", "config", "d_model", "def", "delta_t", "delta_v", "drop_path", "else"...
grounding_dino/modeling_grounding_dino.py:GroundingDinoDeformableLayer
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[ "ACT2FN", "False", "LayerNorm", "Linear", "ModelDeformableLayer", "ModelMultiscaleDeformableAttention", "Module", "None", "__init__", "activation_dropout", "activation_fn", "activation_function", "all", "attention_mask", "attn_weights", "clamp", "clamp_value", "class", "config", ...
grounding_dino/modeling_grounding_dino.py:GroundingDinoEncoderLayer
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[ "ModelDeformableLayer", "ModelEncoderLayer", "ModelFusionLayer", "ModelTextEnhancerLayer", "Module", "None", "_", "__init__", "and", "arange", "attention_mask", "attention_mask_text", "attention_mask_vision", "attention_masks", "batch_size", "class", "config", "d_model", "def", ...
grounding_dino/modeling_grounding_dino.py:GroundingDinoMultiheadAttention
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[ "Dropout", "False", "Linear", "ModelMultiheadAttention", "Module", "None", "The", "ValueError", "_", "__init__", "a", "all_head_size", "and", "attention", "attention_dropout", "attention_head_size", "attention_mask", "attention_probs", "attention_scores", "batch_size", "class...
grounding_dino/modeling_grounding_dino.py:GroundingDinoDecoderLayer
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[ "ACT2FN", "False", "LayerNorm", "Linear", "ModelDecoderLayer", "ModelMultiheadAttention", "ModelMultiscaleDeformableAttention", "Module", "None", "True", "__init__", "activation_dropout", "activation_fn", "activation_function", "attention_mask", "class", "config", "cross_attn_weigh...
grounding_dino/modeling_grounding_dino.py:GroundingDinoContrastiveEmbedding
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[ "ModelContrastiveEmbedding", "Module", "None", "__init__", "class", "config", "def", "device", "float", "forward", "full", "inf", "masked_fill", "max_text_len", "new_output", "nn", "output", "return", "self", "shape", "super", "text_hidden_state", "text_token_mask", "to...
grounding_dino/modeling_grounding_dino.py:GroundingDinoPreTrainedModel
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[ "False", "ModelBiMultiHeadAttention", "ModelConfig", "ModelDecoder", "ModelFusionLayer", "ModelLearnedPositionEmbedding", "ModelMLPPredictionHead", "ModelMultiscaleDeformableAttention", "ModelPreTrainedModel", "PreTrainedModel", "True", "_init_weights", "_set_gradient_checkpointing", "abs"...
grounding_dino/modeling_grounding_dino.py:GroundingDinoEncoder
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[ "ModelEncoder", "ModelEncoderLayer", "ModelEncoderOutput", "ModelPreTrainedModel", "ModuleList", "None", "_", "__init__", "all_attn_deformable", "all_attn_enhanced_text", "all_attn_fused_text", "all_attn_fused_vision", "all_attns", "append", "attentions", "cat", "class", "config", ...
grounding_dino/modeling_grounding_dino.py:GroundingDinoDecoder
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[ "False", "Last", "LayerNorm", "ModelDecoder", "ModelDecoderLayer", "ModelDecoderOutput", "ModelMLPPredictionHead", "ModelPreTrainedModel", "ModuleList", "None", "ValueError", "_", "__init__", "all_attns", "all_cross_attns_text", "all_cross_attns_vision", "all_hidden_states", "all_s...
grounding_dino/modeling_grounding_dino.py:generate_masks_with_special_tokens_and_transfer_map
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[ "Model_masks_with_special_tokens_and_transfer_map", "SPECIAL_TOKENS", "arange", "attention_mask", "batch_size", "bool", "clamp", "cummax", "cummin", "def", "device", "dim", "dims", "dtype", "expand", "eye", "flip", "full", "identity", "indices", "input_ids", "isin", "long...
grounding_dino/modeling_grounding_dino.py:GroundingDinoModel
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[ "AutoModel", "Conv2d", "Embedding", "False", "GroupNorm", "LayerNorm", "Linear", "ModelContrastiveEmbedding", "ModelConvEncoder", "ModelConvModel", "ModelDecoder", "ModelEncoder", "ModelEncoderOutput", "ModelMLPPredictionHead", "ModelModel", "ModelModelOutput", "ModelPreTrainedModel"...
grounding_dino/modeling_grounding_dino.py:GroundingDinoMLPPredictionHead
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grounding_dino/modeling_grounding_dino.py:build_label_maps
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[ "F", "Model_label_maps", "None", "SPECIAL_TOKENS", "cumsum", "def", "delimiter_token_masks", "delimiter_tokens", "device", "dim", "for", "in", "input_ids", "int32", "isin", "label_group", "label_groups", "label_map", "label_maps", "logits", "max_seq_len", "num_labels", "p...
grounding_dino/modeling_grounding_dino.py:build_text_mask
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[ "Model_text_mask", "None", "attention_mask", "bool", "def", "device", "dtype", "logits", "return", "seq_len", "shape", "text_mask", "torch", "zeros_like" ]
grounding_dino/modeling_grounding_dino.py:GroundingDinoForObjectDetection
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[ "FloatTensor", "LongTensor", "ModelContrastiveEmbedding", "ModelForObjectDetection", "ModelMLPPredictionHead", "ModelModel", "ModelObjectDetectionOutput", "ModelPreTrainedModel", "ModuleList", "None", "_", "__init__", "_keys_to_ignore_on_load_missing", "_keys_to_ignore_on_load_unexpected",...
gemma4/modeling_gemma4.py:Gemma4ModelOutputWithPast
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[ "BaseModelOutputWithPast", "ModelModelOutputWithPast", "None", "Tensor", "audio_hidden_states", "class", "image_hidden_states", "r", "shared_kv_states", "torch", "tuple" ]
gemma4/modeling_gemma4.py:Gemma4CausalLMOutputWithPast
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[ "ModelCausalLMOutputWithPast", "ModelOutput", "None", "Tensor", "attentions", "audio_hidden_states", "class", "hidden_states", "image_hidden_states", "logits", "loss", "past_key_values", "r", "shared_kv_states", "torch", "tuple" ]
gemma4/modeling_gemma4.py:Gemma4TextModelOutputWithPast
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[ "BaseModelOutputWithPast", "ModelTextModelOutputWithPast", "None", "Tensor", "class", "shared_kv_states", "torch", "tuple" ]
gemma4/modeling_gemma4.py:Gemma4AudioModelOutput
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[ "BaseModelOutputWithPooling", "ModelAudioModelOutput", "None", "attention_mask", "class", "r" ]
gemma4/modeling_gemma4.py:Gemma4ClippableLinear
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[ "Linear", "ModelClippableLinear", "Module", "__init__", "clamp", "class", "config", "def", "float", "forward", "hidden_states", "if", "in_features", "inf", "input_max", "input_min", "linear", "nn", "out_features", "output_max", "output_min", "register_buffer", "return", ...
gemma4/modeling_gemma4.py:Gemma4RMSNorm
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[ "ModelRMSNorm", "Module", "Parameter", "True", "__init__", "_norm", "class", "def", "dim", "eps", "float", "forward", "hidden_states", "if", "keepdim", "mean", "mean_squared", "nn", "normed_output", "ones", "pow", "requires_grad", "return", "self", "super", "torch",...
gemma4/modeling_gemma4.py:Gemma4AudioRelPositionalEncoding
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gemma4/modeling_gemma4.py:Gemma4AudioAttention
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gemma4/modeling_gemma4.py:Gemma4AudioSubSampleConvProjectionLayer
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[ "Conv2d", "LayerNorm", "ModelAudioSubSampleConvProjectionLayer", "Module", "None", "ReLU", "True", "__init__", "act", "class", "contiguous", "conv", "def", "device", "dtype", "elementwise_affine", "eps", "forward", "hidden_states", "if", "in_channels", "is", "kernel_size"...
gemma4/modeling_gemma4.py:Gemma4AudioSubSampleConvProjection
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gemma4/modeling_gemma4.py:Gemma4AudioFeedForward
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gemma4/modeling_gemma4.py:Gemma4AudioCausalConv1d
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[ "Conv1d", "ModelAudioCausalConv1d", "cached_property", "class", "def", "dilation", "effective_kernel_size", "forward", "functional", "kernel_size", "left_pad", "nn", "pad", "return", "self", "stride", "super", "x" ]
gemma4/modeling_gemma4.py:Gemma4AudioLightConv1d
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[ "ACT2FN", "ModelAudioCausalConv1d", "ModelAudioLightConv1d", "ModelClippableLinear", "ModelRMSNorm", "Module", "True", "__init__", "act_fn", "clamp", "class", "config", "conv_kernel_size", "conv_norm", "def", "depthwise_conv1d", "dim", "dtype", "eps", "finfo", "forward", "f...
gemma4/modeling_gemma4.py:Gemma4AudioLayer
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gemma4/modeling_gemma4.py:Gemma4VisionPatchEmbedder
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gemma4/modeling_gemma4.py:Gemma4VisionPooler
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gemma4/modeling_gemma4.py:Gemma4VisionMLP
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[ "ACT2FN", "ModelClippableLinear", "ModelVisionMLP", "Module", "__init__", "act_fn", "class", "config", "def", "down_proj", "forward", "gate_proj", "hidden_activation", "hidden_size", "intermediate_size", "nn", "return", "self", "super", "up_proj", "x" ]
gemma4/modeling_gemma4.py:Gemma4VisionRotaryEmbedding
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gemma4/modeling_gemma4.py:rotate_half
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[ "Model_half", "cat", "def", "dim", "return", "shape", "torch", "x", "x1", "x2" ]
gemma4/modeling_gemma4.py:apply_rotary_pos_emb
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[ "Model_rotary_pos_emb", "cos", "def", "return", "rotate_half", "sin", "unsqueeze", "unsqueeze_dim", "x" ]
gemma4/modeling_gemma4.py:repeat_kv
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[ "Model_kv", "None", "batch", "def", "expand", "head_dim", "hidden_states", "if", "n_rep", "num_key_value_heads", "reshape", "return", "shape", "slen" ]
gemma4/modeling_gemma4.py:eager_attention_forward
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gemma4/modeling_gemma4.py:apply_multidimensional_rope
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gemma4/modeling_gemma4.py:Gemma4VisionAttention
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gemma4/modeling_gemma4.py:Gemma4VisionEncoderLayer
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gemma4/modeling_gemma4.py:Gemma4VisionEncoder
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gemma4/modeling_gemma4.py:Gemma4TextMLP
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gemma4/modeling_gemma4.py:Gemma4TextRotaryEmbedding
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gemma4/modeling_gemma4.py:Gemma4TextAttention
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gemma4/modeling_gemma4.py:Gemma4TextExperts
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gemma4/modeling_gemma4.py:Gemma4TextRouter
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gemma4/modeling_gemma4.py:Gemma4TextDecoderLayer
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gemma4/modeling_gemma4.py:Gemma4TextScaledWordEmbedding
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gemma4/modeling_gemma4.py:Gemma4PreTrainedModel
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[ "ModelAudioAttention", "ModelAudioLayer", "ModelAudioRelPositionalEncoding", "ModelClippableLinear", "ModelConfig", "ModelPreTrainedModel", "ModelTextDecoderLayer", "ModelTextExperts", "ModelTextRotaryEmbedding", "ModelTextRouter", "ModelTextScaledWordEmbedding", "ModelVisionEncoderLayer", "...
gemma4/modeling_gemma4.py:Gemma4TextModel
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gemma4/modeling_gemma4.py:Gemma4ForCausalLM
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gemma4/modeling_gemma4.py:sliding_window_mask_function
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[ "Model_window", "Model_window_mask_function", "batch_idx", "def", "dist", "head_idx", "inner_mask", "int", "kv_idx", "left_mask", "left_window_size", "q_idx", "return", "right_mask", "right_window_size" ]
gemma4/modeling_gemma4.py:Gemma4AudioModel
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gemma4/modeling_gemma4.py:Gemma4VisionModel
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gemma4/modeling_gemma4.py:Gemma4MultimodalEmbedder
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gemma4/modeling_gemma4.py:create_masks_for_vision_model
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gemma4/modeling_gemma4.py:get_block_sequence_ids_for_mask
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gemma4/modeling_gemma4.py:Gemma4Model
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gemma4/modeling_gemma4.py:Gemma4ForConditionalGeneration
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:KyutaiSpeechToTextFlexibleLinear
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:KyutaiSpeechToTextPreTrainedModel
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:KyutaiSpeechToTextConv1dPaddingCache
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:KyutaiSpeechToTextEmbeddings
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:KyutaiSpeechToTextRMSNorm
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:KyutaiSpeechToTextLinear
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:KyutaiSpeechToTextRotaryEmbedding
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:KyutaiSpeechToTextGatingMLP
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:rotate_half
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:apply_rotary_pos_emb
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:repeat_kv
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:eager_attention_forward
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:KyutaiSpeechToTextAttention
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:KyutaiSpeechToTextDecoderLayer
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:KyutaiSpeechToTextModel
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kyutai_speech_to_text/modeling_kyutai_speech_to_text.py:KyutaiSpeechToTextForConditionalGeneration
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siglip/modeling_siglip.py:SiglipVisionModelOutput
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siglip/modeling_siglip.py:SiglipTextModelOutput
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siglip/modeling_siglip.py:SiglipOutput
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siglip/modeling_siglip.py:SiglipVisionEmbeddings
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siglip/modeling_siglip.py:SiglipTextEmbeddings
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siglip/modeling_siglip.py:eager_attention_forward
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siglip/modeling_siglip.py:SiglipAttention
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siglip/modeling_siglip.py:SiglipMLP
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siglip/modeling_siglip.py:SiglipEncoderLayer
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[ "GradientCheckpointingLayer", "LayerNorm", "ModelAttention", "ModelEncoderLayer", "ModelMLP", "_", "__init__", "attention_mask", "auto_docstring", "class", "config", "def", "embed_dim", "eps", "forward", "hidden_size", "hidden_states", "kwargs", "layer_norm1", "layer_norm2", ...
siglip/modeling_siglip.py:SiglipPreTrainedModel
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[ "Conv2d", "Embedding", "Linear", "Model", "ModelAttention", "ModelConfig", "ModelEncoderLayer", "ModelForImageClassification", "ModelMLP", "ModelModel", "ModelMultiheadAttentionPoolingHead", "ModelPreTrainedModel", "ModelTextEmbeddings", "ModelVisionEmbeddings", "None", "PreTrainedMode...
siglip/modeling_siglip.py:SiglipEncoder
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[ "BaseModelOutput", "False", "ModelEncoder", "ModelEncoderLayer", "Module", "ModuleList", "None", "_", "__init__", "attention_mask", "auto_docstring", "class", "config", "def", "encoder_layer", "for", "forward", "gradient_checkpointing", "hidden_states", "in", "inputs_embeds",...
siglip/modeling_siglip.py:SiglipTextModel
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[ "BaseModelOutputWithPooling", "False", "LayerNorm", "Linear", "ModelEncoder", "ModelPreTrainedModel", "ModelTextConfig", "ModelTextEmbeddings", "ModelTextModel", "None", "__init__", "_input_embed_layer", "attention_mask", "auto_docstring", "base_model_prefix", "capture_outputs", "cla...
siglip/modeling_siglip.py:SiglipVisionModel
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[ "BaseModelOutputWithPooling", "False", "LayerNorm", "ModelEncoder", "ModelMultiheadAttentionPoolingHead", "ModelPreTrainedModel", "ModelVisionConfig", "ModelVisionEmbeddings", "ModelVisionModel", "None", "True", "__init__", "_input_embed_layer", "auto_docstring", "base_model_prefix", "...
siglip/modeling_siglip.py:SiglipMultiheadAttentionPoolingHead
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[ "LayerNorm", "ModelMLP", "ModelMultiheadAttentionPoolingHead", "Module", "MultiheadAttention", "Parameter", "True", "__init__", "attention", "batch_first", "batch_size", "class", "config", "def", "eps", "forward", "hidden_size", "hidden_state", "layer_norm_eps", "layernorm", ...
siglip/modeling_siglip.py:SiglipModel
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[ "False", "ModelConfig", "ModelModel", "ModelOutput", "ModelPreTrainedModel", "ModelTextModel", "ModelVisionModel", "None", "Parameter", "True", "__init__", "_from_config", "attention_mask", "auto_docstring", "can_return_tuple", "class", "config", "def", "device", "dim", "embe...
siglip/modeling_siglip.py:SiglipForImageClassification
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[ "False", "Identity", "ImageClassifierOutput", "Linear", "ModelForImageClassification", "ModelPreTrainedModel", "ModelVisionModel", "None", "__init__", "_from_config", "attentions", "auto_docstring", "can_return_tuple", "class", "classifier", "config", "def", "dim", "else", "emb...