Datasets:
itazap
/
transformers_code_embeddings_v3

Dataset card Data Studio Files
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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
edgetam_video/modeling_edgetam_video.py:EdgeTamVideoPerceiverMLP
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[ "GELU", "LayerNorm", "Linear", "ModelPerceiverMLP", "Module", "__init__", "act_fn", "class", "config", "def", "down_proj", "forward", "hidden_size", "hidden_states", "intermediate_size", "layer_norm", "nn", "perceiver_resampler_hidden_size", "perceiver_resampler_mlp_intermediate_...
edgetam_video/modeling_edgetam_video.py:EdgeTamVideoPerceiverAttention
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[ "ALL_ATTENTION_FUNCTIONS", "False", "Linear", "ModelPerceiverAttention", "Module", "None", "_", "__init__", "_attn_implementation", "attention_dropout", "attention_interface", "attention_mask", "attn_output", "batch_size", "class", "config", "contiguous", "def", "dropout", "eag...
edgetam_video/modeling_edgetam_video.py:EdgeTamVideoPerceiverEncoderLayer
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[ "Dropout", "LayerNorm", "ModelPerceiverAttention", "ModelPerceiverEncoderLayer", "ModelPerceiverMLP", "Module", "None", "__init__", "class", "config", "cross_attention", "cross_attention_output", "def", "dropout", "forward", "input_features", "key", "latents", "layer_norm_input",...
edgetam_video/modeling_edgetam_video.py:window_partition
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[ "Model_partition", "Model_size", "Models", "batch_size", "contiguous", "def", "functional", "height", "hidden_state", "n_h", "n_w", "nn", "num_channels", "pad", "pad_height", "pad_width", "padded_height", "padded_width", "permute", "return", "shape", "view", "width" ]
edgetam_video/modeling_edgetam_video.py:EdgeTamVideoPerceiverResampler
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[ "LayerNorm", "ModelPerceiverEncoderLayer", "ModelPerceiverResampler", "ModelPositionEmbeddingSine", "Module", "ModuleList", "None", "Parameter", "True", "_", "__init__", "_forward_1d", "_forward_2d", "and", "append", "batch_size", "cat", "channels", "class", "combined_latents",...
edgetam_video/modeling_edgetam_video.py:EdgeTamVideoImageSegmentationOutput
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[ "ModelImageSegmentationOutput", "ModelOutput", "None", "class", "high_res_masks", "image_embeddings", "iou_scores", "mask_decoder_attentions", "object_pointer", "object_score_logits", "pred_masks", "r", "vision_attentions", "vision_hidden_states" ]
edgetam_video/modeling_edgetam_video.py:EdgeTamVideoSegmentationOutput
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[ "ModelOutput", "ModelSegmentationOutput", "None", "class", "frame_idx", "object_ids", "object_score_logits", "pred_masks", "r" ]
edgetam_video/modeling_edgetam_video.py:EdgeTamVideoMaskEmbedding
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[ "ACT2FN", "Conv2d", "ModelLayerNorm", "ModelMaskEmbedding", "Module", "__init__", "activation", "channels_first", "class", "config", "conv1", "conv2", "conv3", "data_format", "def", "dense_embeddings", "eps", "forward", "hidden_act", "hidden_size", "hidden_states", "kernel_...
edgetam_video/modeling_edgetam_video.py:EdgeTamVideoPromptEncoder
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[ "Embedding", "ModelMaskEmbedding", "ModelPositionalEmbedding", "ModelPromptEncoder", "Module", "None", "Tensor", "__init__", "_embed_boxes", "_embed_points", "also", "batch_size", "be", "box_embeddings", "boxes", "cat", "clamp", "class", "config", "constant", "coords", "cor...
edgetam_video/modeling_edgetam_video.py:EdgeTamVideoTwoWayTransformer
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[ "LayerNorm", "ModelAttention", "ModelTwoWayAttentionBlock", "ModelTwoWayTransformer", "Module", "ModuleList", "None", "_", "__init__", "append", "attention_similarity", "attn_out", "class", "config", "def", "final_attn_token_to_image", "flatten", "for", "forward", "hidden_size"...
edgetam_video/modeling_edgetam_video.py:EdgeTamVideoMaskDecoder
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[ "Conv2d", "ConvTranspose2d", "Embedding", "GELU", "ModelFeedForward", "ModelLayerNorm", "ModelMaskDecoder", "ModelTwoWayTransformer", "Module", "ModuleList", "None", "True", "_", "__init__", "_dynamic_multimask_via_stability", "_get_stability_scores", "activation", "all_iou_scores"...
edgetam_video/modeling_edgetam_video.py:get_1d_sine_pe
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[ "Model_1d_sine_pe", "arange", "cat", "cos", "def", "device", "dim", "dim_t", "dtype", "float32", "pe_dim", "pos_embed", "pos_inds", "return", "sin", "temperature", "torch", "unsqueeze" ]
edgetam_video/modeling_edgetam_video.py:EdgeTamVideoModel
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[ "AutoModel", "Cannot", "Conv2d", "Exactly", "F", "False", "Got", "Identity", "Linear", "ModelFeedForward", "ModelImageSegmentationOutput", "ModelMaskDecoder", "ModelMemoryAttention", "ModelMemoryEncoder", "ModelModel", "ModelPerceiverResampler", "ModelPositionalEmbedding", "ModelPr...
edgetam/modeling_edgetam.py:EdgeTamLayerNorm
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[ "LayerNorm", "ModelLayerNorm", "NotImplementedError", "Unsupported", "__init__", "channels_first", "channels_last", "class", "data", "data_format", "def", "else", "eps", "f", "features", "format", "forward", "if", "in", "kwargs", "nn", "normalized_shape", "not", "permut...
edgetam/modeling_edgetam.py:EdgeTamVisionEncoderOutput
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[ "BaseModelOutputWithPooling", "ModelVisionEncoderOutput", "None", "class", "fpn_hidden_states", "fpn_position_encoding", "r" ]
edgetam/modeling_edgetam.py:eager_attention_forward
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[ "Model_attention_forward", "None", "attention_mask", "attn_output", "attn_weights", "contiguous", "def", "dim", "dropout", "dtype", "float32", "functional", "if", "is", "key", "kwargs", "matmul", "module", "nn", "not", "p", "query", "return", "scaling", "softmax", "...
edgetam/modeling_edgetam.py:EdgeTamAttention
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[ "ALL_ATTENTION_FUNCTIONS", "Attention", "Falling", "False", "Flash", "Linear", "ModelAttention", "Module", "None", "SDPA", "__init__", "_attn_implementation", "additive", "and", "attention", "attention_downsample_rate", "attention_interface", "attention_mask", "attention_similari...
edgetam/modeling_edgetam.py:EdgeTamTwoWayAttentionBlock
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[ "False", "GradientCheckpointingLayer", "LayerNorm", "ModelAttention", "ModelFeedForward", "ModelTwoWayAttentionBlock", "_", "__init__", "attention_similarity", "attn_out", "class", "config", "cross_attn_image_to_token", "cross_attn_token_to_image", "def", "downsample_rate", "else", ...
edgetam/modeling_edgetam.py:EdgeTamFeedForward
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[ "ACT2FN", "F", "False", "Linear", "ModelFeedForward", "Module", "ModuleList", "_", "__init__", "activation", "class", "def", "for", "forward", "hidden_dim", "hidden_states", "if", "in", "input_dim", "layer", "layers", "nn", "num_layers", "output_dim", "proj_in", "pr...
edgetam/modeling_edgetam.py:EdgeTamPreTrainedModel
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[ "Model", "ModelConfig", "ModelModel", "ModelPreTrainedModel", "None", "PreTrainedModel", "True", "_init_weights", "_keys_to_ignore_on_load_unexpected", "_supports_attention_backend", "_supports_flash_attn", "_supports_sdpa", "base_model_prefix", "class", "config_class", "def", "elif"...
edgetam/modeling_edgetam.py:EdgeTamSinePositionEmbedding
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[ "False", "ModelSinePositionEmbedding", "Module", "None", "_", "__init__", "and", "arange", "batch_size", "build_sine_position_embedding", "cat", "class", "compile_compatible_method_lru_cache", "cos", "cumsum", "def", "device", "dim", "dim_t", "div", "dtype", "else", "embe...
edgetam/modeling_edgetam.py:EdgeTamVisionNeck
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[ "Conv2d", "F", "False", "ModelSinePositionEmbedding", "ModelVisionNeck", "Module", "ModuleList", "None", "True", "__init__", "align_corners", "antialias", "append", "backbone_channel_list", "class", "config", "convs", "def", "device", "dtype", "else", "float32", "for", ...
edgetam/modeling_edgetam.py:EdgeTamVisionModel
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[ "AutoModel", "ModelPreTrainedModel", "ModelVisionConfig", "ModelVisionEncoderOutput", "ModelVisionModel", "ModelVisionNeck", "None", "__init__", "_can_record_outputs", "backbone", "backbone_config", "backbone_output", "capture_outputs", "class", "config", "config_class", "def", "fo...
edgetam/modeling_edgetam.py:EdgeTamImageSegmentationOutput
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[ "ModelImageSegmentationOutput", "ModelOutput", "None", "class", "image_embeddings", "iou_scores", "mask_decoder_attentions", "object_score_logits", "pred_masks", "r", "vision_attentions", "vision_hidden_states" ]
edgetam/modeling_edgetam.py:EdgeTamPositionalEmbedding
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[ "ModelPositionalEmbedding", "Module", "None", "__init__", "cat", "class", "clone", "config", "coordinates", "cos", "def", "dim", "dtype", "float32", "forward", "hidden_size", "if", "input_coords", "input_shape", "is", "nn", "not", "np", "pi", "positional_embedding", ...
edgetam/modeling_edgetam.py:EdgeTamMaskEmbedding
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[ "ACT2FN", "Conv2d", "ModelLayerNorm", "ModelMaskEmbedding", "Module", "__init__", "activation", "channels_first", "class", "config", "conv1", "conv2", "conv3", "data_format", "def", "dense_embeddings", "eps", "forward", "hidden_act", "hidden_size", "hidden_states", "kernel_...
edgetam/modeling_edgetam.py:EdgeTamPromptEncoder
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[ "Embedding", "ModelMaskEmbedding", "ModelPositionalEmbedding", "ModelPromptEncoder", "Module", "None", "Tensor", "__init__", "_embed_boxes", "_embed_points", "also", "batch_size", "be", "box_embeddings", "boxes", "cat", "clamp", "class", "config", "constant", "coords", "cor...
edgetam/modeling_edgetam.py:EdgeTamTwoWayTransformer
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[ "LayerNorm", "ModelAttention", "ModelTwoWayAttentionBlock", "ModelTwoWayTransformer", "Module", "ModuleList", "None", "_", "__init__", "append", "attention_similarity", "attn_out", "class", "config", "def", "final_attn_token_to_image", "flatten", "for", "forward", "hidden_size"...
edgetam/modeling_edgetam.py:EdgeTamMaskDecoder
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[ "Conv2d", "ConvTranspose2d", "Embedding", "GELU", "ModelFeedForward", "ModelLayerNorm", "ModelMaskDecoder", "ModelTwoWayTransformer", "Module", "ModuleList", "None", "True", "_", "__init__", "_dynamic_multimask_via_stability", "_get_stability_scores", "activation", "all_iou_scores"...
edgetam/modeling_edgetam.py:EdgeTamModel
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[ "AutoModel", "Exactly", "F", "False", "Got", "ModelImageSegmentationOutput", "ModelMaskDecoder", "ModelModel", "ModelPositionalEmbedding", "ModelPreTrainedModel", "ModelPromptEncoder", "ModelTwoWayAttentionBlock", "None", "OutputRecorder", "Parameter", "True", "ValueError", "You", ...
pp_ocrv6_small_rec/modeling_pp_ocrv6_small_rec.py:PPOCRV6SmallRecConvLayer
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pp_ocrv6_small_rec/modeling_pp_ocrv6_small_rec.py:PPOCRV6SmallRecAttention
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pp_ocrv6_small_rec/modeling_pp_ocrv6_small_rec.py:PPOCRV6SmallRecMLP
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pp_ocrv6_small_rec/modeling_pp_ocrv6_small_rec.py:PPOCRV6SmallRecBlock
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pp_ocrv6_small_rec/modeling_pp_ocrv6_small_rec.py:eager_attention_forward
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pp_ocrv6_small_rec/modeling_pp_ocrv6_small_rec.py:PPOCRV6SmallRecPreTrainedModel
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pp_ocrv6_small_rec/modeling_pp_ocrv6_small_rec.py:PPOCRV6SmallRecEncoderWithSVTR
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pp_ocrv6_small_rec/modeling_pp_ocrv6_small_rec.py:PPOCRV6SmallRecHead
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pp_ocrv6_small_rec/modeling_pp_ocrv6_small_rec.py:PPOCRV6SmallRecModel
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pp_ocrv6_small_rec/modeling_pp_ocrv6_small_rec.py:PPOCRV6SmallRecForTextRecognitionOutput
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pp_ocrv6_small_rec/modeling_pp_ocrv6_small_rec.py:PPOCRV6SmallRecForTextRecognition
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerGatedAttention
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerBatchNorm
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerPositionalEncoding
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerNormLayer
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerMLP
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerChannelFeatureMixerBlock
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patchtsmixer/modeling_patchtsmixer.py:eager_attention_forward
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerAttention
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patchtsmixer/modeling_patchtsmixer.py:PatchMixerBlock
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patchtsmixer/modeling_patchtsmixer.py:FeatureMixerBlock
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerLayer
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerBlock
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerForPredictionHead
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerLinearHead
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerPreTrainedModel
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerPretrainHead
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patchtsmixer/modeling_patchtsmixer.py:random_masking
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patchtsmixer/modeling_patchtsmixer.py:forecast_masking
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerPatchify
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerMasking
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerStdScaler
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerMeanScaler
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerNOPScaler
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerEncoderOutput
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerEncoder
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerModelOutput
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerModel
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerForPreTrainingOutput
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[ "ModelForPreTrainingOutput", "ModelOutput", "None", "class", "hidden_states", "last_hidden_state", "loss", "prediction_outputs", "r" ]
patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerForPretraining
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerForPredictionOutput
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patchtsmixer/modeling_patchtsmixer.py:SamplePatchTSMixerPredictionOutput
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patchtsmixer/modeling_patchtsmixer.py:SamplePatchTSMixerRegressionOutput
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patchtsmixer/modeling_patchtsmixer.py:nll
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patchtsmixer/modeling_patchtsmixer.py:weighted_average
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerForPrediction
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerForTimeSeriesClassificationOutput
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerForTimeSeriesClassification
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerForRegressionOutput
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patchtsmixer/modeling_patchtsmixer.py:InjectScalerStatistics4D
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patchtsmixer/modeling_patchtsmixer.py:PatchTSMixerForRegression
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swin2sr/modeling_swin2sr.py:Swin2SREncoderOutput
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swin2sr/modeling_swin2sr.py:window_partition
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swin2sr/modeling_swin2sr.py:window_reverse
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swin2sr/modeling_swin2sr.py:Swin2SREmbeddings
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swin2sr/modeling_swin2sr.py:Swin2SRPatchEmbeddings
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swin2sr/modeling_swin2sr.py:Swin2SRPatchUnEmbeddings
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swin2sr/modeling_swin2sr.py:Swin2SRPatchMerging
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swin2sr/modeling_swin2sr.py:Swin2SRSelfAttention
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swin2sr/modeling_swin2sr.py:Swin2SRSelfOutput
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swin2sr/modeling_swin2sr.py:Swin2SRAttention
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swin2sr/modeling_swin2sr.py:Swin2SRIntermediate
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swin2sr/modeling_swin2sr.py:Swin2SROutput
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swin2sr/modeling_swin2sr.py:Swin2SRDropPath
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swin2sr/modeling_swin2sr.py:Swin2SRLayer
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swin2sr/modeling_swin2sr.py:Swin2SRStage
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swin2sr/modeling_swin2sr.py:Swin2SREncoder
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swin2sr/modeling_swin2sr.py:Swin2SRPreTrainedModel
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swin2sr/modeling_swin2sr.py:Swin2SRModel
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[ "BaseModelOutput", "Conv2d", "False", "LayerNorm", "ModelEmbeddings", "ModelEncoder", "ModelModel", "ModelPatchUnEmbeddings", "ModelPreTrainedModel", "None", "_", "__init__", "and", "attentions", "auto_docstring", "class", "config", "conv_after_body", "def", "device", "dtype"...
swin2sr/modeling_swin2sr.py:Upsample
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