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Functions3,853 in github.com/AlayaLab/Hive

↓ 2 callersMethod__init__
(self, img_size=224, patch_size=16, in_chans=3, embed_dim=768)
models/flowsep/latent_diffusion/modules/audiomae/util/patch_embed.py:9
↓ 2 callersMethod__init__
( self, unet_config, sampling_rate=None, timesteps=1000, beta_sch
models/flowsep/latent_diffusion/models/ddpm_flow.py:62
↓ 2 callersMethod__init__
( self, in_channels=3, out_channels=3, down_block_types=("DownEncoderBlock
models/flowsep/diffusers/models/vae.py:40
↓ 2 callersMethod__init__
(self)
models/audiosep/models/CLAP/open_clip/feature_fusion.py:16
↓ 2 callersMethod_clean_caption
(self, caption)
models/flowsep/diffusers/pipelines/deepfloyd_if/pipeline_if_img2img_superresolution.py:289
↓ 2 callersMethod_clean_caption
(self, caption)
models/flowsep/diffusers/pipelines/deepfloyd_if/pipeline_if.py:511
↓ 2 callersMethod_clean_caption
(self, caption)
models/flowsep/diffusers/pipelines/deepfloyd_if/pipeline_if_superresolution.py:247
↓ 2 callersMethod_clean_caption
(self, caption)
models/flowsep/diffusers/pipelines/deepfloyd_if/pipeline_if_img2img.py:559
↓ 2 callersMethod_clean_caption
(self, caption)
models/flowsep/diffusers/pipelines/deepfloyd_if/pipeline_if_inpainting_superresolution.py:291
↓ 2 callersMethod_clean_caption
(self, caption)
models/flowsep/diffusers/pipelines/deepfloyd_if/pipeline_if_inpainting.py:598
↓ 2 callersFunction_concat_init
(tensor, init_funcs)
models/audiosep/models/base.py:36
↓ 2 callersMethod_convert_deprecated_attention_blocks
(self, state_dict)
models/flowsep/diffusers/models/modeling_utils.py:832
↓ 2 callersMethod_decode
(self, z: torch.FloatTensor, return_dict: bool = True)
models/flowsep/diffusers/models/autoencoder_kl.py:173
↓ 2 callersMethod_dict_from_json_file
(cls, json_file: Union[str, os.PathLike])
models/flowsep/diffusers/configuration_utils.py:517
↓ 2 callersMethod_downsample_2d
Fused `Conv2d()` followed by `downsample_2d()`. Padding is performed only once at the beginning, not between the operations. The fused op is
models/flowsep/diffusers/models/resnet.py:360
↓ 2 callersMethod_encode_prompt
r""" Encodes the prompt into text encoder hidden states. Args: prompt (`str` or `List[str]`, *optional*):
models/flowsep/diffusers/pipelines/text_to_video_synthesis/pipeline_text_to_video_synth.py:218
↓ 2 callersMethod_encode_prompt
r""" Encodes the prompt into text encoder hidden states. Args: prompt (`str` or `List[str]`, *optional*):
models/flowsep/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_pix2pix_zero.py:436
↓ 2 callersMethod_encode_prompt
r""" Encodes the prompt into text encoder hidden states. Args: prompt (`str` or `List[str]`, *optional*):
models/flowsep/diffusers/pipelines/stable_diffusion/pipeline_cycle_diffusion.py:304
↓ 2 callersMethod_encode_vae_image
(self, image: torch.Tensor, generator: torch.Generator)
models/flowsep/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint.py:951
↓ 2 callersFunction_flowsep_process_chunk
(model, preprocessor, chunk_wav, text)
app.py:190
↓ 2 callersMethod_generate
( self, prompt_ids: jnp.array, image: jnp.array, params: Union[Dict, Froze
models/flowsep/diffusers/pipelines/controlnet/pipeline_flax_controlnet.py:248
↓ 2 callersMethod_generate
( self, prompt_ids: jnp.array, mask: jnp.array, masked_image: jnp.array,
models/flowsep/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion_inpaint.py:262
↓ 2 callersMethod_generate
( self, prompt_ids: jnp.array, image: jnp.array, params: Union[Dict, Froze
models/flowsep/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion_img2img.py:234
↓ 2 callersMethod_generate
( self, prompt_ids: jnp.array, params: Union[Dict, FrozenDict], prng_seed:
models/flowsep/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion.py:215
↓ 2 callersMethod_get_audio_embed
(self, batch)
models/audiosep/models/clap_encoder.py:50
↓ 2 callersMethod_get_compatibles
(cls)
models/flowsep/diffusers/schedulers/scheduling_utils.py:171
↓ 2 callersMethod_get_has_nsfw_concepts
(self, features, params)
models/flowsep/diffusers/pipelines/controlnet/pipeline_flax_controlnet.py:214
↓ 2 callersMethod_get_has_nsfw_concepts
(self, features, params)
models/flowsep/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion_inpaint.py:228
↓ 2 callersMethod_get_has_nsfw_concepts
(self, features, params)
models/flowsep/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion_img2img.py:192
↓ 2 callersMethod_get_has_nsfw_concepts
(self, features, params)
models/flowsep/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion.py:181
↓ 2 callersFunction_get_library_name
()
models/flowsep/diffusers/utils/logging.py:69
↓ 2 callersFunction_get_pipeline_class
(class_obj, config, custom_pipeline=None, cache_dir=None, revision=None)
models/flowsep/diffusers/pipelines/pipeline_utils.py:326
↓ 2 callersMethod_get_prev_sample
(self, sample, timestep, prev_timestep, model_output)
models/flowsep/diffusers/schedulers/scheduling_pndm.py:358
↓ 2 callersMethod_get_prev_sample
(self, state: PNDMSchedulerState, sample, timestep, prev_timestep, model_output)
models/flowsep/diffusers/schedulers/scheduling_pndm_flax.py:456
↓ 2 callersMethod_get_relative_embeddings
(self, relative_embeddings, length)
models/flowsep/latent_diffusion/modules/phoneme_encoder/attentions.py:213
↓ 2 callersMethod_get_signature_keys
(obj)
models/flowsep/diffusers/pipelines/pipeline_flax_utils.py:496
↓ 2 callersMethod_get_text_embed
(self, batch)
models/audiosep/models/clap_encoder.py:78
↓ 2 callersMethod_pad_spec
(self, log_mel_spec)
infer_flowsep.py:56
↓ 2 callersMethod_pad_spec
(self, log_mel_spec)
app.py:80
↓ 2 callersFunction_process_chunk
(chunk_wav)
infer_flowsep.py:143
↓ 2 callersMethod_relative_path_to_absolute_path
(self, metadata, dataset_name)
models/flowsep/utilities/data/dataset.py:284
↓ 2 callersFunction_rescan_model_configs
()
models/audiosep/models/CLAP/open_clip/factory.py:24
↓ 2 callersFunction_resnet_conv1x1_wav1d
(in_planes, out_planes)
models/flowsep/latent_diffusion/modules/losses/panns_distance/model/models.py:2315
↓ 2 callersFunction_resnet_conv3x1_wav1d
(in_planes, out_planes, dilation)
models/flowsep/latent_diffusion/modules/losses/panns_distance/model/models.py:2301
↓ 2 callersMethod_sigma_to_t
(self, sigma, log_sigmas)
models/flowsep/diffusers/schedulers/scheduling_dpmsolver_sde.py:279
↓ 2 callersMethod_spectrogram
(self, y, n_fft, hop_size, win_size, center=False)
models/flowsep/latent_diffusion/modules/losses/waveform_contperceptual_panns.py:70
↓ 2 callersMethod_spectrogram
(self, y, n_fft, hop_size, win_size, center=False)
models/flowsep/latent_diffusion/modules/losses/waveform_contperceptual.py:64
↓ 2 callersMethod_swap_unet_attention_blocks
Swap the `Transformer2DModel` blocks between the image and text UNets
models/flowsep/diffusers/pipelines/versatile_diffusion/pipeline_versatile_diffusion_text_to_image.py:86
↓ 2 callersMethod_text_preprocessing
(self, text, clean_caption=False)
models/flowsep/diffusers/pipelines/deepfloyd_if/pipeline_if_img2img_superresolution.py:264
↓ 2 callersMethod_text_preprocessing
(self, text, clean_caption=False)
models/flowsep/diffusers/pipelines/deepfloyd_if/pipeline_if.py:487
↓ 2 callersMethod_text_preprocessing
(self, text, clean_caption=False)
models/flowsep/diffusers/pipelines/deepfloyd_if/pipeline_if_superresolution.py:222
↓ 2 callersMethod_text_preprocessing
(self, text, clean_caption=False)
models/flowsep/diffusers/pipelines/deepfloyd_if/pipeline_if_img2img.py:534
↓ 2 callersMethod_text_preprocessing
(self, text, clean_caption=False)
models/flowsep/diffusers/pipelines/deepfloyd_if/pipeline_if_inpainting_superresolution.py:266
↓ 2 callersMethod_text_preprocessing
(self, text, clean_caption=False)
models/flowsep/diffusers/pipelines/deepfloyd_if/pipeline_if_inpainting.py:573
↓ 2 callersMethod_threshold_sample
"Dynamic thresholding: At each sampling step we set s to a certain percentile absolute pixel value in xt0 (the prediction of x_0 at
models/flowsep/diffusers/schedulers/scheduling_dpmsolver_multistep_inverse.py:237
↓ 2 callersMethod_threshold_sample
"Dynamic thresholding: At each sampling step we set s to a certain percentile absolute pixel value in xt0 (the prediction of x_0 at
models/flowsep/diffusers/schedulers/scheduling_dpmsolver_multistep.py:250
↓ 2 callersMethod_to_3d
(self, hidden_states, height, weight)
models/flowsep/diffusers/models/unet_2d_blocks.py:3003
↓ 2 callersMethod_to_4d
(self, hidden_states, height, weight)
models/flowsep/diffusers/models/unet_2d_blocks.py:3006
↓ 2 callersMethod_update
Update d coefficients.
models/flowsep/utilities/sampler.py:389
↓ 2 callersMethod_update_latent
Update the latent according to the computed loss.
models/flowsep/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py:629
↓ 2 callersMethod_upsample_2d
Fused `upsample_2d()` followed by `Conv2d()`. Padding is performed only once at the beginning, not between the operations. The fused op is
models/flowsep/diffusers/models/resnet.py:247
↓ 2 callersFunctionalpha_bar
(t)
models/flowsep/latent_diffusion/modules/diffusionmodules/util.py:140
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_pndm.py:46
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_lms_discrete.py:66
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_ddpm.py:65
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_dpmsolver_sde.py:97
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_repaint.py:64
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_k_dpm_2_ancestral_discrete.py:45
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_unclip.py:65
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_euler_ancestral_discrete.py:68
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_deis_multistep.py:47
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_k_dpm_2_discrete.py:44
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_dpmsolver_multistep_inverse.py:47
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_euler_discrete.py:68
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_dpmsolver_multistep.py:47
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_unipc_multistep.py:46
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_utils_flax.py:205
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_ddim.py:68
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_ddim_inverse.py:67
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_dpmsolver_singlestep.py:50
↓ 2 callersFunctionalpha_bar
(time_step)
models/flowsep/diffusers/schedulers/scheduling_heun_discrete.py:44
↓ 2 callersFunctionalways
(val)
models/flowsep/latent_diffusion/modules/x_transformer.py:62
↓ 2 callersFunctionavg_pool_nd
Create a 1D, 2D, or 3D average pooling module.
models/flowsep/latent_diffusion/modules/diffusionmodules/util.py:302
↓ 2 callersMethodbackward
(ctx, *output_grads)
models/flowsep/latent_diffusion/modules/diffusionmodules/util.py:190
↓ 2 callersFunctionbatch_query
(data: list[dict], model, processor, label_tree: LabelTree)
pipeline/code/05_leaf_label_qwen.py:109
↓ 2 callersFunctionbetas_for_alpha_bar
Create a beta schedule that discretizes the given alpha_t_bar function, which defines the cumulative product of (1-beta) over time from t =
models/flowsep/latent_diffusion/modules/diffusionmodules/util.py:127
↓ 2 callersMethodblend_h
(self, a, b, blend_extent)
models/flowsep/diffusers/models/autoencoder_kl.py:204
↓ 2 callersMethodblend_v
(self, a, b, blend_extent)
models/flowsep/diffusers/models/autoencoder_kl.py:198
↓ 2 callersFunctionbuild_model_from_openai_state_dict
( state_dict: dict, model_cfg, enable_fusion: bool = False, fusion_type: str = "None" )
models/audiosep/models/CLAP/open_clip/model.py:872
↓ 2 callersFunctionbytes_to_unicode
Returns list of utf-8 byte and a corresponding list of unicode strings. The reversible bpe codes work on unicode strings. This means y
models/audiosep/models/CLAP/open_clip/tokenizer.py:24
↓ 2 callersMethodcalculate
(self, fm, fm_hat)
models/flowsep/latent_diffusion/modules/losses/panns_distance/distance.py:40
↓ 2 callersFunctioncalculate_selection_performance_clotho_audiocaps
Calculate performance for Clotho+AudioCaps for model selection.
models/audiosep/models/CLAP/training/train.py:785
↓ 2 callersMethodcheck_image
(self, image, prompt, prompt_embeds)
models/flowsep/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint.py:745
↓ 2 callersMethodcheck_image
(self, image, prompt, prompt_embeds)
models/flowsep/diffusers/pipelines/controlnet/pipeline_controlnet_img2img.py:618
↓ 2 callersMethodcheck_image
(self, image, prompt, prompt_embeds)
models/flowsep/diffusers/pipelines/controlnet/pipeline_controlnet.py:592
↓ 2 callersMethodcheck_inputs
( self, prompt, height, width, callback_steps, negative_
models/flowsep/diffusers/pipelines/text_to_video_synthesis/pipeline_text_to_video_synth.py:406
↓ 2 callersMethodcheck_inputs
( self, prompt, height, width, callback_steps, noise_lev
models/flowsep/diffusers/pipelines/stable_diffusion/pipeline_stable_unclip.py:528
↓ 2 callersMethodchunk_inference
(self, input_dict)
models/audiosep/models/resunet.py:656
↓ 2 callersFunctioncleanup_temp_dir
()
hive_dataset/mix_curation/mix_data_curation.py:19
↓ 2 callersFunctionconv_attn_to_linear
(checkpoint)
models/flowsep/diffusers/pipelines/stable_diffusion/convert_from_ckpt.py:217
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