diff --git a/TODO.md b/TODO.md index c1e467642..e4d663f18 100644 --- a/TODO.md +++ b/TODO.md @@ -4,6 +4,7 @@ Main ToDo list can be found at [GitHub projects](https://github.com/users/vladma ## Current +- Video: API support - ModernUI for custom model loader - ModernUI for history tab @@ -13,10 +14,8 @@ N/A ## Future Candidates -- IPAdapter: negative guidance: - Control: API enhance scripts compatibility -- Video: add generate context menu -- Video: API support +- IPAdapter: negative guidance: - Video: STG: - Video: SmoothCache: https://github.com/huggingface/diffusers/issues/11135 @@ -27,9 +26,7 @@ N/A - control: support scripts via api - fc: autodetect distilled based on model - fc: autodetect tensor format based on model -- hidream: pack latents for remote vae - hypertile: vae breaks when using non-standard sizes -- infotext: handle using regex instead - install: enable ROCm for windows when available - loader: load receipe - loader: save receipe diff --git a/modules/infotext.py b/modules/infotext.py index 497879d31..d655be68e 100644 --- a/modules/infotext.py +++ b/modules/infotext.py @@ -68,7 +68,6 @@ def parse(infotext): debug(f'Raw: {infotext}') remaining = infotext.replace('\nSteps:', ' Steps:') - # TODO infotext: handle using regex instead params = [' steps:', ' seed:', ' width:', ' height:', ' sampler:', ' size:', ' cfg scale:'] # first param is one of those params += ['\nsteps:', '\nseed:', '\nwidth:', '\nheight:', '\nsampler:', '\nsize:', '\ncfg scale:'] params += ['.steps:', '.seed:', '.width:', '.height:', '.sampler:', '.size:', '.cfg scale:'] diff --git a/modules/sd_vae_remote.py b/modules/sd_vae_remote.py index c751bc083..741d349bc 100644 --- a/modules/sd_vae_remote.py +++ b/modules/sd_vae_remote.py @@ -28,13 +28,6 @@ dtypes = { } -def h1_pack_latents(latents, _batch_size, _num_channels_latents, _height, _width): # TODO hidream: pack latents for remote vae - # latents = latents.view(batch_size, num_channels_latents, height // 2, 2, width // 2, 2) - # latents = latents.permute(0, 2, 4, 1, 3, 5) - # latents = latents.reshape(batch_size, (height // 2) * (width // 2) // (num_channels_latents * 4), num_channels_latents * 4) - return latents - - def remote_decode(latents: torch.Tensor, width: int = 0, height: int = 0, model_type: str = None) -> Image.Image: from modules import devices, shared, errors, modelloader tensors = [] @@ -57,9 +50,6 @@ def remote_decode(latents: torch.Tensor, width: int = 0, height: int = 0, model_ latent = latent_copy[i] if model_type != 'f1': latent = latent.unsqueeze(0) - # if model_type == 'h1': - # num_channels_latents = shared.sd_model.transformer.config.in_channels - # latent = h1_pack_latents(latent, 1, num_channels_latents, height, width) # pylint: disable=protected-access params = { "input_tensor_type": "binary", "shape": list(latent.shape),