Fix model configuration
Courtesy of WASasquatch
This commit is contained in:
space-nuko
+232
-28
@@ -64,6 +64,9 @@ diff_model_map = {
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'secondary': { 'downloaded': False, 'sha': '983e3de6f95c88c81b2ca7ebb2c217933be1973b1ff058776b970f901584613a', 'uri_list': ['https://huggingface.co/spaces/huggi/secondary_model_imagenet_2.pth/resolve/main/secondary_model_imagenet_2.pth', 'https://the-eye.eu/public/AI/models/v-diffusion/secondary_model_imagenet_2.pth', 'https://ipfs.pollinations.ai/ipfs/bafybeibaawhhk7fhyhvmm7x24zwwkeuocuizbqbcg5nqx64jq42j75rdiy/secondary_model_imagenet_2.pth'] },
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}
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class ModelSettings:
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def __init__(self, model_name, model_path):
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self.model_path = model_path
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@@ -160,20 +163,14 @@ class ModelSettings:
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else:
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print(f"No additional download resources available for {diffusion_model_name}")
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def setup(self, useCPU):
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# Download the diffusion model(s)
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self.download_model(self.diffusion_model)
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if self.use_secondary_model:
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self.download_model('secondary')
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self.model_config = model_and_diffusion_defaults()
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if self.diffusion_model == '512x512_diffusion_uncond_finetune_008100':
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self.model_config.update({
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def configurate_model(self, diffusion_model, use_checkpoint=False, useCPU=False):
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model_configurations = {
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'512x512_diffusion_uncond_finetune_008100': {
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'attention_resolutions': '32, 16, 8',
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'class_cond': False,
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'diffusion_steps': 1000, #No need to edit this, it is taken care of later.
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'diffusion_steps': 1000,
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'rescale_timesteps': True,
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'timestep_respacing': 250, #No need to edit this, it is taken care of later.
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'timestep_respacing': 250,
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'image_size': 512,
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'learn_sigma': True,
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'noise_schedule': 'linear',
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@@ -181,30 +178,28 @@ class ModelSettings:
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'num_head_channels': 64,
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'num_res_blocks': 2,
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'resblock_updown': True,
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'use_checkpoint': self.use_checkpoint,
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'use_checkpoint': use_checkpoint,
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'use_fp16': not useCPU,
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'use_scale_shift_norm': True,
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})
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elif self.diffusion_model == '256x256_diffusion_uncond':
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self.model_config.update({
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},
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'256x256_diffusion_uncond': {
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'attention_resolutions': '32, 16, 8',
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'class_cond': False,
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'diffusion_steps': 1000, #No need to edit this, it is taken care of later.
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'diffusion_steps': 1000,
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'rescale_timesteps': True,
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'timestep_respacing': 250, #No need to edit this, it is taken care of later.
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'image_size': 256,
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'timestep_respacing': 250,
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'image_size': 512,
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'learn_sigma': True,
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'noise_schedule': 'linear',
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'num_channels': 256,
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'num_head_channels': 64,
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'num_res_blocks': 2,
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'resblock_updown': True,
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'use_checkpoint': self.use_checkpoint,
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'use_checkpoint': use_checkpoint,
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'use_fp16': not useCPU,
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'use_scale_shift_norm': True,
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})
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elif self.diffusion_model == 'portrait_generator_v001':
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self.model_config.update({
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},
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'512x512_OpenAI': {
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'attention_resolutions': '32, 16, 8',
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'class_cond': False,
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'diffusion_steps': 1000,
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@@ -216,12 +211,26 @@ class ModelSettings:
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'num_heads': 4,
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'num_res_blocks': 2,
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'resblock_updown': True,
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'use_checkpoint': self.use_checkpoint,
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'use_checkpoint': use_checkpoint,
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'use_fp16': True,
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'use_scale_shift_norm': True,
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})
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else: # E.g. A model finetuned by KaliYuga
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self.model_config.update({
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},
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'Architecture_Diffusion_1-5m': {
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'attention_resolutions': '32, 16, 8',
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'class_cond': False,
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'diffusion_steps': 1000,
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'image_size': 512,
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'learn_sigma': True,
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'noise_schedule': 'linear',
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'num_channels': 256,
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'num_head_channels': 64,
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'num_res_blocks': 2,
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'resblock_updown': True,
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'rescale_timesteps': True,
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'timestep_respacing': '250',
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'use_scale_shift_norm': True
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},
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'Liminal_Diffusion': {
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'attention_resolutions': '16',
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'class_cond': False,
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'diffusion_steps': 1000,
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@@ -233,10 +242,205 @@ class ModelSettings:
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'num_channels': 128,
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'num_heads': 1,
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'num_res_blocks': 2,
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'use_checkpoint': self.use_checkpoint,
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'use_checkpoint': use_checkpoint,
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'use_fp16': True,
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'use_scale_shift_norm': False,
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})
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},
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'Lithography_Diffusion': {
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'attention_resolutions': '16',
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'class_cond': False,
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'diffusion_steps': 1000,
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'rescale_timesteps': True,
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'timestep_respacing': 'ddim100',
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'image_size': 256,
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'learn_sigma': True,
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'noise_schedule': 'linear',
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'num_channels': 128,
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'num_heads': 1,
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'num_res_blocks': 2,
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'use_checkpoint': use_checkpoint,
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'use_fp16': True,
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'use_scale_shift_norm': False,
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},
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'Medieval_Diffusion': {
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'attention_resolutions': '16',
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'class_cond': False,
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'diffusion_steps': 1000,
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'rescale_timesteps': True,
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'timestep_respacing': 'ddim100',
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'image_size': 256,
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'learn_sigma': True,
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'noise_schedule': 'linear',
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'num_channels': 128,
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'num_heads': 1,
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'num_res_blocks': 2,
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'use_checkpoint': use_checkpoint,
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'use_fp16': True,
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'use_scale_shift_norm': False,
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},
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'Floral_Diffusion': {
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'attention_resolutions': '16',
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'class_cond': False,
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'diffusion_steps': 1000,
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'rescale_timesteps': True,
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'timestep_respacing': 'ddim100',
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'image_size': 256,
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'learn_sigma': True,
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'noise_schedule': 'linear',
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'num_channels': 128,
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'num_heads': 1,
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'num_res_blocks': 2,
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'use_checkpoint': use_checkpoint,
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'use_fp16': True,
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'use_scale_shift_norm': False,
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},
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'FeiArt_Handpainted_CG_Diffusion': {
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'attention_resolutions': '32,16,8',
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'class_cond': False,
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'diffusion_steps': 1000,
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'rescale_timesteps': True,
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'timestep_respacing': 'ddim100',
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'image_size': 512,
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'learn_sigma': True,
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'noise_schedule': 'linear',
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'num_channels': 256,
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'num_head_channels': 64,
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'num_res_blocks': 2,
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'resblock_updown': True,
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'use_checkpoint': use_checkpoint,
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'use_fp16': True,
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'use_scale_shift_norm': True,
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},
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'Textile_Diffusion': {
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'attention_resolutions': '16',
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'class_cond': False,
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'diffusion_steps': 1000,
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'rescale_timesteps': True,
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'timestep_respacing': 'ddim100',
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'image_size': 256,
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'learn_sigma': True,
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'noise_schedule': 'linear',
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'num_channels': 128,
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'num_heads': 1,
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'num_res_blocks': 2,
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'use_checkpoint': use_checkpoint,
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'use_fp16': True,
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'use_scale_shift_norm': False,
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},
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'Isometric_Diffusion_Revrart512px': {
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'attention_resolutions': '32, 16, 8',
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'class_cond': False,
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'diffusion_steps': 1000,
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'rescale_timesteps': True,
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'timestep_respacing': 'ddim100',
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'image_size': 512,
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'learn_sigma': True,
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'noise_schedule': 'linear',
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'num_channels': 256,
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'num_head_channels': 64,
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'num_res_blocks': 2,
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'resblock_updown': True,
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'use_checkpoint': use_checkpoint,
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'use_fp16': True,
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'use_scale_shift_norm': True,
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},
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'Laproper_Diffusion_Deepspace_256': {
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'attention_resolutions': '32, 16, 8',
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'class_cond': False,
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'diffusion_steps': 1000,
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'rescale_timesteps': True,
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'timestep_respacing': 'ddim100',
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'image_size': 256,
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'learn_sigma': True,
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'noise_schedule': 'linear',
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'num_channels': 128,
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'num_heads': 4,
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'num_res_blocks': 2,
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'resblock_updown': True,
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'use_checkpoint': use_checkpoint,
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'use_fp16': True,
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'use_scale_shift_norm': True,
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},
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'Schnippi_Diffusion_512x512_V2': {
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'attention_resolutions': '32, 16, 8',
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'class_cond': False,
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'diffusion_steps': 1000,
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'rescale_timesteps': True,
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'timestep_respacing': 250,
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'image_size': 512,
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'learn_sigma': True,
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'noise_schedule': 'linear',
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'num_channels': 256,
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'num_head_channels': 64,
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'num_res_blocks': 2,
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'resblock_updown': True,
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'use_checkpoint': use_checkpoint,
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'use_fp16': not useCPU,
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'use_scale_shift_norm': True,
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},
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'Kaliyuga': {
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'attention_resolutions': '16',
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'class_cond': False,
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'diffusion_steps': 1000,
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'rescale_timesteps': True,
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'timestep_respacing': 'ddim100',
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'image_size': 256,
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'learn_sigma': True,
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'noise_schedule': 'linear',
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'num_channels': 128,
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'num_heads': 1,
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'num_res_blocks': 2,
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'use_checkpoint': use_checkpoint,
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'use_fp16': True,
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'use_scale_shift_norm': False,
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},
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}
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tmp_model_config = model_and_diffusion_defaults()
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if diffusion_model in ['512x512_diffusion_uncond_finetune_008100', 'Schnippi_Diffusion_512x512_V2']:
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tmp_model_config.update(model_configurations['512x512_diffusion_uncond_finetune_008100'])
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elif diffusion_model == '256x256_diffusion_uncond':
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tmp_model_config.update(model_configurations['256x256_diffusion_uncond'])
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elif diffusion_model in ['concept_art_generator_v000-1_alpha',
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'concept_art_generator_v000-2_alpha',
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'portrait_generator_v001',
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'portrait_generator_v002',
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'portrait_generator_v003',
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'portrait_generator_v004',
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'portrait_generator_v005']:
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tmp_model_config.update(model_configurations['512x512_OpenAI'])
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elif diffusion_model == 'Architecture_Diffusion_1-5m':
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tmp_model_config.update(model_configurations['Architecture_Diffusion_1-5m'])
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elif diffusion_model in ['Liminal_Diffusion_v1',
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'liminal_diffusion_source']:
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tmp_model_config.update(model_configurations['Liminal_Diffusion'])
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elif diffusion_model == 'Lithography_Diffusion':
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tmp_model_config.update(model_configurations['Lithography_Diffusion'])
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elif diffusion_model == 'Medieval_Diffusion':
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tmp_model_config.update(model_configurations['Medieval_Diffusion'])
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elif diffusion_model == 'Floral_Diffusion':
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tmp_model_config.update(model_configurations['Floral_Diffusion'])
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elif diffusion_model == 'FeiArt_Handpainted_CG_Diffusion':
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tmp_model_config.update(model_configurations['FeiArt_Handpainted_CG_Diffusion'])
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elif diffusion_model == 'Textile_Diffusion':
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tmp_model_config.update(model_configurations['Textile_Diffusion'])
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elif diffusion_model == 'Isometric_Diffusion_Revrart512px':
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tmp_model_config.update(model_configurations['Isometric_Diffusion_Revrart512px'])
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elif diffusion_model == 'Laproper_Diffusion_Deepspace_256':
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tmp_model_config.update(model_configurations['Laproper_Diffusion_Deepspace_256'])
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else:
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tmp_model_config.update(model_configurations['Kaliyuga'])
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return tmp_model_config
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def setup(self, useCPU):
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# Download the diffusion model(s)
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self.download_model(self.diffusion_model)
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if self.use_secondary_model:
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self.download_model('secondary')
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self.model_config = self.configurate_model(self.diffusion_model, self.use_checkpoint, useCPU)
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self.model_default = self.model_config['image_size']
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