Fix imports.

This commit is contained in:
comfyanonymous
2023-05-04 18:07:41 -04:00
parent 7e51bbd07f
commit bae4fb4a9d
13 changed files with 42 additions and 42 deletions

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@@ -3,11 +3,11 @@ import torch
import torch.nn.functional as F
from contextlib import contextmanager
from ldm.modules.diffusionmodules.model import Encoder, Decoder
from ldm.modules.distributions.distributions import DiagonalGaussianDistribution
from comfy.ldm.modules.diffusionmodules.model import Encoder, Decoder
from comfy.ldm.modules.distributions.distributions import DiagonalGaussianDistribution
from ldm.util import instantiate_from_config
from ldm.modules.ema import LitEma
from comfy.ldm.util import instantiate_from_config
from comfy.ldm.modules.ema import LitEma
# class AutoencoderKL(pl.LightningModule):
class AutoencoderKL(torch.nn.Module):

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@@ -4,7 +4,7 @@ import torch
import numpy as np
from tqdm import tqdm
from ldm.modules.diffusionmodules.util import make_ddim_sampling_parameters, make_ddim_timesteps, noise_like, extract_into_tensor
from comfy.ldm.modules.diffusionmodules.util import make_ddim_sampling_parameters, make_ddim_timesteps, noise_like, extract_into_tensor
class DDIMSampler(object):

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@@ -19,12 +19,12 @@ from tqdm import tqdm
from torchvision.utils import make_grid
# from pytorch_lightning.utilities.distributed import rank_zero_only
from ldm.util import log_txt_as_img, exists, default, ismap, isimage, mean_flat, count_params, instantiate_from_config
from ldm.modules.ema import LitEma
from ldm.modules.distributions.distributions import normal_kl, DiagonalGaussianDistribution
from ldm.models.autoencoder import IdentityFirstStage, AutoencoderKL
from ldm.modules.diffusionmodules.util import make_beta_schedule, extract_into_tensor, noise_like
from ldm.models.diffusion.ddim import DDIMSampler
from comfy.ldm.util import log_txt_as_img, exists, default, ismap, isimage, mean_flat, count_params, instantiate_from_config
from comfy.ldm.modules.ema import LitEma
from comfy.ldm.modules.distributions.distributions import normal_kl, DiagonalGaussianDistribution
from ..autoencoder import IdentityFirstStage, AutoencoderKL
from comfy.ldm.modules.diffusionmodules.util import make_beta_schedule, extract_into_tensor, noise_like
from .ddim import DDIMSampler
__conditioning_keys__ = {'concat': 'c_concat',

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@@ -6,7 +6,7 @@ from torch import nn, einsum
from einops import rearrange, repeat
from typing import Optional, Any
from ldm.modules.diffusionmodules.util import checkpoint
from .diffusionmodules.util import checkpoint
from .sub_quadratic_attention import efficient_dot_product_attention
from comfy import model_management
@@ -21,7 +21,7 @@ if model_management.xformers_enabled():
import os
_ATTN_PRECISION = os.environ.get("ATTN_PRECISION", "fp32")
from cli_args import args
from comfy.cli_args import args
def exists(val):
return val is not None

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@@ -6,7 +6,7 @@ import numpy as np
from einops import rearrange
from typing import Optional, Any
from ldm.modules.attention import MemoryEfficientCrossAttention
from ..attention import MemoryEfficientCrossAttention
from comfy import model_management
if model_management.xformers_enabled_vae():

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@@ -6,7 +6,7 @@ import torch as th
import torch.nn as nn
import torch.nn.functional as F
from ldm.modules.diffusionmodules.util import (
from .util import (
checkpoint,
conv_nd,
linear,
@@ -15,8 +15,8 @@ from ldm.modules.diffusionmodules.util import (
normalization,
timestep_embedding,
)
from ldm.modules.attention import SpatialTransformer
from ldm.util import exists
from ..attention import SpatialTransformer
from comfy.ldm.util import exists
# dummy replace

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@@ -3,8 +3,8 @@ import torch.nn as nn
import numpy as np
from functools import partial
from ldm.modules.diffusionmodules.util import extract_into_tensor, make_beta_schedule
from ldm.util import default
from .util import extract_into_tensor, make_beta_schedule
from comfy.ldm.util import default
class AbstractLowScaleModel(nn.Module):

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@@ -15,7 +15,7 @@ import torch.nn as nn
import numpy as np
from einops import repeat
from ldm.util import instantiate_from_config
from comfy.ldm.util import instantiate_from_config
def make_beta_schedule(schedule, n_timestep, linear_start=1e-4, linear_end=2e-2, cosine_s=8e-3):

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@@ -1,5 +1,5 @@
from ldm.modules.diffusionmodules.upscaling import ImageConcatWithNoiseAugmentation
from ldm.modules.diffusionmodules.openaimodel import Timestep
from ..diffusionmodules.upscaling import ImageConcatWithNoiseAugmentation
from ..diffusionmodules.openaimodel import Timestep
import torch
class CLIPEmbeddingNoiseAugmentation(ImageConcatWithNoiseAugmentation):