Replace flake8 with ruff and update black (#2279)
* before running make style * remove left overs from flake8 * finish * make fix-copies * final fix * more fixes
This commit is contained in:
parent
f5ccffecf7
commit
a7ca03aa85
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@ -27,9 +27,8 @@ jobs:
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pip install .[quality]
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- name: Check quality
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run: |
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black --check --preview examples tests src utils scripts
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isort --check-only examples tests src utils scripts
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flake8 examples tests src utils scripts
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black --check examples tests src utils scripts
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ruff examples tests src utils scripts
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doc-builder style src/diffusers docs/source --max_len 119 --check_only --path_to_docs docs/source
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check_repository_consistency:
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@ -169,3 +169,6 @@ tags
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# dependencies
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/transformers
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# ruff
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.ruff_cache
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@ -177,7 +177,7 @@ Follow these steps to start contributing ([supported Python versions](https://gi
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$ make style
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```
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🧨 Diffusers also uses `flake8` and a few custom scripts to check for coding mistakes. Quality
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🧨 Diffusers also uses `ruff` and a few custom scripts to check for coding mistakes. Quality
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control runs in CI, however you can also run the same checks with:
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```bash
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14
Makefile
14
Makefile
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@ -9,9 +9,8 @@ modified_only_fixup:
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$(eval modified_py_files := $(shell python utils/get_modified_files.py $(check_dirs)))
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@if test -n "$(modified_py_files)"; then \
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echo "Checking/fixing $(modified_py_files)"; \
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black --preview $(modified_py_files); \
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isort $(modified_py_files); \
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flake8 $(modified_py_files); \
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black $(modified_py_files); \
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ruff $(modified_py_files); \
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else \
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echo "No library .py files were modified"; \
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fi
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@ -41,9 +40,8 @@ repo-consistency:
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# this target runs checks on all files
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quality:
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black --check --preview $(check_dirs)
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isort --check-only $(check_dirs)
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flake8 $(check_dirs)
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black --check $(check_dirs)
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ruff $(check_dirs)
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doc-builder style src/diffusers docs/source --max_len 119 --check_only --path_to_docs docs/source
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python utils/check_doc_toc.py
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@ -57,8 +55,8 @@ extra_style_checks:
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# this target runs checks on all files and potentially modifies some of them
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style:
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black --preview $(check_dirs)
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isort $(check_dirs)
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black $(check_dirs)
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ruff $(check_dirs) --fix
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${MAKE} autogenerate_code
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${MAKE} extra_style_checks
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@ -177,7 +177,7 @@ Follow these steps to start contributing ([supported Python versions](https://gi
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$ make style
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```
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🧨 Diffusers also uses `flake8` and a few custom scripts to check for coding mistakes. Quality
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🧨 Diffusers also uses `ruff` and a few custom scripts to check for coding mistakes. Quality
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control runs in CI, however you can also run the same checks with:
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```bash
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@ -210,6 +210,7 @@ torch.set_grad_enabled(False)
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n_experiments = 2
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unet_runs_per_experiment = 50
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# load inputs
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def generate_inputs():
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sample = torch.randn(2, 4, 64, 64).half().cuda()
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@ -288,6 +289,8 @@ pipe = StableDiffusionPipeline.from_pretrained(
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# use jitted unet
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unet_traced = torch.jit.load("unet_traced.pt")
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# del pipe.unet
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class TracedUNet(torch.nn.Module):
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def __init__(self):
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@ -1,11 +1,11 @@
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from typing import Optional, Tuple, Union
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import torch
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from einops import rearrange, reduce
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from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNet2DConditionModel
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from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
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from diffusers.schedulers.scheduling_ddpm import DDPMSchedulerOutput
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from einops import rearrange, reduce
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BITS = 8
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@ -10,10 +10,11 @@ from diffusers.utils import is_safetensors_available
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if is_safetensors_available():
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import safetensors.torch
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from huggingface_hub import snapshot_download
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from diffusers import DiffusionPipeline, __version__
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from diffusers.schedulers.scheduling_utils import SCHEDULER_CONFIG_NAME
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from diffusers.utils import CONFIG_NAME, DIFFUSERS_CACHE, ONNX_WEIGHTS_NAME, WEIGHTS_NAME
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from huggingface_hub import snapshot_download
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class CheckpointMergerPipeline(DiffusionPipeline):
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@ -4,6 +4,8 @@ from typing import List, Optional, Union
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import torch
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from torch import nn
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from torch.nn import functional as F
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from torchvision import transforms
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from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
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from diffusers import (
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AutoencoderKL,
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@ -14,8 +16,6 @@ from diffusers import (
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UNet2DConditionModel,
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)
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from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion import StableDiffusionPipelineOutput
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from torchvision import transforms
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from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
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class MakeCutouts(nn.Module):
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@ -16,6 +16,8 @@ import inspect
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from typing import Callable, List, Optional, Union
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import torch
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from packaging import version
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
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from diffusers import DiffusionPipeline
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from diffusers.configuration_utils import FrozenDict
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@ -29,8 +31,6 @@ from diffusers.schedulers import (
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PNDMScheduler,
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)
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from diffusers.utils import is_accelerate_available
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from packaging import version
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
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from ...utils import deprecate, logging
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from . import StableDiffusionPipelineOutput
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@ -7,11 +7,16 @@ import warnings
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from typing import List, Optional, Union
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import numpy as np
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import PIL
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import torch
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import torch.nn.functional as F
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import PIL
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from accelerate import Accelerator
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# TODO: remove and import from diffusers.utils when the new version of diffusers is released
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from packaging import version
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from tqdm.auto import tqdm
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
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from diffusers import DiffusionPipeline
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from diffusers.models import AutoencoderKL, UNet2DConditionModel
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from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
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@ -19,11 +24,6 @@ from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionS
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from diffusers.schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
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from diffusers.utils import deprecate, logging
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# TODO: remove and import from diffusers.utils when the new version of diffusers is released
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from packaging import version
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from tqdm.auto import tqdm
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
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if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
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PIL_INTERPOLATION = {
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@ -2,9 +2,10 @@ import inspect
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from typing import Callable, List, Optional, Tuple, Union
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import numpy as np
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import torch
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import PIL
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import torch
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
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from diffusers import DiffusionPipeline
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from diffusers.configuration_utils import FrozenDict
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from diffusers.models import AutoencoderKL, UNet2DConditionModel
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@ -12,7 +13,6 @@ from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
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from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
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from diffusers.schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
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from diffusers.utils import deprecate, logging
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
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logger = logging.get_logger(__name__) # pylint: disable=invalid-name
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@ -5,6 +5,7 @@ from typing import Callable, List, Optional, Union
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import numpy as np
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import torch
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
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from diffusers import DiffusionPipeline
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from diffusers.configuration_utils import FrozenDict
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@ -13,7 +14,6 @@ from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
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from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
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from diffusers.schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
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from diffusers.utils import deprecate, logging
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
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logger = logging.get_logger(__name__) # pylint: disable=invalid-name
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@ -3,16 +3,16 @@ import re
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from typing import Callable, List, Optional, Union
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import numpy as np
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import PIL
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import torch
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from packaging import version
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
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import diffusers
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import PIL
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from diffusers import SchedulerMixin, StableDiffusionPipeline
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from diffusers.models import AutoencoderKL, UNet2DConditionModel
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from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput, StableDiffusionSafetyChecker
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from diffusers.utils import deprecate, logging
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from packaging import version
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
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try:
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@ -3,15 +3,15 @@ import re
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from typing import Callable, List, Optional, Union
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import numpy as np
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import PIL
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import torch
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from packaging import version
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from transformers import CLIPFeatureExtractor, CLIPTokenizer
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import diffusers
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import PIL
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from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, SchedulerMixin
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from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
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from diffusers.utils import deprecate, logging
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from packaging import version
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from transformers import CLIPFeatureExtractor, CLIPTokenizer
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try:
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|
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@ -1,6 +1,10 @@
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from typing import Union
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import torch
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from PIL import Image
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from torchvision import transforms as tfms
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from tqdm.auto import tqdm
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from transformers import CLIPTextModel, CLIPTokenizer
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from diffusers import (
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AutoencoderKL,
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@ -10,10 +14,6 @@ from diffusers import (
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PNDMScheduler,
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UNet2DConditionModel,
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)
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from PIL import Image
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from torchvision import transforms as tfms
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from tqdm.auto import tqdm
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from transformers import CLIPTextModel, CLIPTokenizer
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class MagicMixPipeline(DiffusionPipeline):
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@ -2,14 +2,6 @@ import inspect
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from typing import Callable, List, Optional, Union
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import torch
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from diffusers import DiffusionPipeline
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from diffusers.configuration_utils import FrozenDict
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from diffusers.models import AutoencoderKL, UNet2DConditionModel
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from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
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from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
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from diffusers.schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
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from diffusers.utils import deprecate, logging
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from transformers import (
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CLIPFeatureExtractor,
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CLIPTextModel,
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@ -19,6 +11,14 @@ from transformers import (
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pipeline,
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)
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from diffusers import DiffusionPipeline
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from diffusers.configuration_utils import FrozenDict
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from diffusers.models import AutoencoderKL, UNet2DConditionModel
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from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
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from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
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from diffusers.schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
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from diffusers.utils import deprecate, logging
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logger = logging.get_logger(__name__) # pylint: disable=invalid-name
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|
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@ -17,11 +17,11 @@ import warnings
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from typing import Callable, List, Optional, Union
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import torch
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from k_diffusion.external import CompVisDenoiser, CompVisVDenoiser
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from diffusers import DiffusionPipeline, LMSDiscreteScheduler
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from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
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from diffusers.utils import is_accelerate_available, logging
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from k_diffusion.external import CompVisDenoiser, CompVisVDenoiser
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logger = logging.get_logger(__name__) # pylint: disable=invalid-name
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|
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@ -5,6 +5,7 @@ import inspect
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from typing import Callable, List, Optional, Union
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import torch
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
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from diffusers import DiffusionPipeline
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from diffusers.models import AutoencoderKL, UNet2DConditionModel
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@ -12,7 +13,6 @@ from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
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from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
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from diffusers.schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
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from diffusers.utils import logging
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
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logger = logging.get_logger(__name__) # pylint: disable=invalid-name
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|
|
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@ -2,6 +2,13 @@ import inspect
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from typing import Callable, List, Optional, Union
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import torch
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from transformers import (
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CLIPFeatureExtractor,
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CLIPTextModel,
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CLIPTokenizer,
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WhisperForConditionalGeneration,
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WhisperProcessor,
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)
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from diffusers import (
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AutoencoderKL,
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@ -14,13 +21,6 @@ from diffusers import (
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from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion import StableDiffusionPipelineOutput
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from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
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from diffusers.utils import logging
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from transformers import (
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CLIPFeatureExtractor,
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CLIPTextModel,
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CLIPTokenizer,
|
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WhisperForConditionalGeneration,
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WhisperProcessor,
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)
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logger = logging.get_logger(__name__) # pylint: disable=invalid-name
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|
|
|
@ -1,6 +1,7 @@
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from typing import Any, Callable, Dict, List, Optional, Union
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|
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import torch
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
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from diffusers import (
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AutoencoderKL,
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|
@ -13,7 +14,6 @@ from diffusers import (
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)
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from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
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from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
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pipe1_model_id = "CompVis/stable-diffusion-v1-1"
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|
|
|
@ -1,8 +1,9 @@
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from typing import Any, Callable, Dict, List, Optional, Union
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import torch
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import PIL.Image
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import torch
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from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
|
||||
|
||||
from diffusers import (
|
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AutoencoderKL,
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DDIMScheduler,
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||||
|
@ -17,7 +18,6 @@ from diffusers import (
|
|||
from diffusers.configuration_utils import FrozenDict
|
||||
from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
|
||||
from diffusers.utils import deprecate, logging
|
||||
from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
|
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|
||||
|
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logger = logging.get_logger(__name__) # pylint: disable=invalid-name
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|
|
|
@ -2,13 +2,13 @@ import types
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from typing import List, Optional, Tuple, Union
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import torch
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from transformers import CLIPTextModelWithProjection, CLIPTokenizer
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from transformers.models.clip.modeling_clip import CLIPTextModelOutput
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from diffusers.models import PriorTransformer
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from diffusers.pipelines import DiffusionPipeline, StableDiffusionImageVariationPipeline
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from diffusers.schedulers import UnCLIPScheduler
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from diffusers.utils import logging, randn_tensor
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from transformers import CLIPTextModelWithProjection, CLIPTokenizer
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from transformers.models.clip.modeling_clip import CLIPTextModelOutput
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logger = logging.get_logger(__name__) # pylint: disable=invalid-name
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|
|
|
@ -1,15 +1,7 @@
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from typing import Callable, List, Optional, Union
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|
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import torch
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|
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import PIL
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from diffusers import DiffusionPipeline
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from diffusers.configuration_utils import FrozenDict
|
||||
from diffusers.models import AutoencoderKL, UNet2DConditionModel
|
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from diffusers.pipelines.stable_diffusion import StableDiffusionInpaintPipeline
|
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from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
|
||||
from diffusers.schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
|
||||
from diffusers.utils import deprecate, is_accelerate_available, logging
|
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import torch
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from transformers import (
|
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CLIPFeatureExtractor,
|
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CLIPSegForImageSegmentation,
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|
@ -18,6 +10,14 @@ from transformers import (
|
|||
CLIPTokenizer,
|
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)
|
||||
|
||||
from diffusers import DiffusionPipeline
|
||||
from diffusers.configuration_utils import FrozenDict
|
||||
from diffusers.models import AutoencoderKL, UNet2DConditionModel
|
||||
from diffusers.pipelines.stable_diffusion import StableDiffusionInpaintPipeline
|
||||
from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
|
||||
from diffusers.schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
|
||||
from diffusers.utils import deprecate, is_accelerate_available, logging
|
||||
|
||||
|
||||
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
|
||||
|
||||
|
|
|
@ -16,14 +16,14 @@ import math
|
|||
from typing import Callable, List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
import PIL
|
||||
import torch
|
||||
from PIL import Image
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
|
||||
from diffusers.models import AutoencoderKL, UNet2DConditionModel
|
||||
from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_upscale import StableDiffusionUpscalePipeline
|
||||
from diffusers.schedulers import DDIMScheduler, DDPMScheduler, LMSDiscreteScheduler, PNDMScheduler
|
||||
from PIL import Image
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
|
||||
|
||||
def make_transparency_mask(size, overlap_pixels, remove_borders=[]):
|
||||
|
|
|
@ -6,6 +6,7 @@ from dataclasses import dataclass
|
|||
from typing import Callable, Dict, List, Optional, Union
|
||||
|
||||
import torch
|
||||
from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
|
||||
|
||||
from diffusers import DiffusionPipeline
|
||||
from diffusers.configuration_utils import FrozenDict
|
||||
|
@ -14,7 +15,6 @@ from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion import Stabl
|
|||
from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
|
||||
from diffusers.schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
|
||||
from diffusers.utils import deprecate, logging
|
||||
from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
|
||||
|
||||
|
||||
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
|
||||
|
|
|
@ -23,27 +23,27 @@ import warnings
|
|||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
import accelerate
|
||||
import torch
|
||||
import torch.nn.functional as F
|
||||
import torch.utils.checkpoint
|
||||
from torch.utils.data import Dataset
|
||||
|
||||
import accelerate
|
||||
import diffusers
|
||||
import transformers
|
||||
from accelerate import Accelerator
|
||||
from accelerate.logging import get_logger
|
||||
from accelerate.utils import set_seed
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from packaging import version
|
||||
from PIL import Image
|
||||
from torch.utils.data import Dataset
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import AutoTokenizer, PretrainedConfig
|
||||
|
||||
import diffusers
|
||||
from diffusers import AutoencoderKL, DDPMScheduler, DiffusionPipeline, UNet2DConditionModel
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.utils import check_min_version
|
||||
from diffusers.utils.import_utils import is_xformers_available
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from packaging import version
|
||||
from PIL import Image
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import AutoTokenizer, PretrainedConfig
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
|
|
|
@ -6,15 +6,24 @@ import os
|
|||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
import torch.utils.checkpoint
|
||||
from torch.utils.data import Dataset
|
||||
|
||||
import jax
|
||||
import jax.numpy as jnp
|
||||
import numpy as np
|
||||
import optax
|
||||
import torch
|
||||
import torch.utils.checkpoint
|
||||
import transformers
|
||||
from flax import jax_utils
|
||||
from flax.training import train_state
|
||||
from flax.training.common_utils import shard
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from jax.experimental.compilation_cache import compilation_cache as cc
|
||||
from PIL import Image
|
||||
from torch.utils.data import Dataset
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPFeatureExtractor, CLIPTokenizer, FlaxCLIPTextModel, set_seed
|
||||
|
||||
from diffusers import (
|
||||
FlaxAutoencoderKL,
|
||||
FlaxDDPMScheduler,
|
||||
|
@ -24,15 +33,6 @@ from diffusers import (
|
|||
)
|
||||
from diffusers.pipelines.stable_diffusion import FlaxStableDiffusionSafetyChecker
|
||||
from diffusers.utils import check_min_version
|
||||
from flax import jax_utils
|
||||
from flax.training import train_state
|
||||
from flax.training.common_utils import shard
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from jax.experimental.compilation_cache import compilation_cache as cc
|
||||
from PIL import Image
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPFeatureExtractor, CLIPTokenizer, FlaxCLIPTextModel, set_seed
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
|
|
|
@ -26,13 +26,18 @@ import numpy as np
|
|||
import torch
|
||||
import torch.nn.functional as F
|
||||
import torch.utils.checkpoint
|
||||
from torch.utils.data import Dataset
|
||||
|
||||
import diffusers
|
||||
import transformers
|
||||
from accelerate import Accelerator
|
||||
from accelerate.logging import get_logger
|
||||
from accelerate.utils import set_seed
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from PIL import Image
|
||||
from torch.utils.data import Dataset
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import AutoTokenizer, PretrainedConfig
|
||||
|
||||
import diffusers
|
||||
from diffusers import (
|
||||
AutoencoderKL,
|
||||
DDPMScheduler,
|
||||
|
@ -45,11 +50,6 @@ from diffusers.models.cross_attention import LoRACrossAttnProcessor
|
|||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.utils import check_min_version, is_wandb_available
|
||||
from diffusers.utils.import_utils import is_xformers_available
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from PIL import Image
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import AutoTokenizer, PretrainedConfig
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
|
|
|
@ -5,12 +5,10 @@ import os
|
|||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
import colossalai
|
||||
import torch
|
||||
import torch.nn.functional as F
|
||||
import torch.utils.checkpoint
|
||||
from torch.utils.data import Dataset
|
||||
|
||||
import colossalai
|
||||
from colossalai.context.parallel_mode import ParallelMode
|
||||
from colossalai.core import global_context as gpc
|
||||
from colossalai.logging import disable_existing_loggers, get_dist_logger
|
||||
|
@ -18,14 +16,16 @@ from colossalai.nn.optimizer.gemini_optimizer import GeminiAdamOptimizer
|
|||
from colossalai.nn.parallel.utils import get_static_torch_model
|
||||
from colossalai.utils import get_current_device
|
||||
from colossalai.utils.model.colo_init_context import ColoInitContext
|
||||
from diffusers import AutoencoderKL, DDPMScheduler, DiffusionPipeline, UNet2DConditionModel
|
||||
from diffusers.optimization import get_scheduler
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from PIL import Image
|
||||
from torch.utils.data import Dataset
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import AutoTokenizer, PretrainedConfig
|
||||
|
||||
from diffusers import AutoencoderKL, DDPMScheduler, DiffusionPipeline, UNet2DConditionModel
|
||||
from diffusers.optimization import get_scheduler
|
||||
|
||||
|
||||
disable_existing_loggers()
|
||||
logger = get_dist_logger()
|
||||
|
|
|
@ -11,11 +11,16 @@ import numpy as np
|
|||
import torch
|
||||
import torch.nn.functional as F
|
||||
import torch.utils.checkpoint
|
||||
from torch.utils.data import Dataset
|
||||
|
||||
from accelerate import Accelerator
|
||||
from accelerate.logging import get_logger
|
||||
from accelerate.utils import set_seed
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from PIL import Image, ImageDraw
|
||||
from torch.utils.data import Dataset
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
|
||||
from diffusers import (
|
||||
AutoencoderKL,
|
||||
DDPMScheduler,
|
||||
|
@ -25,11 +30,6 @@ from diffusers import (
|
|||
)
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.utils import check_min_version
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from PIL import Image, ImageDraw
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
|
|
|
@ -10,22 +10,22 @@ import numpy as np
|
|||
import torch
|
||||
import torch.nn.functional as F
|
||||
import torch.utils.checkpoint
|
||||
from torch.utils.data import Dataset
|
||||
|
||||
from accelerate import Accelerator
|
||||
from accelerate.logging import get_logger
|
||||
from accelerate.utils import set_seed
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from PIL import Image, ImageDraw
|
||||
from torch.utils.data import Dataset
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
|
||||
from diffusers import AutoencoderKL, DDPMScheduler, StableDiffusionInpaintPipeline, UNet2DConditionModel
|
||||
from diffusers.loaders import AttnProcsLayers
|
||||
from diffusers.models.cross_attention import LoRACrossAttnProcessor
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.utils import check_min_version
|
||||
from diffusers.utils.import_utils import is_xformers_available
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from PIL import Image, ImageDraw
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
|
|
|
@ -1,9 +1,9 @@
|
|||
import torch
|
||||
|
||||
import intel_extension_for_pytorch as ipex
|
||||
from diffusers import StableDiffusionPipeline
|
||||
import torch
|
||||
from PIL import Image
|
||||
|
||||
from diffusers import StableDiffusionPipeline
|
||||
|
||||
|
||||
def image_grid(imgs, rows, cols):
|
||||
assert len(imgs) == rows * cols
|
||||
|
|
|
@ -6,30 +6,30 @@ import random
|
|||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
import intel_extension_for_pytorch as ipex
|
||||
import numpy as np
|
||||
import PIL
|
||||
import torch
|
||||
import torch.nn.functional as F
|
||||
import torch.utils.checkpoint
|
||||
from torch.utils.data import Dataset
|
||||
|
||||
import intel_extension_for_pytorch as ipex
|
||||
import PIL
|
||||
from accelerate import Accelerator
|
||||
from accelerate.logging import get_logger
|
||||
from accelerate.utils import set_seed
|
||||
from diffusers import AutoencoderKL, DDPMScheduler, PNDMScheduler, StableDiffusionPipeline, UNet2DConditionModel
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.pipelines.stable_diffusion import StableDiffusionSafetyChecker
|
||||
from diffusers.utils import check_min_version
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
|
||||
# TODO: remove and import from diffusers.utils when the new version of diffusers is released
|
||||
from packaging import version
|
||||
from PIL import Image
|
||||
from torch.utils.data import Dataset
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
|
||||
|
||||
from diffusers import AutoencoderKL, DDPMScheduler, PNDMScheduler, StableDiffusionPipeline, UNet2DConditionModel
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.pipelines.stable_diffusion import StableDiffusionSafetyChecker
|
||||
from diffusers.utils import check_min_version
|
||||
|
||||
|
||||
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
|
||||
PIL_INTERPOLATION = {
|
||||
|
|
|
@ -8,26 +8,26 @@ import warnings
|
|||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
import datasets
|
||||
import torch
|
||||
import torch.nn.functional as F
|
||||
import torch.utils.checkpoint
|
||||
from torch.utils.data import Dataset
|
||||
|
||||
import datasets
|
||||
import diffusers
|
||||
import transformers
|
||||
from accelerate import Accelerator
|
||||
from accelerate.logging import get_logger
|
||||
from accelerate.utils import set_seed
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from PIL import Image
|
||||
from torch.utils.data import Dataset
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import AutoTokenizer, PretrainedConfig
|
||||
|
||||
import diffusers
|
||||
from diffusers import AutoencoderKL, DDPMScheduler, DiffusionPipeline, UNet2DConditionModel
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.utils import check_min_version
|
||||
from diffusers.utils.import_utils import is_xformers_available
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from PIL import Image
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import AutoTokenizer, PretrainedConfig
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
|
|
|
@ -21,29 +21,29 @@ import random
|
|||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
import datasets
|
||||
import numpy as np
|
||||
import torch
|
||||
import torch.nn.functional as F
|
||||
import torch.utils.checkpoint
|
||||
|
||||
import datasets
|
||||
import diffusers
|
||||
import transformers
|
||||
from accelerate import Accelerator
|
||||
from accelerate.logging import get_logger
|
||||
from accelerate.utils import set_seed
|
||||
from datasets import load_dataset
|
||||
from diffusers import AutoencoderKL, DDPMScheduler, StableDiffusionPipeline, UNet2DConditionModel
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.training_utils import EMAModel
|
||||
from diffusers.utils import check_min_version
|
||||
from diffusers.utils.import_utils import is_xformers_available
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from onnxruntime.training.ortmodule import ORTModule
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
|
||||
import diffusers
|
||||
from diffusers import AutoencoderKL, DDPMScheduler, StableDiffusionPipeline, UNet2DConditionModel
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.training_utils import EMAModel
|
||||
from diffusers.utils import check_min_version
|
||||
from diffusers.utils.import_utils import is_xformers_available
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.13.0.dev0")
|
||||
|
|
|
@ -21,19 +21,28 @@ import random
|
|||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
import datasets
|
||||
import numpy as np
|
||||
import PIL
|
||||
import torch
|
||||
import torch.nn.functional as F
|
||||
import torch.utils.checkpoint
|
||||
from torch.utils.data import Dataset
|
||||
|
||||
import datasets
|
||||
import diffusers
|
||||
import PIL
|
||||
import transformers
|
||||
from accelerate import Accelerator
|
||||
from accelerate.logging import get_logger
|
||||
from accelerate.utils import set_seed
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from onnxruntime.training.ortmodule import ORTModule
|
||||
|
||||
# TODO: remove and import from diffusers.utils when the new version of diffusers is released
|
||||
from packaging import version
|
||||
from PIL import Image
|
||||
from torch.utils.data import Dataset
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
|
||||
import diffusers
|
||||
from diffusers import (
|
||||
AutoencoderKL,
|
||||
DDPMScheduler,
|
||||
|
@ -45,15 +54,6 @@ from diffusers import (
|
|||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.utils import check_min_version, is_wandb_available
|
||||
from diffusers.utils.import_utils import is_xformers_available
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from onnxruntime.training.ortmodule import ORTModule
|
||||
|
||||
# TODO: remove and import from diffusers.utils when the new version of diffusers is released
|
||||
from packaging import version
|
||||
from PIL import Image
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
|
||||
|
||||
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
|
||||
|
|
|
@ -6,23 +6,23 @@ import os
|
|||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
import datasets
|
||||
import torch
|
||||
import torch.nn.functional as F
|
||||
|
||||
import datasets
|
||||
import diffusers
|
||||
from accelerate import Accelerator
|
||||
from accelerate.logging import get_logger
|
||||
from datasets import load_dataset
|
||||
from diffusers import DDPMPipeline, DDPMScheduler, UNet2DModel
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.training_utils import EMAModel
|
||||
from diffusers.utils import check_min_version
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from onnxruntime.training.ortmodule import ORTModule
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
|
||||
import diffusers
|
||||
from diffusers import DDPMPipeline, DDPMScheduler, UNet2DModel
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.training_utils import EMAModel
|
||||
from diffusers.utils import check_min_version
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.13.0.dev0")
|
||||
|
|
|
@ -24,6 +24,7 @@ import unittest
|
|||
from typing import List
|
||||
|
||||
from accelerate.utils import write_basic_config
|
||||
|
||||
from diffusers.utils import slow
|
||||
|
||||
|
||||
|
|
|
@ -21,30 +21,30 @@ import random
|
|||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
import accelerate
|
||||
import datasets
|
||||
import numpy as np
|
||||
import torch
|
||||
import torch.nn.functional as F
|
||||
import torch.utils.checkpoint
|
||||
|
||||
import accelerate
|
||||
import datasets
|
||||
import diffusers
|
||||
import transformers
|
||||
from accelerate import Accelerator
|
||||
from accelerate.logging import get_logger
|
||||
from accelerate.utils import set_seed
|
||||
from datasets import load_dataset
|
||||
from diffusers import AutoencoderKL, DDPMScheduler, StableDiffusionPipeline, UNet2DConditionModel
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.training_utils import EMAModel
|
||||
from diffusers.utils import check_min_version, deprecate
|
||||
from diffusers.utils.import_utils import is_xformers_available
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from packaging import version
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
|
||||
import diffusers
|
||||
from diffusers import AutoencoderKL, DDPMScheduler, StableDiffusionPipeline, UNet2DConditionModel
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.training_utils import EMAModel
|
||||
from diffusers.utils import check_min_version, deprecate
|
||||
from diffusers.utils.import_utils import is_xformers_available
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.13.0.dev0")
|
||||
|
|
|
@ -6,15 +6,22 @@ import random
|
|||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
import torch.utils.checkpoint
|
||||
|
||||
import jax
|
||||
import jax.numpy as jnp
|
||||
import numpy as np
|
||||
import optax
|
||||
import torch
|
||||
import torch.utils.checkpoint
|
||||
import transformers
|
||||
from datasets import load_dataset
|
||||
from flax import jax_utils
|
||||
from flax.training import train_state
|
||||
from flax.training.common_utils import shard
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPFeatureExtractor, CLIPTokenizer, FlaxCLIPTextModel, set_seed
|
||||
|
||||
from diffusers import (
|
||||
FlaxAutoencoderKL,
|
||||
FlaxDDPMScheduler,
|
||||
|
@ -24,13 +31,6 @@ from diffusers import (
|
|||
)
|
||||
from diffusers.pipelines.stable_diffusion import FlaxStableDiffusionSafetyChecker
|
||||
from diffusers.utils import check_min_version
|
||||
from flax import jax_utils
|
||||
from flax.training import train_state
|
||||
from flax.training.common_utils import shard
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPFeatureExtractor, CLIPTokenizer, FlaxCLIPTextModel, set_seed
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
|
|
|
@ -22,28 +22,28 @@ import random
|
|||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
import datasets
|
||||
import numpy as np
|
||||
import torch
|
||||
import torch.nn.functional as F
|
||||
import torch.utils.checkpoint
|
||||
|
||||
import datasets
|
||||
import diffusers
|
||||
import transformers
|
||||
from accelerate import Accelerator
|
||||
from accelerate.logging import get_logger
|
||||
from accelerate.utils import set_seed
|
||||
from datasets import load_dataset
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
|
||||
import diffusers
|
||||
from diffusers import AutoencoderKL, DDPMScheduler, DiffusionPipeline, UNet2DConditionModel
|
||||
from diffusers.loaders import AttnProcsLayers
|
||||
from diffusers.models.cross_attention import LoRACrossAttnProcessor
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.utils import check_min_version, is_wandb_available
|
||||
from diffusers.utils.import_utils import is_xformers_available
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
|
|
|
@ -22,17 +22,25 @@ from pathlib import Path
|
|||
from typing import Optional
|
||||
|
||||
import numpy as np
|
||||
import PIL
|
||||
import torch
|
||||
import torch.nn.functional as F
|
||||
import torch.utils.checkpoint
|
||||
from torch.utils.data import Dataset
|
||||
|
||||
import diffusers
|
||||
import PIL
|
||||
import transformers
|
||||
from accelerate import Accelerator
|
||||
from accelerate.logging import get_logger
|
||||
from accelerate.utils import set_seed
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
|
||||
# TODO: remove and import from diffusers.utils when the new version of diffusers is released
|
||||
from packaging import version
|
||||
from PIL import Image
|
||||
from torch.utils.data import Dataset
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
|
||||
import diffusers
|
||||
from diffusers import (
|
||||
AutoencoderKL,
|
||||
DDPMScheduler,
|
||||
|
@ -44,14 +52,6 @@ from diffusers import (
|
|||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.utils import check_min_version, is_wandb_available
|
||||
from diffusers.utils.import_utils import is_xformers_available
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
|
||||
# TODO: remove and import from diffusers.utils when the new version of diffusers is released
|
||||
from packaging import version
|
||||
from PIL import Image
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
|
||||
|
||||
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
|
||||
|
|
|
@ -6,16 +6,27 @@ import random
|
|||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
import torch.utils.checkpoint
|
||||
from torch.utils.data import Dataset
|
||||
|
||||
import jax
|
||||
import jax.numpy as jnp
|
||||
import numpy as np
|
||||
import optax
|
||||
import PIL
|
||||
import torch
|
||||
import torch.utils.checkpoint
|
||||
import transformers
|
||||
from flax import jax_utils
|
||||
from flax.training import train_state
|
||||
from flax.training.common_utils import shard
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
|
||||
# TODO: remove and import from diffusers.utils when the new version of diffusers is released
|
||||
from packaging import version
|
||||
from PIL import Image
|
||||
from torch.utils.data import Dataset
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPFeatureExtractor, CLIPTokenizer, FlaxCLIPTextModel, set_seed
|
||||
|
||||
from diffusers import (
|
||||
FlaxAutoencoderKL,
|
||||
FlaxDDPMScheduler,
|
||||
|
@ -25,17 +36,6 @@ from diffusers import (
|
|||
)
|
||||
from diffusers.pipelines.stable_diffusion import FlaxStableDiffusionSafetyChecker
|
||||
from diffusers.utils import check_min_version
|
||||
from flax import jax_utils
|
||||
from flax.training import train_state
|
||||
from flax.training.common_utils import shard
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
|
||||
# TODO: remove and import from diffusers.utils when the new version of diffusers is released
|
||||
from packaging import version
|
||||
from PIL import Image
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
from transformers import CLIPFeatureExtractor, CLIPTokenizer, FlaxCLIPTextModel, set_seed
|
||||
|
||||
|
||||
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
|
||||
|
|
|
@ -6,24 +6,24 @@ import os
|
|||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
import torch
|
||||
import torch.nn.functional as F
|
||||
|
||||
import accelerate
|
||||
import datasets
|
||||
import diffusers
|
||||
import torch
|
||||
import torch.nn.functional as F
|
||||
from accelerate import Accelerator
|
||||
from accelerate.logging import get_logger
|
||||
from datasets import load_dataset
|
||||
from diffusers import DDPMPipeline, DDPMScheduler, UNet2DModel
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.training_utils import EMAModel
|
||||
from diffusers.utils import check_min_version
|
||||
from huggingface_hub import HfFolder, Repository, create_repo, whoami
|
||||
from packaging import version
|
||||
from torchvision import transforms
|
||||
from tqdm.auto import tqdm
|
||||
|
||||
import diffusers
|
||||
from diffusers import DDPMPipeline, DDPMScheduler, UNet2DModel
|
||||
from diffusers.optimization import get_scheduler
|
||||
from diffusers.training_utils import EMAModel
|
||||
from diffusers.utils import check_min_version
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.13.0.dev0")
|
||||
|
|
|
@ -1,3 +1,18 @@
|
|||
[tool.black]
|
||||
line-length = 119
|
||||
target-version = ['py36']
|
||||
target-version = ['py37']
|
||||
|
||||
[tool.ruff]
|
||||
# Never enforce `E501` (line length violations).
|
||||
ignore = ["E501", "E741", "W605"]
|
||||
select = ["E", "F", "I", "W"]
|
||||
line-length = 119
|
||||
|
||||
# Ignore import violations in all `__init__.py` files.
|
||||
[tool.ruff.per-file-ignores]
|
||||
"__init__.py" = ["E402", "F401", "F403", "F811"]
|
||||
"src/diffusers/utils/dummy_*.py" = ["F401"]
|
||||
|
||||
[tool.ruff.isort]
|
||||
lines-after-imports = 2
|
||||
known-first-party = ["diffusers"]
|
||||
|
|
|
@ -19,9 +19,9 @@ import json
|
|||
import os
|
||||
|
||||
import torch
|
||||
from transformers.file_utils import has_file
|
||||
|
||||
from diffusers import UNet2DConditionModel, UNet2DModel
|
||||
from transformers.file_utils import has_file
|
||||
|
||||
|
||||
do_only_config = False
|
||||
|
|
|
@ -1,8 +1,8 @@
|
|||
import argparse
|
||||
|
||||
import OmegaConf
|
||||
import torch
|
||||
|
||||
import OmegaConf
|
||||
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
|
||||
|
||||
|
||||
|
|
|
@ -5,11 +5,11 @@ import os
|
|||
from copy import deepcopy
|
||||
|
||||
import torch
|
||||
from audio_diffusion.models import DiffusionAttnUnet1D
|
||||
from diffusion import sampling
|
||||
from torch import nn
|
||||
|
||||
from audio_diffusion.models import DiffusionAttnUnet1D
|
||||
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNet1DModel
|
||||
from diffusion import sampling
|
||||
|
||||
|
||||
MODELS_MAP = {
|
||||
|
|
|
@ -7,7 +7,6 @@ import os.path as osp
|
|||
import re
|
||||
|
||||
import torch
|
||||
|
||||
from safetensors.torch import load_file, save_file
|
||||
|
||||
|
||||
|
|
|
@ -2,9 +2,9 @@ import argparse
|
|||
import os
|
||||
|
||||
import torch
|
||||
from torchvision.datasets.utils import download_url
|
||||
|
||||
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, Transformer2DModel
|
||||
from torchvision.datasets.utils import download_url
|
||||
|
||||
|
||||
pretrained_models = {512: "DiT-XL-2-512x512.pt", 256: "DiT-XL-2-256x256.pt"}
|
||||
|
|
|
@ -1,9 +1,9 @@
|
|||
import argparse
|
||||
|
||||
import torch
|
||||
|
||||
import huggingface_hub
|
||||
import k_diffusion as K
|
||||
import torch
|
||||
|
||||
from diffusers import UNet2DConditionModel
|
||||
|
||||
|
||||
|
|
|
@ -2,13 +2,13 @@ import argparse
|
|||
import tempfile
|
||||
|
||||
import torch
|
||||
|
||||
from accelerate import load_checkpoint_and_dispatch
|
||||
from transformers import CLIPTextModelWithProjection, CLIPTokenizer
|
||||
|
||||
from diffusers import UnCLIPPipeline, UNet2DConditionModel, UNet2DModel
|
||||
from diffusers.models.prior_transformer import PriorTransformer
|
||||
from diffusers.pipelines.unclip.text_proj import UnCLIPTextProjModel
|
||||
from diffusers.schedulers.scheduling_unclip import UnCLIPScheduler
|
||||
from transformers import CLIPTextModelWithProjection, CLIPTokenizer
|
||||
|
||||
|
||||
"""
|
||||
|
@ -249,7 +249,6 @@ DECODER_CONFIG = {
|
|||
"class_embed_type": "identity",
|
||||
"attention_head_dim": 64,
|
||||
"resnet_time_scale_shift": "scale_shift",
|
||||
"class_embed_type": "identity",
|
||||
}
|
||||
|
||||
|
||||
|
|
|
@ -355,5 +355,5 @@ if __name__ == "__main__":
|
|||
|
||||
pipe = LDMPipeline(unet=model, scheduler=scheduler, vae=vqvae)
|
||||
pipe.save_pretrained(args.dump_path)
|
||||
except:
|
||||
except: # noqa: E722
|
||||
model.save_pretrained(args.dump_path)
|
||||
|
|
|
@ -181,5 +181,5 @@ if __name__ == "__main__":
|
|||
|
||||
pipe = ScoreSdeVePipeline(unet=model, scheduler=scheduler)
|
||||
pipe.save_pretrained(args.dump_path)
|
||||
except:
|
||||
except: # noqa: E722
|
||||
model.save_pretrained(args.dump_path)
|
||||
|
|
|
@ -17,12 +17,12 @@ import os
|
|||
import shutil
|
||||
from pathlib import Path
|
||||
|
||||
import onnx
|
||||
import torch
|
||||
from packaging import version
|
||||
from torch.onnx import export
|
||||
|
||||
import onnx
|
||||
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
|
||||
from packaging import version
|
||||
|
||||
|
||||
is_torch_less_than_1_11 = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
|
||||
|
|
|
@ -1,8 +1,9 @@
|
|||
import argparse
|
||||
|
||||
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
|
||||
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
|
||||
|
||||
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser()
|
||||
|
|
|
@ -1,9 +1,10 @@
|
|||
import argparse
|
||||
import io
|
||||
|
||||
import torch
|
||||
|
||||
import requests
|
||||
import torch
|
||||
from omegaconf import OmegaConf
|
||||
|
||||
from diffusers import AutoencoderKL
|
||||
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
|
||||
assign_to_checkpoint,
|
||||
|
@ -12,7 +13,6 @@ from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
|
|||
renew_vae_attention_paths,
|
||||
renew_vae_resnet_paths,
|
||||
)
|
||||
from omegaconf import OmegaConf
|
||||
|
||||
|
||||
def custom_convert_ldm_vae_checkpoint(checkpoint, config):
|
||||
|
|
|
@ -18,6 +18,12 @@ import argparse
|
|||
from argparse import Namespace
|
||||
|
||||
import torch
|
||||
from transformers import (
|
||||
CLIPFeatureExtractor,
|
||||
CLIPTextModelWithProjection,
|
||||
CLIPTokenizer,
|
||||
CLIPVisionModelWithProjection,
|
||||
)
|
||||
|
||||
from diffusers import (
|
||||
AutoencoderKL,
|
||||
|
@ -31,12 +37,6 @@ from diffusers import (
|
|||
VersatileDiffusionPipeline,
|
||||
)
|
||||
from diffusers.pipelines.versatile_diffusion.modeling_text_unet import UNetFlatConditionModel
|
||||
from transformers import (
|
||||
CLIPFeatureExtractor,
|
||||
CLIPTextModelWithProjection,
|
||||
CLIPTokenizer,
|
||||
CLIPVisionModelWithProjection,
|
||||
)
|
||||
|
||||
|
||||
SCHEDULER_CONFIG = Namespace(
|
||||
|
|
|
@ -36,14 +36,14 @@ import argparse
|
|||
import tempfile
|
||||
|
||||
import torch
|
||||
|
||||
import yaml
|
||||
from accelerate import init_empty_weights, load_checkpoint_and_dispatch
|
||||
from diffusers import Transformer2DModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
|
||||
from diffusers.pipelines.vq_diffusion.pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings
|
||||
from transformers import CLIPTextModel, CLIPTokenizer
|
||||
from yaml.loader import FullLoader
|
||||
|
||||
from diffusers import Transformer2DModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
|
||||
from diffusers.pipelines.vq_diffusion.pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings
|
||||
|
||||
|
||||
try:
|
||||
from omegaconf import OmegaConf
|
||||
|
|
|
@ -1,9 +1,9 @@
|
|||
import random
|
||||
|
||||
import torch
|
||||
from huggingface_hub import HfApi
|
||||
|
||||
from diffusers import UNet2DModel
|
||||
from huggingface_hub import HfApi
|
||||
|
||||
|
||||
api = HfApi()
|
||||
|
|
6
setup.py
6
setup.py
|
@ -80,10 +80,9 @@ from setuptools import find_packages, setup
|
|||
_deps = [
|
||||
"Pillow", # keep the PIL.Image.Resampling deprecation away
|
||||
"accelerate>=0.11.0",
|
||||
"black==22.12",
|
||||
"black~=23.1",
|
||||
"datasets",
|
||||
"filelock",
|
||||
"flake8>=3.8.3",
|
||||
"flax>=0.4.1",
|
||||
"hf-doc-builder>=0.3.0",
|
||||
"huggingface-hub>=0.10.0",
|
||||
|
@ -99,6 +98,7 @@ _deps = [
|
|||
"pytest",
|
||||
"pytest-timeout",
|
||||
"pytest-xdist",
|
||||
"ruff>=0.0.241",
|
||||
"safetensors",
|
||||
"sentencepiece>=0.1.91,!=0.1.92",
|
||||
"scipy",
|
||||
|
@ -178,7 +178,7 @@ extras = {}
|
|||
|
||||
|
||||
extras = {}
|
||||
extras["quality"] = deps_list("black", "isort", "flake8", "hf-doc-builder")
|
||||
extras["quality"] = deps_list("black", "isort", "ruff", "hf-doc-builder")
|
||||
extras["docs"] = deps_list("hf-doc-builder")
|
||||
extras["training"] = deps_list("accelerate", "datasets", "tensorboard", "Jinja2")
|
||||
extras["test"] = deps_list(
|
||||
|
|
|
@ -26,7 +26,6 @@ from pathlib import PosixPath
|
|||
from typing import Any, Dict, Tuple, Union
|
||||
|
||||
import numpy as np
|
||||
|
||||
from huggingface_hub import hf_hub_download
|
||||
from huggingface_hub.utils import EntryNotFoundError, RepositoryNotFoundError, RevisionNotFoundError
|
||||
from requests import HTTPError
|
||||
|
|
|
@ -4,10 +4,9 @@
|
|||
deps = {
|
||||
"Pillow": "Pillow",
|
||||
"accelerate": "accelerate>=0.11.0",
|
||||
"black": "black==22.12",
|
||||
"black": "black~=23.1",
|
||||
"datasets": "datasets",
|
||||
"filelock": "filelock",
|
||||
"flake8": "flake8>=3.8.3",
|
||||
"flax": "flax>=0.4.1",
|
||||
"hf-doc-builder": "hf-doc-builder>=0.3.0",
|
||||
"huggingface-hub": "huggingface-hub>=0.10.0",
|
||||
|
@ -23,6 +22,7 @@ deps = {
|
|||
"pytest": "pytest",
|
||||
"pytest-timeout": "pytest-timeout",
|
||||
"pytest-xdist": "pytest-xdist",
|
||||
"ruff": "ruff>=0.0.241",
|
||||
"safetensors": "safetensors",
|
||||
"sentencepiece": "sentencepiece>=0.1.91,!=0.1.92",
|
||||
"scipy": "scipy",
|
||||
|
|
|
@ -14,7 +14,6 @@
|
|||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
import tqdm
|
||||
|
||||
from ...models.unet_1d import UNet1DModel
|
||||
|
@ -57,13 +56,13 @@ class ValueGuidedRLPipeline(DiffusionPipeline):
|
|||
for key in self.data.keys():
|
||||
try:
|
||||
self.means[key] = self.data[key].mean()
|
||||
except:
|
||||
except: # noqa: E722
|
||||
pass
|
||||
self.stds = dict()
|
||||
for key in self.data.keys():
|
||||
try:
|
||||
self.stds[key] = self.data[key].std()
|
||||
except:
|
||||
except: # noqa: E722
|
||||
pass
|
||||
self.state_dim = env.observation_space.shape[0]
|
||||
self.action_dim = env.action_space.shape[0]
|
||||
|
|
|
@ -16,10 +16,9 @@
|
|||
|
||||
from pickle import UnpicklingError
|
||||
|
||||
import numpy as np
|
||||
|
||||
import jax
|
||||
import jax.numpy as jnp
|
||||
import numpy as np
|
||||
from flax.serialization import from_bytes
|
||||
from flax.traverse_util import flatten_dict
|
||||
|
||||
|
|
|
@ -20,11 +20,10 @@ from functools import partial
|
|||
from typing import Callable, List, Optional, Tuple, Union
|
||||
|
||||
import torch
|
||||
from torch import Tensor, device
|
||||
|
||||
from huggingface_hub import hf_hub_download
|
||||
from huggingface_hub.utils import EntryNotFoundError, RepositoryNotFoundError, RevisionNotFoundError
|
||||
from requests import HTTPError
|
||||
from torch import Tensor, device
|
||||
|
||||
from .. import __version__
|
||||
from ..utils import (
|
||||
|
@ -500,7 +499,7 @@ class ModelMixin(torch.nn.Module):
|
|||
subfolder=subfolder,
|
||||
user_agent=user_agent,
|
||||
)
|
||||
except:
|
||||
except: # noqa: E722
|
||||
pass
|
||||
if model_file is None:
|
||||
model_file = _get_model_file(
|
||||
|
|
|
@ -2,7 +2,6 @@ from dataclasses import dataclass
|
|||
from typing import List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
|
||||
import PIL
|
||||
from PIL import Image
|
||||
|
||||
|
|
|
@ -3,7 +3,6 @@ from typing import Optional, Tuple
|
|||
|
||||
import torch
|
||||
from torch import nn
|
||||
|
||||
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
|
||||
from transformers.utils import ModelOutput
|
||||
|
||||
|
|
|
@ -16,11 +16,11 @@ import inspect
|
|||
from typing import Any, Callable, Dict, List, Optional, Union
|
||||
|
||||
import torch
|
||||
|
||||
from diffusers.utils import is_accelerate_available
|
||||
from packaging import version
|
||||
from transformers import CLIPFeatureExtractor, XLMRobertaTokenizer
|
||||
|
||||
from diffusers.utils import is_accelerate_available
|
||||
|
||||
from ...configuration_utils import FrozenDict
|
||||
from ...models import AutoencoderKL, UNet2DConditionModel
|
||||
from ...schedulers import KarrasDiffusionSchedulers
|
||||
|
|
|
@ -16,13 +16,13 @@ import inspect
|
|||
from typing import Callable, List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
import PIL
|
||||
from diffusers.utils import is_accelerate_available
|
||||
import torch
|
||||
from packaging import version
|
||||
from transformers import CLIPFeatureExtractor, XLMRobertaTokenizer
|
||||
|
||||
from diffusers.utils import is_accelerate_available
|
||||
|
||||
from ...configuration_utils import FrozenDict
|
||||
from ...models import AutoencoderKL, UNet2DConditionModel
|
||||
from ...schedulers import KarrasDiffusionSchedulers
|
||||
|
|
|
@ -1,3 +1,2 @@
|
|||
# flake8: noqa
|
||||
from .mel import Mel
|
||||
from .pipeline_audio_diffusion import AudioDiffusionPipeline
|
||||
|
|
|
@ -18,7 +18,6 @@ from typing import List, Tuple, Union
|
|||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
from PIL import Image
|
||||
|
||||
from ...models import AutoencoderKL, UNet2DConditionModel
|
||||
|
|
|
@ -1,2 +1 @@
|
|||
# flake8: noqa
|
||||
from .pipeline_dance_diffusion import DanceDiffusionPipeline
|
||||
|
|
|
@ -1,2 +1 @@
|
|||
# flake8: noqa
|
||||
from .pipeline_ddim import DDIMPipeline
|
||||
|
|
|
@ -1,2 +1 @@
|
|||
# flake8: noqa
|
||||
from .pipeline_ddpm import DDPMPipeline
|
||||
|
|
|
@ -1,4 +1,3 @@
|
|||
# flake8: noqa
|
||||
from ...utils import is_transformers_available
|
||||
from .pipeline_latent_diffusion_superresolution import LDMSuperResolutionPipeline
|
||||
|
||||
|
|
|
@ -18,7 +18,6 @@ from typing import List, Optional, Tuple, Union
|
|||
import torch
|
||||
import torch.nn as nn
|
||||
import torch.utils.checkpoint
|
||||
|
||||
from transformers import PretrainedConfig, PreTrainedModel, PreTrainedTokenizer
|
||||
from transformers.activations import ACT2FN
|
||||
from transformers.modeling_outputs import BaseModelOutput
|
||||
|
|
|
@ -2,11 +2,10 @@ import inspect
|
|||
from typing import List, Optional, Tuple, Union
|
||||
|
||||
import numpy as np
|
||||
import PIL
|
||||
import torch
|
||||
import torch.utils.checkpoint
|
||||
|
||||
import PIL
|
||||
|
||||
from ...models import UNet2DModel, VQModel
|
||||
from ...schedulers import (
|
||||
DDIMScheduler,
|
||||
|
|
|
@ -1,2 +1 @@
|
|||
# flake8: noqa
|
||||
from .pipeline_latent_diffusion_uncond import LDMPipeline
|
||||
|
|
|
@ -21,7 +21,6 @@ from pathlib import Path
|
|||
from typing import Optional, Union
|
||||
|
||||
import numpy as np
|
||||
|
||||
from huggingface_hub import hf_hub_download
|
||||
|
||||
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
|
||||
|
|
|
@ -2,7 +2,6 @@ from dataclasses import dataclass
|
|||
from typing import List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
|
||||
import PIL
|
||||
from PIL import Image
|
||||
|
||||
|
|
|
@ -13,7 +13,6 @@
|
|||
# limitations under the License.
|
||||
import torch
|
||||
from torch import nn
|
||||
|
||||
from transformers import CLIPPreTrainedModel, CLIPVisionModel
|
||||
|
||||
from ...models.attention import BasicTransformerBlock
|
||||
|
|
|
@ -16,12 +16,12 @@ import inspect
|
|||
from typing import Callable, List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
import PIL
|
||||
from diffusers.utils import is_accelerate_available
|
||||
import torch
|
||||
from transformers import CLIPFeatureExtractor
|
||||
|
||||
from diffusers.utils import is_accelerate_available
|
||||
|
||||
from ...models import AutoencoderKL, UNet2DConditionModel
|
||||
from ...schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
|
||||
from ...utils import logging, randn_tensor
|
||||
|
|
|
@ -19,9 +19,8 @@ import inspect
|
|||
import os
|
||||
from typing import Any, Dict, List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
|
||||
import flax
|
||||
import numpy as np
|
||||
import PIL
|
||||
from flax.core.frozen_dict import FrozenDict
|
||||
from huggingface_hub import snapshot_download
|
||||
|
|
|
@ -22,15 +22,15 @@ from pathlib import Path
|
|||
from typing import Any, Callable, Dict, List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
import diffusers
|
||||
import PIL
|
||||
import torch
|
||||
from huggingface_hub import model_info, snapshot_download
|
||||
from packaging import version
|
||||
from PIL import Image
|
||||
from tqdm.auto import tqdm
|
||||
|
||||
import diffusers
|
||||
|
||||
from ..configuration_utils import ConfigMixin
|
||||
from ..models.modeling_utils import _LOW_CPU_MEM_USAGE_DEFAULT
|
||||
from ..schedulers.scheduling_utils import SCHEDULER_CONFIG_NAME
|
||||
|
|
|
@ -1,2 +1 @@
|
|||
# flake8: noqa
|
||||
from .pipeline_pndm import PNDMPipeline
|
||||
|
|
|
@ -16,9 +16,8 @@
|
|||
from typing import List, Optional, Tuple, Union
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
import PIL
|
||||
import torch
|
||||
|
||||
from ...models import UNet2DModel
|
||||
from ...schedulers import RePaintScheduler
|
||||
|
|
|
@ -1,2 +1 @@
|
|||
# flake8: noqa
|
||||
from .pipeline_score_sde_ve import ScoreSdeVePipeline
|
||||
|
|
|
@ -2,7 +2,6 @@ from dataclasses import dataclass
|
|||
from typing import List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
|
||||
import PIL
|
||||
from PIL import Image
|
||||
|
||||
|
|
|
@ -18,9 +18,10 @@ import os
|
|||
import re
|
||||
import tempfile
|
||||
|
||||
import torch
|
||||
|
||||
import requests
|
||||
import torch
|
||||
from transformers import AutoFeatureExtractor, BertTokenizerFast, CLIPTextModel, CLIPTokenizer, CLIPVisionConfig
|
||||
|
||||
from diffusers import (
|
||||
AutoencoderKL,
|
||||
DDIMScheduler,
|
||||
|
@ -37,7 +38,6 @@ from diffusers import (
|
|||
from diffusers.pipelines.latent_diffusion.pipeline_latent_diffusion import LDMBertConfig, LDMBertModel
|
||||
from diffusers.pipelines.paint_by_example import PaintByExampleImageEncoder, PaintByExamplePipeline
|
||||
from diffusers.pipelines.stable_diffusion import StableDiffusionSafetyChecker
|
||||
from transformers import AutoFeatureExtractor, BertTokenizerFast, CLIPTextModel, CLIPTokenizer, CLIPVisionConfig
|
||||
|
||||
from ...utils import is_omegaconf_available, is_safetensors_available
|
||||
from ...utils.import_utils import BACKENDS_MAPPING
|
||||
|
|
|
@ -16,13 +16,13 @@ import inspect
|
|||
from typing import Callable, List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
import PIL
|
||||
from diffusers.utils import is_accelerate_available
|
||||
import torch
|
||||
from packaging import version
|
||||
from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
|
||||
|
||||
from diffusers.utils import is_accelerate_available
|
||||
|
||||
from ...configuration_utils import FrozenDict
|
||||
from ...models import AutoencoderKL, UNet2DConditionModel
|
||||
from ...schedulers import DDIMScheduler
|
||||
|
|
|
@ -16,10 +16,9 @@ import warnings
|
|||
from functools import partial
|
||||
from typing import Dict, List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
|
||||
import jax
|
||||
import jax.numpy as jnp
|
||||
import numpy as np
|
||||
from flax.core.frozen_dict import FrozenDict
|
||||
from flax.jax_utils import unreplicate
|
||||
from flax.training.common_utils import shard
|
||||
|
|
|
@ -16,10 +16,9 @@ import warnings
|
|||
from functools import partial
|
||||
from typing import Dict, List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
|
||||
import jax
|
||||
import jax.numpy as jnp
|
||||
import numpy as np
|
||||
from flax.core.frozen_dict import FrozenDict
|
||||
from flax.jax_utils import unreplicate
|
||||
from flax.training.common_utils import shard
|
||||
|
|
|
@ -16,10 +16,9 @@ import warnings
|
|||
from functools import partial
|
||||
from typing import Dict, List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
|
||||
import jax
|
||||
import jax.numpy as jnp
|
||||
import numpy as np
|
||||
from flax.core.frozen_dict import FrozenDict
|
||||
from flax.jax_utils import unreplicate
|
||||
from flax.training.common_utils import shard
|
||||
|
|
|
@ -17,7 +17,6 @@ from typing import Callable, List, Optional, Union
|
|||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
from transformers import CLIPFeatureExtractor, CLIPTokenizer
|
||||
|
||||
from ...configuration_utils import FrozenDict
|
||||
|
|
|
@ -16,9 +16,8 @@ import inspect
|
|||
from typing import Callable, List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
import PIL
|
||||
import torch
|
||||
from transformers import CLIPFeatureExtractor, CLIPTokenizer
|
||||
|
||||
from ...configuration_utils import FrozenDict
|
||||
|
|
|
@ -16,9 +16,8 @@ import inspect
|
|||
from typing import Callable, List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
import PIL
|
||||
import torch
|
||||
from transformers import CLIPFeatureExtractor, CLIPTokenizer
|
||||
|
||||
from ...configuration_utils import FrozenDict
|
||||
|
|
|
@ -2,9 +2,8 @@ import inspect
|
|||
from typing import Callable, List, Optional, Union
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
import PIL
|
||||
import torch
|
||||
from transformers import CLIPFeatureExtractor, CLIPTokenizer
|
||||
|
||||
from ...configuration_utils import FrozenDict
|
||||
|
|
|
@ -16,7 +16,6 @@ import inspect
|
|||
from typing import Any, Callable, Dict, List, Optional, Union
|
||||
|
||||
import torch
|
||||
|
||||
from packaging import version
|
||||
from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
|
||||
|
||||
|
|
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue