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Deprecate KarrasVeScheduler and ScoreSdeVpScheduler (#5269)

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* deprecated: KarrasVeScheduler, ScoreSdeVpScheduler

* delete tests relevant to deprecated schedulers

* chore: run make style

* fix: import error caused due to incorrect _import_structure after deprecation

* fix: ScoreSdeVpScheduler was not importable from diffusers

* remove import added by assumption

* Update src/diffusers/schedulers/__init__.py as suggested by @patrickvonplaten

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* make it a part deprecated

* Apply suggestions from code review

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Fix

* fix

* fix doc

* fix doc....again.......

* remove karras_ve test folder

Co-Authored-By: YiYi Xu <yixu310@gmail.com>

---------

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail,com>
This commit is contained in:
Aryan V S
2023-11-27 17:03:02 +05:30
committed by GitHub
parent 3f7c3511dc
commit 9c357bda3f
8 changed files with 61 additions and 99 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
docs/source/en/api/schedulers/score_sde_vp.md
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@@ -25,4 +25,4 @@ The abstract from the paper is:
</Tip>
## ScoreSdeVpScheduler
[[autodoc]] schedulers.scheduling_sde_vp.ScoreSdeVpScheduler
[[autodoc]] schedulers.deprecated.scheduling_sde_vp.ScoreSdeVpScheduler

2
docs/source/en/api/schedulers/stochastic_karras_ve.md
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@@ -18,4 +18,4 @@ specific language governing permissions and limitations under the License.
[[autodoc]] KarrasVeScheduler
## KarrasVeOutput
[[autodoc]] schedulers.scheduling_karras_ve.KarrasVeOutput
[[autodoc]] schedulers.deprecated.scheduling_karras_ve.KarrasVeOutput

6
src/diffusers/schedulers/__init__.py
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@@ -38,6 +38,7 @@ except OptionalDependencyNotAvailable:
_dummy_modules.update(get_objects_from_module(dummy_pt_objects))
else:
_import_structure["deprecated"] = ["KarrasVeScheduler", "ScoreSdeVpScheduler"]
_import_structure["scheduling_consistency_decoder"] = ["ConsistencyDecoderScheduler"]
_import_structure["scheduling_consistency_models"] = ["CMStochasticIterativeScheduler"]
_import_structure["scheduling_ddim"] = ["DDIMScheduler"]
@@ -56,12 +57,10 @@ else:
_import_structure["scheduling_ipndm"] = ["IPNDMScheduler"]
_import_structure["scheduling_k_dpm_2_ancestral_discrete"] = ["KDPM2AncestralDiscreteScheduler"]
_import_structure["scheduling_k_dpm_2_discrete"] = ["KDPM2DiscreteScheduler"]
_import_structure["scheduling_karras_ve"] = ["KarrasVeScheduler"]
_import_structure["scheduling_lcm"] = ["LCMScheduler"]
_import_structure["scheduling_pndm"] = ["PNDMScheduler"]
_import_structure["scheduling_repaint"] = ["RePaintScheduler"]
_import_structure["scheduling_sde_ve"] = ["ScoreSdeVeScheduler"]
_import_structure["scheduling_sde_vp"] = ["ScoreSdeVpScheduler"]
_import_structure["scheduling_unclip"] = ["UnCLIPScheduler"]
_import_structure["scheduling_unipc_multistep"] = ["UniPCMultistepScheduler"]
_import_structure["scheduling_utils"] = ["KarrasDiffusionSchedulers", "SchedulerMixin"]
@@ -129,6 +128,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
except OptionalDependencyNotAvailable:
from ..utils.dummy_pt_objects import * # noqa F403
else:
from .deprecated import KarrasVeScheduler, ScoreSdeVpScheduler
from .scheduling_consistency_decoder import ConsistencyDecoderScheduler
from .scheduling_consistency_models import CMStochasticIterativeScheduler
from .scheduling_ddim import DDIMScheduler
@@ -147,12 +147,10 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
from .scheduling_ipndm import IPNDMScheduler
from .scheduling_k_dpm_2_ancestral_discrete import KDPM2AncestralDiscreteScheduler
from .scheduling_k_dpm_2_discrete import KDPM2DiscreteScheduler
from .scheduling_karras_ve import KarrasVeScheduler
from .scheduling_lcm import LCMScheduler
from .scheduling_pndm import PNDMScheduler
from .scheduling_repaint import RePaintScheduler
from .scheduling_sde_ve import ScoreSdeVeScheduler
from .scheduling_sde_vp import ScoreSdeVpScheduler
from .scheduling_unclip import UnCLIPScheduler
from .scheduling_unipc_multistep import UniPCMultistepScheduler
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin

50
src/diffusers/schedulers/deprecated/__init__.py Normal file
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@@ -0,0 +1,50 @@
from typing import TYPE_CHECKING
from ...utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
get_objects_from_module,
is_torch_available,
is_transformers_available,
)
_dummy_objects = {}
_import_structure = {}
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils import dummy_pt_objects # noqa F403
_dummy_objects.update(get_objects_from_module(dummy_pt_objects))
else:
_import_structure["scheduling_karras_ve"] = ["KarrasVeScheduler"]
_import_structure["scheduling_sde_vp"] = ["ScoreSdeVpScheduler"]
if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..utils.dummy_pt_objects import * # noqa F403
else:
from .scheduling_karras_ve import KarrasVeScheduler
from .scheduling_sde_vp import ScoreSdeVpScheduler
else:
import sys
sys.modules[__name__] = _LazyModule(
__name__,
globals()["__file__"],
_import_structure,
module_spec=__spec__,
)
for name, value in _dummy_objects.items():
setattr(sys.modules[__name__], name, value)

8
src/diffusers/schedulers/scheduling_karras_ve.py → src/diffusers/schedulers/deprecated/scheduling_karras_ve.py
View File

@@ -19,10 +19,10 @@ from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from ..utils.torch_utils import randn_tensor
from .scheduling_utils import SchedulerMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...utils import BaseOutput
from ...utils.torch_utils import randn_tensor
from ..scheduling_utils import SchedulerMixin
@dataclass

6
src/diffusers/schedulers/scheduling_sde_vp.py → src/diffusers/schedulers/deprecated/scheduling_sde_vp.py
View File

@@ -19,9 +19,9 @@ from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils.torch_utils import randn_tensor
from .scheduling_utils import SchedulerMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...utils.torch_utils import randn_tensor
from ..scheduling_utils import SchedulerMixin
class ScoreSdeVpScheduler(SchedulerMixin, ConfigMixin):

0
tests/pipelines/karras_ve/__init__.py
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86
tests/pipelines/karras_ve/test_karras_ve.py
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@@ -1,86 +0,0 @@
# coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNet2DModel
from diffusers.utils.testing_utils import enable_full_determinism, nightly, require_torch, torch_device
enable_full_determinism()
class KarrasVePipelineFastTests(unittest.TestCase):
@property
def dummy_uncond_unet(self):
torch.manual_seed(0)
model = UNet2DModel(
block_out_channels=(32, 64),
layers_per_block=2,
sample_size=32,
in_channels=3,
out_channels=3,
down_block_types=("DownBlock2D", "AttnDownBlock2D"),
up_block_types=("AttnUpBlock2D", "UpBlock2D"),
)
return model
def test_inference(self):
unet = self.dummy_uncond_unet
scheduler = KarrasVeScheduler()
pipe = KarrasVePipeline(unet=unet, scheduler=scheduler)
pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
generator = torch.manual_seed(0)
image = pipe(num_inference_steps=2, generator=generator, output_type="numpy").images
generator = torch.manual_seed(0)
image_from_tuple = pipe(num_inference_steps=2, generator=generator, output_type="numpy", return_dict=False)[0]
image_slice = image[0, -3:, -3:, -1]
image_from_tuple_slice = image_from_tuple[0, -3:, -3:, -1]
assert image.shape == (1, 32, 32, 3)
expected_slice = np.array([0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0])
assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
assert np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1e-2
@nightly
@require_torch
class KarrasVePipelineIntegrationTests(unittest.TestCase):
def test_inference(self):
model_id = "google/ncsnpp-celebahq-256"
model = UNet2DModel.from_pretrained(model_id)
scheduler = KarrasVeScheduler()
pipe = KarrasVePipeline(unet=model, scheduler=scheduler)
pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
generator = torch.manual_seed(0)
image = pipe(num_inference_steps=20, generator=generator, output_type="numpy").images
image_slice = image[0, -3:, -3:, -1]
assert image.shape == (1, 256, 256, 3)
expected_slice = np.array([0.578, 0.5811, 0.5924, 0.5809, 0.587, 0.5886, 0.5861, 0.5802, 0.586])
assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2