text stringlengths 41 89.8k | type stringclasses 1
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class DDPMSchedulerState:
common: CommonSchedulerState
# setable values
init_noise_sigma: jnp.ndarray
timesteps: jnp.ndarray
num_inference_steps: Optional[int] = None
@classmethod
def create(cls, common: CommonSchedulerState, init_noise_sigma: jnp.ndarray, timesteps: jnp.ndarray):
... | class_definition | 1,126 | 1,527 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddpm_flax.py | null | 1,300 |
class FlaxDDPMSchedulerOutput(FlaxSchedulerOutput):
state: DDPMSchedulerState | class_definition | 1,541 | 1,622 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddpm_flax.py | null | 1,301 |
class FlaxDDPMScheduler(FlaxSchedulerMixin, ConfigMixin):
"""
Denoising diffusion probabilistic models (DDPMs) explores the connections between denoising score matching and
Langevin dynamics sampling.
[`~ConfigMixin`] takes care of storing all config attributes that are passed in the scheduler's `__ini... | class_definition | 1,625 | 12,541 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddpm_flax.py | null | 1,302 |
class DPMSolverSDESchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used ... | class_definition | 1,126 | 1,895 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_dpmsolver_sde.py | null | 1,303 |
class BatchedBrownianTree:
"""A wrapper around torchsde.BrownianTree that enables batches of entropy."""
def __init__(self, x, t0, t1, seed=None, **kwargs):
t0, t1, self.sign = self.sort(t0, t1)
w0 = kwargs.get("w0", torch.zeros_like(x))
if seed is None:
seed = torch.randint... | class_definition | 1,898 | 3,098 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_dpmsolver_sde.py | null | 1,304 |
class BrownianTreeNoiseSampler:
"""A noise sampler backed by a torchsde.BrownianTree.
Args:
x (Tensor): The tensor whose shape, device and dtype to use to generate
random samples.
sigma_min (float): The low end of the valid interval.
sigma_max (float): The high end of the va... | class_definition | 3,101 | 4,253 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_dpmsolver_sde.py | null | 1,305 |
class DPMSolverSDEScheduler(SchedulerMixin, ConfigMixin):
"""
DPMSolverSDEScheduler implements the stochastic sampler from the [Elucidating the Design Space of Diffusion-Based
Generative Models](https://huggingface.co/papers/2206.00364) paper.
This model inherits from [`SchedulerMixin`] and [`ConfigMix... | class_definition | 5,873 | 29,482 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_dpmsolver_sde.py | null | 1,306 |
class DDIMSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used as next ... | class_definition | 1,166 | 1,927 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddim_inverse.py | null | 1,307 |
class DDIMInverseScheduler(SchedulerMixin, ConfigMixin):
"""
`DDIMInverseScheduler` is the reverse scheduler of [`DDIMScheduler`].
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the library implements for all schedulers such a... | class_definition | 4,733 | 17,767 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddim_inverse.py | null | 1,308 |
class ScoreSdeVeSchedulerState:
# setable values
timesteps: Optional[jnp.ndarray] = None
discrete_sigmas: Optional[jnp.ndarray] = None
sigmas: Optional[jnp.ndarray] = None
@classmethod
def create(cls):
return cls() | class_definition | 1,066 | 1,313 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_sde_ve_flax.py | null | 1,309 |
class FlaxSdeVeOutput(FlaxSchedulerOutput):
"""
Output class for the ScoreSdeVeScheduler's step function output.
Args:
state (`ScoreSdeVeSchedulerState`):
prev_sample (`jnp.ndarray` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample (x_{t-1}) of pr... | class_definition | 1,327 | 2,086 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_sde_ve_flax.py | null | 1,310 |
class FlaxScoreSdeVeScheduler(FlaxSchedulerMixin, ConfigMixin):
"""
The variance exploding stochastic differential equation (SDE) scheduler.
For more information, see the original paper: https://arxiv.org/abs/2011.13456
[`~ConfigMixin`] takes care of storing all config attributes that are passed in th... | class_definition | 2,089 | 12,133 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_sde_ve_flax.py | null | 1,311 |
class EDMDPMSolverMultistepScheduler(SchedulerMixin, ConfigMixin):
"""
Implements DPMSolverMultistepScheduler in EDM formulation as presented in Karras et al. 2022 [1].
`EDMDPMSolverMultistepScheduler` is a fast dedicated high-order solver for diffusion ODEs.
[1] Karras, Tero, et al. "Elucidating the D... | class_definition | 1,017 | 31,657 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_edm_dpmsolver_multistep.py | null | 1,312 |
class LMSDiscreteSchedulerState:
common: CommonSchedulerState
# setable values
init_noise_sigma: jnp.ndarray
timesteps: jnp.ndarray
sigmas: jnp.ndarray
num_inference_steps: Optional[int] = None
# running values
derivatives: Optional[jnp.ndarray] = None
@classmethod
def create(... | class_definition | 1,045 | 1,595 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_lms_discrete_flax.py | null | 1,313 |
class FlaxLMSSchedulerOutput(FlaxSchedulerOutput):
state: LMSDiscreteSchedulerState | class_definition | 1,609 | 1,696 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_lms_discrete_flax.py | null | 1,314 |
class FlaxLMSDiscreteScheduler(FlaxSchedulerMixin, ConfigMixin):
"""
Linear Multistep Scheduler for discrete beta schedules. Based on the original k-diffusion implementation by
Katherine Crowson:
https://github.com/crowsonkb/k-diffusion/blob/481677d114f6ea445aa009cf5bd7a9cdee909e47/k_diffusion/sampling.... | class_definition | 1,699 | 11,076 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_lms_discrete_flax.py | null | 1,315 |
class DPMSolverMultistepInverseScheduler(SchedulerMixin, ConfigMixin):
"""
`DPMSolverMultistepInverseScheduler` is the reverse scheduler of [`DPMSolverMultistepScheduler`].
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the li... | class_definition | 2,727 | 48,824 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_dpmsolver_multistep_inverse.py | null | 1,316 |
class KDPM2AncestralDiscreteSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` shoul... | class_definition | 1,165 | 1,944 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_k_dpm_2_ancestral_discrete.py | null | 1,317 |
class KDPM2AncestralDiscreteScheduler(SchedulerMixin, ConfigMixin):
"""
KDPM2DiscreteScheduler with ancestral sampling is inspired by the DPMSolver2 and Algorithm 2 from the [Elucidating
the Design Space of Diffusion-Based Generative Models](https://huggingface.co/papers/2206.00364) paper.
This model i... | class_definition | 3,564 | 27,584 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_k_dpm_2_ancestral_discrete.py | null | 1,318 |
class LMSDiscreteSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used a... | class_definition | 1,095 | 1,863 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_lms_discrete.py | null | 1,319 |
class LMSDiscreteScheduler(SchedulerMixin, ConfigMixin):
"""
A linear multistep scheduler for discrete beta schedules.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the library implements for all schedulers such as loading an... | class_definition | 3,483 | 24,363 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_lms_discrete.py | null | 1,320 |
class EulerDiscreteSchedulerState:
common: CommonSchedulerState
# setable values
init_noise_sigma: jnp.ndarray
timesteps: jnp.ndarray
sigmas: jnp.ndarray
num_inference_steps: Optional[int] = None
@classmethod
def create(
cls, common: CommonSchedulerState, init_noise_sigma: jnp.... | class_definition | 1,017 | 1,501 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_euler_discrete_flax.py | null | 1,321 |
class FlaxEulerDiscreteSchedulerOutput(FlaxSchedulerOutput):
state: EulerDiscreteSchedulerState | class_definition | 1,515 | 1,614 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_euler_discrete_flax.py | null | 1,322 |
class FlaxEulerDiscreteScheduler(FlaxSchedulerMixin, ConfigMixin):
"""
Euler scheduler (Algorithm 2) from Karras et al. (2022) https://arxiv.org/abs/2206.00364. . Based on the original
k-diffusion implementation by Katherine Crowson:
https://github.com/crowsonkb/k-diffusion/blob/481677d114f6ea445aa009cf... | class_definition | 1,617 | 10,800 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_euler_discrete_flax.py | null | 1,323 |
class CMStochasticIterativeSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be use... | class_definition | 1,004 | 1,419 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_consistency_models.py | null | 1,324 |
class CMStochasticIterativeScheduler(SchedulerMixin, ConfigMixin):
"""
Multistep and onestep sampling for consistency models.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the library implements for all schedulers such as loa... | class_definition | 1,422 | 18,722 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_consistency_models.py | null | 1,325 |
class DPMSolverSinglestepScheduler(SchedulerMixin, ConfigMixin):
"""
`DPMSolverSinglestepScheduler` is a fast dedicated high-order solver for diffusion ODEs.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the library implement... | class_definition | 2,807 | 54,222 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_dpmsolver_singlestep.py | null | 1,326 |
class DDIMSchedulerState:
common: CommonSchedulerState
final_alpha_cumprod: jnp.ndarray
# setable values
init_noise_sigma: jnp.ndarray
timesteps: jnp.ndarray
num_inference_steps: Optional[int] = None
@classmethod
def create(
cls,
common: CommonSchedulerState,
fi... | class_definition | 1,180 | 1,799 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddim_flax.py | null | 1,327 |
class FlaxDDIMSchedulerOutput(FlaxSchedulerOutput):
state: DDIMSchedulerState | class_definition | 1,813 | 1,894 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddim_flax.py | null | 1,328 |
class FlaxDDIMScheduler(FlaxSchedulerMixin, ConfigMixin):
"""
Denoising diffusion implicit models is a scheduler that extends the denoising procedure introduced in denoising
diffusion probabilistic models (DDPMs) with non-Markovian guidance.
[`~ConfigMixin`] takes care of storing all config attributes ... | class_definition | 1,897 | 13,121 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddim_flax.py | null | 1,329 |
class DPMSolverMultistepSchedulerState:
common: CommonSchedulerState
alpha_t: jnp.ndarray
sigma_t: jnp.ndarray
lambda_t: jnp.ndarray
# setable values
init_noise_sigma: jnp.ndarray
timesteps: jnp.ndarray
num_inference_steps: Optional[int] = None
# running values
model_outputs: O... | class_definition | 1,107 | 2,074 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_dpmsolver_multistep_flax.py | null | 1,330 |
class FlaxDPMSolverMultistepSchedulerOutput(FlaxSchedulerOutput):
state: DPMSolverMultistepSchedulerState | class_definition | 2,088 | 2,197 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_dpmsolver_multistep_flax.py | null | 1,331 |
class FlaxDPMSolverMultistepScheduler(FlaxSchedulerMixin, ConfigMixin):
"""
DPM-Solver (and the improved version DPM-Solver++) is a fast dedicated high-order solver for diffusion ODEs with
the convergence order guarantee. Empirically, sampling by DPM-Solver with only 20 steps can generate high-quality
s... | class_definition | 2,200 | 28,720 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_dpmsolver_multistep_flax.py | null | 1,332 |
class DDIMSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used as next ... | class_definition | 1,203 | 1,964 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddim_cogvideox.py | null | 1,333 |
class CogVideoXDDIMScheduler(SchedulerMixin, ConfigMixin):
"""
`DDIMScheduler` extends the denoising procedure introduced in denoising diffusion probabilistic models (DDPMs) with
non-Markovian guidance.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation ... | class_definition | 4,457 | 21,330 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddim_cogvideox.py | null | 1,334 |
class TCDSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used as next m... | class_definition | 1,200 | 1,870 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_tcd.py | null | 1,335 |
class TCDScheduler(SchedulerMixin, ConfigMixin):
"""
`TCDScheduler` incorporates the `Strategic Stochastic Sampling` introduced by the paper `Trajectory Consistency
Distillation`, extending the original Multistep Consistency Sampling to enable unrestricted trajectory traversal.
This code is based on th... | class_definition | 4,706 | 34,760 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_tcd.py | null | 1,336 |
class EulerAncestralDiscreteSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` shoul... | class_definition | 1,170 | 1,949 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_euler_ancestral_discrete.py | null | 1,337 |
class EulerAncestralDiscreteScheduler(SchedulerMixin, ConfigMixin):
"""
Ancestral sampling with Euler method steps.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the library implements for all schedulers such as loading and s... | class_definition | 4,755 | 21,085 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_euler_ancestral_discrete.py | null | 1,338 |
class KarrasDiffusionSchedulers(Enum):
DDIMScheduler = 1
DDPMScheduler = 2
PNDMScheduler = 3
LMSDiscreteScheduler = 4
EulerDiscreteScheduler = 5
HeunDiscreteScheduler = 6
EulerAncestralDiscreteScheduler = 7
DPMSolverMultistepScheduler = 8
DPMSolverSinglestepScheduler = 9
KDPM2Dis... | class_definition | 1,170 | 1,673 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_utils.py | null | 1,339 |
class SchedulerOutput(BaseOutput):
"""
Base class for the output of a scheduler's `step` function.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used as next m... | class_definition | 2,203 | 2,607 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_utils.py | null | 1,340 |
class SchedulerMixin(PushToHubMixin):
"""
Base class for all schedulers.
[`SchedulerMixin`] contains common functions shared by all schedulers such as general loading and saving
functionalities.
[`ConfigMixin`] takes care of storing the configuration attributes (like `num_train_timesteps`) that ar... | class_definition | 2,610 | 8,664 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_utils.py | null | 1,341 |
class EDMEulerSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used as n... | class_definition | 1,109 | 1,874 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_edm_euler.py | null | 1,342 |
class EDMEulerScheduler(SchedulerMixin, ConfigMixin):
"""
Implements the Euler scheduler in EDM formulation as presented in Karras et al. 2022 [1].
[1] Karras, Tero, et al. "Elucidating the Design Space of Diffusion-Based Generative Models."
https://arxiv.org/abs/2206.00364
This model inherits fro... | class_definition | 1,877 | 17,311 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_edm_euler.py | null | 1,343 |
class DDPMParallelSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used ... | class_definition | 1,141 | 1,910 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddpm_parallel.py | null | 1,344 |
class DDPMParallelScheduler(SchedulerMixin, ConfigMixin):
"""
Denoising diffusion probabilistic models (DDPMs) explores the connections between denoising score matching and
Langevin dynamics sampling.
[`~ConfigMixin`] takes care of storing all config attributes that are passed in the scheduler's `__ini... | class_definition | 4,716 | 30,976 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddpm_parallel.py | null | 1,345 |
class DDIMParallelSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used ... | class_definition | 1,198 | 1,967 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddim_parallel.py | null | 1,346 |
class DDIMParallelScheduler(SchedulerMixin, ConfigMixin):
"""
Denoising diffusion implicit models is a scheduler that extends the denoising procedure introduced in denoising
diffusion probabilistic models (DDPMs) with non-Markovian guidance.
[`~ConfigMixin`] takes care of storing all config attributes ... | class_definition | 4,773 | 31,501 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddim_parallel.py | null | 1,347 |
class DDPMWuerstchenSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's step function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample (x_{t-1}) of previous timestep. `prev_sample` should be used as... | class_definition | 1,071 | 1,482 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddpm_wuerstchen.py | null | 1,348 |
class DDPMWuerstchenScheduler(SchedulerMixin, ConfigMixin):
"""
Denoising diffusion probabilistic models (DDPMs) explores the connections between denoising score matching and
Langevin dynamics sampling.
[`~ConfigMixin`] takes care of storing all config attributes that are passed in the scheduler's `__i... | class_definition | 3,031 | 8,929 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddpm_wuerstchen.py | null | 1,349 |
class FlaxKarrasDiffusionSchedulers(Enum):
FlaxDDIMScheduler = 1
FlaxDDPMScheduler = 2
FlaxPNDMScheduler = 3
FlaxLMSDiscreteScheduler = 4
FlaxDPMSolverMultistepScheduler = 5
FlaxEulerDiscreteScheduler = 6 | class_definition | 1,212 | 1,440 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_utils_flax.py | null | 1,350 |
class FlaxSchedulerOutput(BaseOutput):
"""
Base class for the scheduler's step function output.
Args:
prev_sample (`jnp.ndarray` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample (x_{t-1}) of previous timestep. `prev_sample` should be used as next model i... | class_definition | 1,454 | 1,851 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_utils_flax.py | null | 1,351 |
class FlaxSchedulerMixin(PushToHubMixin):
"""
Mixin containing common functions for the schedulers.
Class attributes:
- **_compatibles** (`List[str]`) -- A list of classes that are compatible with the parent class, so that
`from_config` can be used from a class different than the one used... | class_definition | 1,854 | 8,030 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_utils_flax.py | null | 1,352 |
class CommonSchedulerState:
alphas: jnp.ndarray
betas: jnp.ndarray
alphas_cumprod: jnp.ndarray
@classmethod
def create(cls, scheduler):
config = scheduler.config
if config.trained_betas is not None:
betas = jnp.asarray(config.trained_betas, dtype=scheduler.dtype)
... | class_definition | 9,376 | 10,789 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_utils_flax.py | null | 1,353 |
class SdeVeOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used as next model in... | class_definition | 1,042 | 1,646 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_sde_ve.py | null | 1,354 |
class ScoreSdeVeScheduler(SchedulerMixin, ConfigMixin):
"""
`ScoreSdeVeScheduler` is a variance exploding stochastic differential equation (SDE) scheduler.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the library implements ... | class_definition | 1,649 | 13,320 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_sde_ve.py | null | 1,355 |
class IPNDMScheduler(SchedulerMixin, ConfigMixin):
"""
A fourth-order Improved Pseudo Linear Multistep scheduler.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the library implements for all schedulers such as loading and sav... | class_definition | 860 | 8,763 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ipndm.py | null | 1,356 |
class DEISMultistepScheduler(SchedulerMixin, ConfigMixin):
"""
`DEISMultistepScheduler` is a fast high order solver for diffusion ordinary differential equations (ODEs).
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the libra... | class_definition | 2,838 | 39,693 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_deis_multistep.py | null | 1,357 |
class UnCLIPSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used as nex... | class_definition | 1,034 | 1,797 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_unclip.py | null | 1,358 |
class UnCLIPScheduler(SchedulerMixin, ConfigMixin):
"""
NOTE: do not use this scheduler. The DDPM scheduler has been updated to support the changes made here. This
scheduler will be removed and replaced with DDPM.
This is a modified DDPM Scheduler specifically for the karlo unCLIP model.
This sche... | class_definition | 3,417 | 15,039 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_unclip.py | null | 1,359 |
class AmusedSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used as nex... | class_definition | 900 | 1,653 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_amused.py | null | 1,360 |
class AmusedScheduler(SchedulerMixin, ConfigMixin):
order = 1
temperatures: torch.Tensor
@register_to_config
def __init__(
self,
mask_token_id: int,
masking_schedule: str = "cosine",
):
self.temperatures = None
self.timesteps = None
def set_timesteps(
... | class_definition | 1,656 | 6,589 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_amused.py | null | 1,361 |
class ConsistencyDecoderSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used a... | class_definition | 1,920 | 2,332 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_consistency_decoder.py | null | 1,362 |
class ConsistencyDecoderScheduler(SchedulerMixin, ConfigMixin):
order = 1
@register_to_config
def __init__(
self,
num_train_timesteps: int = 1024,
sigma_data: float = 0.5,
):
betas = betas_for_alpha_bar(num_train_timesteps)
alphas = 1.0 - betas
alphas_cu... | class_definition | 2,335 | 6,816 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_consistency_decoder.py | null | 1,363 |
class VQDiffusionSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's step function output.
Args:
prev_sample (`torch.LongTensor` of shape `(batch size, num latent pixels)`):
Computed sample x_{t-1} of previous timestep. `prev_sample` should be used as next model input in t... | class_definition | 918 | 1,311 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_vq_diffusion.py | null | 1,364 |
class VQDiffusionScheduler(SchedulerMixin, ConfigMixin):
"""
A scheduler for vector quantized diffusion.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the library implements for all schedulers such as loading and saving.
... | class_definition | 3,360 | 22,953 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_vq_diffusion.py | null | 1,365 |
class RePaintSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's step function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample (x_{t-1}) of previous timestep. `prev_sample` should be used as next m... | class_definition | 964 | 1,706 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_repaint.py | null | 1,366 |
class RePaintScheduler(SchedulerMixin, ConfigMixin):
"""
`RePaintScheduler` is a scheduler for DDPM inpainting inside a given mask.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the library implements for all schedulers such ... | class_definition | 3,326 | 15,233 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_repaint.py | null | 1,367 |
class DDIMSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used as next ... | class_definition | 1,221 | 1,982 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddim.py | null | 1,368 |
class DDIMScheduler(SchedulerMixin, ConfigMixin):
"""
`DDIMScheduler` extends the denoising procedure introduced in denoising diffusion probabilistic models (DDPMs) with
non-Markovian guidance.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the g... | class_definition | 4,711 | 24,882 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_ddim.py | null | 1,369 |
class FlowMatchHeunDiscreteSchedulerOutput(BaseOutput):
"""
Output class for the scheduler's `step` function output.
Args:
prev_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample `(x_{t-1})` of previous timestep. `prev_sample` s... | class_definition | 1,034 | 1,466 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_flow_match_heun_discrete.py | null | 1,370 |
class FlowMatchHeunDiscreteScheduler(SchedulerMixin, ConfigMixin):
"""
Heun scheduler.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the library implements for all schedulers such as loading and saving.
Args:
num... | class_definition | 1,469 | 12,071 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_flow_match_heun_discrete.py | null | 1,371 |
class PNDMScheduler(SchedulerMixin, ConfigMixin):
"""
`PNDMScheduler` uses pseudo numerical methods for diffusion models such as the Runge-Kutta and linear multi-step
method.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods ... | class_definition | 2,590 | 21,714 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_pndm.py | null | 1,372 |
class DPMSolverMultistepScheduler(SchedulerMixin, ConfigMixin):
"""
`DPMSolverMultistepScheduler` is a fast dedicated high-order solver for diffusion ODEs.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the library implements ... | class_definition | 3,913 | 55,079 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_dpmsolver_multistep.py | null | 1,373 |
class UniPCMultistepScheduler(SchedulerMixin, ConfigMixin):
"""
`UniPCMultistepScheduler` is a training-free framework designed for the fast sampling of diffusion models.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the libr... | class_definition | 4,027 | 46,654 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/scheduling_unipc_multistep.py | null | 1,374 |
class ScoreSdeVpScheduler(SchedulerMixin, ConfigMixin):
"""
`ScoreSdeVpScheduler` is a variance preserving stochastic differential equation (SDE) scheduler.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the library implements... | class_definition | 935 | 4,293 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/deprecated/scheduling_sde_vp.py | null | 1,375 |
class KarrasVeOutput(BaseOutput):
"""
Output class for the scheduler's step function output.
Args:
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images):
Computed sample (x_{t-1}) of previous timestep. `prev_sample` should be used as next model inp... | class_definition | 933 | 1,878 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/deprecated/scheduling_karras_ve.py | null | 1,376 |
class KarrasVeScheduler(SchedulerMixin, ConfigMixin):
"""
A stochastic scheduler tailored to variance-expanding models.
This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
methods the library implements for all schedulers such as loading a... | class_definition | 1,881 | 9,711 | 0 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/schedulers/deprecated/scheduling_karras_ve.py | null | 1,377 |
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