resolve conflicts

This reverts commit 65efbcead5.

examples/conftest.py

@@ -25,6 +25,11 @@ from os.path import abspath, dirname, join
 git_repo_path = abspath(join(dirname(dirname(dirname(__file__))), "src"))
 sys.path.insert(1, git_repo_path)
 
+# Add parent directory to path so we can import from tests
+repo_root = abspath(dirname(dirname(__file__)))
+if repo_root not in sys.path:
+    sys.path.insert(0, repo_root)
+
 
 # silence FutureWarning warnings in tests since often we can't act on them until
 # they become normal warnings - i.e. the tests still need to test the current functionality
@@ -32,13 +37,13 @@ warnings.simplefilter(action="ignore", category=FutureWarning)
 
 
 def pytest_addoption(parser):
-    from diffusers.utils.testing_utils import pytest_addoption_shared
+    from tests.testing_utils import pytest_addoption_shared
 
     pytest_addoption_shared(parser)
 
 
 def pytest_terminal_summary(terminalreporter):
-    from diffusers.utils.testing_utils import pytest_terminal_summary_main
+    from tests.testing_utils import pytest_terminal_summary_main
 
     make_reports = terminalreporter.config.getoption("--make-reports")
     if make_reports:

examples/controlnet/train_controlnet_sd3.py

@@ -24,6 +24,8 @@ import math
 import os
 import random
 import shutil
+
+# Add repo root to path to import from tests
 from pathlib import Path
 
 import accelerate
@@ -54,8 +56,7 @@ from diffusers.optimization import get_scheduler
 from diffusers.training_utils import compute_density_for_timestep_sampling, compute_loss_weighting_for_sd3, free_memory
 from diffusers.utils import check_min_version, is_wandb_available, make_image_grid
 from diffusers.utils.hub_utils import load_or_create_model_card, populate_model_card
-from diffusers.utils.testing_utils import backend_empty_cache
-from diffusers.utils.torch_utils import is_compiled_module
+from diffusers.utils.torch_utils import backend_empty_cache, is_compiled_module
 
 
 if is_wandb_available():

examples/vqgan/test_vqgan.py

@@ -24,12 +24,18 @@ import tempfile
 import torch
 
 from diffusers import VQModel
-from diffusers.utils.testing_utils import require_timm
 
 
+# Add parent directories to path to import from tests
 sys.path.append("..")
+repo_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "../.."))
+if repo_root not in sys.path:
+    sys.path.insert(0, repo_root)
+
 from test_examples_utils import ExamplesTestsAccelerate, run_command  # noqa: E402
 
+from tests.testing_utils import require_timm  # noqa
+
 
 logging.basicConfig(level=logging.DEBUG)
 

src/diffusers/modular_pipelines/modular_pipeline.py

@@ -128,6 +128,15 @@ class PipelineState:
         """
         return {**self.__dict__}
 
+    def __getattr__(self, name):
+        """
+        Allow attribute access to intermediate values. If an attribute is not found in the object, look for it in the
+        intermediates dict.
+        """
+        if name in self.intermediates:
+            return self.intermediates[name]
+        raise AttributeError(f"'{self.__class__.__name__}' object has no attribute '{name}'")
+
     def __repr__(self):
         def format_value(v):
             if hasattr(v, "shape") and hasattr(v, "dtype"):
@@ -638,7 +647,7 @@ class AutoPipelineBlocks(ModularPipelineBlocks):
                 break
 
         if block is None:
-            logger.warning(f"skipping auto block: {self.__class__.__name__}")
+            logger.info(f"skipping auto block: {self.__class__.__name__}")
             return pipeline, state
 
         try:
@@ -1450,9 +1459,10 @@ class ModularPipeline(ConfigMixin, PushToHubMixin):
         Args:
             blocks: `ModularPipelineBlocks` instance. If None, will attempt to load
                    default blocks based on the pipeline class name.
-            pretrained_model_name_or_path: Path to a pretrained pipeline configuration. If provided,
-                    will load component specs (only for from_pretrained components) and config values from the saved
-                    modular_model_index.json file.
+            pretrained_model_name_or_path: Path to a pretrained pipeline configuration. Can be None if the pipeline
+                    does not require any additional loading config. If provided, will first try to load component specs
+                    (only for from_pretrained components) and config values from `modular_model_index.json`, then
+                    fallback to `model_index.json` for compatibility with standard non-modular repositories.
             components_manager:
                 Optional ComponentsManager for managing multiple component cross different pipelines and apply
                 offloading strategies.
@@ -1501,18 +1511,70 @@ class ModularPipeline(ConfigMixin, PushToHubMixin):
 
         # update component_specs and config_specs from modular_repo
         if pretrained_model_name_or_path is not None:
-            config_dict = self.load_config(pretrained_model_name_or_path, **kwargs)
+            cache_dir = kwargs.pop("cache_dir", None)
+            force_download = kwargs.pop("force_download", False)
+            proxies = kwargs.pop("proxies", None)
+            token = kwargs.pop("token", None)
+            local_files_only = kwargs.pop("local_files_only", False)
+            revision = kwargs.pop("revision", None)
 
-            for name, value in config_dict.items():
-                # all the components in modular_model_index.json are from_pretrained components
-                if name in self._component_specs and isinstance(value, (tuple, list)) and len(value) == 3:
-                    library, class_name, component_spec_dict = value
-                    component_spec = self._dict_to_component_spec(name, component_spec_dict)
-                    component_spec.default_creation_method = "from_pretrained"
-                    self._component_specs[name] = component_spec
+            load_config_kwargs = {
+                "cache_dir": cache_dir,
+                "force_download": force_download,
+                "proxies": proxies,
+                "token": token,
+                "local_files_only": local_files_only,
+                "revision": revision,
+            }
+            # try to load modular_model_index.json
+            try:
+                config_dict = self.load_config(pretrained_model_name_or_path, **load_config_kwargs)
+            except EnvironmentError as e:
+                logger.debug(f"modular_model_index.json not found: {e}")
+                config_dict = None
 
-                elif name in self._config_specs:
-                    self._config_specs[name].default = value
+            # update component_specs and config_specs based on modular_model_index.json
+            if config_dict is not None:
+                for name, value in config_dict.items():
+                    # all the components in modular_model_index.json are from_pretrained components
+                    if name in self._component_specs and isinstance(value, (tuple, list)) and len(value) == 3:
+                        library, class_name, component_spec_dict = value
+                        component_spec = self._dict_to_component_spec(name, component_spec_dict)
+                        component_spec.default_creation_method = "from_pretrained"
+                        self._component_specs[name] = component_spec
+
+                    elif name in self._config_specs:
+                        self._config_specs[name].default = value
+
+            # if modular_model_index.json is not found, try to load model_index.json
+            else:
+                logger.debug(" loading config from model_index.json")
+                try:
+                    from diffusers import DiffusionPipeline
+
+                    config_dict = DiffusionPipeline.load_config(pretrained_model_name_or_path, **load_config_kwargs)
+                except EnvironmentError as e:
+                    logger.debug(f" model_index.json not found in the repo: {e}")
+                    config_dict = None
+
+                # update component_specs and config_specs based on model_index.json
+                if config_dict is not None:
+                    for name, value in config_dict.items():
+                        if name in self._component_specs and isinstance(value, (tuple, list)) and len(value) == 2:
+                            library, class_name = value
+                            component_spec_dict = {
+                                "repo": pretrained_model_name_or_path,
+                                "subfolder": name,
+                                "type_hint": (library, class_name),
+                            }
+                            component_spec = self._dict_to_component_spec(name, component_spec_dict)
+                            component_spec.default_creation_method = "from_pretrained"
+                            self._component_specs[name] = component_spec
+                        elif name in self._config_specs:
+                            self._config_specs[name].default = value
+
+        if len(kwargs) > 0:
+            logger.warning(f"Unexpected input '{kwargs.keys()}' provided. This input will be ignored.")
 
         register_components_dict = {}
         for name, component_spec in self._component_specs.items():
@@ -1570,8 +1632,10 @@ class ModularPipeline(ConfigMixin, PushToHubMixin):
 
         Args:
             pretrained_model_name_or_path (`str` or `os.PathLike`, optional):
-                Path to a pretrained pipeline configuration. If provided, will load component specs (only for
-                from_pretrained components) and config values from the modular_model_index.json file.
+                Path to a pretrained pipeline configuration. It will first try to load config from
+                `modular_model_index.json`, then fallback to `model_index.json` for compatibility with standard
+                non-modular repositories. If the repo does not contain any pipeline config, it will be set to None
+                during initialization.
             trust_remote_code (`bool`, optional):
                 Whether to trust remote code when loading the pipeline, need to be set to True if you want to create
                 pipeline blocks based on the custom code in `pretrained_model_name_or_path`
@@ -1607,11 +1671,35 @@ class ModularPipeline(ConfigMixin, PushToHubMixin):
         }
 
         try:
+            # try to load modular_model_index.json
             config_dict = cls.load_config(pretrained_model_name_or_path, **load_config_kwargs)
+        except EnvironmentError as e:
+            logger.debug(f" modular_model_index.json not found in the repo: {e}")
+            config_dict = None
+
+        if config_dict is not None:
             pipeline_class = _get_pipeline_class(cls, config=config_dict)
-        except EnvironmentError:
-            pipeline_class = cls
-            pretrained_model_name_or_path = None
+        else:
+            try:
+                logger.debug(" try to load model_index.json")
+                from diffusers import DiffusionPipeline
+                from diffusers.pipelines.auto_pipeline import _get_model
+
+                config_dict = DiffusionPipeline.load_config(pretrained_model_name_or_path, **load_config_kwargs)
+            except EnvironmentError as e:
+                logger.debug(f" model_index.json not found in the repo: {e}")
+
+            if config_dict is not None:
+                logger.debug(" try to determine the modular pipeline class from model_index.json")
+                standard_pipeline_class = _get_pipeline_class(cls, config=config_dict)
+                model_name = _get_model(standard_pipeline_class.__name__)
+                pipeline_class_name = MODULAR_PIPELINE_MAPPING.get(model_name, ModularPipeline.__name__)
+                diffusers_module = importlib.import_module("diffusers")
+                pipeline_class = getattr(diffusers_module, pipeline_class_name)
+            else:
+                # there is no config for modular pipeline, assuming that the pipeline block does not need any from_pretrained components
+                pipeline_class = cls
+                pretrained_model_name_or_path = None
 
         pipeline = pipeline_class(
             blocks=blocks,
@@ -1949,17 +2037,31 @@ class ModularPipeline(ConfigMixin, PushToHubMixin):
         for name, component in passed_components.items():
             current_component_spec = self._component_specs[name]
 
-            # warn if type changed
+            # log if type changed
             if current_component_spec.type_hint is not None and not isinstance(
                 component, current_component_spec.type_hint
             ):
-                logger.warning(
+                logger.info(
                     f"ModularPipeline.update_components: adding {name} with new type: {component.__class__.__name__}, previous type: {current_component_spec.type_hint.__name__}"
                 )
             # update _component_specs based on the new component
-            new_component_spec = ComponentSpec.from_component(name, component)
-            if new_component_spec.default_creation_method != current_component_spec.default_creation_method:
+            if component is None:
+                new_component_spec = current_component_spec
+                if hasattr(self, name) and getattr(self, name) is not None:
+                    logger.warning(f"ModularPipeline.update_components: setting {name} to None (spec unchanged)")
+            elif current_component_spec.default_creation_method == "from_pretrained" and not (
+                hasattr(component, "_diffusers_load_id") and component._diffusers_load_id is not None
+            ):
                 logger.warning(
+                    f"ModularPipeline.update_components: {name} has no valid _diffusers_load_id. "
+                    f"This will result in empty loading spec, use ComponentSpec.load() for proper specs"
+                )
+                new_component_spec = ComponentSpec(name=name, type_hint=type(component))
+            else:
+                new_component_spec = ComponentSpec.from_component(name, component)
+
+            if new_component_spec.default_creation_method != current_component_spec.default_creation_method:
+                logger.info(
                     f"ModularPipeline.update_components: changing the default_creation_method of {name} from {current_component_spec.default_creation_method} to {new_component_spec.default_creation_method}."
                 )
 
@@ -1980,7 +2082,7 @@ class ModularPipeline(ConfigMixin, PushToHubMixin):
             if current_component_spec.type_hint is not None and not isinstance(
                 created_components[name], current_component_spec.type_hint
             ):
-                logger.warning(
+                logger.info(
                     f"ModularPipeline.update_components: adding {name} with new type: {created_components[name].__class__.__name__}, previous type: {current_component_spec.type_hint.__name__}"
                 )
             # update _component_specs based on the user passed component_spec

src/diffusers/modular_pipelines/stable_diffusion_xl/before_denoise.py

@@ -22,7 +22,7 @@ from ...configuration_utils import FrozenDict
 from ...guiders import ClassifierFreeGuidance
 from ...image_processor import VaeImageProcessor
 from ...models import AutoencoderKL, ControlNetModel, ControlNetUnionModel, UNet2DConditionModel
-from ...pipelines.controlnet.multicontrolnet import MultiControlNetModel
+from ...models.controlnets.multicontrolnet import MultiControlNetModel
 from ...schedulers import EulerDiscreteScheduler
 from ...utils import logging
 from ...utils.torch_utils import randn_tensor, unwrap_module

src/diffusers/pipelines/pipeline_utils.py

@@ -1709,6 +1709,36 @@ class DiffusionPipeline(ConfigMixin, PushToHubMixin):
                 logger.warning(f"cannot get type annotation for Parameter {k} of {cls}.")
         return signature_types
 
+    @property
+    def parameters(self) -> Dict[str, Any]:
+        r"""
+        The `self.parameters` property can be useful to run different pipelines with the same weights and
+        configurations without reallocating additional memory.
+
+        Returns (`dict`):
+            A dictionary containing all the optional parameters needed to initialize the pipeline.
+
+        Examples:
+
+        ```py
+        >>> from diffusers import (
+        ...     StableDiffusionPipeline,
+        ...     StableDiffusionImg2ImgPipeline,
+        ...     StableDiffusionInpaintPipeline,
+        ... )
+
+        >>> text2img = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
+        >>> img2img = StableDiffusionImg2ImgPipeline(**text2img.components, **text2img.parameters)
+        >>> inpaint = StableDiffusionInpaintPipeline(**text2img.components, **text2img.parameters)
+        ```
+        """
+        expected_modules, optional_parameters = self._get_signature_keys(self)
+        pipeline_parameters = {
+            k: self.config[k] for k in self.config.keys() if not k.startswith("_") and k in optional_parameters
+        }
+
+        return pipeline_parameters
+
     @property
     def components(self) -> Dict[str, Any]:
         r"""

src/diffusers/utils/testing_utils.py

@@ -66,7 +66,10 @@ else:
 global_rng = random.Random()
 
 logger = get_logger(__name__)
-
+logger.warning(
+    "diffusers.utils.testing_utils' is deprecated and will be removed in a future version. "
+    "Determinism and device backend utilities have been moved to `diffusers.utils.torch_utils`. "
+)
 _required_peft_version = is_peft_available() and version.parse(
     version.parse(importlib.metadata.version("peft")).base_version
 ) > version.parse("0.5")
@@ -801,10 +804,9 @@ def export_to_ply(mesh, output_ply_path: str = None):
                 f.write(format.pack(*vertex))
 
         if faces is not None:
-            format = struct.Struct("<B3I")
             for tri in faces.tolist():
                 f.write(format.pack(len(tri), *tri))
-
+            format = struct.Struct("<B3I")
     return output_ply_path
 
 
@@ -1144,23 +1146,23 @@ def enable_full_determinism():
     Helper function for reproducible behavior during distributed training. See
     - https://pytorch.org/docs/stable/notes/randomness.html for pytorch
     """
-    #  Enable PyTorch deterministic mode. This potentially requires either the environment
-    #  variable 'CUDA_LAUNCH_BLOCKING' or 'CUBLAS_WORKSPACE_CONFIG' to be set,
-    # depending on the CUDA version, so we set them both here
-    os.environ["CUDA_LAUNCH_BLOCKING"] = "1"
-    os.environ["CUBLAS_WORKSPACE_CONFIG"] = ":16:8"
-    torch.use_deterministic_algorithms(True)
+    from .torch_utils import enable_full_determinism as _enable_full_determinism
 
-    # Enable CUDNN deterministic mode
-    torch.backends.cudnn.deterministic = True
-    torch.backends.cudnn.benchmark = False
-    torch.backends.cuda.matmul.allow_tf32 = False
+    logger.warning(
+        "enable_full_determinism has been moved to diffusers.utils.torch_utils. "
+        "Importing from diffusers.utils.testing_utils is deprecated and will be removed in a future version."
+    )
+    return _enable_full_determinism()
 
 
 def disable_full_determinism():
-    os.environ["CUDA_LAUNCH_BLOCKING"] = "0"
-    os.environ["CUBLAS_WORKSPACE_CONFIG"] = ""
-    torch.use_deterministic_algorithms(False)
+    from .torch_utils import disable_full_determinism as _disable_full_determinism
+
+    logger.warning(
+        "disable_full_determinism has been moved to diffusers.utils.torch_utils. "
+        "Importing from diffusers.utils.testing_utils is deprecated and will be removed in a future version."
+    )
+    return _disable_full_determinism()
 
 
 # Utils for custom and alternative accelerator devices
@@ -1282,43 +1284,85 @@ def _device_agnostic_dispatch(device: str, dispatch_table: Dict[str, Callable],
 
 # These are callables which automatically dispatch the function specific to the accelerator
 def backend_manual_seed(device: str, seed: int):
-    return _device_agnostic_dispatch(device, BACKEND_MANUAL_SEED, seed)
+    from .torch_utils import backend_manual_seed as _backend_manual_seed
+
+    logger.warning(
+        "backend_manual_seed has been moved to diffusers.utils.torch_utils. "
+        "diffusers.utils.testing_utils is deprecated and will be removed in a future version."
+    )
+    return _backend_manual_seed(device, seed)
 
 
 def backend_synchronize(device: str):
-    return _device_agnostic_dispatch(device, BACKEND_SYNCHRONIZE)
+    from .torch_utils import backend_synchronize as _backend_synchronize
+
+    logger.warning(
+        "backend_synchronize has been moved to diffusers.utils.torch_utils. "
+        "diffusers.utils.testing_utils is deprecated and will be removed in a future version."
+    )
+    return _backend_synchronize(device)
 
 
 def backend_empty_cache(device: str):
-    return _device_agnostic_dispatch(device, BACKEND_EMPTY_CACHE)
+    from .torch_utils import backend_empty_cache as _backend_empty_cache
+
+    logger.warning(
+        "backend_empty_cache has been moved to diffusers.utils.torch_utils. "
+        "diffusers.utils.testing_utils is deprecated and will be removed in a future version."
+    )
+    return _backend_empty_cache(device)
 
 
 def backend_device_count(device: str):
-    return _device_agnostic_dispatch(device, BACKEND_DEVICE_COUNT)
+    from .torch_utils import backend_device_count as _backend_device_count
+
+    logger.warning(
+        "backend_device_count has been moved to diffusers.utils.torch_utils. "
+        "diffusers.utils.testing_utils is deprecated and will be removed in a future version."
+    )
+    return _backend_device_count(device)
 
 
 def backend_reset_peak_memory_stats(device: str):
-    return _device_agnostic_dispatch(device, BACKEND_RESET_PEAK_MEMORY_STATS)
+    from .torch_utils import backend_reset_peak_memory_stats as _backend_reset_peak_memory_stats
+
+    logger.warning(
+        "backend_reset_peak_memory_stats has been moved to diffusers.utils.torch_utils. "
+        "diffusers.utils.testing_utils is deprecated and will be removed in a future version."
+    )
+    return _backend_reset_peak_memory_stats(device)
 
 
 def backend_reset_max_memory_allocated(device: str):
-    return _device_agnostic_dispatch(device, BACKEND_RESET_MAX_MEMORY_ALLOCATED)
+    from .torch_utils import backend_reset_max_memory_allocated as _backend_reset_max_memory_allocated
+
+    logger.warning(
+        "backend_reset_max_memory_allocated has been moved to diffusers.utils.torch_utils. "
+        "diffusers.utils.testing_utils is deprecated and will be removed in a future version."
+    )
+    return _backend_reset_max_memory_allocated(device)
 
 
 def backend_max_memory_allocated(device: str):
-    return _device_agnostic_dispatch(device, BACKEND_MAX_MEMORY_ALLOCATED)
+    from .torch_utils import backend_max_memory_allocated as _backend_max_memory_allocated
+
+    logger.warning(
+        "backend_max_memory_allocated has been moved to diffusers.utils.torch_utils. "
+        "diffusers.utils.testing_utils is deprecated and will be removed in a future version."
+    )
+    return _backend_max_memory_allocated(device)
 
 
 # These are callables which return boolean behaviour flags and can be used to specify some
 # device agnostic alternative where the feature is unsupported.
 def backend_supports_training(device: str):
-    if not is_torch_available():
-        return False
+    from .torch_utils import backend_supports_training as _backend_supports_training
 
-    if device not in BACKEND_SUPPORTS_TRAINING:
-        device = "default"
-
-    return BACKEND_SUPPORTS_TRAINING[device]
+    logger.warning(
+        "backend_supports_training has been moved to diffusers.utils.torch_utils. "
+        "diffusers.utils.testing_utils is deprecated and will be removed in a future version."
+    )
+    return _backend_supports_training(device)
 
 
 # Guard for when Torch is not available

src/diffusers/utils/torch_utils.py

@@ -16,7 +16,8 @@ PyTorch utilities: Utilities related to PyTorch
 """
 
 import functools
-from typing import List, Optional, Tuple, Union
+import os
+from typing import Callable, Dict, List, Optional, Tuple, Union
 
 from . import logging
 from .import_utils import is_torch_available, is_torch_npu_available, is_torch_version
@@ -26,6 +27,56 @@ if is_torch_available():
     import torch
     from torch.fft import fftn, fftshift, ifftn, ifftshift
 
+    BACKEND_SUPPORTS_TRAINING = {"cuda": True, "xpu": True, "cpu": True, "mps": False, "default": True}
+    BACKEND_EMPTY_CACHE = {
+        "cuda": torch.cuda.empty_cache,
+        "xpu": torch.xpu.empty_cache,
+        "cpu": None,
+        "mps": torch.mps.empty_cache,
+        "default": None,
+    }
+    BACKEND_DEVICE_COUNT = {
+        "cuda": torch.cuda.device_count,
+        "xpu": torch.xpu.device_count,
+        "cpu": lambda: 0,
+        "mps": lambda: 0,
+        "default": 0,
+    }
+    BACKEND_MANUAL_SEED = {
+        "cuda": torch.cuda.manual_seed,
+        "xpu": torch.xpu.manual_seed,
+        "cpu": torch.manual_seed,
+        "mps": torch.mps.manual_seed,
+        "default": torch.manual_seed,
+    }
+    BACKEND_RESET_PEAK_MEMORY_STATS = {
+        "cuda": torch.cuda.reset_peak_memory_stats,
+        "xpu": getattr(torch.xpu, "reset_peak_memory_stats", None),
+        "cpu": None,
+        "mps": None,
+        "default": None,
+    }
+    BACKEND_RESET_MAX_MEMORY_ALLOCATED = {
+        "cuda": torch.cuda.reset_max_memory_allocated,
+        "xpu": getattr(torch.xpu, "reset_peak_memory_stats", None),
+        "cpu": None,
+        "mps": None,
+        "default": None,
+    }
+    BACKEND_MAX_MEMORY_ALLOCATED = {
+        "cuda": torch.cuda.max_memory_allocated,
+        "xpu": getattr(torch.xpu, "max_memory_allocated", None),
+        "cpu": 0,
+        "mps": 0,
+        "default": 0,
+    }
+    BACKEND_SYNCHRONIZE = {
+        "cuda": torch.cuda.synchronize,
+        "xpu": getattr(torch.xpu, "synchronize", None),
+        "cpu": None,
+        "mps": None,
+        "default": None,
+    }
 logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
 
 try:
@@ -36,6 +87,62 @@ except (ImportError, ModuleNotFoundError):
         return cls
 
 
+# This dispatches a defined function according to the accelerator from the function definitions.
+def _device_agnostic_dispatch(device: str, dispatch_table: Dict[str, Callable], *args, **kwargs):
+    if device not in dispatch_table:
+        return dispatch_table["default"](*args, **kwargs)
+
+    fn = dispatch_table[device]
+
+    # Some device agnostic functions return values. Need to guard against 'None' instead at
+    # user level
+    if not callable(fn):
+        return fn
+
+    return fn(*args, **kwargs)
+
+
+# These are callables which automatically dispatch the function specific to the accelerator
+def backend_manual_seed(device: str, seed: int):
+    return _device_agnostic_dispatch(device, BACKEND_MANUAL_SEED, seed)
+
+
+def backend_synchronize(device: str):
+    return _device_agnostic_dispatch(device, BACKEND_SYNCHRONIZE)
+
+
+def backend_empty_cache(device: str):
+    return _device_agnostic_dispatch(device, BACKEND_EMPTY_CACHE)
+
+
+def backend_device_count(device: str):
+    return _device_agnostic_dispatch(device, BACKEND_DEVICE_COUNT)
+
+
+def backend_reset_peak_memory_stats(device: str):
+    return _device_agnostic_dispatch(device, BACKEND_RESET_PEAK_MEMORY_STATS)
+
+
+def backend_reset_max_memory_allocated(device: str):
+    return _device_agnostic_dispatch(device, BACKEND_RESET_MAX_MEMORY_ALLOCATED)
+
+
+def backend_max_memory_allocated(device: str):
+    return _device_agnostic_dispatch(device, BACKEND_MAX_MEMORY_ALLOCATED)
+
+
+# These are callables which return boolean behaviour flags and can be used to specify some
+# device agnostic alternative where the feature is unsupported.
+def backend_supports_training(device: str):
+    if not is_torch_available():
+        return False
+
+    if device not in BACKEND_SUPPORTS_TRAINING:
+        device = "default"
+
+    return BACKEND_SUPPORTS_TRAINING[device]
+
+
 def randn_tensor(
     shape: Union[Tuple, List],
     generator: Optional[Union[List["torch.Generator"], "torch.Generator"]] = None,
@@ -197,3 +304,31 @@ def device_synchronize(device_type: Optional[str] = None):
         device_type = get_device()
     device_mod = getattr(torch, device_type, torch.cuda)
     device_mod.synchronize()
+
+
+def enable_full_determinism():
+    """
+    Helper function for reproducible behavior during distributed training. See
+    - https://pytorch.org/docs/stable/notes/randomness.html for pytorch
+    """
+    #  Enable PyTorch deterministic mode. This potentially requires either the environment
+    #  variable 'CUDA_LAUNCH_BLOCKING' or 'CUBLAS_WORKSPACE_CONFIG' to be set,
+    # depending on the CUDA version, so we set them both here
+    os.environ["CUDA_LAUNCH_BLOCKING"] = "1"
+    os.environ["CUBLAS_WORKSPACE_CONFIG"] = ":16:8"
+    torch.use_deterministic_algorithms(True)
+
+    # Enable CUDNN deterministic mode
+    torch.backends.cudnn.deterministic = True
+    torch.backends.cudnn.benchmark = False
+    torch.backends.cuda.matmul.allow_tf32 = False
+
+
+def disable_full_determinism():
+    os.environ["CUDA_LAUNCH_BLOCKING"] = "0"
+    os.environ["CUBLAS_WORKSPACE_CONFIG"] = ""
+    torch.use_deterministic_algorithms(False)
+
+
+if is_torch_available():
+    torch_device = get_device()

tests/conftest.py

@@ -35,13 +35,13 @@ def pytest_configure(config):
 
 
 def pytest_addoption(parser):
-    from diffusers.utils.testing_utils import pytest_addoption_shared
+    from .testing_utils import pytest_addoption_shared
 
     pytest_addoption_shared(parser)
 
 
 def pytest_terminal_summary(terminalreporter):
-    from diffusers.utils.testing_utils import pytest_terminal_summary_main
+    from .testing_utils import pytest_terminal_summary_main
 
     make_reports = terminalreporter.config.getoption("--make-reports")
     if make_reports:

tests/hooks/test_group_offloading.py

@@ -24,7 +24,8 @@ from diffusers.models import ModelMixin
 from diffusers.pipelines.pipeline_utils import DiffusionPipeline
 from diffusers.utils import get_logger
 from diffusers.utils.import_utils import compare_versions
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     backend_empty_cache,
     backend_max_memory_allocated,
     backend_reset_peak_memory_stats,

tests/hooks/test_hooks.py

@@ -20,7 +20,8 @@ import torch
 from diffusers.hooks import HookRegistry, ModelHook
 from diffusers.training_utils import free_memory
 from diffusers.utils.logging import get_logger
-from diffusers.utils.testing_utils import CaptureLogger, torch_device
+
+from ..testing_utils import CaptureLogger, torch_device
 
 
 logger = get_logger(__name__)  # pylint: disable=invalid-name

tests/lora/test_lora_layers_auraflow.py

@@ -23,7 +23,8 @@ from diffusers import (
     AuraFlowTransformer2DModel,
     FlowMatchEulerDiscreteScheduler,
 )
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     floats_tensor,
     is_peft_available,
     require_peft_backend,
@@ -35,7 +36,7 @@ if is_peft_available():
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 
 
 @require_peft_backend

tests/lora/test_lora_layers_cogvideox.py

@@ -26,7 +26,8 @@ from diffusers import (
     CogVideoXPipeline,
     CogVideoXTransformer3DModel,
 )
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     floats_tensor,
     require_peft_backend,
     require_torch_accelerator,
@@ -35,7 +36,7 @@ from diffusers.utils.testing_utils import (
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 
 
 @require_peft_backend

tests/lora/test_lora_layers_cogview4.py

@@ -22,7 +22,8 @@ from parameterized import parameterized
 from transformers import AutoTokenizer, GlmModel
 
 from diffusers import AutoencoderKL, CogView4Pipeline, CogView4Transformer2DModel, FlowMatchEulerDiscreteScheduler
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     floats_tensor,
     require_peft_backend,
     require_torch_accelerator,
@@ -33,7 +34,7 @@ from diffusers.utils.testing_utils import (
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 
 
 class TokenizerWrapper:

tests/lora/test_lora_layers_flux.py

@@ -28,7 +28,8 @@ from transformers import AutoTokenizer, CLIPTextModel, CLIPTokenizer, T5EncoderM
 
 from diffusers import FlowMatchEulerDiscreteScheduler, FluxControlPipeline, FluxPipeline, FluxTransformer2DModel
 from diffusers.utils import load_image, logging
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     CaptureLogger,
     backend_empty_cache,
     floats_tensor,
@@ -48,7 +49,7 @@ if is_peft_available():
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests, check_if_lora_correctly_set  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests, check_if_lora_correctly_set  # noqa: E402
 
 
 @require_peft_backend

tests/lora/test_lora_layers_hunyuanvideo.py

@@ -26,7 +26,8 @@ from diffusers import (
     HunyuanVideoPipeline,
     HunyuanVideoTransformer3DModel,
 )
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     Expectations,
     backend_empty_cache,
     floats_tensor,
@@ -42,7 +43,7 @@ from diffusers.utils.testing_utils import (
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 
 
 @require_peft_backend

tests/lora/test_lora_layers_ltx_video.py

@@ -24,12 +24,13 @@ from diffusers import (
     LTXPipeline,
     LTXVideoTransformer3DModel,
 )
-from diffusers.utils.testing_utils import floats_tensor, require_peft_backend
+
+from ..testing_utils import floats_tensor, require_peft_backend
 
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 
 
 @require_peft_backend

tests/lora/test_lora_layers_lumina2.py

@@ -26,12 +26,13 @@ from diffusers import (
     Lumina2Pipeline,
     Lumina2Transformer2DModel,
 )
-from diffusers.utils.testing_utils import floats_tensor, is_torch_version, require_peft_backend, skip_mps, torch_device
+
+from ..testing_utils import floats_tensor, is_torch_version, require_peft_backend, skip_mps, torch_device
 
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests, check_if_lora_correctly_set  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests, check_if_lora_correctly_set  # noqa: E402
 
 
 @require_peft_backend

tests/lora/test_lora_layers_mochi.py

@@ -19,7 +19,8 @@ import torch
 from transformers import AutoTokenizer, T5EncoderModel
 
 from diffusers import AutoencoderKLMochi, FlowMatchEulerDiscreteScheduler, MochiPipeline, MochiTransformer3DModel
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     floats_tensor,
     require_peft_backend,
     skip_mps,
@@ -28,7 +29,7 @@ from diffusers.utils.testing_utils import (
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 
 
 @require_peft_backend

tests/lora/test_lora_layers_qwenimage.py

@@ -24,12 +24,13 @@ from diffusers import (
     QwenImagePipeline,
     QwenImageTransformer2DModel,
 )
-from diffusers.utils.testing_utils import floats_tensor, require_peft_backend
+
+from ..testing_utils import floats_tensor, require_peft_backend
 
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 
 
 @require_peft_backend

tests/lora/test_lora_layers_sana.py

@@ -19,12 +19,13 @@ import torch
 from transformers import Gemma2Model, GemmaTokenizer
 
 from diffusers import AutoencoderDC, FlowMatchEulerDiscreteScheduler, SanaPipeline, SanaTransformer2DModel
-from diffusers.utils.testing_utils import floats_tensor, require_peft_backend
+
+from ..testing_utils import floats_tensor, require_peft_backend
 
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 
 
 @require_peft_backend

tests/lora/test_lora_layers_sd.py

@@ -32,7 +32,8 @@ from diffusers import (
     StableDiffusionPipeline,
 )
 from diffusers.utils.import_utils import is_accelerate_available
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     Expectations,
     backend_empty_cache,
     load_image,
@@ -47,7 +48,7 @@ from diffusers.utils.testing_utils import (
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests, check_if_lora_correctly_set  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests, check_if_lora_correctly_set  # noqa: E402
 
 
 if is_accelerate_available():

tests/lora/test_lora_layers_sd3.py

@@ -28,7 +28,8 @@ from diffusers import (
 )
 from diffusers.utils import load_image
 from diffusers.utils.import_utils import is_accelerate_available
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     backend_empty_cache,
     is_flaky,
     nightly,
@@ -42,7 +43,7 @@ from diffusers.utils.testing_utils import (
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 
 
 if is_accelerate_available():

tests/lora/test_lora_layers_sdxl.py

@@ -35,7 +35,8 @@ from diffusers import (
 )
 from diffusers.utils import logging
 from diffusers.utils.import_utils import is_accelerate_available
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     CaptureLogger,
     backend_empty_cache,
     is_flaky,
@@ -51,7 +52,7 @@ from diffusers.utils.testing_utils import (
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests, check_if_lora_correctly_set, state_dicts_almost_equal  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests, check_if_lora_correctly_set, state_dicts_almost_equal  # noqa: E402
 
 
 if is_accelerate_available():

tests/lora/test_lora_layers_wan.py

@@ -24,7 +24,8 @@ from diffusers import (
     WanPipeline,
     WanTransformer3DModel,
 )
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     floats_tensor,
     require_peft_backend,
     skip_mps,
@@ -33,7 +34,7 @@ from diffusers.utils.testing_utils import (
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 
 
 @require_peft_backend

tests/lora/test_lora_layers_wanvace.py

@@ -25,7 +25,8 @@ from transformers import AutoTokenizer, T5EncoderModel
 
 from diffusers import AutoencoderKLWan, FlowMatchEulerDiscreteScheduler, WanVACEPipeline, WanVACETransformer3DModel
 from diffusers.utils.import_utils import is_peft_available
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     floats_tensor,
     is_flaky,
     require_peft_backend,
@@ -40,7 +41,7 @@ if is_peft_available():
 
 sys.path.append(".")
 
-from utils import PeftLoraLoaderMixinTests  # noqa: E402
+from .utils import PeftLoraLoaderMixinTests  # noqa: E402
 
 
 @require_peft_backend

tests/lora/utils.py

@@ -32,7 +32,8 @@ from diffusers import (
 )
 from diffusers.utils import logging
 from diffusers.utils.import_utils import is_peft_available
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     CaptureLogger,
     check_if_dicts_are_equal,
     floats_tensor,

tests/models/autoencoders/test_models_asymmetric_autoencoder_kl.py

@@ -21,7 +21,8 @@ from parameterized import parameterized
 
 from diffusers import AsymmetricAutoencoderKL
 from diffusers.utils.import_utils import is_xformers_available
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     Expectations,
     backend_empty_cache,
     enable_full_determinism,
@@ -34,7 +35,6 @@ from diffusers.utils.testing_utils import (
     torch_all_close,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/autoencoders/test_models_autoencoder_cosmos.py

@@ -15,8 +15,8 @@
 import unittest
 
 from diffusers import AutoencoderKLCosmos
-from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, torch_device
 
+from ...testing_utils import enable_full_determinism, floats_tensor, torch_device
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/autoencoders/test_models_autoencoder_dc.py

@@ -16,12 +16,12 @@
 import unittest
 
 from diffusers import AutoencoderDC
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     floats_tensor,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/autoencoders/test_models_autoencoder_hunyuan_video.py

@@ -19,12 +19,12 @@ import torch
 
 from diffusers import AutoencoderKLHunyuanVideo
 from diffusers.models.autoencoders.autoencoder_kl_hunyuan_video import prepare_causal_attention_mask
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     floats_tensor,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/autoencoders/test_models_autoencoder_kl.py

@@ -21,7 +21,8 @@ from parameterized import parameterized
 
 from diffusers import AutoencoderKL
 from diffusers.utils.import_utils import is_xformers_available
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     backend_empty_cache,
     enable_full_determinism,
     floats_tensor,
@@ -34,7 +35,6 @@ from diffusers.utils.testing_utils import (
     torch_all_close,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/autoencoders/test_models_autoencoder_kl_cogvideox.py

@@ -18,12 +18,12 @@ import unittest
 import torch
 
 from diffusers import AutoencoderKLCogVideoX
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     floats_tensor,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/autoencoders/test_models_autoencoder_kl_temporal_decoder.py

@@ -16,12 +16,12 @@
 import unittest
 
 from diffusers import AutoencoderKLTemporalDecoder
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     floats_tensor,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/autoencoders/test_models_autoencoder_ltx_video.py

@@ -18,12 +18,12 @@ import unittest
 import torch
 
 from diffusers import AutoencoderKLLTXVideo
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     floats_tensor,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/autoencoders/test_models_autoencoder_magvit.py

@@ -16,8 +16,8 @@
 import unittest
 
 from diffusers import AutoencoderKLMagvit
-from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, torch_device
 
+from ...testing_utils import enable_full_determinism, floats_tensor, torch_device
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/autoencoders/test_models_autoencoder_mochi.py

@@ -16,12 +16,12 @@
 import unittest
 
 from diffusers import AutoencoderKLMochi
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     floats_tensor,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/autoencoders/test_models_autoencoder_oobleck.py

@@ -21,7 +21,8 @@ from datasets import load_dataset
 from parameterized import parameterized
 
 from diffusers import AutoencoderOobleck
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     backend_empty_cache,
     enable_full_determinism,
     floats_tensor,
@@ -29,7 +30,6 @@ from diffusers.utils.testing_utils import (
     torch_all_close,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/autoencoders/test_models_autoencoder_tiny.py

@@ -21,7 +21,8 @@ import torch
 from parameterized import parameterized
 
 from diffusers import AutoencoderTiny
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     backend_empty_cache,
     enable_full_determinism,
     floats_tensor,
@@ -30,7 +31,6 @@ from diffusers.utils.testing_utils import (
     torch_all_close,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/autoencoders/test_models_autoencoder_wan.py

@@ -18,8 +18,8 @@ import unittest
 import torch
 
 from diffusers import AutoencoderKLWan
-from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, torch_device
 
+from ...testing_utils import enable_full_determinism, floats_tensor, torch_device
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/autoencoders/test_models_consistency_decoder_vae.py

@@ -20,7 +20,9 @@ import numpy as np
 import torch
 
 from diffusers import ConsistencyDecoderVAE, StableDiffusionPipeline
-from diffusers.utils.testing_utils import (
+from diffusers.utils.torch_utils import randn_tensor
+
+from ...testing_utils import (
     backend_empty_cache,
     enable_full_determinism,
     load_image,
@@ -28,8 +30,6 @@ from diffusers.utils.testing_utils import (
     torch_all_close,
     torch_device,
 )
-from diffusers.utils.torch_utils import randn_tensor
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/autoencoders/test_models_vq.py

@@ -18,13 +18,13 @@ import unittest
 import torch
 
 from diffusers import VQModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     backend_manual_seed,
     enable_full_determinism,
     floats_tensor,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/test_attention_processor.py

@@ -7,7 +7,8 @@ import torch
 
 from diffusers import DiffusionPipeline
 from diffusers.models.attention_processor import Attention, AttnAddedKVProcessor
-from diffusers.utils.testing_utils import torch_device
+
+from ..testing_utils import torch_device
 
 
 class AttnAddedKVProcessorTests(unittest.TestCase):

tests/models/test_layers_utils.py

@@ -24,7 +24,8 @@ from diffusers.models.attention import GEGLU, AdaLayerNorm, ApproximateGELU
 from diffusers.models.embeddings import get_timestep_embedding
 from diffusers.models.resnet import Downsample2D, ResnetBlock2D, Upsample2D
 from diffusers.models.transformers.transformer_2d import Transformer2DModel
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     backend_manual_seed,
     require_torch_accelerator_with_fp64,
     require_torch_version_greater_equal,

tests/models/test_modeling_common.py

@@ -59,7 +59,10 @@ from diffusers.utils import (
     logging,
 )
 from diffusers.utils.hub_utils import _add_variant
-from diffusers.utils.testing_utils import (
+from diffusers.utils.torch_utils import get_torch_cuda_device_capability
+
+from ..others.test_utils import TOKEN, USER, is_staging_test
+from ..testing_utils import (
     CaptureLogger,
     _check_safetensors_serialization,
     backend_empty_cache,
@@ -82,9 +85,6 @@ from diffusers.utils.testing_utils import (
     torch_all_close,
     torch_device,
 )
-from diffusers.utils.torch_utils import get_torch_cuda_device_capability
-
-from ..others.test_utils import TOKEN, USER, is_staging_test
 
 
 if is_peft_available():

tests/models/transformers/test_models_dit_transformer2d.py

@@ -18,13 +18,13 @@ import unittest
 import torch
 
 from diffusers import DiTTransformer2DModel, Transformer2DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     floats_tensor,
     slow,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_pixart_transformer2d.py

@@ -18,13 +18,13 @@ import unittest
 import torch
 
 from diffusers import PixArtTransformer2DModel, Transformer2DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     floats_tensor,
     slow,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_prior.py

@@ -21,7 +21,8 @@ import torch
 from parameterized import parameterized
 
 from diffusers import PriorTransformer
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     backend_empty_cache,
     enable_full_determinism,
     floats_tensor,
@@ -29,7 +30,6 @@ from diffusers.utils.testing_utils import (
     torch_all_close,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_allegro.py

@@ -17,11 +17,11 @@ import unittest
 import torch
 
 from diffusers import AllegroTransformer3DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_aura_flow.py

@@ -18,8 +18,8 @@ import unittest
 import torch
 
 from diffusers import AuraFlowTransformer2DModel
-from diffusers.utils.testing_utils import enable_full_determinism, torch_device
 
+from ...testing_utils import enable_full_determinism, torch_device
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_bria.py

@@ -20,8 +20,8 @@ import torch
 from diffusers import BriaTransformer2DModel
 from diffusers.models.attention_processor import FluxIPAdapterJointAttnProcessor2_0
 from diffusers.models.embeddings import ImageProjection
-from diffusers.utils.testing_utils import enable_full_determinism, torch_device
 
+from ...testing_utils import enable_full_determinism, torch_device
 from ..test_modeling_common import LoraHotSwappingForModelTesterMixin, ModelTesterMixin, TorchCompileTesterMixin
 
 

tests/models/transformers/test_models_transformer_chroma.py

@@ -20,8 +20,8 @@ import torch
 from diffusers import ChromaTransformer2DModel
 from diffusers.models.attention_processor import FluxIPAdapterJointAttnProcessor2_0
 from diffusers.models.embeddings import ImageProjection
-from diffusers.utils.testing_utils import enable_full_determinism, torch_device
 
+from ...testing_utils import enable_full_determinism, torch_device
 from ..test_modeling_common import LoraHotSwappingForModelTesterMixin, ModelTesterMixin, TorchCompileTesterMixin
 
 

tests/models/transformers/test_models_transformer_cogvideox.py

@@ -18,11 +18,11 @@ import unittest
 import torch
 
 from diffusers import CogVideoXTransformer3DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_cogview3plus.py

@@ -18,11 +18,11 @@ import unittest
 import torch
 
 from diffusers import CogView3PlusTransformer2DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_cogview4.py

@@ -17,8 +17,8 @@ import unittest
 import torch
 
 from diffusers import CogView4Transformer2DModel
-from diffusers.utils.testing_utils import enable_full_determinism, torch_device
 
+from ...testing_utils import enable_full_determinism, torch_device
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_consisid.py

@@ -18,11 +18,11 @@ import unittest
 import torch
 
 from diffusers import ConsisIDTransformer3DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_cosmos.py

@@ -17,8 +17,8 @@ import unittest
 import torch
 
 from diffusers import CosmosTransformer3DModel
-from diffusers.utils.testing_utils import enable_full_determinism, torch_device
 
+from ...testing_utils import enable_full_determinism, torch_device
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_easyanimate.py

@@ -18,8 +18,8 @@ import unittest
 import torch
 
 from diffusers import EasyAnimateTransformer3DModel
-from diffusers.utils.testing_utils import enable_full_determinism, torch_device
 
+from ...testing_utils import enable_full_determinism, torch_device
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_flux.py

@@ -20,8 +20,8 @@ import torch
 from diffusers import FluxTransformer2DModel
 from diffusers.models.attention_processor import FluxIPAdapterJointAttnProcessor2_0
 from diffusers.models.embeddings import ImageProjection
-from diffusers.utils.testing_utils import enable_full_determinism, is_peft_available, torch_device
 
+from ...testing_utils import enable_full_determinism, is_peft_available, torch_device
 from ..test_modeling_common import LoraHotSwappingForModelTesterMixin, ModelTesterMixin, TorchCompileTesterMixin
 
 

tests/models/transformers/test_models_transformer_hidream.py

@@ -18,11 +18,11 @@ import unittest
 import torch
 
 from diffusers import HiDreamImageTransformer2DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_hunyuan_dit.py

@@ -18,11 +18,11 @@ import unittest
 import torch
 
 from diffusers import HunyuanDiT2DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_hunyuan_video.py

@@ -17,11 +17,11 @@ import unittest
 import torch
 
 from diffusers import HunyuanVideoTransformer3DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, TorchCompileTesterMixin
 
 

tests/models/transformers/test_models_transformer_hunyuan_video_framepack.py

@@ -17,11 +17,11 @@ import unittest
 import torch
 
 from diffusers import HunyuanVideoFramepackTransformer3DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_latte.py

@@ -18,11 +18,11 @@ import unittest
 import torch
 
 from diffusers import LatteTransformer3DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_ltx.py

@@ -18,8 +18,8 @@ import unittest
 import torch
 
 from diffusers import LTXVideoTransformer3DModel
-from diffusers.utils.testing_utils import enable_full_determinism, torch_device
 
+from ...testing_utils import enable_full_determinism, torch_device
 from ..test_modeling_common import ModelTesterMixin, TorchCompileTesterMixin
 
 

tests/models/transformers/test_models_transformer_lumina.py

@@ -18,11 +18,11 @@ import unittest
 import torch
 
 from diffusers import LuminaNextDiT2DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_lumina2.py

@@ -18,11 +18,11 @@ import unittest
 import torch
 
 from diffusers import Lumina2Transformer2DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_mochi.py

@@ -18,8 +18,8 @@ import unittest
 import torch
 
 from diffusers import MochiTransformer3DModel
-from diffusers.utils.testing_utils import enable_full_determinism, torch_device
 
+from ...testing_utils import enable_full_determinism, torch_device
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_omnigen.py

@@ -18,8 +18,8 @@ import unittest
 import torch
 
 from diffusers import OmniGenTransformer2DModel
-from diffusers.utils.testing_utils import enable_full_determinism, torch_device
 
+from ...testing_utils import enable_full_determinism, torch_device
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_qwenimage.py

@@ -19,8 +19,8 @@ import pytest
 import torch
 
 from diffusers import QwenImageTransformer2DModel
-from diffusers.utils.testing_utils import enable_full_determinism, torch_device
 
+from ...testing_utils import enable_full_determinism, torch_device
 from ..test_modeling_common import ModelTesterMixin, TorchCompileTesterMixin
 
 

tests/models/transformers/test_models_transformer_sana.py

@@ -17,11 +17,11 @@ import unittest
 import torch
 
 from diffusers import SanaTransformer2DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_sd3.py

@@ -19,11 +19,11 @@ import torch
 
 from diffusers import SD3Transformer2DModel
 from diffusers.utils.import_utils import is_xformers_available
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_skyreels_v2.py

@@ -17,11 +17,11 @@ import unittest
 import torch
 
 from diffusers import SkyReelsV2Transformer3DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, TorchCompileTesterMixin
 
 

tests/models/transformers/test_models_transformer_temporal.py

@@ -18,11 +18,11 @@ import unittest
 import torch
 
 from diffusers.models.transformers import TransformerTemporalModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin
 
 

tests/models/transformers/test_models_transformer_wan.py

@@ -17,11 +17,11 @@ import unittest
 import torch
 
 from diffusers import WanTransformer3DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, TorchCompileTesterMixin
 
 

tests/models/unets/test_models_unet_1d.py

@@ -19,13 +19,13 @@ import pytest
 import torch
 
 from diffusers import UNet1DModel
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     backend_manual_seed,
     floats_tensor,
     slow,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/unets/test_models_unet_2d.py

@@ -21,7 +21,8 @@ import torch
 
 from diffusers import UNet2DModel
 from diffusers.utils import logging
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     backend_empty_cache,
     enable_full_determinism,
     floats_tensor,
@@ -30,7 +31,6 @@ from diffusers.utils.testing_utils import (
     torch_all_close,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/unets/test_models_unet_2d_condition.py

@@ -34,7 +34,8 @@ from diffusers.models.attention_processor import (
 from diffusers.models.embeddings import ImageProjection, IPAdapterFaceIDImageProjection, IPAdapterPlusImageProjection
 from diffusers.utils import logging
 from diffusers.utils.import_utils import is_xformers_available
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     backend_empty_cache,
     backend_max_memory_allocated,
     backend_reset_max_memory_allocated,
@@ -51,7 +52,6 @@ from diffusers.utils.testing_utils import (
     torch_all_close,
     torch_device,
 )
-
 from ..test_modeling_common import (
     LoraHotSwappingForModelTesterMixin,
     ModelTesterMixin,

tests/models/unets/test_models_unet_3d_condition.py

@@ -21,8 +21,8 @@ import torch
 from diffusers.models import ModelMixin, UNet3DConditionModel
 from diffusers.utils import logging
 from diffusers.utils.import_utils import is_xformers_available
-from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, skip_mps, torch_device
 
+from ...testing_utils import enable_full_determinism, floats_tensor, skip_mps, torch_device
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/unets/test_models_unet_controlnetxs.py

@@ -21,8 +21,8 @@ from torch import nn
 
 from diffusers import ControlNetXSAdapter, UNet2DConditionModel, UNetControlNetXSModel
 from diffusers.utils import logging
-from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, is_flaky, torch_device
 
+from ...testing_utils import enable_full_determinism, floats_tensor, is_flaky, torch_device
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/unets/test_models_unet_motion.py

@@ -24,12 +24,12 @@ import torch
 from diffusers import MotionAdapter, UNet2DConditionModel, UNetMotionModel
 from diffusers.utils import logging
 from diffusers.utils.import_utils import is_xformers_available
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     floats_tensor,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/unets/test_models_unet_spatiotemporal.py

@@ -21,13 +21,13 @@ import torch
 from diffusers import UNetSpatioTemporalConditionModel
 from diffusers.utils import logging
 from diffusers.utils.import_utils import is_xformers_available
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     enable_full_determinism,
     floats_tensor,
     skip_mps,
     torch_device,
 )
-
 from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
 
 

tests/models/unets/test_unet_2d_blocks.py

@@ -15,8 +15,8 @@
 import unittest
 
 from diffusers.models.unets.unet_2d_blocks import *  # noqa F403
-from diffusers.utils.testing_utils import torch_device
 
+from ...testing_utils import torch_device
 from .test_unet_blocks_common import UNetBlockTesterMixin
 
 

tests/models/unets/test_unet_blocks_common.py

@@ -16,14 +16,15 @@ from typing import Tuple
 
 import torch
 
-from diffusers.utils.testing_utils import (
+from diffusers.utils.torch_utils import randn_tensor
+
+from ...testing_utils import (
     floats_tensor,
     require_torch,
     require_torch_accelerator_with_training,
     torch_all_close,
     torch_device,
 )
-from diffusers.utils.torch_utils import randn_tensor
 
 
 @require_torch

tests/modular_pipelines/stable_diffusion_xl/test_modular_pipeline_stable_diffusion_xl.py

@@ -27,15 +27,15 @@ from diffusers import (
     StableDiffusionXLModularPipeline,
 )
 from diffusers.loaders import ModularIPAdapterMixin
-from diffusers.utils.testing_utils import (
-    enable_full_determinism,
-    floats_tensor,
-    torch_device,
-)
 
 from ...models.unets.test_models_unet_2d_condition import (
     create_ip_adapter_state_dict,
 )
+from ...testing_utils import (
+    enable_full_determinism,
+    floats_tensor,
+    torch_device,
+)
 from ..test_modular_pipelines_common import (
     ModularPipelineTesterMixin,
 )

tests/modular_pipelines/test_modular_pipelines_common.py

@@ -9,7 +9,8 @@ import torch
 import diffusers
 from diffusers import ComponentsManager, ModularPipeline, ModularPipelineBlocks
 from diffusers.utils import logging
-from diffusers.utils.testing_utils import (
+
+from ..testing_utils import (
     backend_empty_cache,
     numpy_cosine_similarity_distance,
     require_accelerator,

tests/others/test_config.py

@@ -28,7 +28,8 @@ from diffusers import (
     logging,
 )
 from diffusers.configuration_utils import ConfigMixin, register_to_config
-from diffusers.utils.testing_utils import CaptureLogger
+
+from ..testing_utils import CaptureLogger
 
 
 class SampleObject(ConfigMixin):

tests/others/test_ema.py

@@ -20,7 +20,8 @@ import torch
 
 from diffusers import UNet2DConditionModel
 from diffusers.training_utils import EMAModel
-from diffusers.utils.testing_utils import enable_full_determinism, skip_mps, torch_device
+
+from ..testing_utils import enable_full_determinism, skip_mps, torch_device
 
 
 enable_full_determinism()

tests/others/test_outputs.py

@@ -7,7 +7,8 @@ import numpy as np
 import PIL.Image
 
 from diffusers.utils.outputs import BaseOutput
-from diffusers.utils.testing_utils import require_torch
+
+from ..testing_utils import require_torch
 
 
 @dataclass

tests/others/test_training.py

@@ -19,7 +19,8 @@ import torch
 
 from diffusers import DDIMScheduler, DDPMScheduler, UNet2DModel
 from diffusers.training_utils import set_seed
-from diffusers.utils.testing_utils import slow
+
+from ..testing_utils import slow
 
 
 torch.backends.cuda.matmul.allow_tf32 = False

tests/others/test_utils.py

@@ -20,7 +20,8 @@ import pytest
 
 from diffusers import __version__
 from diffusers.utils import deprecate
-from diffusers.utils.testing_utils import Expectations, str_to_bool
+
+from ..testing_utils import Expectations, str_to_bool
 
 
 # Used to test the hub

tests/pipelines/allegro/test_allegro.py

@@ -23,7 +23,8 @@ import torch
 from transformers import AutoTokenizer, T5Config, T5EncoderModel
 
 from diffusers import AllegroPipeline, AllegroTransformer3DModel, AutoencoderKLAllegro, DDIMScheduler
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     backend_empty_cache,
     enable_full_determinism,
     numpy_cosine_similarity_distance,
@@ -33,7 +34,6 @@ from diffusers.utils.testing_utils import (
     slow,
     torch_device,
 )
-
 from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
 from ..test_pipelines_common import PipelineTesterMixin, PyramidAttentionBroadcastTesterMixin, to_np
 

tests/pipelines/animatediff/test_animatediff.py

@@ -19,7 +19,8 @@ from diffusers import (
 )
 from diffusers.models.attention import FreeNoiseTransformerBlock
 from diffusers.utils import is_xformers_available, logging
-from diffusers.utils.testing_utils import (
+
+from ...testing_utils import (
     backend_empty_cache,
     numpy_cosine_similarity_distance,
     require_accelerator,
@@ -27,7 +28,6 @@ from diffusers.utils.testing_utils import (
     slow,
     torch_device,
 )
-
 from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_PARAMS
 from ..test_pipelines_common import (
     IPAdapterTesterMixin,

tests/pipelines/animatediff/test_animatediff_controlnet.py

@@ -21,8 +21,8 @@ from diffusers import (
 from diffusers.models.attention import FreeNoiseTransformerBlock
 from diffusers.utils import logging
 from diffusers.utils.import_utils import is_xformers_available
-from diffusers.utils.testing_utils import require_accelerator, torch_device
 
+from ...testing_utils import require_accelerator, torch_device
 from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_PARAMS
 from ..test_pipelines_common import (
     IPAdapterTesterMixin,

tests/pipelines/animatediff/test_animatediff_sdxl.py

@@ -14,8 +14,8 @@ from diffusers import (
     UNetMotionModel,
 )
 from diffusers.utils import is_xformers_available, logging
-from diffusers.utils.testing_utils import require_accelerator, torch_device
 
+from ...testing_utils import require_accelerator, torch_device
 from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_CALLBACK_CFG_PARAMS, TEXT_TO_IMAGE_PARAMS
 from ..test_pipelines_common import (
     IPAdapterTesterMixin,

tests/pipelines/animatediff/test_animatediff_sparsectrl.py

@@ -20,8 +20,8 @@ from diffusers import (
 )
 from diffusers.utils import logging
 from diffusers.utils.import_utils import is_xformers_available
-from diffusers.utils.testing_utils import require_accelerator, torch_device
 
+from ...testing_utils import require_accelerator, torch_device
 from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_PARAMS
 from ..test_pipelines_common import (
     IPAdapterTesterMixin,

tests/pipelines/animatediff/test_animatediff_video2video.py

@@ -19,8 +19,8 @@ from diffusers import (
 )
 from diffusers.models.attention import FreeNoiseTransformerBlock
 from diffusers.utils import is_xformers_available, logging
-from diffusers.utils.testing_utils import require_accelerator, torch_device
 
+from ...testing_utils import require_accelerator, torch_device
 from ..pipeline_params import TEXT_TO_IMAGE_PARAMS, VIDEO_TO_VIDEO_BATCH_PARAMS
 from ..test_pipelines_common import IPAdapterTesterMixin, PipelineFromPipeTesterMixin, PipelineTesterMixin