post release 0.33.0 (#11255)

* post release

* update

* fix deprecations

* remaining

* update

---------
Co-authored-by: YiYi Xu <yixu310@gmail.com>

examples/text_to_image/train_text_to_image_lora_sdxl.py

@@ -68,7 +68,7 @@ if is_wandb_available():
     import wandb
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.33.0.dev0")
+check_min_version("0.34.0.dev0")
 
 logger = get_logger(__name__)
 if is_torch_npu_available():

examples/text_to_image/train_text_to_image_sdxl.py

@@ -55,7 +55,7 @@ from diffusers.utils.torch_utils import is_compiled_module
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.33.0.dev0")
+check_min_version("0.34.0.dev0")
 
 logger = get_logger(__name__)
 if is_torch_npu_available():

examples/textual_inversion/textual_inversion.py

@@ -81,7 +81,7 @@ else:
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.33.0.dev0")
+check_min_version("0.34.0.dev0")
 
 logger = get_logger(__name__)
 

examples/textual_inversion/textual_inversion_flax.py

@@ -56,7 +56,7 @@ else:
 # ------------------------------------------------------------------------------
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.33.0.dev0")
+check_min_version("0.34.0.dev0")
 
 logger = logging.getLogger(__name__)
 

examples/textual_inversion/textual_inversion_sdxl.py

@@ -76,7 +76,7 @@ else:
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.33.0.dev0")
+check_min_version("0.34.0.dev0")
 
 logger = get_logger(__name__)
 

examples/unconditional_image_generation/train_unconditional.py

@@ -29,7 +29,7 @@ from diffusers.utils.import_utils import is_xformers_available
 
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.33.0.dev0")
+check_min_version("0.34.0.dev0")
 
 logger = get_logger(__name__, log_level="INFO")
 

examples/vqgan/train_vqgan.py

@@ -50,7 +50,7 @@ if is_wandb_available():
     import wandb
 
 # Will error if the minimal version of diffusers is not installed. Remove at your own risks.
-check_min_version("0.33.0.dev0")
+check_min_version("0.34.0.dev0")
 
 logger = get_logger(__name__, log_level="INFO")
 

setup.py

@@ -269,7 +269,7 @@ version_range_max = max(sys.version_info[1], 10) + 1
 
 setup(
     name="diffusers",
-    version="0.33.0.dev0",  # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
+    version="0.34.0.dev0",  # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
     description="State-of-the-art diffusion in PyTorch and JAX.",
     long_description=open("README.md", "r", encoding="utf-8").read(),
     long_description_content_type="text/markdown",

src/diffusers/__init__.py

-__version__ = "0.33.0.dev0"
+__version__ = "0.34.0.dev0"
 
 from typing import TYPE_CHECKING
 

tests/lora/test_lora_layers_lumina2.py

@@ -23,7 +23,7 @@ from transformers import AutoTokenizer, GemmaForCausalLM
 from diffusers import (
     AutoencoderKL,
     FlowMatchEulerDiscreteScheduler,
-    Lumina2Text2ImgPipeline,
+    Lumina2Pipeline,
     Lumina2Transformer2DModel,
 )
 from diffusers.utils.testing_utils import floats_tensor, is_torch_version, require_peft_backend, skip_mps, torch_device
@@ -36,7 +36,7 @@ from utils import PeftLoraLoaderMixinTests, check_if_lora_correctly_set  # noqa:
 
 @require_peft_backend
 class Lumina2LoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
-    pipeline_class = Lumina2Text2ImgPipeline
+    pipeline_class = Lumina2Pipeline
     scheduler_cls = FlowMatchEulerDiscreteScheduler
     scheduler_classes = [FlowMatchEulerDiscreteScheduler]
     scheduler_kwargs = {}

tests/pipelines/lumina/test_lumina_nextdit.py

@@ -10,7 +10,6 @@ from diffusers import (
     FlowMatchEulerDiscreteScheduler,
     LuminaNextDiT2DModel,
     LuminaPipeline,
-    LuminaText2ImgPipeline,
 )
 from diffusers.utils.testing_utils import (
     backend_empty_cache,
@@ -105,12 +104,6 @@ class LuminaPipelineFastTests(unittest.TestCase, PipelineTesterMixin):
     def test_xformers_attention_forwardGenerator_pass(self):
         pass
 
-    def test_deprecation_raises_warning(self):
-        with self.assertWarns(FutureWarning) as warning:
-            _ = LuminaText2ImgPipeline(**self.get_dummy_components()).to(torch_device)
-        warning_message = str(warning.warnings[0].message)
-        assert "renamed to `LuminaPipeline`" in warning_message
-
 
 @slow
 @require_torch_accelerator

tests/pipelines/lumina2/test_pipeline_lumina2.py

@@ -7,10 +7,8 @@ from diffusers import (
     AutoencoderKL,
     FlowMatchEulerDiscreteScheduler,
     Lumina2Pipeline,
-    Lumina2Text2ImgPipeline,
     Lumina2Transformer2DModel,
 )
-from diffusers.utils.testing_utils import torch_device
 
 from ..test_pipelines_common import PipelineTesterMixin
 
@@ -117,9 +115,3 @@ class Lumina2PipelineFastTests(unittest.TestCase, PipelineTesterMixin):
             "output_type": "np",
         }
         return inputs
-
-    def test_deprecation_raises_warning(self):
-        with self.assertWarns(FutureWarning) as warning:
-            _ = Lumina2Text2ImgPipeline(**self.get_dummy_components()).to(torch_device)
-        warning_message = str(warning.warnings[0].message)
-        assert "renamed to `Lumina2Pipeline`" in warning_message