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13 | 13 | # limitations under the License.
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14 | 14 |
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15 | 15 | import inspect
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16 |
| -from typing import Any, Callable, Dict, List, Optional, Union, Tuple |
| 16 | +from typing import Any, Callable, Dict, List, Optional, Union |
| 17 | + |
17 | 18 | import numpy as np
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18 | 19 | import torch
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19 | 20 | from transformers import (
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| 21 | + CLIPImageProcessor, |
20 | 22 | CLIPTextModel,
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21 | 23 | CLIPTokenizer,
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| 24 | + CLIPVisionModelWithProjection, |
22 | 25 | T5EncoderModel,
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23 | 26 | T5TokenizerFast,
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24 |
| - CLIPVisionModelWithProjection, |
25 |
| - CLIPImageProcessor |
26 | 27 | )
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27 |
| -from diffusers.pipelines.flux.pipeline_output import FluxPipelineOutput |
28 |
| -from diffusers.image_processor import VaeImageProcessor, PipelineImageInput |
29 |
| -from diffusers.loaders import FluxLoraLoaderMixin, TextualInversionLoaderMixin, FromSingleFileMixin, FluxIPAdapterMixin |
| 28 | + |
| 29 | +from diffusers.image_processor import PipelineImageInput, VaeImageProcessor |
| 30 | +from diffusers.loaders import FluxIPAdapterMixin, FluxLoraLoaderMixin, FromSingleFileMixin, TextualInversionLoaderMixin |
30 | 31 | from diffusers.models.autoencoders import AutoencoderKL
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31 | 32 | from diffusers.models.transformers import FluxTransformer2DModel
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| 33 | +from diffusers.pipelines.flux.pipeline_output import FluxPipelineOutput |
| 34 | +from diffusers.pipelines.pipeline_utils import DiffusionPipeline |
32 | 35 | from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
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33 | 36 | from diffusers.utils import (
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34 | 37 | USE_PEFT_BACKEND,
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39 | 42 | unscale_lora_layers,
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40 | 43 | )
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41 | 44 | from diffusers.utils.torch_utils import randn_tensor
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42 |
| -from diffusers.pipelines.pipeline_utils import DiffusionPipeline |
| 45 | + |
43 | 46 |
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44 | 47 | if is_torch_xla_available():
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45 | 48 | import torch_xla.core.xla_model as xm
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57 | 60 | >>> from diffusers import DiffusionPipeline
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58 | 61 |
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59 | 62 | >>> pipe = DiffusionPipeline.from_pretrained(
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60 |
| - >>> "black-forest-labs/FLUX.1-dev", |
| 63 | + >>> "black-forest-labs/FLUX.1-dev", |
61 | 64 | >>> custom_pipeline="pipeline_flux_semantic_guidance",
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62 | 65 | >>> torch_dtype=torch.bfloat16
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63 | 66 | >>> )
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