From 3dcb97c9ea0354ff0d91e238b2cabf99eb86a432 Mon Sep 17 00:00:00 2001 From: sayakpaul Date: Mon, 19 Jan 2026 13:43:47 +0530 Subject: [PATCH] tie embedding issue. --- .../controlnet_flux/test_controlnet_flux.py | 5 +++-- .../test_controlnet_flux_img2img.py | 9 ++++----- .../test_controlnet_flux_inpaint.py | 19 ++++--------------- .../test_controlnet_inpaint_sd3.py | 17 +++++++++++------ .../controlnet_sd3/test_controlnet_sd3.py | 12 ++++++++++-- tests/pipelines/flux/test_pipeline_flux.py | 5 +++-- .../flux/test_pipeline_flux_control.py | 5 +++-- .../test_pipeline_flux_control_img2img.py | 5 +++-- .../test_pipeline_flux_control_inpaint.py | 5 +++-- .../pipelines/flux/test_pipeline_flux_fill.py | 5 +++-- .../flux/test_pipeline_flux_img2img.py | 5 +++-- .../flux/test_pipeline_flux_inpaint.py | 5 +++-- .../flux/test_pipeline_flux_kontext.py | 5 +++-- .../test_pipeline_flux_kontext_inpaint.py | 5 +++-- .../test_pipeline_stable_diffusion_3.py | 13 +++++++++++-- ...est_pipeline_stable_diffusion_3_img2img.py | 13 +++++++++++-- ...est_pipeline_stable_diffusion_3_inpaint.py | 13 +++++++++++-- 17 files changed, 92 insertions(+), 54 deletions(-) diff --git a/tests/pipelines/controlnet_flux/test_controlnet_flux.py b/tests/pipelines/controlnet_flux/test_controlnet_flux.py index 0895d9de35..8607cd6944 100644 --- a/tests/pipelines/controlnet_flux/test_controlnet_flux.py +++ b/tests/pipelines/controlnet_flux/test_controlnet_flux.py @@ -19,7 +19,7 @@ import unittest import numpy as np import torch from huggingface_hub import hf_hub_download -from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5TokenizerFast +from transformers import AutoConfig, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5TokenizerFast from diffusers import ( AutoencoderKL, @@ -97,7 +97,8 @@ class FluxControlNetPipelineFastTests(unittest.TestCase, PipelineTesterMixin, Fl text_encoder = CLIPTextModel(clip_text_encoder_config) torch.manual_seed(0) - text_encoder_2 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_2 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = T5TokenizerFast.from_pretrained("hf-internal-testing/tiny-random-t5") diff --git a/tests/pipelines/controlnet_flux/test_controlnet_flux_img2img.py b/tests/pipelines/controlnet_flux/test_controlnet_flux_img2img.py index 3d8378a578..a4749188df 100644 --- a/tests/pipelines/controlnet_flux/test_controlnet_flux_img2img.py +++ b/tests/pipelines/controlnet_flux/test_controlnet_flux_img2img.py @@ -2,7 +2,7 @@ import unittest import numpy as np import torch -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel +from transformers import AutoConfig, AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel from diffusers import ( AutoencoderKL, @@ -13,9 +13,7 @@ from diffusers import ( ) from diffusers.utils.torch_utils import randn_tensor -from ...testing_utils import ( - torch_device, -) +from ...testing_utils import torch_device from ..test_pipelines_common import PipelineTesterMixin, check_qkv_fused_layers_exist @@ -70,7 +68,8 @@ class FluxControlNetImg2ImgPipelineFastTests(unittest.TestCase, PipelineTesterMi text_encoder = CLIPTextModel(clip_text_encoder_config) torch.manual_seed(0) - text_encoder_2 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_2 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5") diff --git a/tests/pipelines/controlnet_flux/test_controlnet_flux_inpaint.py b/tests/pipelines/controlnet_flux/test_controlnet_flux_inpaint.py index 3ba475deb8..6eb560d908 100644 --- a/tests/pipelines/controlnet_flux/test_controlnet_flux_inpaint.py +++ b/tests/pipelines/controlnet_flux/test_controlnet_flux_inpaint.py @@ -3,15 +3,7 @@ import unittest import numpy as np import torch - -# torch_device, # {{ edit_1 }} Removed unused import -from transformers import ( - AutoTokenizer, - CLIPTextConfig, - CLIPTextModel, - CLIPTokenizer, - T5EncoderModel, -) +from transformers import AutoConfig, AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel from diffusers import ( AutoencoderKL, @@ -22,11 +14,7 @@ from diffusers import ( ) from diffusers.utils.torch_utils import randn_tensor -from ...testing_utils import ( - enable_full_determinism, - floats_tensor, - torch_device, -) +from ...testing_utils import enable_full_determinism, floats_tensor, torch_device from ..test_pipelines_common import PipelineTesterMixin @@ -85,7 +73,8 @@ class FluxControlNetInpaintPipelineTests(unittest.TestCase, PipelineTesterMixin) text_encoder = CLIPTextModel(clip_text_encoder_config) torch.manual_seed(0) - text_encoder_2 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_2 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5") diff --git a/tests/pipelines/controlnet_sd3/test_controlnet_inpaint_sd3.py b/tests/pipelines/controlnet_sd3/test_controlnet_inpaint_sd3.py index 34c34b7a2c..072f9aa405 100644 --- a/tests/pipelines/controlnet_sd3/test_controlnet_inpaint_sd3.py +++ b/tests/pipelines/controlnet_sd3/test_controlnet_inpaint_sd3.py @@ -17,7 +17,14 @@ import unittest import numpy as np import torch -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel +from transformers import ( + AutoConfig, + AutoTokenizer, + CLIPTextConfig, + CLIPTextModelWithProjection, + CLIPTokenizer, + T5EncoderModel, +) from diffusers import ( AutoencoderKL, @@ -28,10 +35,7 @@ from diffusers import ( from diffusers.models import SD3ControlNetModel from diffusers.utils.torch_utils import randn_tensor -from ...testing_utils import ( - enable_full_determinism, - torch_device, -) +from ...testing_utils import enable_full_determinism, torch_device from ..test_pipelines_common import PipelineTesterMixin @@ -103,7 +107,8 @@ class StableDiffusion3ControlInpaintNetPipelineFastTests(unittest.TestCase, Pipe text_encoder_2 = CLIPTextModelWithProjection(clip_text_encoder_config) torch.manual_seed(0) - text_encoder_3 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_3 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") diff --git a/tests/pipelines/controlnet_sd3/test_controlnet_sd3.py b/tests/pipelines/controlnet_sd3/test_controlnet_sd3.py index 2b6cf8d1e8..82ab4308f3 100644 --- a/tests/pipelines/controlnet_sd3/test_controlnet_sd3.py +++ b/tests/pipelines/controlnet_sd3/test_controlnet_sd3.py @@ -19,7 +19,14 @@ from typing import Optional import numpy as np import torch -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel +from transformers import ( + AutoConfig, + AutoTokenizer, + CLIPTextConfig, + CLIPTextModelWithProjection, + CLIPTokenizer, + T5EncoderModel, +) from diffusers import ( AutoencoderKL, @@ -118,7 +125,8 @@ class StableDiffusion3ControlNetPipelineFastTests(unittest.TestCase, PipelineTes text_encoder_2 = CLIPTextModelWithProjection(clip_text_encoder_config) torch.manual_seed(0) - text_encoder_3 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_3 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") diff --git a/tests/pipelines/flux/test_pipeline_flux.py b/tests/pipelines/flux/test_pipeline_flux.py index 74499bfa60..281ac5ad3b 100644 --- a/tests/pipelines/flux/test_pipeline_flux.py +++ b/tests/pipelines/flux/test_pipeline_flux.py @@ -4,7 +4,7 @@ import unittest import numpy as np import torch from huggingface_hub import hf_hub_download -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel +from transformers import AutoConfig, AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel from diffusers import ( AutoencoderKL, @@ -91,7 +91,8 @@ class FluxPipelineFastTests( text_encoder = CLIPTextModel(clip_text_encoder_config) torch.manual_seed(0) - text_encoder_2 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_2 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5") diff --git a/tests/pipelines/flux/test_pipeline_flux_control.py b/tests/pipelines/flux/test_pipeline_flux_control.py index 7e966470a3..44efca9b9f 100644 --- a/tests/pipelines/flux/test_pipeline_flux_control.py +++ b/tests/pipelines/flux/test_pipeline_flux_control.py @@ -3,7 +3,7 @@ import unittest import numpy as np import torch from PIL import Image -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel +from transformers import AutoConfig, AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel from diffusers import AutoencoderKL, FlowMatchEulerDiscreteScheduler, FluxControlPipeline, FluxTransformer2DModel @@ -53,7 +53,8 @@ class FluxControlPipelineFastTests(unittest.TestCase, PipelineTesterMixin): text_encoder = CLIPTextModel(clip_text_encoder_config) torch.manual_seed(0) - text_encoder_2 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_2 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5") diff --git a/tests/pipelines/flux/test_pipeline_flux_control_img2img.py b/tests/pipelines/flux/test_pipeline_flux_control_img2img.py index e56136f2e9..0f0bc09341 100644 --- a/tests/pipelines/flux/test_pipeline_flux_control_img2img.py +++ b/tests/pipelines/flux/test_pipeline_flux_control_img2img.py @@ -3,7 +3,7 @@ import unittest import numpy as np import torch from PIL import Image -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel +from transformers import AutoConfig, AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel from diffusers import ( AutoencoderKL, @@ -57,7 +57,8 @@ class FluxControlImg2ImgPipelineFastTests(unittest.TestCase, PipelineTesterMixin text_encoder = CLIPTextModel(clip_text_encoder_config) torch.manual_seed(0) - text_encoder_2 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_2 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5") diff --git a/tests/pipelines/flux/test_pipeline_flux_control_inpaint.py b/tests/pipelines/flux/test_pipeline_flux_control_inpaint.py index e42c5fc2aa..ae2b6b829e 100644 --- a/tests/pipelines/flux/test_pipeline_flux_control_inpaint.py +++ b/tests/pipelines/flux/test_pipeline_flux_control_inpaint.py @@ -3,7 +3,7 @@ import unittest import numpy as np import torch from PIL import Image -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel +from transformers import AutoConfig, AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel from diffusers import ( AutoencoderKL, @@ -58,7 +58,8 @@ class FluxControlInpaintPipelineFastTests(unittest.TestCase, PipelineTesterMixin text_encoder = CLIPTextModel(clip_text_encoder_config) torch.manual_seed(0) - text_encoder_2 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_2 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5") diff --git a/tests/pipelines/flux/test_pipeline_flux_fill.py b/tests/pipelines/flux/test_pipeline_flux_fill.py index 25a4a33548..42cd1efad4 100644 --- a/tests/pipelines/flux/test_pipeline_flux_fill.py +++ b/tests/pipelines/flux/test_pipeline_flux_fill.py @@ -3,7 +3,7 @@ import unittest import numpy as np import torch -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel +from transformers import AutoConfig, AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel from diffusers import AutoencoderKL, FlowMatchEulerDiscreteScheduler, FluxFillPipeline, FluxTransformer2DModel @@ -58,7 +58,8 @@ class FluxFillPipelineFastTests(unittest.TestCase, PipelineTesterMixin): text_encoder = CLIPTextModel(clip_text_encoder_config) torch.manual_seed(0) - text_encoder_2 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_2 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5") diff --git a/tests/pipelines/flux/test_pipeline_flux_img2img.py b/tests/pipelines/flux/test_pipeline_flux_img2img.py index 6f435760ae..00587905d3 100644 --- a/tests/pipelines/flux/test_pipeline_flux_img2img.py +++ b/tests/pipelines/flux/test_pipeline_flux_img2img.py @@ -3,7 +3,7 @@ import unittest import numpy as np import torch -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel +from transformers import AutoConfig, AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel from diffusers import AutoencoderKL, FlowMatchEulerDiscreteScheduler, FluxImg2ImgPipeline, FluxTransformer2DModel @@ -55,7 +55,8 @@ class FluxImg2ImgPipelineFastTests(unittest.TestCase, PipelineTesterMixin, FluxI text_encoder = CLIPTextModel(clip_text_encoder_config) torch.manual_seed(0) - text_encoder_2 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_2 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5") diff --git a/tests/pipelines/flux/test_pipeline_flux_inpaint.py b/tests/pipelines/flux/test_pipeline_flux_inpaint.py index 6324ff236e..14edb9e441 100644 --- a/tests/pipelines/flux/test_pipeline_flux_inpaint.py +++ b/tests/pipelines/flux/test_pipeline_flux_inpaint.py @@ -3,7 +3,7 @@ import unittest import numpy as np import torch -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel +from transformers import AutoConfig, AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel from diffusers import AutoencoderKL, FlowMatchEulerDiscreteScheduler, FluxInpaintPipeline, FluxTransformer2DModel @@ -55,7 +55,8 @@ class FluxInpaintPipelineFastTests(unittest.TestCase, PipelineTesterMixin, FluxI text_encoder = CLIPTextModel(clip_text_encoder_config) torch.manual_seed(0) - text_encoder_2 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_2 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5") diff --git a/tests/pipelines/flux/test_pipeline_flux_kontext.py b/tests/pipelines/flux/test_pipeline_flux_kontext.py index 5c78964ea5..1c018f14b5 100644 --- a/tests/pipelines/flux/test_pipeline_flux_kontext.py +++ b/tests/pipelines/flux/test_pipeline_flux_kontext.py @@ -3,7 +3,7 @@ import unittest import numpy as np import PIL.Image import torch -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel +from transformers import AutoConfig, AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel from diffusers import ( AutoencoderKL, @@ -79,7 +79,8 @@ class FluxKontextPipelineFastTests( text_encoder = CLIPTextModel(clip_text_encoder_config) torch.manual_seed(0) - text_encoder_2 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_2 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5") diff --git a/tests/pipelines/flux/test_pipeline_flux_kontext_inpaint.py b/tests/pipelines/flux/test_pipeline_flux_kontext_inpaint.py index 9a2e32056d..b5f8570ebd 100644 --- a/tests/pipelines/flux/test_pipeline_flux_kontext_inpaint.py +++ b/tests/pipelines/flux/test_pipeline_flux_kontext_inpaint.py @@ -3,7 +3,7 @@ import unittest import numpy as np import torch -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel +from transformers import AutoConfig, AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel from diffusers import ( AutoencoderKL, @@ -79,7 +79,8 @@ class FluxKontextInpaintPipelineFastTests( text_encoder = CLIPTextModel(clip_text_encoder_config) torch.manual_seed(0) - text_encoder_2 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_2 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5") diff --git a/tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3.py b/tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3.py index 3ccefe3de3..200c832d09 100644 --- a/tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3.py +++ b/tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3.py @@ -3,7 +3,14 @@ import unittest import numpy as np import torch -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel +from transformers import ( + AutoConfig, + AutoTokenizer, + CLIPTextConfig, + CLIPTextModelWithProjection, + CLIPTokenizer, + T5EncoderModel, +) from diffusers import AutoencoderKL, FlowMatchEulerDiscreteScheduler, SD3Transformer2DModel, StableDiffusion3Pipeline @@ -72,7 +79,9 @@ class StableDiffusion3PipelineFastTests(unittest.TestCase, PipelineTesterMixin): torch.manual_seed(0) text_encoder_2 = CLIPTextModelWithProjection(clip_text_encoder_config) - text_encoder_3 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + torch.manual_seed(0) + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_3 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") diff --git a/tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3_img2img.py b/tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3_img2img.py index 9025b1060c..3f46b341a0 100644 --- a/tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3_img2img.py +++ b/tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3_img2img.py @@ -4,7 +4,14 @@ import unittest import numpy as np import torch -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel +from transformers import ( + AutoConfig, + AutoTokenizer, + CLIPTextConfig, + CLIPTextModelWithProjection, + CLIPTokenizer, + T5EncoderModel, +) from diffusers import ( AutoencoderKL, @@ -73,7 +80,9 @@ class StableDiffusion3Img2ImgPipelineFastTests(PipelineLatentTesterMixin, unitte torch.manual_seed(0) text_encoder_2 = CLIPTextModelWithProjection(clip_text_encoder_config) - text_encoder_3 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + torch.manual_seed(0) + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_3 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") diff --git a/tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3_inpaint.py b/tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3_inpaint.py index 6289303402..a90ca21a80 100644 --- a/tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3_inpaint.py +++ b/tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3_inpaint.py @@ -3,7 +3,14 @@ import unittest import numpy as np import torch -from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel +from transformers import ( + AutoConfig, + AutoTokenizer, + CLIPTextConfig, + CLIPTextModelWithProjection, + CLIPTokenizer, + T5EncoderModel, +) from diffusers import ( AutoencoderKL, @@ -73,7 +80,9 @@ class StableDiffusion3InpaintPipelineFastTests(PipelineLatentTesterMixin, unitte torch.manual_seed(0) text_encoder_2 = CLIPTextModelWithProjection(clip_text_encoder_config) - text_encoder_3 = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5") + torch.manual_seed(0) + config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5") + text_encoder_3 = T5EncoderModel(config) tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip") tokenizer_2 = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip")