add tests

tests/pipelines/flux/test_pipeline_flux.py

@@ -29,6 +29,7 @@ from ..test_pipelines_common import (
     FluxIPAdapterTesterMixin,
     PipelineTesterMixin,
     PyramidAttentionBroadcastTesterMixin,
+    TaylorSeerCacheTesterMixin,
     check_qkv_fused_layers_exist,
 )
 
@@ -39,6 +40,7 @@ class FluxPipelineFastTests(
     PyramidAttentionBroadcastTesterMixin,
     FasterCacheTesterMixin,
     FirstBlockCacheTesterMixin,
+    TaylorSeerCacheTesterMixin,
     unittest.TestCase,
 ):
     pipeline_class = FluxPipeline

tests/pipelines/flux/test_pipeline_flux_kontext.py

@@ -19,6 +19,7 @@ from ..test_pipelines_common import (
     FluxIPAdapterTesterMixin,
     PipelineTesterMixin,
     PyramidAttentionBroadcastTesterMixin,
+    TaylorSeerCacheTesterMixin,
 )
 
 
@@ -28,6 +29,7 @@ class FluxKontextPipelineFastTests(
     FluxIPAdapterTesterMixin,
     PyramidAttentionBroadcastTesterMixin,
     FasterCacheTesterMixin,
+    TaylorSeerCacheTesterMixin,
 ):
     pipeline_class = FluxKontextPipeline
     params = frozenset(

tests/pipelines/flux/test_pipeline_flux_kontext_inpaint.py

@@ -19,6 +19,7 @@ from ..test_pipelines_common import (
     FluxIPAdapterTesterMixin,
     PipelineTesterMixin,
     PyramidAttentionBroadcastTesterMixin,
+    TaylorSeerCacheTesterMixin,
 )
 
 
@@ -28,6 +29,7 @@ class FluxKontextInpaintPipelineFastTests(
     FluxIPAdapterTesterMixin,
     PyramidAttentionBroadcastTesterMixin,
     FasterCacheTesterMixin,
+    TaylorSeerCacheTesterMixin,
 ):
     pipeline_class = FluxKontextInpaintPipeline
     params = frozenset(

tests/pipelines/flux2/test_pipeline_flux2.py

@@ -16,11 +16,12 @@ from ...testing_utils import (
 )
 from ..test_pipelines_common import (
     PipelineTesterMixin,
+    TaylorSeerCacheTesterMixin,
     check_qkv_fused_layers_exist,
 )
 
 
-class Flux2PipelineFastTests(PipelineTesterMixin, unittest.TestCase):
+class Flux2PipelineFastTests(PipelineTesterMixin, TaylorSeerCacheTesterMixin, unittest.TestCase):
     pipeline_class = Flux2Pipeline
     params = frozenset(["prompt", "height", "width", "guidance_scale", "prompt_embeds"])
     batch_params = frozenset(["prompt"])

tests/pipelines/hunyuan_video/test_hunyuan_video.py

@@ -33,6 +33,7 @@ from ..test_pipelines_common import (
     FirstBlockCacheTesterMixin,
     PipelineTesterMixin,
     PyramidAttentionBroadcastTesterMixin,
+    TaylorSeerCacheTesterMixin,
     to_np,
 )
 
@@ -45,6 +46,7 @@ class HunyuanVideoPipelineFastTests(
     PyramidAttentionBroadcastTesterMixin,
     FasterCacheTesterMixin,
     FirstBlockCacheTesterMixin,
+    TaylorSeerCacheTesterMixin,
     unittest.TestCase,
 ):
     pipeline_class = HunyuanVideoPipeline

tests/pipelines/test_pipelines_common.py

@@ -36,6 +36,7 @@ from diffusers.hooks import apply_group_offloading
 from diffusers.hooks.faster_cache import FasterCacheBlockHook, FasterCacheDenoiserHook
 from diffusers.hooks.first_block_cache import FirstBlockCacheConfig
 from diffusers.hooks.pyramid_attention_broadcast import PyramidAttentionBroadcastHook
+from diffusers.hooks.taylorseer_cache import TaylorSeerCacheConfig
 from diffusers.image_processor import VaeImageProcessor
 from diffusers.loaders import FluxIPAdapterMixin, IPAdapterMixin
 from diffusers.models.attention import AttentionModuleMixin
@@ -2923,6 +2924,56 @@ class FirstBlockCacheTesterMixin:
             "Outputs from normal inference and after disabling cache should not differ."
         )
 
+class TaylorSeerCacheTesterMixin:
+    taylorseer_cache_config = TaylorSeerCacheConfig(
+        cache_interval=5,
+        disable_cache_before_step=10,
+        max_order=1,
+        taylor_factors_dtype=torch.bfloat16,
+        use_lite_mode=True,
+    )
+
+    def test_taylorseer_cache_inference(self, expected_atol: float = 0.1):
+        device = "cpu"  # ensure determinism for the device-dependent torch.Generator
+
+        def create_pipe():
+            torch.manual_seed(0)
+            num_layers = 2
+            components = self.get_dummy_components(num_layers=num_layers)
+            pipe = self.pipeline_class(**components)
+            pipe = pipe.to(device)
+            pipe.set_progress_bar_config(disable=None)
+            return pipe
+
+        def run_forward(pipe):
+            torch.manual_seed(0)
+            inputs = self.get_dummy_inputs(device)
+            inputs["num_inference_steps"] = 50
+            return pipe(**inputs)[0]
+
+        # Run inference without TaylorSeerCache
+        pipe = create_pipe()
+        output = run_forward(pipe).flatten()
+        original_image_slice = np.concatenate((output[:8], output[-8:]))
+
+        # Run inference with TaylorSeerCache enabled
+        pipe = create_pipe()
+        pipe.transformer.enable_cache(self.taylorseer_cache_config)
+        output = run_forward(pipe).flatten()
+        image_slice_fbc_enabled = np.concatenate((output[:8], output[-8:]))
+
+        # Run inference with TaylorSeerCache disabled
+        pipe.transformer.disable_cache()
+        output = run_forward(pipe).flatten()
+        image_slice_fbc_disabled = np.concatenate((output[:8], output[-8:]))
+
+        assert np.allclose(original_image_slice, image_slice_fbc_enabled, atol=expected_atol), (
+            "TaylorSeerCache outputs should not differ much."
+        )
+        assert np.allclose(original_image_slice, image_slice_fbc_disabled, atol=1e-4), (
+            "Outputs from normal inference and after disabling cache should not differ."
+        )
+
 
 # Some models (e.g. unCLIP) are extremely likely to significantly deviate depending on which hardware is used.
 # This helper function is used to check that the image doesn't deviate on average more than 10 pixels from a