AI/diffusers
1
0
Fork 0
mirror of https://github.com/huggingface/diffusers.git synced 2026-01-27 17:22:53 +03:00
Code Activity

enable marigold_intrinsics cases on XPU (#11445)

Browse Source 
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
This commit is contained in:
Yao Matrix
2025-04-30 13:37:37 +08:00
committed by GitHub
parent 8fe5a14d9b
commit 60892c55a4
1 changed files with 22 additions and 21 deletions
Download Patch File Download Diff File Expand all files Collapse all files

43
tests/pipelines/marigold/test_marigold_intrinsics.py
View File

@@ -33,10 +33,11 @@ from diffusers import (
UNet2DConditionModel,
)
from diffusers.utils.testing_utils import (
backend_empty_cache,
enable_full_determinism,
floats_tensor,
load_image,
require_torch_gpu,
require_torch_accelerator,
slow,
torch_device,
)
@@ -395,17 +396,17 @@ class MarigoldIntrinsicsPipelineFastTests(MarigoldIntrinsicsPipelineTesterMixin,
@slow
@require_torch_gpu
@require_torch_accelerator
class MarigoldIntrinsicsPipelineIntegrationTests(unittest.TestCase):
def setUp(self):
super().setUp()
gc.collect()
torch.cuda.empty_cache()
backend_empty_cache(torch_device)
def tearDown(self):
super().tearDown()
gc.collect()
torch.cuda.empty_cache()
backend_empty_cache(torch_device)
def _test_marigold_intrinsics(
self,
@@ -424,7 +425,7 @@ class MarigoldIntrinsicsPipelineIntegrationTests(unittest.TestCase):
from_pretrained_kwargs["torch_dtype"] = torch.float16
pipe = MarigoldIntrinsicsPipeline.from_pretrained(model_id, **from_pretrained_kwargs)
if device == "cuda":
if device in ["cuda", "xpu"]:
pipe.enable_model_cpu_offload()
pipe.set_progress_bar_config(disable=None)
@@ -464,10 +465,10 @@ class MarigoldIntrinsicsPipelineIntegrationTests(unittest.TestCase):
match_input_resolution=True,
)
def test_marigold_intrinsics_einstein_f32_cuda_G0_S1_P768_E1_B1_M1(self):
def test_marigold_intrinsics_einstein_f32_accelerator_G0_S1_P768_E1_B1_M1(self):
self._test_marigold_intrinsics(
is_fp16=False,
device="cuda",
device=torch_device,
generator_seed=0,
expected_slice=np.array([0.62127, 0.61906, 0.61687, 0.61946, 0.61903, 0.61961, 0.61808, 0.62099, 0.62894]),
num_inference_steps=1,
@@ -477,10 +478,10 @@ class MarigoldIntrinsicsPipelineIntegrationTests(unittest.TestCase):
match_input_resolution=True,
)
def test_marigold_intrinsics_einstein_f16_cuda_G0_S1_P768_E1_B1_M1(self):
def test_marigold_intrinsics_einstein_f16_accelerator_G0_S1_P768_E1_B1_M1(self):
self._test_marigold_intrinsics(
is_fp16=True,
device="cuda",
device=torch_device,
generator_seed=0,
expected_slice=np.array([0.62109, 0.61914, 0.61719, 0.61963, 0.61914, 0.61963, 0.61816, 0.62109, 0.62891]),
num_inference_steps=1,
@@ -490,10 +491,10 @@ class MarigoldIntrinsicsPipelineIntegrationTests(unittest.TestCase):
match_input_resolution=True,
)
def test_marigold_intrinsics_einstein_f16_cuda_G2024_S1_P768_E1_B1_M1(self):
def test_marigold_intrinsics_einstein_f16_accelerator_G2024_S1_P768_E1_B1_M1(self):
self._test_marigold_intrinsics(
is_fp16=True,
device="cuda",
device=torch_device,
generator_seed=2024,
expected_slice=np.array([0.64111, 0.63916, 0.63623, 0.63965, 0.63916, 0.63965, 0.6377, 0.64062, 0.64941]),
num_inference_steps=1,
@@ -503,10 +504,10 @@ class MarigoldIntrinsicsPipelineIntegrationTests(unittest.TestCase):
match_input_resolution=True,
)
def test_marigold_intrinsics_einstein_f16_cuda_G0_S2_P768_E1_B1_M1(self):
def test_marigold_intrinsics_einstein_f16_accelerator_G0_S2_P768_E1_B1_M1(self):
self._test_marigold_intrinsics(
is_fp16=True,
device="cuda",
device=torch_device,
generator_seed=0,
expected_slice=np.array([0.60254, 0.60059, 0.59961, 0.60156, 0.60107, 0.60205, 0.60254, 0.60449, 0.61133]),
num_inference_steps=2,
@@ -516,10 +517,10 @@ class MarigoldIntrinsicsPipelineIntegrationTests(unittest.TestCase):
match_input_resolution=True,
)
def test_marigold_intrinsics_einstein_f16_cuda_G0_S1_P512_E1_B1_M1(self):
def test_marigold_intrinsics_einstein_f16_accelerator_G0_S1_P512_E1_B1_M1(self):
self._test_marigold_intrinsics(
is_fp16=True,
device="cuda",
device=torch_device,
generator_seed=0,
expected_slice=np.array([0.64551, 0.64453, 0.64404, 0.64502, 0.64844, 0.65039, 0.64502, 0.65039, 0.65332]),
num_inference_steps=1,
@@ -529,10 +530,10 @@ class MarigoldIntrinsicsPipelineIntegrationTests(unittest.TestCase):
match_input_resolution=True,
)
def test_marigold_intrinsics_einstein_f16_cuda_G0_S1_P768_E3_B1_M1(self):
def test_marigold_intrinsics_einstein_f16_accelerator_G0_S1_P768_E3_B1_M1(self):
self._test_marigold_intrinsics(
is_fp16=True,
device="cuda",
device=torch_device,
generator_seed=0,
expected_slice=np.array([0.61572, 0.61377, 0.61182, 0.61426, 0.61377, 0.61426, 0.61279, 0.61572, 0.62354]),
num_inference_steps=1,
@@ -543,10 +544,10 @@ class MarigoldIntrinsicsPipelineIntegrationTests(unittest.TestCase):
match_input_resolution=True,
)
def test_marigold_intrinsics_einstein_f16_cuda_G0_S1_P768_E4_B2_M1(self):
def test_marigold_intrinsics_einstein_f16_accelerator_G0_S1_P768_E4_B2_M1(self):
self._test_marigold_intrinsics(
is_fp16=True,
device="cuda",
device=torch_device,
generator_seed=0,
expected_slice=np.array([0.61914, 0.6167, 0.61475, 0.61719, 0.61719, 0.61768, 0.61572, 0.61914, 0.62695]),
num_inference_steps=1,
@@ -557,10 +558,10 @@ class MarigoldIntrinsicsPipelineIntegrationTests(unittest.TestCase):
match_input_resolution=True,
)
def test_marigold_intrinsics_einstein_f16_cuda_G0_S1_P512_E1_B1_M0(self):
def test_marigold_intrinsics_einstein_f16_accelerator_G0_S1_P512_E1_B1_M0(self):
self._test_marigold_intrinsics(
is_fp16=True,
device="cuda",
device=torch_device,
generator_seed=0,
expected_slice=np.array([0.65332, 0.64697, 0.64648, 0.64844, 0.64697, 0.64111, 0.64941, 0.64209, 0.65332]),
num_inference_steps=1,