Improve pos embed for Flux.1 inference on Ascend NPU

[gameofdimension]

What does this PR do?

Moving pos_embed computation from NPU to CPU results in a 1.4x speedup in Flux.1's end-to-end latency.

model	device	e2e latency
FLUX.1-dev	npu	31s
FLUX.1-dev	cpu	21s
FLUX.1-Fill-dev	npu	64s
FLUX.1-Fill-dev	cpu	46s

Tested hardware:

Ascend 910B2C

Repro Code

FLUX.1-dev

importtorchfromdiffusersimportFluxPipelinepipe=FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to("npu")
prompt="A cat holding a sign that says hello world"image=pipe(
prompt,
height=1024,
width=1024,
guidance_scale=3.5,
num_inference_steps=50,
max_sequence_length=512,
generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save("flux-dev.png")

FLUX.1-Fill-dev

importtorchfromdiffusersimportFluxFillPipelinefromdiffusers.utilsimportload_imageimage=load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup.png")
mask=load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup_mask.png")
pipe=FluxFillPipeline.from_pretrained("black-forest-labs/FLUX.1-Fill-dev", torch_dtype=torch.bfloat16).to("npu")
image=pipe(
prompt="a white paper cup",
image=image,
mask_image=mask,
height=1632,
width=1232,
guidance_scale=30,
num_inference_steps=50,
max_sequence_length=512,
generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save(f"flux-fill-dev.png")

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[yiyixuxu]

thanks!