[ip-adapter] make sure length of scale is same as number of ip-adapters when using set_ip_adapter_scale

[yiyixuxu]

importtorchfromdiffusersimportAutoPipelineForText2Imagepipeline=AutoPipelineForText2Image.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
torch_dtype=torch.float16
)
pipeline.load_ip_adapter(
"h94/IP-Adapter", subfolder="sdxl_models", weight_name=["ip-adapter-plus_sdxl_vit-h.safetensors", "ip-adapter-plus-face_sdxl_vit-h.safetensors"]
)
print(f" testing scale = 0.7")
try:
pipeline.set_ip_adapter_scale(0.7)
exceptExceptionase:
print(f"Error: {e}")
print(f" testing scale = [0.7]")
try:
pipeline.set_ip_adapter_scale([0.7])
exceptExceptionase:
print(f"Error: {e}")
print(f" testing scale = [0.7, 0.6]")
try:
pipeline.set_ip_adapter_scale([0.7, 0.6])
exceptExceptionase:
print(f"Error: {e}"
)
print(f" testing scale = [0.7, 0.5, 0.6]")
try:
pipeline.set_ip_adapter_scale([0.7, 0.5, 0.6])
exceptExceptionase:
print(f"Error: {e}")

outputs are expected

 testing scale = 0.7
testing scale = [0.7]
Error: `scale` should be a list of same length as the number if ip-adapters Expected 2 but got 1.
testing scale = [0.7, 0.6]
testing scale = [0.7, 0.5, 0.6]
Error: `scale` should be a list of same length as the number if ip-adapters Expected 2 but got 3.

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[yiyixuxu]

@asomoza feel free to give this a review:)

[sayakpaul]

So good!

I believe the testing will be added in #6829?

[asomoza]

thank you, this resolves the issue.