add cpuoffload support for image pipelines

examples/image_synthesis/flux_text_to_image_cpu_offload.py

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+import torch
+from diffsynth import ModelManager, FluxImagePipeline, download_models
+
+
+download_models(["FLUX.1-dev"])
+model_manager = ModelManager(torch_dtype=torch.bfloat16, device="cpu")
+model_manager.load_models([
+    "models/FLUX/FLUX.1-dev/text_encoder/model.safetensors",
+    "models/FLUX/FLUX.1-dev/text_encoder_2",
+    "models/FLUX/FLUX.1-dev/ae.safetensors",
+    "models/FLUX/FLUX.1-dev/flux1-dev.safetensors"
+])
+pipe = FluxImagePipeline.from_model_manager(model_manager, device='cuda')
+pipe.enable_cpu_offload()
+
+prompt = "CG. Full body. A captivating fantasy magic woman portrait in the deep sea. The woman, with blue spaghetti strap silk dress, swims in the sea. Her flowing silver hair shimmers with every color of the rainbow and cascades down, merging with the floating flora around her. Smooth, delicate and fair skin."
+negative_prompt = "dark, worst quality, low quality, monochrome, zombie, interlocked fingers, Aissist, dim, fuzzy, depth of Field, nsfw,"
+
+# Disable classifier-free guidance (consistent with the original implementation of FLUX.1)
+torch.manual_seed(6)
+image = pipe(
+    prompt=prompt,
+    num_inference_steps=30, embedded_guidance=3.5
+)
+image.save("image_1024.jpg")
+
+# Enable classifier-free guidance
+torch.manual_seed(6)
+image = pipe(
+    prompt=prompt, negative_prompt=negative_prompt,
+    num_inference_steps=30, cfg_scale=2.0, embedded_guidance=3.5
+)
+image.save("image_1024_cfg.jpg")
+
+# Highres-fix
+torch.manual_seed(7)
+image = pipe(
+    prompt=prompt,
+    num_inference_steps=30, embedded_guidance=3.5,
+    input_image=image.resize((2048, 2048)), height=2048, width=2048, denoising_strength=0.6, tiled=True
+)
+image.save("image_2048_highres.jpg")