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[refactor]: move examples to generate(request) and from_config

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Every example calls VideoGenerator.generate with a nested request instead
of generate_video keywords, and passes settings outside the from_pretrained
convenience keywords through VideoGenerator.from_config at their typed
paths. Each request and generator config equals what the keyword call built.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7
This commit is contained in:
Davids048
2026-10-03 02:14:36 +00:00
co-authored by Claude Opus 5.5
parent 96b7c0d223
commit f571621ae7
66 changed files with 1514 additions and 1130 deletions
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examples/inference/basic/basic_longcat_vc.py
+110 -83
View File
@@ -57,34 +57,39 @@ def basic_generation():
raise FileNotFoundError(f"Video not found at {VIDEO_PATH}. "
"Please provide a valid video path.")
generator = VideoGenerator.from_pretrained(
"FastVideo/LongCat-Video-VC-Diffusers",
num_gpus=1,
use_fsdp_inference=False, # set to True if GPU is out of memory
dit_cpu_offload=False,
vae_cpu_offload=True,
text_encoder_cpu_offload=True,
pin_cpu_memory=False,
enable_bsa=False,
)
generator = VideoGenerator.from_config({
"model_path": "FastVideo/LongCat-Video-VC-Diffusers",
"engine": {
"num_gpus": 1,
"use_fsdp_inference": False, # set to True if GPU is out of memory
"offload": {
"dit": False,
"vae": True,
"text_encoder": True,
"pin_cpu_memory": False,
},
},
"pipeline": {"longcat": {"enable_bsa": False}},
})
output_path = "outputs_video/longcat_vc_basic"
generator.generate_video(
prompt=PROMPT,
negative_prompt=NEGATIVE_PROMPT,
video_path=VIDEO_PATH,
num_cond_frames=NUM_COND_FRAMES,
output_path=output_path,
save_video=True,
height=480,
width=832,
num_frames=93,
num_inference_steps=50,
fps=15,
guidance_scale=4.0,
seed=SEED,
)
generator.generate({
"prompt": PROMPT,
"negative_prompt": NEGATIVE_PROMPT,
"inputs": {"video_path": VIDEO_PATH},
"sampling": {
"height": 480,
"width": 832,
"num_frames": 93,
"num_inference_steps": 50,
"fps": 15,
"guidance_scale": 4.0,
"seed": SEED,
},
"output": {"output_path": output_path, "save_video": True},
"extensions": {"num_cond_frames": NUM_COND_FRAMES},
})
print(f"\nBasic generation complete! Video saved to: {output_path}")
generator.shutdown()
@@ -110,36 +115,45 @@ def distill_refine_generation():
print("\n[Stage 1] Distilled generation (16 steps, 480p)")
print("-" * 40)
generator = VideoGenerator.from_pretrained(
"FastVideo/LongCat-Video-VC-Diffusers",
num_gpus=1,
use_fsdp_inference=True,
dit_cpu_offload=False,
vae_cpu_offload=True,
text_encoder_cpu_offload=True,
pin_cpu_memory=False,
enable_bsa=False,
lora_path="FastVideo/LongCat-Video-T2V-Distilled-LoRA",
lora_nickname="distilled",
)
generator = VideoGenerator.from_config({
"model_path": "FastVideo/LongCat-Video-VC-Diffusers",
"engine": {
"num_gpus": 1,
"use_fsdp_inference": True,
"offload": {
"dit": False,
"vae": True,
"text_encoder": True,
"pin_cpu_memory": False,
},
},
"pipeline": {
"longcat": {"enable_bsa": False},
"components": {
"lora_path": "FastVideo/LongCat-Video-T2V-Distilled-LoRA",
"lora_nickname": "distilled",
},
},
})
distill_output_path = "outputs_video/longcat_vc_distill"
generator.generate_video(
prompt=PROMPT,
negative_prompt=NEGATIVE_PROMPT,
video_path=VIDEO_PATH,
num_cond_frames=NUM_COND_FRAMES,
output_path=distill_output_path,
save_video=True,
height=480,
width=832,
num_frames=93,
num_inference_steps=16,
fps=15,
guidance_scale=1.0,
seed=SEED,
)
generator.generate({
"prompt": PROMPT,
"negative_prompt": NEGATIVE_PROMPT,
"inputs": {"video_path": VIDEO_PATH},
"sampling": {
"height": 480,
"width": 832,
"num_frames": 93,
"num_inference_steps": 16,
"fps": 15,
"guidance_scale": 1.0,
"seed": SEED,
},
"output": {"output_path": distill_output_path, "save_video": True},
"extensions": {"num_cond_frames": NUM_COND_FRAMES},
})
print(f"Distilled generation complete! Video saved to: {distill_output_path}")
generator.shutdown()
@@ -158,40 +172,53 @@ def distill_refine_generation():
# Create a new generator with refinement LoRA and BSA enabled
# Note: Refinement uses the T2V model (not VC) since it's upscaling the generated video
refine_generator = VideoGenerator.from_pretrained(
"FastVideo/LongCat-Video-T2V-Diffusers",
num_gpus=1,
use_fsdp_inference=True,
dit_cpu_offload=True,
vae_cpu_offload=True,
text_encoder_cpu_offload=True,
pin_cpu_memory=False,
enable_bsa=True,
bsa_sparsity=0.875,
bsa_chunk_q=[4, 4, 8],
bsa_chunk_k=[4, 4, 8],
lora_path="FastVideo/LongCat-Video-T2V-Refinement-LoRA",
lora_nickname="refinement",
)
refine_generator = VideoGenerator.from_config({
"model_path": "FastVideo/LongCat-Video-T2V-Diffusers",
"engine": {
"num_gpus": 1,
"use_fsdp_inference": True,
"offload": {
"dit": True,
"vae": True,
"text_encoder": True,
"pin_cpu_memory": False,
},
},
"pipeline": {
"longcat": {
"enable_bsa": True,
"bsa_sparsity": 0.875,
"bsa_chunk_q": [4, 4, 8],
"bsa_chunk_k": [4, 4, 8],
},
"components": {
"lora_path": "FastVideo/LongCat-Video-T2V-Refinement-LoRA",
"lora_nickname": "refinement",
},
},
})
refine_output_path = "outputs_video/longcat_vc_refine_720p"
refine_generator.generate_video(
prompt=PROMPT,
negative_prompt=NEGATIVE_PROMPT,
output_path=refine_output_path,
save_video=True,
refine_from=distill_video_path,
t_thresh=0.5,
spatial_refine_only=False,
num_cond_frames=0, # For refinement, no conditioning frames
height=720,
width=1280,
num_inference_steps=50,
fps=30,
guidance_scale=1.0,
seed=SEED,
)
refine_generator.generate({
"prompt": PROMPT,
"negative_prompt": NEGATIVE_PROMPT,
"inputs": {"refine_from": distill_video_path},
"sampling": {
"height": 720,
"width": 1280,
"num_inference_steps": 50,
"fps": 30,
"guidance_scale": 1.0,
"seed": SEED,
},
"output": {"output_path": refine_output_path, "save_video": True},
"extensions": {
"t_thresh": 0.5,
"spatial_refine_only": False,
"num_cond_frames": 0, # For refinement, no conditioning frames
},
})
print(f"Refinement complete! Video saved to: {refine_output_path}")
refine_generator.shutdown()