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[refactor]: migrate examples/scripts to typed VideoGenerator API; rename api/compat.py to api/translation.py

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Move all examples/inference and scripts off the legacy
VideoGenerator.from_pretrained(model, **kwargs) +
generate_video(prompt, **kwargs) surface onto the typed
from_config(GeneratorConfig(...)) + generate(GenerationRequest(...))
convention, including the Kandinsky-5 and DreamX-World examples added
on main after the original migration. git-mv api/compat.py to
api/translation.py ('compat' implied a temporary shim; the forward
translation is its honest permanent role) and repoint all importers,
tests, and doc links.
This commit is contained in:
SolitaryThinker
2026-07-11 03:26:24 -07:00
parent 19a51a1fe6
commit bbbb7ab021
87 changed files with 2493 additions and 1461 deletions
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examples/inference/basic/basic_dreamx_world.py
+42 -27
View File
@@ -1,6 +1,9 @@
import os
from fastvideo import VideoGenerator
from fastvideo.api import (ComponentConfig, EngineConfig, GenerationRequest,
GeneratorConfig, InputConfig, OffloadConfig,
OutputConfig, PipelineSelection, SamplingConfig)
OUTPUT_PATH = os.getenv("DREAMX_WORLD_OUTPUT_PATH", "video_samples_dreamx_world")
@@ -16,16 +19,22 @@ def _env_float(name: str, default: float) -> float:
def main():
model_name = os.getenv("DREAMX_WORLD_MODEL_DIR", "FastVideo/DreamX-World-5B-Cam-Diffusers")
generator = VideoGenerator.from_pretrained(
model_name,
num_gpus=1,
use_fsdp_inference=False,
dit_cpu_offload=False,
vae_cpu_offload=True,
text_encoder_cpu_offload=True,
pin_cpu_memory=False,
override_pipeline_cls_name="DreamXWorldPipeline",
)
generator = VideoGenerator.from_config(
GeneratorConfig(
model_path=model_name,
engine=EngineConfig(
num_gpus=1,
use_fsdp_inference=False,
offload=OffloadConfig(
dit=False,
vae=True,
text_encoder=True,
pin_cpu_memory=False,
),
),
pipeline=PipelineSelection(
components=ComponentConfig(override_pipeline_cls_name="DreamXWorldPipeline"), ),
))
prompt = os.getenv(
"DREAMX_WORLD_PROMPT",
@@ -37,25 +46,31 @@ def main():
"https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/wan_i2v_input.JPG",
)
kwargs = {
"output_path": OUTPUT_PATH,
"save_video": os.getenv("DREAMX_WORLD_SAVE_VIDEO", "1") != "0",
"height": _env_int("DREAMX_WORLD_HEIGHT", 480),
"width": _env_int("DREAMX_WORLD_WIDTH", 832),
"num_frames": _env_int("DREAMX_WORLD_NUM_FRAMES", 161),
"num_inference_steps": _env_int("DREAMX_WORLD_STEPS", 30),
"guidance_scale": _env_float("DREAMX_WORLD_GUIDANCE", 5.0),
"action_list": os.getenv("DREAMX_WORLD_ACTIONS", "w,d,w").split(","),
"action_speed_list": [
float(value)
for value in os.getenv("DREAMX_WORLD_ACTION_SPEEDS", "4.0,2.0,4.0").split(",")
],
}
if image_path:
kwargs["image_path"] = image_path
request = GenerationRequest(
prompt=prompt,
inputs=InputConfig(image_path=image_path or None),
sampling=SamplingConfig(
height=_env_int("DREAMX_WORLD_HEIGHT", 480),
width=_env_int("DREAMX_WORLD_WIDTH", 832),
num_frames=_env_int("DREAMX_WORLD_NUM_FRAMES", 161),
num_inference_steps=_env_int("DREAMX_WORLD_STEPS", 30),
guidance_scale=_env_float("DREAMX_WORLD_GUIDANCE", 5.0),
),
output=OutputConfig(
output_path=OUTPUT_PATH,
save_video=os.getenv("DREAMX_WORLD_SAVE_VIDEO", "1") != "0",
),
extensions={
"action_list": os.getenv("DREAMX_WORLD_ACTIONS", "w,d,w").split(","),
"action_speed_list": [
float(value)
for value in os.getenv("DREAMX_WORLD_ACTION_SPEEDS", "4.0,2.0,4.0").split(",")
],
},
)
try:
generator.generate_video(prompt, **kwargs)
generator.generate(request)
finally:
generator.shutdown()