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Merge a0bf867138 into 679ccc6c68
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@ -27,6 +27,9 @@ EXAMPLE_PROMPT = {
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"t2i-14B": {
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"prompt": "一个朴素端庄的美人",
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},
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"t2i-1.3B": {
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"prompt": "一个朴素端庄的美人",
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},
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"i2v-14B": {
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"prompt":
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"Summer beach vacation style, a white cat wearing sunglasses sits on a surfboard. The fluffy-furred feline gazes directly at the camera with a relaxed expression. Blurred beach scenery forms the background featuring crystal-clear waters, distant green hills, and a blue sky dotted with white clouds. The cat assumes a naturally relaxed posture, as if savoring the sea breeze and warm sunlight. A close-up shot highlights the feline's intricate details and the refreshing atmosphere of the seaside.",
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205
gradio/t2i_1.3B_singleGPU.py
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205
gradio/t2i_1.3B_singleGPU.py
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@ -0,0 +1,205 @@
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# Copyright 2024-2025 The Alibaba Wan Team Authors. All rights reserved.
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import argparse
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import os.path as osp
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import os
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import sys
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import warnings
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import gradio as gr
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warnings.filterwarnings('ignore')
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# Model
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sys.path.insert(0, os.path.sep.join(osp.realpath(__file__).split(os.path.sep)[:-2]))
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import wan
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from wan.configs import WAN_CONFIGS
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from wan.utils.prompt_extend import DashScopePromptExpander, QwenPromptExpander
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from wan.utils.utils import cache_image
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# Global Var
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prompt_expander = None
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wan_t2i = None
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# Button Func
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def prompt_enc(prompt, tar_lang):
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global prompt_expander
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prompt_output = prompt_expander(prompt, tar_lang=tar_lang.lower())
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if prompt_output.status == False:
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return prompt
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else:
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return prompt_output.prompt
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def t2i_generation(txt2img_prompt, resolution, sd_steps, guide_scale,
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shift_scale, seed, n_prompt):
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global wan_t2i
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# print(f"{txt2img_prompt},{resolution},{sd_steps},{guide_scale},{shift_scale},{seed},{n_prompt}")
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W = int(resolution.split("*")[0])
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H = int(resolution.split("*")[1])
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video = wan_t2i.generate(
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txt2img_prompt,
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size=(W, H),
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frame_num=1,
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shift=shift_scale,
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sampling_steps=sd_steps,
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guide_scale=guide_scale,
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n_prompt=n_prompt,
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seed=seed,
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offload_model=True)
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cache_image(
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tensor=video.squeeze(1)[None],
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save_file="example.png",
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nrow=1,
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normalize=True,
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value_range=(-1, 1))
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return "example.png"
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# Interface
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def gradio_interface():
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with gr.Blocks() as demo:
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gr.Markdown("""
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<div style="text-align: center; font-size: 32px; font-weight: bold; margin-bottom: 20px;">
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Wan2.1 (T2I-1.3B)
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</div>
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<div style="text-align: center; font-size: 16px; font-weight: normal; margin-bottom: 20px;">
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Wan: Open and Advanced Large-Scale Video Generative Models.
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</div>
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""")
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with gr.Row():
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with gr.Column():
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txt2img_prompt = gr.Textbox(
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label="Prompt",
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placeholder="Describe the image you want to generate",
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)
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tar_lang = gr.Radio(
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choices=["ZH", "EN"],
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label="Target language of prompt enhance",
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value="ZH")
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run_p_button = gr.Button(value="Prompt Enhance")
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with gr.Accordion("Advanced Options", open=True):
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resolution = gr.Dropdown(
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label='Resolution(Width*Height)',
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choices=[
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'720*1280', '1280*720', '960*960', '1088*832',
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'832*1088', '480*832', '832*480', '624*624',
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'704*544', '544*704'
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],
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value='720*1280')
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with gr.Row():
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sd_steps = gr.Slider(
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label="Diffusion steps",
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minimum=1,
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maximum=1000,
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value=50,
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step=1)
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guide_scale = gr.Slider(
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label="Guide scale",
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minimum=0,
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maximum=20,
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value=5.0,
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step=1)
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with gr.Row():
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shift_scale = gr.Slider(
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label="Shift scale",
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minimum=0,
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maximum=10,
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value=5.0,
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step=1)
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seed = gr.Slider(
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label="Seed",
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minimum=-1,
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maximum=2147483647,
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step=1,
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value=-1)
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n_prompt = gr.Textbox(
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label="Negative Prompt",
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placeholder="Describe the negative prompt you want to add"
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)
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run_t2i_button = gr.Button("Generate Image")
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with gr.Column():
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result_gallery = gr.Image(
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label='Generated Image', interactive=False, height=600)
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run_p_button.click(
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fn=prompt_enc,
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inputs=[txt2img_prompt, tar_lang],
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outputs=[txt2img_prompt])
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run_t2i_button.click(
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fn=t2i_generation,
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inputs=[
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txt2img_prompt, resolution, sd_steps, guide_scale, shift_scale,
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seed, n_prompt
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],
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outputs=[result_gallery],
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)
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return demo
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# Main
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def _parse_args():
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parser = argparse.ArgumentParser(
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description="Generate a image from a text prompt or image using Gradio")
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parser.add_argument(
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"--ckpt_dir",
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type=str,
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default="cache",
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help="The path to the checkpoint directory.")
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parser.add_argument(
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"--prompt_extend_method",
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type=str,
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default="local_qwen",
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choices=["dashscope", "local_qwen"],
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help="The prompt extend method to use.")
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parser.add_argument(
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"--prompt_extend_model",
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type=str,
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default=None,
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help="The prompt extend model to use.")
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args = parser.parse_args()
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return args
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if __name__ == '__main__':
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args = _parse_args()
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print("Step1: Init prompt_expander...", end='', flush=True)
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if args.prompt_extend_method == "dashscope":
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prompt_expander = DashScopePromptExpander(
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model_name=args.prompt_extend_model, is_vl=False)
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elif args.prompt_extend_method == "local_qwen":
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prompt_expander = QwenPromptExpander(
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model_name=args.prompt_extend_model, is_vl=False, device=0)
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else:
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raise NotImplementedError(
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f"Unsupport prompt_extend_method: {args.prompt_extend_method}")
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print("done", flush=True)
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print("Step2: Init 1.3B t2i model...", end='', flush=True)
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cfg = WAN_CONFIGS['t2i-1.3B']
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wan_t2i = wan.WanT2V(
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config=cfg,
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checkpoint_dir=args.ckpt_dir,
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device_id=0,
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rank=0,
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t5_fsdp=False,
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dit_fsdp=False,
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use_usp=False,
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)
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print("done", flush=True)
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demo = gradio_interface()
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demo.launch(server_name="0.0.0.0", share=False, server_port=7860)
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@ -11,12 +11,15 @@ from .wan_t2v_14B import t2v_14B
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# the config of t2i_14B is the same as t2v_14B
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t2i_14B = copy.deepcopy(t2v_14B)
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t2i_14B.__name__ = 'Config: Wan T2I 14B'
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t2i_1_3B = copy.deepcopy(t2v_1_3B)
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t2i_1_3B.__name__ = 'Config: Wan T2I 1.3B'
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WAN_CONFIGS = {
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't2v-14B': t2v_14B,
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't2v-1.3B': t2v_1_3B,
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'i2v-14B': i2v_14B,
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't2i-14B': t2i_14B,
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't2i-1.3B': t2i_1_3B,
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}
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SIZE_CONFIGS = {
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@ -39,4 +42,5 @@ SUPPORTED_SIZES = {
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't2v-1.3B': ('480*832', '832*480'),
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'i2v-14B': ('720*1280', '1280*720', '480*832', '832*480'),
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't2i-14B': tuple(SIZE_CONFIGS.keys()),
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't2i-1.3B': tuple(SIZE_CONFIGS.keys()),
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}
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