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ppdiffusers/deploy/sd3/README.md

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@@ -8,14 +8,11 @@ python -m pip install triton
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python -m pip install git+https://github.com/zhoutianzi666/UseTritonInPaddle.git
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python -c "import use_triton_in_paddle; use_triton_in_paddle.make_triton_compatible_with_paddle()"
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# 安装develop版本的paddle
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# 安装develop版本的paddle,请根据自己的cuda版本选择对应的paddle版本,这里选择12.3的cuda版本
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python -m pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu123/
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# 指定Tensor-RT的lib路径
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export LD_LIBRARY_PATH=/your_TensorRT_dir//lib:$LD_LIBRARY_PATH
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# 指定cutlass包路径
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export LD_LIBRARY_PATH=/your_dir/Paddle/paddle/phi/kernels/fusion/cutlass/conv2d/build:$LD_LIBRARY_PATH
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# 指定 libCutlassGemmEpilogue.so 的路径
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# 详情请参考 https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/phi/kernels/fusion/cutlass/gemm_epilogue/README.md
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export LD_LIBRARY_PATH=/your_dir/Paddle/paddle/phi/kernels/fusion/cutlass/gemm_epilogue/build:$LD_LIBRARY_PATH
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```
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ppdiffusers/ppdiffusers/pipelines/stable_diffusion_3/pipeline_stable_diffusion_3.py

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@@ -802,7 +802,7 @@ def __call__(
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# broadcast to batch dimension in a way that's compatible with ONNX/Core ML
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timestep = t.expand(latent_model_input.shape[0])
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noise_pred_out = self.transformer(
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model_output = self.transformer(
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hidden_states=latent_model_input,
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timestep=timestep,
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encoder_hidden_states=prompt_embeds,
@@ -812,9 +812,9 @@ def __call__(
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)
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if is_inference_mode(self.transformer):
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noise_pred = noise_pred_out
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noise_pred = model_output
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else:
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noise_pred = noise_pred_out[0]
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noise_pred = model_output[0]
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# perform guidance
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if self.do_classifier_free_guidance:

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