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[PPDiffusers]fix bugs and release 0.29.0 (PaddlePaddle#742)
Co-authored-by: nifeng <nemonameless@qq.com>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1 +1 @@ | ||
| 0.24.1 | ||
| 0.29.0 |
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ppdiffusers/deploy/sd3/text_to_image_generation-stable_diffusion_3.py
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,145 @@ | ||
| # Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved. | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
| import os | ||
| import argparse | ||
| import paddle | ||
| def parse_args(): | ||
| parser = argparse.ArgumentParser( | ||
| description=" Use PaddleMIX to accelerate the Stable Diffusion3 image generation model." | ||
| ) | ||
| parser.add_argument( | ||
| "--benchmark", | ||
| type=(lambda x: str(x).lower() in ["true", "1", "yes"]), | ||
| default=False, | ||
| help="if set to True, measure inference performance", | ||
| ) | ||
| parser.add_argument( | ||
| "--inference_optimize", | ||
| type=(lambda x: str(x).lower() in ["true", "1", "yes"]), | ||
| default=False, | ||
| help="If set to True, all optimizations except Triton are enabled.", | ||
| ) | ||
| parser.add_argument( | ||
| "--inference_optimize_bp", | ||
| type=(lambda x: str(x).lower() in ["true", "1", "yes"]), | ||
| default=False, | ||
| help="If set to True, batch parallel is enabled in DIT and dual-GPU acceleration is used.", | ||
| ) | ||
| parser.add_argument("--height", type=int, default=512, help="Height of the generated image.") | ||
| parser.add_argument("--width", type=int, default=512, help="Width of the generated image.") | ||
| parser.add_argument("--num-inference-steps", type=int, default=50, help="Number of inference steps.") | ||
| parser.add_argument("--dtype", type=str, default="float32", help="Inference data types.") | ||
|
|
||
| return parser.parse_args() | ||
|
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| args = parse_args() | ||
|
|
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| if args.inference_optimize: | ||
| os.environ["INFERENCE_OPTIMIZE"] = "True" | ||
| os.environ["INFERENCE_OPTIMIZE_TRITON"] = "True" | ||
| if args.inference_optimize_bp: | ||
| os.environ["INFERENCE_OPTIMIZE_BP"] = "True" | ||
| if args.dtype == "float32": | ||
| inference_dtype = paddle.float32 | ||
| elif args.dtype == "float16": | ||
| inference_dtype = paddle.float16 | ||
|
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|
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| if args.inference_optimize_bp: | ||
| from paddle.distributed import fleet | ||
| from paddle.distributed.fleet.utils import recompute | ||
| import numpy as np | ||
| import random | ||
| import paddle.distributed as dist | ||
| import paddle.distributed.fleet as fleet | ||
| strategy = fleet.DistributedStrategy() | ||
| model_parallel_size = 2 | ||
| data_parallel_size = 1 | ||
| strategy.hybrid_configs = { | ||
| "dp_degree": data_parallel_size, | ||
| "mp_degree": model_parallel_size, | ||
| "pp_degree": 1 | ||
| } | ||
| fleet.init(is_collective=True, strategy=strategy) | ||
| hcg = fleet.get_hybrid_communicate_group() | ||
| mp_id = hcg.get_model_parallel_rank() | ||
| rank_id = dist.get_rank() | ||
|
|
||
| import datetime | ||
| from ppdiffusers import StableDiffusion3Pipeline | ||
|
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| pipe = StableDiffusion3Pipeline.from_pretrained( | ||
| "stabilityai/stable-diffusion-3-medium-diffusers", | ||
| paddle_dtype=inference_dtype, | ||
| ) | ||
|
|
||
| pipe.transformer = paddle.incubate.jit.inference( | ||
| pipe.transformer, | ||
| save_model_dir="./tmp/sd3", | ||
| enable_new_ir=True, | ||
| cache_static_model=True, | ||
| # V100环境下，需设置exp_enable_use_cutlass=False, | ||
| exp_enable_use_cutlass=True, | ||
| delete_pass_lists=["add_norm_fuse_pass"], | ||
| ) | ||
|
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| generator = paddle.Generator().manual_seed(42) | ||
| prompt = "A cat holding a sign that says hello world" | ||
|
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| image = pipe( | ||
| prompt, num_inference_steps=args.num_inference_steps, width=args.width, height=args.height, generator=generator | ||
| ).images[0] | ||
|
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||
| if args.benchmark: | ||
| # warmup | ||
| for i in range(3): | ||
| image = pipe( | ||
| prompt, | ||
| num_inference_steps=args.num_inference_steps, | ||
| width=args.width, | ||
| height=args.height, | ||
| generator=generator, | ||
| ).images[0] | ||
|
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||
| repeat_times = 10 | ||
| sumtime = 0.0 | ||
| for i in range(repeat_times): | ||
| paddle.device.synchronize() | ||
| starttime = datetime.datetime.now() | ||
| image = pipe( | ||
| prompt, | ||
| num_inference_steps=args.num_inference_steps, | ||
| width=args.width, | ||
| height=args.height, | ||
| generator=generator, | ||
| ).images[0] | ||
| paddle.device.synchronize() | ||
| endtime = datetime.datetime.now() | ||
| duringtime = endtime - starttime | ||
| duringtime = duringtime.seconds * 1000 + duringtime.microseconds / 1000.0 | ||
| sumtime += duringtime | ||
| print("SD3 end to end time : ", duringtime, "ms") | ||
|
|
||
| print("SD3 ave end to end time : ", sumtime / repeat_times, "ms") | ||
| cuda_mem_after_used = paddle.device.cuda.max_memory_allocated() / (1024**3) | ||
| print(f"Max used CUDA memory : {cuda_mem_after_used:.3f} GiB") | ||
|
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| if args.inference_optimize_bp: | ||
| if rank_id == 0: | ||
| image.save("text_to_image_generation-stable_diffusion_3-result.png") | ||
| else: | ||
| image.save("text_to_image_generation-stable_diffusion_3-result.png") |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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|
@@ -4,3 +4,5 @@ paddlenlp>=2.7.2 | |
| opencv-python | ||
| ppdiffusers>=0.24.0 | ||
| cchardet | ||
| gradio==3.16.2 | ||
| basicsr==1.4.2 | ||
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