95 lines
2.9 KiB
Python
95 lines
2.9 KiB
Python
import gc
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import os
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from typing import *
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import torch
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from .models import BaseModel
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from .utilities import (
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build_engine,
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export_onnx,
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optimize_onnx,
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)
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def create_onnx_path(name, onnx_dir, opt=True):
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return os.path.join(onnx_dir, name + (".opt" if opt else "") + ".onnx")
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class EngineBuilder:
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def __init__(
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self,
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model: BaseModel,
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network: Any,
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device=torch.device("cuda"),
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):
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self.device = device
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self.model = model
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self.network = network
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def build(
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self,
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onnx_path: str,
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onnx_opt_path: str,
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engine_path: str,
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opt_image_height: int = 512,
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opt_image_width: int = 512,
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opt_batch_size: int = 1,
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min_image_resolution: int = 256,
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max_image_resolution: int = 1024,
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build_enable_refit: bool = False,
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build_static_batch: bool = False,
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build_dynamic_shape: bool = False,
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build_all_tactics: bool = False,
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onnx_opset: int = 17,
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force_engine_build: bool = False,
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force_onnx_export: bool = False,
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force_onnx_optimize: bool = False,
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):
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if not force_onnx_export and os.path.exists(onnx_path):
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print(f"Found cached model: {onnx_path}")
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else:
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print(f"Exporting model: {onnx_path}")
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export_onnx(
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self.network,
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onnx_path=onnx_path,
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model_data=self.model,
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opt_image_height=opt_image_height,
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opt_image_width=opt_image_width,
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opt_batch_size=opt_batch_size,
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onnx_opset=onnx_opset,
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)
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del self.network
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gc.collect()
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torch.cuda.empty_cache()
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if not force_onnx_optimize and os.path.exists(onnx_opt_path):
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print(f"Found cached model: {onnx_opt_path}")
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else:
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print(f"Generating optimizing model: {onnx_opt_path}")
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optimize_onnx(
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onnx_path=onnx_path,
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onnx_opt_path=onnx_opt_path,
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model_data=self.model,
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)
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self.model.min_latent_shape = min_image_resolution // 8
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self.model.max_latent_shape = max_image_resolution // 8
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if not force_engine_build and os.path.exists(engine_path):
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print(f"Found cached engine: {engine_path}")
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else:
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build_engine(
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engine_path=engine_path,
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onnx_opt_path=onnx_opt_path,
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model_data=self.model,
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opt_image_height=opt_image_height,
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opt_image_width=opt_image_width,
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opt_batch_size=opt_batch_size,
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build_static_batch=build_static_batch,
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build_dynamic_shape=build_dynamic_shape,
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build_all_tactics=build_all_tactics,
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build_enable_refit=build_enable_refit,
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)
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gc.collect()
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torch.cuda.empty_cache()
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