model = onnx.load('model.onnx') # 优化模型 passes = ["fuse_bn_into_conv"] model = optimize(model, passes) # 保存优化后的模型 onnx.save(model, 'model_optimized.onnx') 3. 使用GPU加速 ONNX模型可以在不同的硬件平台上运行,其中GPU是常用的硬件加速平
defoptimize(model:onnx.ModelProto,skip_fuse_bn:bool,skipped_optimizers:Optional[Sequence[str]])->onnx.ModelProto:""":model参数: 待优化的ONXX模型.:return: 优化之后的ONNX模型.简化之前, 使用这个方法产生会在'forward_all'用到的ValueInfo简化之后,使用这个方法去折叠前一步产生的常量到initializer中并且...
从onnx.proto3协议中我们需要重点知道的数据结构如下: ModelProto:模型的定义,包含版本信息,生产者和GraphProto。 GraphProto: 包含很多重复的NodeProto, initializer, ValueInfoProto等,这些元素共同构成一个计算图,在GraphProto中,这些元素都是以列表的方式存储,连接关系是通过Node之间的输入输出进行表达的。 NodeProto...
model = onnx.load("model.onnx") optimized_model = optimizer.optimize(model) ``` 经过优化的模型可以提高推理效率,减少模型运行所需的计算资源,适合部署在嵌入式设备和移动端等资源受限的环境中。 2. 深度学习库的优化支持 除了ONNX库提供的优化方法外,许多深度学习库也提供了针对ONNX模型的优化支持。PyTorch...
model_input: Path, model_output: Path, op_types_to_quantize=None, per_channel=False, reduce_range=False, weight_type=QuantType.QInt8, nodes_to_quantize=None, nodes_to_exclude=None, optimize_model=True, use_external_data_format=False, ...
使用graph_optimize_level参数开启并指定图优化级别,并支持通过shut_down_structures参数指定需关闭优化的图结构。同时,在图优化过程中需要将onnx模型转换为om模型,用户可以通过om_method参数指定转换工具。 根据onnx模型和调用OnnxCalibrator封装量化算法,可以根据模型量化情况配置精度保持策略。 初始化OnnxCalibrator后...
In this post, I discuss how to use ONNX Runtime at a high level. I also go into more depth about how to optimize your models. Figure 1. ONNX Runtime high-level architecture Run a model with ONNX Runtime ONNX Runtime is compatible with most programming languages. As in the other ...
original_model=onnx.load('path/to/the/model.onnx') ## Pick the 'fuse_bn_into_conv' pass. passes=['fuse_bn_into_conv'] ## Apply the optimization on the original model. optimized_model=optimizer.optimize(original_model, passes)
Learn how use of the Open Neural Network Exchange (ONNX) can help to optimize the inference of your machine learning model. Inference or model scoring, is the process of using a deployed model to generate predictions on production data.
Large scale transformer model with ONNX Runtime ONNX(Open Neural Network Exchange) andONNX Runtimeplay an important role in accelerating and simplifying transformer model inference in production. ONNX is an open standard format representing machine learning models. Models trained ...