[python][onnxruntime]自动获取Provider

import onnxruntime as ort
all_providers = ort.get_all_providers()
print(all_providers)
available_providers = ort.get_available_providers()
print(available_providers)

import os  
import onnxruntime as ort  
  
def get_available_providers():  
    providers = []  
    # 检查 CUDA 是否可用  
    if os.path.exists("/usr/local/cuda/bin/nvcc"):  
        providers.append('CUDAExecutionProvider')  
    # CPU 总是可用的  
    providers.append('CPUExecutionProvider')  
    return providers  
  
def create_ort_session(model_path, providers):  
    # 使用指定的提供者列表创建会话  
    session_options = ort.SessionOptions()  
    session_options.enable_profiling = True  # 可选，开启性能分析  
    session_options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_ALL  
    session = ort.InferenceSession(model_path, sess_options=session_options, providers=providers)  
    return session  
  
# 模型路径  
model_path = 'your_model.onnx'  
  
# 获取可用的执行提供者  
providers = get_available_providers()  
  
# 创建会话  
session = create_ort_session(model_path, providers)  
  
# 现在你可以使用 session 来运行模型了  
# 例如: results = session.run(None, {'input_name': input_data})