input: dynamic input is missing dimensions in profile

input: dynamic input is missing dimensions in profile

onnx2trt代码报错：

      import numpy as np
      import tensorrt as trt
      import os
      import pycuda.driver as cuda
      import argparse
      def GiB(val):
         return val * 1 << 30
      def ONNX_build_engine(onnx_file_path, write_engine=True):
         # :return: engine
          G_LOGGER = trt.Logger(trt.Logger.WARNING)
         # 1、动态输入第一点必须要写的
          explicit_batch = 1 << (int)(trt.NetworkDefinitionCreationFlag.EXPLICIT_BATCH)
          batch_size = 8  # trt推理时最大支持的batchsize
         with trt.Builder(G_LOGGER) as builder, builder.create_network(explicit_batch) as network, trt.OnnxParser(network,
                                                                                                                   G_LOGGER) as parser:
              builder.max_batch_size = batch_size
              config = builder.create_builder_config()
              config.max_workspace_size = GiB(2)
              config.set_flag(trt.BuilderFlag.FP16)
             print('Loading ONNX file from path {}...'.format(onnx_file_path))
             with open(onnx_file_path, 'rb') as model:
                 print('Beginning ONNX file parsing')
                  parser.parse(model.read())
             print('Completed parsing of ONNX file')
             print('Building an engine from file {}; this may take a while...'.format(onnx_file_path))
             # 重点
              profile = builder.create_optimization_profile()  # 动态输入时候需要 分别为最小输入、常规输入、最大输入
             # 有几个输入就要写几个profile.set_shape 名字和转onnx的时候要对应
             # tensorrt6以后的版本是支持动态输入的，需要给每个动态输入绑定一个profile，用于指定最小值，常规值和最大值，如果超出这个范围会报异常。
              profile.set_shape("input", (1, 3, 128, 128), (4, 3, 128, 128), (16, 3, 128, 128))
              config.add_optimization_profile(profile)
              engine = builder.build_engine(network, config)
             print("Completed creating Engine")
             # 保存engine文件
             if write_engine:
                  engine_file_path = 'efficientnet_b1.trt'
                 with open(engine_file_path, "wb") as f:
                      f.write(engine.serialize())
             return engine
      onnx_file_path = r'skipnet_0712.onnx'
      onnx_file_path = r'model2.onnx'
      onnx_file_path = r'skip_simp2.onnx'
      # onnx_file_path = r'mobileone_0713.onnx'
      write_engine = True
      engine = ONNX_build_engine(onnx_file_path, write_engine)
  
 

  
 
 

原错误代码：

profile.set_shape("inputs", (1, 3, 240, 240), (8, 3, 240, 240), (16, 3, 480, 480))

改之后代码：

profile.set_shape("inputs", (1, 3, 128, 128), (8, 3, 128, 128), (16, 3, 128, 128))

文章来源: blog.csdn.net，作者：AI视觉网奇，版权归原作者所有，如需转载，请联系作者。

原文链接：blog.csdn.net/jacke121/article/details/125903947