pb文件生成event... 用tensorboard查看

博客提及将PB文件进行转储的事件,涉及信息技术中文件处理相关内容。

将PB文件转储我的.pb文件事件

import tensorflow as tf
from tensorflow.python.platform import gfile

INCEPTION_LOG_DIR = '/tmp/inception_v3_log'

if not os.path.exists(INCEPTION_LOG_DIR):
    os.makedirs(INCEPTION_LOG_DIR)
with tf.Session() as sess:
    model_filename = './model/tensorflow_inception_v3_stripped_optimized_quantized.pb'
    with gfile.FastGFile(model_filename, 'rb') as f:
        graph_def = tf.GraphDef()
        graph_def.ParseFromString(f.read())
        _ = tf.import_graph_def(graph_def, name='')
    #writer = tf.train.SummaryWriter(INCEPTION_LOG_DIR, graph_def)
    writer=tf.summary.FileWriter(INCEPTION_LOG_DIR, graph_def)                                                
    writer.close()

 

D:\anaconda3\envs\pytorch-tf-gpu-py310\python.exe D:\PycharmProjects\pythonProject2\tb.py Traceback (most recent call last): File "D:\PycharmProjects\pythonProject2\tb.py", line 1, in <module> from torch.utils.tensorboard import SummaryWriter File "D:\anaconda3\envs\pytorch-tf-gpu-py310\lib\site-packages\torch\utils\tensorboard\__init__.py", line 12, in <module> from .writer import FileWriter, SummaryWriter File "D:\anaconda3\envs\pytorch-tf-gpu-py310\lib\site-packages\torch\utils\tensorboard\writer.py", line 13, in <module> from tensorboard.compat.proto import event_pb2 File "D:\anaconda3\envs\pytorch-tf-gpu-py310\lib\site-packages\tensorboard\compat\proto\event_pb2.py", line 17, in <module> from tensorboard.compat.proto import summary_pb2 as tensorboard_dot_compat_dot_proto_dot_summary__pb2 File "D:\anaconda3\envs\pytorch-tf-gpu-py310\lib\site-packages\tensorboard\compat\proto\summary_pb2.py", line 17, in <module> from tensorboard.compat.proto import tensor_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__pb2 File "D:\anaconda3\envs\pytorch-tf-gpu-py310\lib\site-packages\tensorboard\compat\proto\tensor_pb2.py", line 16, in <module> from tensorboard.compat.proto import resource_handle_pb2 as tensorboard_dot_compat_dot_proto_dot_resource__handle__pb2 File "D:\anaconda3\envs\pytorch-tf-gpu-py310\lib\site-packages\tensorboard\compat\proto\resource_handle_pb2.py", line 16, in <module> from tensorboard.compat.proto import tensor_shape_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__shape__pb2 File "D:\anaconda3\envs\pytorch-tf-gpu-py310\lib\site-packages\tensorboard\compat\proto\tensor_shape_pb2.py", line 36, in <module> _descriptor.FieldDescriptor( File "D:\anaconda3\envs\pytorch-tf-gpu-py310\lib\site-packages\google\protobuf\descriptor.py", line 621, in __new__ _message.Message._CheckCalledFromGeneratedFile() TypeError: Descriptors cannot be created directly. If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0. If you cannot immediately regenerate your protos, some other possible workarounds are: 1. Downgrade the protobuf package to 3.20.x or lower. 2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower). More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates 进程已结束,退出代码为 1怎么回事
最新发布
08-06
File "c:/Users/lianlian/Downloads/yolov5-6.0/yolov5-6.0/train.py", line 48, in <module> from utils.loggers.wandb.wandb_utils import check_wandb_resume File "c:\Users\lianlian\Downloads\yolov5-6.0\yolov5-6.0\utils\loggers\__init__.py", line 10, in <module> from torch.utils.tensorboard import SummaryWriter File "D:\anaconda3\envs\yolo_v5\lib\site-packages\torch\utils\tensorboard\__init__.py", line 8, in <module> from .writer import FileWriter, SummaryWriter # noqa F401 File "D:\anaconda3\envs\yolo_v5\lib\site-packages\torch\utils\tensorboard\writer.py", line 9, in <module> from tensorboard.compat.proto.event_pb2 import SessionLog File "D:\anaconda3\envs\yolo_v5\lib\site-packages\tensorboard\compat\proto\event_pb2.py", line 17, in <module> from tensorboard.compat.proto import summary_pb2 as tensorboard_dot_compat_dot_proto_dot_summary__pb2 File "D:\anaconda3\envs\yolo_v5\lib\site-packages\tensorboard\compat\proto\summary_pb2.py", line 17, in <module> from tensorboard.compat.proto import tensor_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__pb2 File "D:\anaconda3\envs\yolo_v5\lib\site-packages\tensorboard\compat\proto\tensor_pb2.py", line 16, in <module> from tensorboard.compat.proto import resource_handle_pb2 as tensorboard_dot_compat_dot_proto_dot_resource__handle__pb2 File "D:\anaconda3\envs\yolo_v5\lib\site-packages\tensorboard\compat\proto\resource_handle_pb2.py", line 16, in <module> from tensorboard.compat.proto import tensor_shape_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__shape__pb2 File "D:\anaconda3\envs\yolo_v5\lib\site-packages\tensorboard\compat\proto\tensor_shape_pb2.py", line 36, in <module> _descriptor.FieldDescriptor( File "D:\anaconda3\envs\yolo_v5\lib\site-packages\google\protobuf\descriptor.py", line 621, in __new__ _message.Message._CheckCalledFromGeneratedFile() TypeError: Descriptors cannot be created directly. If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0. If you cannot immediately regenerate your protos, some other possible workarounds are: 1. Downgrade the protobuf package to 3.20.x or lower. 2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower). More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates这个报错是为什么
03-28
C:\Users\30944\.conda\envs\beshepytorch\python.exe D:/0/BSgithub/yolov5-7.0/train.py Traceback (most recent call last): File "D:\0\BSgithub\yolov5-7.0\train.py", line 55, in <module> from utils.loggers import Loggers File "D:\0\BSgithub\yolov5-7.0\utils\loggers\__init__.py", line 12, in <module> from torch.utils.tensorboard import SummaryWriter File "C:\Users\30944\.conda\envs\beshepytorch\lib\site-packages\torch\utils\tensorboard\__init__.py", line 12, in <module> from .writer import FileWriter, SummaryWriter # noqa: F401 File "C:\Users\30944\.conda\envs\beshepytorch\lib\site-packages\torch\utils\tensorboard\writer.py", line 12, in <module> from tensorboard.compat.proto import event_pb2 File "C:\Users\30944\.conda\envs\beshepytorch\lib\site-packages\tensorboard\compat\proto\event_pb2.py", line 17, in <module> from tensorboard.compat.proto import summary_pb2 as tensorboard_dot_compat_dot_proto_dot_summary__pb2 File "C:\Users\30944\.conda\envs\beshepytorch\lib\site-packages\tensorboard\compat\proto\summary_pb2.py", line 17, in <module> from tensorboard.compat.proto import tensor_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__pb2 File "C:\Users\30944\.conda\envs\beshepytorch\lib\site-packages\tensorboard\compat\proto\tensor_pb2.py", line 16, in <module> from tensorboard.compat.proto import resource_handle_pb2 as tensorboard_dot_compat_dot_proto_dot_resource__handle__pb2 File "C:\Users\30944\.conda\envs\beshepytorch\lib\site-packages\tensorboard\compat\proto\resource_handle_pb2.py", line 16, in <module> from tensorboard.compat.proto import tensor_shape_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__shape__pb2 File "C:\Users\30944\.conda\envs\beshepytorch\lib\site-packages\tensorboard\compat\proto\tensor_shape_pb2.py", line 36, in <module> _descriptor.FieldDescriptor( File "C:\Users\30944\.conda\envs\beshepytorch\lib\site-packages\google\protobuf\descriptor.py", line 621, in __new__ _message.Message._CheckCalledFromGeneratedFile() TypeError: Descriptors cannot be created directly. If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0. If you cannot immediately regenerate your protos, some other possible workarounds are: 1. Downgrade the protobuf package to 3.20.x or lower. 2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower). More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates
05-11
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