D:\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\dtypes.py:585: FutureWarning: In the future `np.object` will be defined as the corresponding NumPy scalar. np.object, Traceback (most recent call last): File "F:\KXZB\LSTM.py", line 3, in <module>

时间: 2023-07-06 09:31:27 浏览: 70
这个错误是由于 TensorFlow 库版本太旧造成的。在新版本的 TensorFlow 中,`np.object` 已经被更改为 `object`。您可以尝试更新 TensorFlow 库,或者使用以下代码解决该问题: ``` import numpy as np import tensorflow.compat.v1 as tf tf.disable_v2_behavior() # your code here ``` 这个代码段将 TensorFlow 切换到使用 v1 版本的 API,可以避免上述错误。
相关问题

D:\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\dtypes.py:585: FutureWarning: In the future `np.object` will be defined as the corresponding NumPy scalar. np.object,

这个错误是由于您所使用的 TensorFlow 库版本比较旧,而在较新的版本中,`np.object` 已经被更改为 `object`。因此,您可以尝试更新 TensorFlow 库的版本来解决这个问题。可以使用以下命令来更新 TensorFlow 库: ``` pip install --upgrade tensorflow ``` 如果您已经使用了 Anaconda 管理您的 Python 包,您可以使用以下命令来更新 TensorFlow 库: ``` conda update tensorflow ``` 更新完成后,您可以重新运行您的代码,应该不再出现该错误。

File "D:\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\sparse_tensor.py", line 28, in <module> from tensorflow.python.framework import constant_op File "D:\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\constant_op.py", line 29, in <module> from tensorflow.python.eager import execute File "D:\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\eager\execute.py", line 27, in <module> from tensorflow.python.framework import dtypes File "D:\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\dtypes.py", line 585, in <module> np.object, File "D:\Anaconda3\envs\tensorflow\lib\site-packages\numpy\__init__.py", line 305, in __getattr__ raise AttributeError(__former_attrs__[attr])

这个错误可能是由于您的 TensorFlow 库与 NumPy 库版本不兼容造成的。您可以尝试更新 NumPy 库,或者降低 TensorFlow 库的版本。以下是一些可能的解决方案: 1. 更新 NumPy 库: ``` pip install --upgrade numpy ``` 2. 降低 TensorFlow 库的版本: ``` pip install tensorflow==2.1.0 ``` 请注意,这个命令将 TensorFlow 库版本降级到 2.1.0,您可以根据需要更改版本号。 更新或降级库版本后,您可以重新运行代码,应该不再出现该错误。

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D:\Anaconda\envs\tf1\python.exe C:/Users/夏芷琳/Desktop/VAE-LSTM-for-anomaly-detection-master/codes/train.py Traceback (most recent call last): File "C:/Users/夏芷琳/Desktop/VAE-LSTM-for-anomaly-detection-master/codes/train.py", line 2, in <module> import tensorflow as tf File "D:\Anaconda\envs\tf1\lib\site-packages\tensorflow\__init__.py", line 24, in <module> from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import File "D:\Anaconda\envs\tf1\lib\site-packages\tensorflow\python\__init__.py", line 52, in <module> from tensorflow.core.framework.graph_pb2 import * File "D:\Anaconda\envs\tf1\lib\site-packages\tensorflow\core\framework\graph_pb2.py", line 15, in <module> from tensorflow.core.framework import node_def_pb2 as tensorflow_dot_core_dot_framework_dot_node__def__pb2 File "D:\Anaconda\envs\tf1\lib\site-packages\tensorflow\core\framework\node_def_pb2.py", line 15, in <module> from tensorflow.core.framework import attr_value_pb2 as tensorflow_dot_core_dot_framework_dot_attr__value__pb2 File "D:\Anaconda\envs\tf1\lib\site-packages\tensorflow\core\framework\attr_value_pb2.py", line 15, in <module> from tensorflow.core.framework import tensor_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__pb2 File "D:\Anaconda\envs\tf1\lib\site-packages\tensorflow\core\framework\tensor_pb2.py", line 15, in <module> from tensorflow.core.framework import resource_handle_pb2 as tensorflow_dot_core_dot_framework_dot_resource__handle__pb2 File "D:\Anaconda\envs\tf1\lib\site-packages\tensorflow\core\framework\resource_handle_pb2.py", line 41, in <module> serialized_options=None, file=DESCRIPTOR), File "D:\Anaconda\envs\tf1\lib\site-packages\google\protobuf\descriptor.py", line 561, in __new__ _message.Message._CheckCalledFromGeneratedFile() TypeError: Descriptors cannot not 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

Traceback (most recent call last): File "/home/chb/anaconda3/envs/deepmd2/lib/python3.10/site-packages/deepmd/env.py", line 373, in get_module module = tf.load_op_library(str(module_file)) File "/home/chb/anaconda3/envs/deepmd2/lib/python3.10/site-packages/tensorflow/python/framework/load_library.py", line 54, in load_op_library lib_handle = py_tf.TF_LoadLibrary(library_filename) tensorflow.python.framework.errors_impl.NotFoundError: /home/chb/anaconda3/envs/deepmd2/lib/python3.10/site-packages/deepmd/op/libdeepmd_op.so: undefined symbol: _ZN6deepmd33prod_env_mat_a_nvnmd_quantize_cpuIdEEvPT_S2_S2_PiPKS1_PKiRKNS_10InputNlistEiS5_S5_iiffSt6vectorIiSaIiEE The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/chb/anaconda3/envs/deepmd2/bin/dp", line 7, in <module> from deepmd.entrypoints.main import main File "/home/chb/anaconda3/envs/deepmd2/lib/python3.10/site-packages/deepmd/__init__.py", line 10, in <module> import deepmd.utils.network as network File "/home/chb/anaconda3/envs/deepmd2/lib/python3.10/site-packages/deepmd/utils/__init__.py", line 2, in <module> from .data import ( File "/home/chb/anaconda3/envs/deepmd2/lib/python3.10/site-packages/deepmd/utils/data.py", line 11, in <module> from deepmd.env import ( File "/home/chb/anaconda3/envs/deepmd2/lib/python3.10/site-packages/deepmd/env.py", line 459, in <module> op_module = get_module("deepmd_op") File "/home/chb/anaconda3/envs/deepmd2/lib/python3.10/site-packages/deepmd/env.py", line 430, in get_module raise RuntimeError(error_message) from e RuntimeError: This deepmd-kit package is inconsitent with TensorFlow Runtime, thus an error is raised when loading deepmd_op. You need to rebuild deepmd-kit against this TensorFlow runtime. WARNING: devtoolset on RHEL6 and RHEL7 does not support _GLIBCXX_USE_CXX11_ABI=1. See https://bugzilla.redhat.com/show_bug.cgi?id=1546704

Traceback (most recent call last): File "D:\Pycharm\PyCharm 2020.2.5\plugins\python\helpers\pydev\pydevd.py", line 1448, in _exec pydev_imports.execfile(file, globals, locals) # execute the script File "D:\Pycharm\PyCharm 2020.2.5\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile exec(compile(contents+"\n", file, 'exec'), glob, loc) File "C:/Users/wz/Desktop/Framework to practice/多尺度Demo/demo.py", line 269, in <module> summary(net, (3, 224, 224)) File "D:\anaconda3\envs\pytorch\lib\site-packages\torchsummary\torchsummary.py", line 72, in summary model(*x) File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "C:/Users/wz/Desktop/Framework to practice/多尺度Demo/demo.py", line 228, in forward out = self.MSB3d(out) File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1148, in _call_impl result = forward_call(*input, **kwargs) File "C:/Users/wz/Desktop/Framework to practice/多尺度Demo/demo.py", line 135, in forward self.branch3x3dbl_3b(branch3x3dbl), File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1148, in _call_impl result = forward_call(*input, **kwargs) File "C:/Users/wz/Desktop/Framework to practice/多尺度Demo/demo.py", line 42, in forward x = self.conv(x) File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1148, in _call_impl result = forward_call(*input, **kwargs) File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\conv.py", line 457, in forward return self._conv_forward(input, self.weight, self.bias) File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\conv.py", line 453, in _conv_forward return F.conv2d(input, weight, bias, self.stride, RuntimeError: Given groups=1, weight of size [256, 256, 3, 1], expected input[2, 128, 14, 14] to have 256 channels, but got 128 channels instead

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