在使用python试图执行代码

model = tf.keras.Sequential([
    tf.keras.layers.Dense(32, activation='relu', input_shape=(1,)),
    tf.keras.layers.Dense(32, activation='relu'),
    tf.keras.layers.Dense(1)
])

后出现报错，python内核崩溃，报错信息如下：

/usr/lib/python3.12/site-packages/keras/src/layers/core/dense.py:87: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.
  super().__init__(activity_regularizer=activity_regularizer, **kwargs)
/usr/include/c++/14.1.1/bits/stl_vector.h:1130: constexpr std::vector<_Tp, _Alloc>::reference std::vector<_Tp, _Alloc>::operator[](size_type) [with _Tp = pybind11::object; _Alloc = std::allocator<pybind11::object>; reference = pybind11::object&; size_type = long unsigned int]: Assertion '__n < this->size()' failed.

[1]    11798 IOT instruction (core dumped)  ipython

我已尝试在google和tensorflow文档寻求解决方案，但是没有结果

附：系统环境 python版本Python 3.12.7，tensorflow版本2.18.0，cuda版本如下：

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2024 NVIDIA Corporation
Built on Thu_Sep_12_02:18:05_PDT_2024
Cuda compilation tools, release 12.6, V12.6.77
Build cuda_12.6.r12.6/compiler.34841621_0