Question

我最近看到了一个有关“线性回归”的例子
他在用numpy按dtype = numpy.float64

顺序创建数组时使用的位置

x = numpy.array([1,2,3,4] , dtype = numpy.float64)

我尝试了不使用flaot64的情况，在flaot64中它返回不同的值而不是错误
为什么？

Answer 1

要使用哪种数据类型取决于用例。

 Traceback (most recent call last):

   File "<ipython-input-5-e5959b6300f2>", line 1, in <module>
    runfile('D:/Mask R-CNN/test.py', wdir='D:/Mask R-CNN')

   File "D:\Anaconda3\Anaconda3-5.3.0\envs\cv2\lib\site- 
    packages\spyder_kernels\customize\spydercustomize.py", line 704, in runfile
    execfile(filename, namespace)

   File "D:\Anaconda3\Anaconda3-5.3.0\envs\cv2\lib\site- 
    packages\spyder_kernels\customize\spydercustomize.py", line 108, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

   File "D:/Mask R-CNN/test.py", line 49, in <module>
    model.load_weights(COCO_MODEL_PATH, by_name=True, exclude=[ 
   "mrcnn_class_logits", "mrcnn_bbox_fc"])

   File "D:\Mask R-CNN\mrcnn\model.py", line 2131, in load_weights
    saving.load_weights_from_hdf5_group_by_name(f, layers)

   File "D:\Anaconda3\Anaconda3-5.3.0\envs\cv2\lib\site- 
    packages\keras\engine\saving.py", line 1104, in 
    load_weights_from_hdf5_group_by_name
    g = f[name]

   File "h5py\_objects.pyx", line 54, in h5py._objects.with_phil.wrapper

   File "h5py\_objects.pyx", line 55, in h5py._objects.with_phil.wrapper

   File "D:\Anaconda3\Anaconda3-5.3.0\envs\cv2\lib\site- 
    packages\h5py\_hl\group.py", line 177, in __getitem__
    oid = h5o.open(self.id, self._e(name), lapl=self._lapl)

   File "h5py\_objects.pyx", line 54, in h5py._objects.with_phil.wrapper

   File "h5py\_objects.pyx", line 55, in h5py._objects.with_phil.wrapper

   File "h5py\h5o.pyx", line 190, in h5py.h5o.open

   KeyError: 'Unable to open object (wrong B-tree signature)'

此处数组的元素类型为float64（双精度浮点数）。

    x = numpy.array([1,2,3,4] , dtype = numpy.float64)

此处元素的类型为int64（整数）

是否需要使用“ numpy.float64”？

1 个答案: