错误信息“expected type 'int', got 'float' instead”直译为“期望类型为'int',但得到了'float'”。这表示在程序的某个环节,预期应该有一个整数类型的值,但实际上却接收到了一个浮点数类型的值。这种类型不匹配可能导致程序运行出错,因为整数和浮点数在内存中的存储方式、运算规则等方面存在差异。 2. 识别出...
make_tensor_proto _AssertCompatible(values, dtype) C:\Users\saivi\anaconda3\envs\mention\lib\site-packages\tensorflow\python\framework\tensor_util.py:331 _AssertCompatible (dtype.name, repr(mismatch), type(mismatch).__name__)) TypeError: Expected int32, got 1e-07 of type 'float' instead....
File"E:\Python\lib\site-packages\PIL\Image.py", line 2192,inresizereturnself._new(self.im.resize(size, resample, box)) TypeError: integer argument expected, got float 意思就是得到的是float数据,不是整数。这里需要获取整数。所以需要更改一下:正确代码如下: fromPILimportImage image=Image.open('....
I am trying to use the NUTS sampling example from the Modeling with JointDistribution example notebook to sample from my own model. Recall that the key function that contains the sampler logic is as follows: @tf.function(autograph=False,...
在pytorch中float32为float类型,而float64则为double类型,注意tensor的数据类型。 可以通过指定数据类型来获得所需要的类型数据。 torch.zeros([self.batch_size, self.num_layers, self.hidden_size], dt
在用函数raw = mne.io.read_raw_edf(f, verbose=False) 读取一个EEG(心音)数据集的时候,碰到错误:TypeError: expected dtype object, got 'numpy.dtype[float64]'。 然后,使用函数 paddle.set_default_dtype("float64") 将默认数据类型置为float64,但问题还是没有解决 各位同行,请问这个问题该如何解决? 0 ...
今天在使用Numpy的时候,打印array的时候突然出现了TypeError: integer argument expected, got float 这个报错,部分代码如下: importnumpyasnp importpandasaspd # 设置显示精度 np.set_printoptions(np.inf) df=pd.read_hdf('db.h5',mode='r',key='600000') ...
在PyTorch 中,如遇到了 "RuntimeError: Expected object of scalar type Float but got scalar type Long for argument",首先先定位是那裡報錯了,再者,將資料型態調整為函式所能接受的即可。
The mentioned error message occurs when an operation receives an object of a different type instead of astringorbytes-likeobject as input, as expected. The sample objects of the different types areint,float, andlist. Here are sample codes that cause this error: ...
UPDATE: I Know I could implement an Inception Like block with functions but I wanted it to be a layer so I could share the layer across inputs. Its not obvious to to me how to do that with function blocks. I added a compute_output_shape to the mix and that fixed the output shape...