-> Tensor: Expected a value of type 'number' for argument 'other' but instead found type 'bool'. aten::mul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!): Expected a value of type 'Tensor' for argument 'other' but instead found type 'bool'. aten::mul.Scalar...
Ah, I see, thecopy_call. Still, if we replace the weight Tensor instead (ensuring the proper shape upon creation), it also works, e.g: kernel = torch.from_numpy(np.random.random_sample((1, 1, 1, 3))).double() ... model[0].weight.data = kernel ...
/pytorch/aten/src/ATen/native/IndexingUtils.h:20: UserWarning: indexing with dtype torch.uint8 is now deprecated, please use a dtype torch.bool instead. RuntimeError: zero-dimensional tensor (at position 0) cannot be concatenated object of type <class 'numpy.float64'> cannot be safely interp...
根据你提供的错误信息,实际参数是(tensor, NoneType, bool, tuple)。这里的问题在于第二个参数是NoneType,这通常表示没有提供输出尺寸或比例因子。 根据期望参数和实际参数的不匹配情况,调整函数调用: 你需要确保为upsample_bicubic2d函数提供正确的参数。如果函数需要输出尺寸,你应该提供一个整数元组作为第二个参数。
使用pytorch 带有就地操作的方法,一般是方法名后跟一个下划线 “_”,如tensor.add_(),tensor.scatter_(),F.relu_() 使用就地操作的运算符,如y += x,y *= x 4.避免中间变量 forward函数里避免使用不必要的中间变量,尽量在之前已申请的内存里进行操作,如下代码就使用太多中间变量,占用大量不必要的显存: ...
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/tensor_util.py", line 302, in _AssertCompatible (dtype.name, repr(mismatch), type(mismatch).name)) TypeError: Expected int32, got list containing Tensors of type '_Message' instead. ...