torch.tensor() does not respect device placement when initialized with numpy array #9455
Description
Issue description
torch.tensor() does not respect device placement when initialized with numpy array if a dtype is not given.
Code example
import numpy as np
import torch
x = np.arange(10, dtype=np.int64)
y = torch.tensor(x, device="cuda:0")
print(y.device)
z = torch.tensor(x, device="cuda:0", dtype=torch.int64)
print(z.device)
Output
cpu # y.device - expected: 'cuda:0' but got 'cpu' instead
cuda:0 # z.device - correct
System Info
PyTorch version: 0.4.0
Is debug build: No
CUDA used to build PyTorch: 9.0.176
OS: Ubuntu 16.04.4 LTS
GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.9) 5.4.0 20160609
CMake version: version 3.5.1
Python version: 3.6
Is CUDA available: Yes
CUDA runtime version: 9.0.176
GPU models and configuration:
GPU 0: TITAN Xp
GPU 1: TITAN Xp
GPU 2: TITAN Xp
GPU 3: TITAN Xp
Nvidia driver version: 390.25
cuDNN version: Probably one of the following:
/usr/local/cuda-9.0/lib64/libcudnn.so.7.0.4
/usr/local/cuda-9.0/lib64/libcudnn_static.a
/usr/local/cuda-9.1/lib64/libcudnn.so.7.0.5
/usr/local/cuda-9.1/lib64/libcudnn_static.a
Versions of relevant libraries:
[pip] numpy (1.14.5)
[pip] torch (0.4.0)
[pip] torchvision (0.2.1)
[conda] Could not collect