How to convert numpy array(float data) to torch tensor?
test = ['0.01171875', '0.01757812', '0.02929688']  
test = np.array(test).astype(float)   
print(test)  
-&gt;[0.01171875 0.01757812 0.02929688]


test_torch = torch.from_numpy(test)  
test_torch  
-&gt;tensor([0.0117, 0.0176, 0.0293], dtype=torch.float64)

It looks like from_numpy() loses some precision there... If I want to convert this float data exactly the same, what kind of functions do I use?

The data precision is the same, it's just that the format used by PyTorch to print the values is different, it will round the floats down:
&gt;&gt;&gt; test_torch = torch.from_numpy(test)
&gt;&gt;&gt; test_torch
tensor([0.0117, 0.0176, 0.0293], dtype=torch.float64)

You can check that it matches your original input by converting to a list with tolist:
&gt;&gt;&gt; test_torch.tolist()
[0.01171875, 0.01757812, 0.02929688]

