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[Solved] Cannot convert list to array: ValueError: only one element tensors can be converted to Python scalars

Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error Cannot convert list to array: ValueError: only one element tensors can be converted to Python scalars in python. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

How Cannot convert list to array: ValueError: only one element tensors can be converted to Python scalars Error Occurs?

Today I get the following error Cannot convert list to array: ValueError: only one element tensors can be converted to Python scalars in python.

How To Solve Cannot convert list to array: ValueError: only one element tensors can be converted to Python scalars Error ?

  1. How To Solve Cannot convert list to array: ValueError: only one element tensors can be converted to Python scalars Error ?

    To Solve Cannot convert list to array: ValueError: only one element tensors can be converted to Python scalars Error It seems like you have a list of tensors. For each tensor you can see its size() (no need to convert to list/numpy). If you insist, you can convert a tensor to numpy array using numpy():

  2. Cannot convert list to array: ValueError: only one element tensors can be converted to Python scalars

    To Solve Cannot convert list to array: ValueError: only one element tensors can be converted to Python scalars Error It seems like you have a list of tensors. For each tensor you can see its size() (no need to convert to list/numpy). If you insist, you can convert a tensor to numpy array using numpy():

Solution 1

It seems like you have a list of tensors. For each tensor you can see its size() (no need to convert to list/numpy). If you insist, you can convert a tensor to numpy array using numpy():

Return a list of tensor shapes:

>> [t.size() for t in my_list_of_tensors]

Returns a list of numpy arrays:

>> [t.numpy() for t in my_list_of_tensors]

In terms of performance, it is always best to avoid casting of tensors into numpy arrays, as it may incur sync of device/host memory. If you only need to check the shape of a tensor, use size() function.

Solution 2

The simplest way to convert pytorch tensor to numpy array is:

nparray = tensor.numpy()

Also, for size and shape:

tensor_size = tensor.size()
tensor_shape = tensor.shape()
tensor_size
>>> (1080)
tensor_shape
>>> (32, 3, 128, 128)

Summery

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you? Thank You.

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