How to Convert Pytorch tensor to Numpy array?
To convert a PyTorch tensor to a NumPy array, you can use the numpy() method provided by the PyTorch tensor object. Here's how you can do it:
- First, ensure you have both PyTorch and NumPy installed. If not, install them:
pip install torch numpy
- Use the
numpy()method to convert a PyTorch tensor to a NumPy array:
import torch # Create a PyTorch tensor tensor = torch.tensor([1, 2, 3, 4, 5]) # Convert tensor to NumPy array numpy_array = tensor.numpy() print(type(numpy_array)) # <class 'numpy.ndarray'> print(numpy_array) # [1 2 3 4 5]
Note:
- The resulting NumPy array and the original tensor share the same memory. This means if you modify the NumPy array, the tensor will also be modified, and vice-versa.
- If the tensor is on the GPU (CUDA), you need to first move it to the CPU before converting it to a NumPy array. You can do this using the
cpu()method:
# Assume tensor is on CUDA tensor = torch.tensor([1, 2, 3, 4, 5], device='cuda') # Move tensor to CPU and then convert to NumPy array numpy_array = tensor.cpu().numpy()
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