# Example 2 b
ip_tensor=torch.randn(2,1,3,1)
print(ip_tensor)
print(f"Input Tensor shape:{ip_tensor.shape}\n")
op_tensor=torch.squeeze(ip_tensor,dim=1)
print(op_tensor)
print(f"Output Tensor shape:{op_tensor.shape}\n")

# Output

tensor([[[[-1.7004],
          [-0.1863],
          [ 1.1550]]],


        [[[-1.1890],
          [-0.4821],
          [-0.3731]]]])
Input Tensor shape:torch.Size([2, 1, 3, 1])

tensor([[[-1.7004],
         [-0.1863],
         [ 1.1550]],

        [[-1.1890],
         [-0.4821],
         [-0.3731]]])
Output Tensor shape:torch.Size([2, 3, 1])