code: def _torch_sparse_csr_tensor(
      indptr, indices, val, torch_sparse_shape
  ):
      with warnings.catch_warnings():
          warnings.simplefilter("ignore", category=UserWarning)
          return torch.sparse_csr_tensor(
              indptr, indices, val, torch_sparse_shape
          )
  
imports: import unittest
  import warnings
  import backend
  import pytest
  import torch
  from dgl.sparse import diag, from_coo, from_csc, from_csr, from_torch_sparse, identity, to_torch_sparse_coo, to_torch_sparse_csc, to_torch_sparse_csr, val_like
  from .utils import rand_coo, rand_csc, rand_csr, rand_diag, sparse_matrix_to_dense
label_desc: Use image node_id 1 for calling a global function with example usage: _torch_sparse_csr_tensor(indptr, indices, val, torch_sparse_shape) and returns: torch