code: def save_sparse_csr(filename, matrix, metadata=None):
      data = {
          "data": matrix.data,
          "indices": matrix.indices,
          "indptr": matrix.indptr,
          "shape": matrix.shape,
          "metadata": metadata,
      }
      np.savez(filename, **data)
  
file_path: ParlAI/parlai/agents/tfidf_retriever/utils.py
imports: import regex
  import unicodedata
  import numpy
  import scipy.sparse
  from sklearn.utils import murmurhash3_32
label_desc: Use image node_id 1 for calling a global function with example usage: save_sparse_csr(filename, matrix, metadata) without return types