code: def skipgram_batch(centers, contexts, num_tokens, dtype, index_dtype):
      
      contexts = mx.nd.array(contexts[2], dtype=index_dtype)
      indptr = mx.nd.arange(len(centers) + 1)
      centers = mx.nd.array(centers, dtype=index_dtype)
      centers_csr = mx.nd.sparse.csr_matrix(
          (mx.nd.ones(centers.shape), centers, indptr), dtype=dtype,
          shape=(len(centers), num_tokens))
      return centers_csr, contexts, centers
docs: Create a batch for SG training objective.