eric-haibin-lin commented on a change in pull request #7911: More sparse
related docs
URL: https://github.com/apache/incubator-mxnet/pull/7911#discussion_r141240857
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File path: python/mxnet/test_utils.py
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@@ -134,22 +134,32 @@ def _get_uniform_dataset_csr(num_rows, num_cols,
density=0.1, dtype=None,
"""Returns CSRNDArray with uniform distribution
This generates a csr matrix with totalnnz unique randomly chosen numbers
from num_rows*num_cols and arranges them in the 2d array in the
- following way: row_index = (random_number_generated / num_rows)
+ following way:
+ row_index = (random_number_generated / num_rows)
col_index = random_number_generated - row_index * num_cols
"""
_validate_csr_generation_inputs(num_rows, num_cols, density,
distribution="uniform")
- from scipy import sparse as spsp
- csr = spsp.rand(num_rows, num_cols, density, dtype=dtype, format="csr")
- if data_init is not None:
- csr.data.fill(data_init)
- if shuffle_csr_indices is True:
- shuffle_csr_column_indices(csr)
- result = mx.nd.sparse.csr_matrix(csr.data, csr.indptr, csr.indices,
- (num_rows, num_cols), dtype=dtype)
+ try:
+ from scipy import sparse as spsp
Review comment:
The code still works without scipy. Since it's only related to the sparse
feature in mxnet it's now kept as an optional dependency.
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