[GitHub] asitstands closed pull request #10258: [MXNET-145] Remove the dependences of mx.io and mx.initializer on the numpy's global random number generator

[GitBox <gi...@apache.org>]

asitstands closed pull request #10258: [MXNET-145]  Remove the dependences of mx.io and mx.initializer on the numpy's global random number generator
URL: https://github.com/apache/incubator-mxnet/pull/10258
 
 
   

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diff --git a/python/mxnet/initializer.py b/python/mxnet/initializer.py
index 78afa2dbd29..1297c3da9a7 100755
--- a/python/mxnet/initializer.py
+++ b/python/mxnet/initializer.py
@@ -530,9 +530,9 @@ def _init_weight(self, _, arr):
         nout = arr.shape[0]
         nin = np.prod(arr.shape[1:])
         if self.rand_type == "uniform":
-            tmp = np.random.uniform(-1.0, 1.0, (nout, nin))
+            tmp = random.uniform(-1.0, 1.0, shape=(nout, nin)).asnumpy()
         elif self.rand_type == "normal":
-            tmp = np.random.normal(0.0, 1.0, (nout, nin))
+            tmp = random.normal(0.0, 1.0, shape=(nout, nin)).asnumpy()
         u, _, v = np.linalg.svd(tmp, full_matrices=False) # pylint: disable=invalid-name
         if u.shape == tmp.shape:
             res = u
diff --git a/python/mxnet/io.py b/python/mxnet/io.py
index 201414e8f6e..14500182792 100644
--- a/python/mxnet/io.py
+++ b/python/mxnet/io.py
@@ -39,6 +39,8 @@
 from .ndarray import _ndarray_cls
 from .ndarray import array
 from .ndarray import concatenate
+from .ndarray import arange
+from .ndarray.random import shuffle as random_shuffle
 
 class DataDesc(namedtuple('DataDesc', ['name', 'shape'])):
     """DataDesc is used to store name, shape, type and layout
@@ -535,9 +537,9 @@ def _shuffle(data, idx):
         if (isinstance(v, h5py.Dataset) if h5py else False):
             shuffle_data.append((k, v))
         elif isinstance(v, CSRNDArray):
-            shuffle_data.append((k, sparse_array(v.asscipy()[idx], v.context)))
+            shuffle_data.append((k, sparse_array(v.asscipy()[idx.asnumpy()], v.context)))
         else:
-            shuffle_data.append((k, array(v.asnumpy()[idx], v.context)))
+            shuffle_data.append((k, v[idx.as_in_context(v.context)]))
 
     return shuffle_data
 
@@ -651,10 +653,10 @@ def __init__(self, data, label=None, batch_size=1, shuffle=False,
             raise NotImplementedError("`NDArrayIter` only supports ``CSRNDArray``" \
                                       " with `last_batch_handle` set to `discard`.")
 
-        self.idx = np.arange(self.data[0][1].shape[0])
+        self.idx = arange(self.data[0][1].shape[0])
         # shuffle data
         if shuffle:
-            np.random.shuffle(self.idx)
+            random_shuffle(self.idx, out=self.idx)
             self.data = _shuffle(self.data, self.idx)
             self.label = _shuffle(self.label, self.idx)
 


 

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