anirudh2290 commented on a change in pull request #12749: [MXNET-1029] Feature
request: randint operator
URL: https://github.com/apache/incubator-mxnet/pull/12749#discussion_r235789783
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File path: tests/python/unittest/test_random.py
##########
@@ -844,6 +836,48 @@ def testLarge(data, repeat):
testLarge(mx.nd.arange(0, 100000).reshape((10, 10000)), 10)
testLarge(mx.nd.arange(0, 100000).reshape((10000, 10)), 10)
+@with_seed()
+def test_randint():
+ dtypes = ['int32', 'int64']
+ for dtype in dtypes:
+ params = {
+ 'low': -1,
+ 'high': 3,
+ 'shape' : (500, 500),
+ 'dtype' : dtype,
+ 'ctx' : mx.context.current_context()
+ }
+ mx.random.seed(128)
+ ret1 = mx.nd.random.randint(**params).asnumpy()
+ mx.random.seed(128)
+ ret2 = mx.nd.random.randint(**params).asnumpy()
+ assert same(ret1, ret2), \
+ "ndarray test: `%s` should give the same result with the same
seed"
+
+@with_seed()
+def test_randint_extremes():
+ a = mx.nd.random.randint(dtype='int64', low=50000000, high=50000010,
ctx=mx.context.current_context())
+ assert a>=50000000 and a<=50000010
+
+@with_seed()
+def test_randint_generator():
+ ctx = mx.context.current_context()
+ for dtype in ['int32', 'int64']:
+ for low, high in [(50000000,
50001000),(-50000000,-9900),(-500,199),(-2147483647,2147483647)]:
+ scale = high - low
+ buckets, probs = gen_buckets_probs_with_ppf(lambda x:
ss.uniform.ppf(x, loc=low, scale=scale), 5)
+ # Quantize bucket boundaries to reflect the actual dtype and
adjust probs accordingly
+ buckets = np.array(buckets, dtype=dtype).tolist()
+ probs = [(buckets[i][1] - buckets[i][0]) / float(scale) for i in
range(5)]
+ generator_mx = lambda x: mx.nd.random.randint(low, high, shape=x,
ctx=ctx, dtype=dtype).asnumpy()
Review comment:
please add a test without the dtype param.
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