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@ -86,53 +86,53 @@ def set_seed(seed):
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>>>
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>>> # 3. If neither global seed nor op seed is set, mindspore.ops.composite.random_ops and
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>>> # mindspore.nn.probability.distribution will choose a random seed:
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>>> c1 = C.uniform((1, 4)) # C1
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>>> c2 = C.uniform((1, 4)) # C2
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>>> c1 = C.uniform((1, 4), 1.0, 2.0) # C1
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>>> c2 = C.uniform((1, 4), 1.0, 2.0) # C2
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>>> Rerun the program will get different results:
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>>> c1 = C.uniform((1, 4)) # C3
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>>> c2 = C.uniform((1, 4)) # C4
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>>> c1 = C.uniform((1, 4), 1.0, 2.0) # C3
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>>> c2 = C.uniform((1, 4), 1.0, 2.0) # C4
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>>>
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>>> # 4. If global seed is set, but op seed is not set, mindspore.ops.composite.random_ops and
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>>> # mindspore.nn.probability.distribution will caculate a seed according to global seed and
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>>> # default op seed. Each call will change the default op seed, thus each call get different
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>>> # results.
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>>> set_seed(1234)
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>>> c1 = C.uniform((1, 4)) # C1
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>>> c2 = C.uniform((1, 4)) # C2
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>>> c1 = C.uniform((1, 4), 1.0, 2.0) # C1
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>>> c2 = C.uniform((1, 4), 1.0, 2.0) # C2
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>>> # Rerun the program will get the same results:
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>>> set_seed(1234)
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>>> c1 = C.uniform((1, 4)) # C1
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>>> c2 = C.uniform((1, 4)) # C2
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>>> c1 = C.uniform((1, 4), 1.0, 2.0) # C1
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>>> c2 = C.uniform((1, 4), 1.0, 2.0) # C2
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>>>
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>>> # 5. If both global seed and op seed are set, mindspore.ops.composite.random_ops and
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>>> # mindspore.nn.probability.distribution will caculate a seed according to global seed and
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>>> # op seed counter. Each call will change the op seed counter, thus each call get different
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>>> # results.
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>>> set_seed(1234)
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>>> c1 = C.uniform((1, 4), seed=2) # C1
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>>> c2 = C.uniform((1, 4), seed=2) # C2
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>>> c1 = C.uniform((1, 4), 1.0, 2.0, seed=2) # C1
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>>> c2 = C.uniform((1, 4), 1.0, 2.0, seed=2) # C2
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>>> Rerun the program will get the same results:
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>>> set_seed(1234)
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>>> c1 = C.uniform((1, 4), seed=2) # C1
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>>> c2 = C.uniform((1, 4), seed=2) # C2
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>>> c1 = C.uniform((1, 4), 1.0, 2.0, seed=2) # C1
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>>> c2 = C.uniform((1, 4), 1.0, 2.0, seed=2) # C2
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>>>
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>>> # 6. If op seed is set but global seed is not set, 0 will be used as global seed. Then
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>>> # mindspore.ops.composite.random_ops and mindspore.nn.probability.distribution act as in
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>>> # condition 5.
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>>> c1 = C.uniform((1, 4), seed=2) # C1
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>>> c2 = C.uniform((1, 4), seed=2) # C2
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>>> #Rerun the program will get the same results:
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>>> c1 = C.uniform((1, 4), seed=2) # C1
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>>> c2 = C.uniform((1, 4), seed=2) # C2
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>>> c1 = C.uniform((1, 4), 1.0, 2.0, seed=2) # C1
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>>> c2 = C.uniform((1, 4), 1.0, 2.0, seed=2) # C2
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>>> # Rerun the program will get the same results:
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>>> c1 = C.uniform((1, 4), 1.0, 2.0, seed=2) # C1
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>>> c2 = C.uniform((1, 4), 1.0, 2.0, seed=2) # C2
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>>>
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>>> # 7. Recall set_seed() in the program will reset numpy seed and op seed counter of
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>>> # mindspore.ops.composite.random_ops and mindspore.nn.probability.distribution.
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>>> set_seed(1234)
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>>> np_1 = np.random.normal(0, 1, [1]).astype(np.float32) # A1
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>>> c1 = C.uniform((1, 4), seed=2) # C1
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>>> c1 = C.uniform((1, 4), 1.0, 2.0, seed=2) # C1
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>>> set_seed(1234)
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>>> np_2 = np.random.normal(0, 1, [1]).astype(np.float32) # still get A1
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>>> c2 = C.uniform((1, 4), seed=2) # still get C1
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>>> c2 = C.uniform((1, 4), 1.0, 2.0, seed=2) # still get C1
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"""
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if not isinstance(seed, int):
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raise TypeError("The seed must be type of int.")
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