fix multinomial

mindspore/ops/composite/random_ops.py

@@ -20,7 +20,6 @@ from .. import functional as F
 from ..primitive import constexpr
 from .multitype_ops import _constexpr_utils as const_utils
 from ...common import dtype as mstype
-from ...common.tensor import Tensor
 from ..._checkparam import Validator as validator
 from ..._checkparam import check_int_positive
 from ..._checkparam import Rel
@@ -134,9 +133,7 @@ def multinomial(inputs, num_sample=None, replacement=True, seed=0):
         n_dist = 1
         if len(shape(inputs)) > 1:
             n_dist = shape(inputs)[-2]
-        a = Tensor(0.0, mstype.float32)
-        b = Tensor(1.0, mstype.float32)
-        random_uniform = P.UniformReal(seed=seed)((n_dist * num_sample,), a, b)
+        random_uniform = P.UniformReal(seed=seed)((n_dist * num_sample,))
         if n_dist != 1:
             random_uniform = reshape(random_uniform, (n_dist, num_sample))
         vals = P.RealDiv()(P.Log()(random_uniform), inputs + 1e-6)

tests/st/ops/gpu/test_multinomial_op.py

@@ -30,10 +30,6 @@ def test_multinomial():
     out0 = C.multinomial(x0, 1, True)
     out1 = C.multinomial(x0, 2, True)
     out2 = C.multinomial(x1, 6, True)
-    out3 = C.multinomial(x0, 1, False)
-    out4 = C.multinomial(x0, 2, False)
     assert out0.asnumpy().shape == (1,)
     assert out1.asnumpy().shape == (2,)
     assert out2.asnumpy().shape == (2, 6)
-    assert out3.asnumpy().shape == (1,)
-    assert out4.asnumpy().shape == (2,)