Home
last modified time | relevance | path

Searched refs:randint (Results 1 – 25 of 140) sorted by relevance

123456

/third_party/mindspore/tests/ut/python/ops/
Dtest_tensor_slice.py657 input_3d_np = np.random.randint(3, size=(3, 4, 5)).astype(np.int32)
774 Tensor(np.random.randint(6, size=(5, 4)), mstype.int32)],
779 Tensor(np.random.randint(6, size=(3, 4, 5)), mstype.int32),
780 Tensor(np.random.randint(7, size=(4, 5)), mstype.int32)],
785 Tensor(np.random.randint(6, size=(3, 4, 5)), mstype.int32),
786 Tensor(np.random.randint(7, size=(4, 5)), mstype.int32),
787 Tensor(np.random.randint(8, size=(5, 3, 4, 5)), mstype.int32)],
792 Tensor(np.random.randint(3, size=(3, 4, 5)), mstype.int32),
793 Tensor(np.random.randint(4, size=(4, 5)), mstype.int32)],
798 Tensor(np.random.randint(3, size=(3, 4, 5)), mstype.int32),
[all …]
/third_party/mindspore/tests/st/ops/cpu/
Dtest_arithmetic_op.py89 x0_np = np.random.randint(1, 100, (2, 3, 4, 4)).astype(np.float32) * prop
90 y0_np = np.random.randint(1, 100, (2, 3, 4, 4)).astype(np.float32) * prop
91 x1_np = np.random.randint(1, 100, (2, 3, 4, 4)).astype(np.float32) * prop
92 y1_np = np.random.randint(1, 100, (2, 1, 4, 4)).astype(np.float32) * prop
93 x2_np = np.random.randint(1, 100, (2, 1, 1, 4)).astype(np.float16) * prop
94 y2_np = np.random.randint(1, 100, (2, 3, 4, 4)).astype(np.float16) * prop
95 x3_np = np.random.randint(1, 100, 1).astype(np.float32) * prop
96 y3_np = np.random.randint(1, 100, 1).astype(np.float32) * prop
99 x5_np = np.random.randint(1, 100, (2, 1, 1, 4)).astype(np.int32) * prop
100 y5_np = np.random.randint(1, 100, (2, 3, 4, 4)).astype(np.int32) * prop
[all …]
Dtest_less_equal_op.py36 x0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
37 y0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
38 x1_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
39 y1_np = np.random.randint(1, 5, (2, 1, 4, 4)).astype(np.float32)
40 x2_np = np.random.randint(1, 5, (2, 1, 1, 4)).astype(np.float32)
41 y2_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
42 x3_np = np.random.randint(1, 5, 1).astype(np.float32)
43 y3_np = np.random.randint(1, 5, 1).astype(np.float32)
90 x0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float16)
91 y0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float16)
[all …]
Dtest_less_op.py36 x0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
37 y0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
38 x1_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
39 y1_np = np.random.randint(1, 5, (2, 1, 4, 4)).astype(np.float32)
40 x2_np = np.random.randint(1, 5, (2, 1, 1, 4)).astype(np.float32)
41 y2_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
42 x3_np = np.random.randint(1, 5, 1).astype(np.float32)
43 y3_np = np.random.randint(1, 5, 1).astype(np.float32)
Dtest_realdiv_op.py38 x0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
39 y0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
40 x1_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
41 y1_np = np.random.randint(1, 5, (2, 1, 4, 4)).astype(np.float32)
42 x2_np = np.random.randint(1, 5, (2, 1, 1, 4)).astype(np.float32)
43 y2_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
44 x3_np = np.random.randint(1, 5, 1).astype(np.float32)
45 y3_np = np.random.randint(1, 5, 1).astype(np.float32)
Dtest_time_distributed_op.py40 inputs = np.random.randint(0, 10, [32, 12, 10, 10])
55 inputs = np.random.randint(0, 10, [32, 12, 10, 10])
70 inputs = np.random.randint(0, 10, [32, 10])
86 inputs = np.random.randint(0, 10, [32, 10])
101 inputs = np.random.randint(0, 10, [32, 10])
116 inputs = np.random.randint(0, 10, [3, 4])
131 inputs = np.random.randint(0, 10, [3, 4, 5])
146 inputs = np.random.randint(0, 10, [32, 12, 10, 10])
161 inputs = np.random.randint(0, 10, [32, 12, 10, 10])
176 inputs = np.random.randint(0, 10, [32, 10])
[all …]
Dtest_gather_d_grad_op.py55 index = np.random.randint(0, 5, (5, 3, 5)).astype(np.int32)
60 dout = np.random.randint(0, 5, index.shape).astype(np.float32) * prop
73 index = np.random.randint(0, 5, (3, 5, 5)).astype(np.int32)
78 dout = np.random.randint(0, 5, index.shape).astype(np.float16) * prop
91 index = np.random.randint(0, 5, (5, 5, 7)).astype(np.int64)
96 dout = np.random.randint(0, 5, index.shape).astype(np.int32) * prop
Dtest_pow_op.py38 x0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
39 y0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
40 x1_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
Dtest_searchsorted_op.py41 input1 = np.sort(np.array(np.random.randint(10, size=(2, 3, 9)), dtype=np.int32), axis=-1)
43 input2 = np.array(np.random.randint(10, size=(2, 3, 1)), dtype=np.int32)
63 input1 = np.sort(np.array(np.random.randint(10, size=(2, 3, 9)), dtype=np.int64), axis=-1)
65 input2 = np.array(np.random.randint(10, size=(2, 3, 1)), dtype=np.int64)
Dtest_gather_d_op.py42 index = np.random.randint(0, 5, (5, 3, 5)).astype(np.int32)
63 index = np.random.randint(0, 5, (3, 5, 5)).astype(np.int64)
85 index = np.random.randint(0, 5, (5, 5, 8)).astype(np.int32)
106 index = np.random.randint(0, 5, (5, 5, 8)).astype(np.int32)
/third_party/ltp/testcases/network/nfsv4/acl/
Drandom_gen.py32 group = self.gList[random.randint(0,len(self.gList)-1)][0]
154 l=random.randint(0,maxlength)
156 a = random.randint(0,a_length-1)
164 a = random.randint(0,a_length-1)
178 type = ace_type[random.randint(0,len(ace_type))]
179 flag = ace_flags[random.randint(0,len(ace_flags))]
180 mask = ace_mask[random.randint(0,len(ace_mask))]
181 who = ace_who[random.randint(0,len(ace_who))]
190 n = random.randint(0,userListSize-1)
200 if random.randint(0,1) == 1:
[all …]
/third_party/mindspore/tests/st/ops/gpu/
Dtest_floordiv_op.py36 x0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
37 y0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
38 x1_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
39 y1_np = np.random.randint(1, 5, (2, 1, 4, 4)).astype(np.float32)
40 x2_np = np.random.randint(1, 5, (2, 1, 1, 4, 9)).astype(np.float32)
41 y2_np = np.random.randint(1, 5, (2, 3, 4, 4, 9)).astype(np.float32)
42 x3_np = np.random.randint(1, 5, 1).astype(np.float32)
43 y3_np = np.random.randint(1, 5, 1).astype(np.float32)
46 x5_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float16)
47 y5_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float16)
[all …]
Dtest_div_op.py33 x0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(nptype)
34 y0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(nptype)
35 x1_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(nptype)
36 y1_np = np.random.randint(1, 5, (2, 1, 4, 4)).astype(nptype)
37 x2_np = np.random.randint(1, 5, (2, 1, 1, 4)).astype(nptype)
38 y2_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(nptype)
39 x3_np = np.random.randint(1, 5, 1).astype(nptype)
40 y3_np = np.random.randint(1, 5, 1).astype(nptype)
Dtest_time_distributed_op.py40 inputs = np.random.randint(0, 10, [32, 12, 10, 10])
55 inputs = np.random.randint(0, 10, [32, 12, 10, 10])
70 inputs = np.random.randint(0, 10, [32, 10])
85 inputs = np.random.randint(0, 10, [32, 10])
100 inputs = np.random.randint(0, 10, [3, 4])
115 inputs = np.random.randint(0, 10, [3, 4, 5])
130 inputs = np.random.randint(0, 10, [32, 12, 10, 10])
145 inputs = np.random.randint(0, 10, [32, 12, 10, 10])
160 inputs = np.random.randint(0, 10, [32, 10])
175 inputs = np.random.randint(0, 10, [3, 4])
[all …]
Dtest_realdiv_op.py38 x0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
39 y0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
40 x1_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
41 y1_np = np.random.randint(1, 5, (2, 1, 4, 4)).astype(np.float32)
42 x2_np = np.random.randint(1, 5, (2, 1, 1, 4)).astype(np.float32)
43 y2_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
44 x3_np = np.random.randint(1, 5, 1).astype(np.float32)
45 y3_np = np.random.randint(1, 5, 1).astype(np.float32)
Dtest_pyfunc_op.py50 x1 = np.random.randint(-5, 5, size=shape).astype(np_dtype)
51 x2 = np.random.randint(-5, 5, size=shape).astype(np_dtype)
82 x1 = np.random.randint(-5, 5, size=shape).astype(np.float32)
83 x2 = np.random.randint(-5, 5, size=shape).astype(np.float32)
110 x1 = np.random.randint(-5, 5, size=shape).astype(np.float32)
111 x2 = np.random.randint(-5, 5, size=shape).astype(np.float32)
/third_party/mindspore/tests/ut/python/nn/
Dtest_dense.py37 input_data = Tensor(np.random.randint(0, 255, [1, 1]).astype(np.float32))
46 input_data = Tensor(np.random.randint(0, 255, [1, 1]).astype(np.float32))
55 input_data = Tensor(np.random.randint(0, 255, [1, 1]).astype(np.float32))
114 weight = Tensor(np.random.randint(0, 255, [8, 64]).astype(np.float32))
115 bias = Tensor(np.random.randint(0, 255, [8]).astype(np.float32))
117 input_data = Tensor(np.random.randint(0, 255, [128, 64]).astype(np.float32))
129 weight = Tensor(np.random.randint(0, 255, [8, 64]).astype(np.float32))
131 input_data = Tensor(np.random.randint(0, 255, [128, 64]).astype(np.float32))
146 input_data = Tensor(np.random.randint(0, 255, [128, 128]).astype(np.float32))
161 input_data = Tensor(np.random.randint(0, 255, [128, 128]).astype(np.float32))
Dtest_checkparameter.py25 a = np.random.randint(-100, 100)
47 a = np.random.randint(1, 100)
51 a = np.random.randint(-100, 0)
64 a = np.random.randint(-100, -1)
68 a = np.random.randint(0, 100)
81 a = np.random.randint(-100, 0)
85 a = np.random.randint(1, 100)
/third_party/mindspore/tests/ut/python/utils/
Dtest_serialize.py65 _input_x = Tensor(np.random.randint(0, 255, [1, 3, 224, 224]).astype(np.float32))
108 one_param['data'] = Tensor(np.random.randint(0, 255, [1, 3, 224, 224]), dtype=mstype.float32)
110 param1['data'] = Tensor(np.random.randint(0, 255, [12, 1024]), dtype=mstype.float32)
112 param2['data'] = Tensor(np.random.randint(0, 255, [12, 1024, 1]), dtype=mstype.float32)
132 one_param['data'] = Tensor(np.random.randint(0, 255, [1, 3, 224, 224]), dtype=mstype.float32)
134 param1['data'] = Tensor(np.random.randint(0, 255, [12, 1024]), dtype=mstype.float32)
136 param2['data'] = Tensor(np.random.randint(0, 255, [12, 1024, 1]), dtype=mstype.float32)
376 input_data = Tensor(np.random.randint(0, 255, [1, 3, 224, 224]).astype(np.float32))
384 input_data = Tensor(np.random.randint(0, 255, [1, 3, 224, 224]).astype(np.float32))
391 input_data = Tensor(np.random.randint(0, 255, [1, 3, 224, 224]).astype(np.float32))
[all …]
/third_party/mindspore/tests/ut/python/pynative_mode/nn/
Dtest_dense.py31 input_data = Tensor(np.random.randint(0, 255, [1, 3]).astype(np.float32))
41 input_data = Tensor(np.random.randint(0, 255, [1, 3]).astype(np.float32))
52 input_data = Tensor(np.random.randint(0, 255, [2, 3]).astype(np.float32))
62 input_data = Tensor(np.random.randint(0, 255, [2, 3]).astype(np.float32))
77 input_data = Tensor(np.random.randint(0, 255, [1, 1]).astype(np.float32))
Dtest_batchnorm.py61 input_data = Tensor(np.random.randint(0, 1, [1, 3, 224, 224]).astype(np.float32))
70 input_data = Tensor(np.random.randint(0, 1, [1, 3]).astype(np.float32))
80 Tensor(np.random.randint(0, 255, [1, 3, 224, 224]))
Dtest_loss.py37 logits = Tensor(np.random.randint(0, 9, [100, 10]).astype(np.float32))
38 labels = Tensor(np.random.randint(0, 9, [100, 10]).astype(np.float32))
/third_party/mindspore/tests/st/pynative/
Dtest_tensor_getitem.py183 index_0 = np.random.randint(6, size=(3, 4, 5)).astype(np.int32)
184 index_1 = np.random.randint(6, size=(4, 5)).astype(np.int32)
185 index_2 = np.random.randint(6, size=(5, 3, 4, 5)).astype(np.int32)
231 index_np_0 = np.random.randint(3, size=(3, 4, 5)).astype(np.int32)
232 index_np_1 = np.random.randint(4, size=(4, 5)).astype(np.int32)
259 input_3d_np = np.random.randint(3, size=(3, 4, 5)).astype(np.int32)
285 input_3d_np = np.random.randint(3, size=(3, 4, 5)).astype(np.int32)
320 input_3d_np = np.random.randint(3, size=(3, 4, 5)).astype(np.int32)
370 index_0 = np.random.randint(3, size=(3, 4, 5))
371 index_1 = np.random.randint(4, size=(4, 5))
[all …]
/third_party/mindspore/tests/ut/python/dataset/
Dtest_slice_patches.py144 image = np.random.randint(0, 255, (158, 126, 1)).astype(np.int32)
151 image = np.random.randint(0, 255, (158, 126)).astype(np.int32)
158 np_data = np.random.randint(0, 255, (1, 56, 82, 256)).astype(np.uint8)
169 image = np.random.randint(0, 255, (56, 82, 256)).astype(np.uint8)
176 image = np.random.randint(0, 255, (7000, 7000, 255)).astype(np.uint8)
182 np_data = np.random.randint(0, 255, (1, 7000, 7000, 256)).astype(np.uint8)
/third_party/mindspore/tests/ut/python/pipeline/parse/
Dtest_operator.py173 x = Tensor(np.random.randint(low=1, high=10, size=(2, 3, 4), dtype=np.int32))
174 y = Tensor(np.random.randint(low=10, high=20, size=(2, 3, 4), dtype=np.int32))
200 x = Tensor(np.random.randint(low=1, high=10, size=(2, 3, 4), dtype=np.int32))
201 y = Tensor(np.random.randint(low=10, high=20, size=(2, 3, 4), dtype=np.int32))
202 z = Tensor(np.random.randint(low=20, high=30, size=(2, 3, 4), dtype=np.int32))

123456