| /third_party/mindspore/tests/st/ops/cpu/ |
| D | test_cumsum_op.py | 27 axis0 = 0 variable
43 list2 = [axis0, axis1, axis2, axis3, axis4, axis5, axis6]
51 self.axis0 = axis0
66 self.axis7 = axis0
81 self.axis14 = axis0
96 self.axis21 = axis0
111 self.axis28 = axis0
126 self.axis35 = axis0
129 return (self.cumsum_op(self.x0, self.axis0),
185 expect = np.cumsum(x5, axis=axis0)
[all …]
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| D | test_reduce_op.py | 30 self.axis0 = 0
44 return (self.reduce_mean(indice, self.axis0),
49 self.reduce_sum(indice, self.axis0),
51 self.reduce_max(indice, self.axis0),
55 self.reduce_min(indice, self.axis0),
67 self.axis0 = 0
76 return (self.reduce_all(indice, self.axis0),
80 self.reduce_any(indice, self.axis0),
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| /third_party/mindspore/tests/st/ops/gpu/ |
| D | test_reduce_max_op.py | 28 axis0 = 3 variable
72 self.axis0 = axis0
109 return (P.ReduceMax(self.keep_dims0)(self.x0, self.axis0),
128 expect0 = np.max(x0, axis=axis0, keepdims=keep_dims0)
221 self.axis0 = axis0
225 return P.ReduceMax(self.keep_dims0)(self.x0, self.axis0)
234 expect = np.max(x0, axis=axis0, keepdims=keep_dims0).astype(np.float64)
243 expect = np.max(x0, axis=axis0, keepdims=keep_dims0).astype(np.float64)
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| D | test_reduce_all_op.py | 27 axis0 = 0 variable
48 self.axis0 = axis0
66 return (P.ReduceAll(self.keep_dims0)(self.x0, self.axis0),
80 expect0 = np.all(x0, axis=axis0, keepdims=keep_dims0)
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| D | test_reduce_any_op.py | 27 axis0 = 0 variable
48 self.axis0 = axis0
66 return (P.ReduceAny(self.keep_dims0)(self.x0, self.axis0),
80 expect0 = np.any(x0, axis=axis0, keepdims=keep_dims0)
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| D | test_reduce_sum_op.py | 27 axis0 = 3 variable
95 self.axis0 = axis0
156 return (P.ReduceSum(self.keep_dims0)(self.x0, self.axis0),
181 expect0 = np.sum(x0, axis=axis0, keepdims=keep_dims0)
313 self.axis0 = axis0
317 return P.ReduceSum(self.keep_dims0)(self.x0, self.axis0)
326 expect = np.sum(x0, axis=axis0, keepdims=keep_dims0).astype(np.float64)
335 expect = np.sum(x0, axis=axis0, keepdims=keep_dims0).astype(np.float64)
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| D | test_cumsum_op.py | 28 axis0 = 3
53 self.axis0 = axis0
75 return (P.CumSum()(self.x0, self.axis0),
87 expect0 = np.cumsum(x0, axis=axis0)
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| D | test_cumprod_op.py | 28 axis0 = 3
53 self.axis0 = axis0
75 return (P.CumProd()(self.x0, self.axis0),
87 expect0 = np.cumprod(x0, axis=axis0)
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| D | test_reduce_min_op.py | 28 axis0 = 3 variable
72 self.axis0 = axis0
109 return (P.ReduceMin(self.keep_dims0)(self.x0, self.axis0),
128 expect0 = np.min(x0, axis=axis0, keepdims=keep_dims0)
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| D | test_reduce_mean_op.py | 27 axis0 = 3 variable
93 self.axis0 = axis0
154 return (P.ReduceMean(self.keep_dims0)(self.x0, self.axis0),
179 expect0 = np.mean(x0, axis=axis0, keepdims=keep_dims0)
288 net2 = ReduceMeanDynamic(Tensor(x0), axis0, keepdims=True)
298 expect_2 = np.mean(x0, axis=axis0, keepdims=True)
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| D | test_reduce_prod_op.py | 26 axis0 = 3 variable
70 self.axis0 = axis0
107 return (P.ReduceProd(self.keep_dims0)(self.x0, self.axis0),
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| D | test_index_add_op.py | 45 axis0 = 0
49 net = NetIndexAdd(x, axis0)
53 net = NetIndexAdd(x, axis0)
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| /third_party/mindspore/tests/st/ops/graph_kernel/ |
| D | test_argmax.py | 42 axis0 = 3
43 expect = get_output(x0, axis0, False)
44 output = get_output(x0, axis0, True)
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| D | test_reduce_max.py | 42 axis0 = 3
44 expect = get_output(x0, axis0, keep_dims0, False)
45 output = get_output(x0, axis0, keep_dims0, True)
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| D | test_reduce_min.py | 42 axis0 = 3
44 expect = get_output(x0, axis0, keep_dims0, False)
45 output = get_output(x0, axis0, keep_dims0, True)
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| /third_party/mindspore/mindspore/numpy/ |
| D | math_ops.py | 5532 axis0, axis1 = axis
5534 if _check_is_inf(_abs(_ord)) and axis0 > axis1:
5535 axis0 -= 1
5536 elif _abs(_ord) == 1 and axis1 > axis0:
5539 return P.ReduceMax(keepdims)(P.ReduceSum(keepdims)(absolute(x), axis1), axis0)
5541 return P.ReduceMin(keepdims)(P.ReduceSum(keepdims)(absolute(x), axis1), axis0)
5543 return P.ReduceMax(keepdims)(P.ReduceSum(keepdims)(absolute(x), axis0), axis1)
5545 return P.ReduceMin(keepdims)(P.ReduceSum(keepdims)(absolute(x), axis0), axis1)
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