Searched refs:arr_x (Results 1 – 9 of 9) sorted by relevance
| /third_party/mindspore/tests/st/ops/cpu/ |
| D | test_tile_op.py | 35 arr_x = np.array([[0], [1], [2], [3]]).astype(np.int32) variable
43 print(arr_x)
44 output = tile(Tensor(arr_x))
48 arr_x = np.array([[0], [1], [2], [3]]).astype(np.float64) variable
56 print(arr_x)
57 output = tile(Tensor(arr_x))
61 arr_x = np.array([[0], [1], [2], [3]]).astype(np.bool_) variable
69 print(arr_x)
70 output = tile(Tensor(arr_x))
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| /third_party/mindspore/tests/st/ops/ascend/test_tbe_ops/ |
| D | test_tile.py | 34 arr_x = np.array([[0], [1], [2], [3]]).astype(np.int32) variable
39 print(arr_x)
40 output = tile(Tensor(arr_x))
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| D | test_sqrt.py | 34 arr_x = np.array([1.0, 4.0, 9.0]).astype(np.float32) variable
39 output = sqrt(Tensor(arr_x))
40 print(arr_x)
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| D | test_softmax.py | 34 arr_x = np.array([[5, 1]]).astype(np.float32) variable
39 output = softmax(Tensor(arr_x))
40 print(arr_x)
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| D | test_split.py | 34 arr_x = np.random.randn(2, 4).astype(np.float32) variable
39 output = split(Tensor(arr_x))
41 print(arr_x)
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| D | test_square.py | 34 arr_x = np.array([1.0, 4.0, 9.0]).astype(np.float32) variable
39 output = square(Tensor(arr_x))
40 print(arr_x)
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| D | test_sub.py | 34 arr_x = np.random.randn(1, 3, 3, 4).astype(np.float32) variable
40 output = sub(Tensor(arr_x), Tensor(arr_y))
41 print(arr_x)
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| D | test_pad.py | 37 arr_x = np.random.random(size=(2, 2)).astype(np.float32) variable
42 output = pad(Tensor(arr_x))
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| /third_party/mindspore/tests/ut/cpp/operator/ |
| D | composite_test.cc | 260 AbstractTensorPtr arr_x = UTCompositeUtils::ArrayInt32Of({2, 3, 4}); in TEST_F() local
263 std::vector<AbstractAttribute> tensor_map{{"x", arr_x}, {"y", arr_y}, {"z", arr_z}}; in TEST_F()
287 AbstractTensorPtr arr_x = UTCompositeUtils::ArrayInt32Of({2, 3, 4}); in TEST_F() local
290 std::vector<AbstractAttribute> tensor_map{{"x", arr_x}, {"y", arr_y}, {"z", arr_z}}; in TEST_F()
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