/third_party/mindspore/tests/st/ops/gpu/ |
D | test_cast_op.py | 60 x0 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.float32)) 62 x1 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.float16)) 78 x0 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.int32)) 80 x1 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.bool)) 95 x0 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.float16)) 97 x1 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.float16)) 112 x0 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.int64)) 114 x1 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.float32)) 129 x0 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.int32)) 131 x1 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.int32)) [all …]
|
D | test_addn_op.py | 41 x = np.arange(1 * 3 * 3 * 4).reshape(1, 3, 3, 4).astype(np.float32) 42 y = np.arange(1 * 3 * 3 * 4).reshape(1, 3, 3, 4).astype(np.float32) 43 z = np.arange(1 * 3 * 3 * 4).reshape(1, 3, 3, 4).astype(np.float32) 64 x = np.arange(1 * 3 * 3 * 4).reshape(1, 3, 3, 4).astype(np.float64) 65 y = np.arange(1 * 3 * 3 * 4).reshape(1, 3, 3, 4).astype(np.float64) 66 z = np.arange(1 * 3 * 3 * 4).reshape(1, 3, 3, 4).astype(np.float64) 81 x = np.arange(1 * 3 * 3 * 4).reshape(1, 3, 3, 4).astype(np.float64) 82 y = np.arange(1 * 3 * 3 * 4).reshape(1, 3, 3, 4).astype(np.float64) 83 z = np.arange(1 * 3 * 3 * 4).reshape(1, 3, 3, 4).astype(np.float64) 103 x = np.arange(1 * 3 * 3 * 4).reshape(1, 3, 3, 4).astype(np.int64) [all …]
|
D | test_batch_matmul.py | 39 input_x = Tensor(np.arange(2 * 4 * 1 * 3).reshape(2, 4, 1, 3), mstype.float32) 40 input_y = Tensor(np.arange(2 * 4 * 3 * 4).reshape(2, 4, 3, 4), mstype.float32) 61 input_x = Tensor(np.arange(2 * 4 * 1 * 3).reshape(2, 4, 1, 3), mstype.float64) 62 input_y = Tensor(np.arange(2 * 4 * 3 * 4).reshape(2, 4, 3, 4), mstype.float64) 83 input_x = Tensor(np.arange(2 * 4 * 3 * 1).reshape(2, 4, 3, 1), mstype.float32) 84 input_y = Tensor(np.arange(2 * 4 * 3 * 4).reshape(2, 4, 3, 4), mstype.float32) 105 input_x = Tensor(np.arange(2 * 4 * 1 * 3).reshape(2, 4, 1, 3), mstype.float32) 106 input_y = Tensor(np.arange(2 * 4 * 4 * 3).reshape(2, 4, 4, 3), mstype.float32) 127 input_x = Tensor(np.arange(2 * 4 * 3 * 1).reshape(2, 4, 3, 1), mstype.float32) 128 input_y = Tensor(np.arange(2 * 4 * 4 * 3).reshape(2, 4, 4, 3), mstype.float32) [all …]
|
D | test_apply_gradient_descent_op.py | 40 var = Tensor(np.arange(10).reshape(2, 5).astype(np.float32) / 10) 43 delta = Tensor(np.arange(34, 44).reshape(2, 5).astype(np.float32)) 51 var = Tensor(np.arange(10).reshape(2, 5).astype(np.float32) / 10) 54 delta = Tensor(np.arange(34, 44).reshape(2, 5).astype(np.float32)) 67 var = Tensor(np.arange(10).reshape(2, 5).astype(np.float16) / 10) 70 delta = Tensor(np.arange(34, 44).reshape(2, 5).astype(np.float16)) 78 var = Tensor(np.arange(10).reshape(2, 5).astype(np.float16) / 10) 81 delta = Tensor(np.arange(34, 44).reshape(2, 5).astype(np.float16))
|
D | test_repeat_elements_op.py | 43 a = np.arange(1) 54 a = np.arange(1) 69 a = np.arange(24) 80 a = np.arange(24) 91 a = np.arange(1).reshape(1, 1) 106 a = np.arange(1).reshape(1, 1) 121 a = np.arange(24).reshape(12, 2) 136 a = np.arange(24).reshape(8, 3) 151 a = np.arange(1).reshape(1, 1, 1) 170 a = np.arange(1).reshape(1, 1, 1) [all …]
|
D | test_zeroslike_op.py | 97 x = Tensor(np.arange(120).reshape(3, 4, 1, 2, 5).astype(np.bool)) 106 x = Tensor(np.arange(24).reshape(1, 4, 1, 6).astype(np.int8)) 115 x = Tensor(np.arange(30).reshape(3, 2, 5).astype(np.uint8)) 124 x = Tensor(np.arange(16).reshape(2, 2, 2, 2).astype(np.int32)) 133 x = Tensor(np.arange(120).reshape(3, 4, 1, 2, 5).astype(np.float16)) 142 x = Tensor(np.arange(63).reshape(3, 7, 3).astype(np.float32)) 151 x = Tensor(np.arange(2).reshape(2, 1, 1).astype(np.float64)) 163 x = Tensor(np.arange(4).reshape(4).astype(np.float32)) 168 x = Tensor(np.arange(8).reshape(2, 1, 2, 2).astype(np.uint8)) 173 x = Tensor(np.arange(1).reshape(1).astype(np.float16))
|
D | test_sparse_apply_proximal_adagrad_op.py | 48 var = Tensor(np.arange(9).reshape(3, 3).astype(np.float32)) 69 var = Tensor(np.arange(9).reshape(3, 3).astype(np.float32)) 91 var = Tensor(np.arange(9).reshape(3, 3).astype(np.float32)) 112 var = Tensor(np.arange(9).reshape(3, 3).astype(np.float32)) 113 accum = Tensor(np.arange(63, 72).reshape(3, 3).astype(np.float32)) 117 grad = Tensor(np.arange(34, 43).reshape(3, 3).astype(np.float32) * 8) 133 var = Tensor(np.arange(24).reshape((2, 3, 4)).astype(np.float32)) 134 accum = Tensor(np.arange(34, 58).reshape((2, 3, 4)).astype(np.float32)) 139 indices = Tensor(np.arange(2).astype(np.int32))
|
D | test_scatter_func_op.py | 110 updates = Tensor(np.arange(12).reshape((2, 2, 3)).astype(np.float32)) 134 updates = Tensor(np.arange(12).reshape((2, 2, 3)).astype(np.float32)) 162 updates = Tensor(np.arange(96).reshape((2, 2, 2, 3, 4)).astype(np.float32)) 271 updates = Tensor(np.arange(6).reshape((2, 3)).astype(np.float32)) 303 updates = Tensor(np.arange(34, 70).reshape((2, 2, 3, 3)).astype(np.float32)) 343 updates = Tensor(np.arange(12).reshape((2, 2, 3)).astype(np.float16)) 367 updates = Tensor(np.arange(63, 111).reshape((2, 2, 3, 4)).astype(np.float16)) 420 inputx = Tensor(np.flip(np.arange(34, 46).reshape(3, 4).astype(np.float16))) 422 updates = Tensor(np.arange(63, 111).reshape((2, 2, 3, 4)).astype(np.float16)) 456 updates = Tensor(np.arange(63, 111).reshape((2, 2, 3, 4)).astype(np.int32)) [all …]
|
D | test_unique_op.py | 109 x_np1 = np.arange(100) 110 x_np2 = np.arange(100, 200) 111 x_np3 = np.arange(200, 300) 114 exp_output = np.arange(300).astype(np.float32) 169 x_np1 = np.arange(100) 170 x_np2 = np.arange(100, 200) 171 x_np3 = np.arange(200, 300) 174 exp_output = np.arange(300).astype(np.float16) 229 x_np1 = np.arange(100) 230 x_np2 = np.arange(100, 200) [all …]
|
D | test_conv2d_op.py | 50 x = Tensor(np.arange(1 * 3 * 3 * 3).reshape(1, 3, 3, 3).astype(np.float32)) 51 w = Tensor(np.arange(2 * 3 * 1 * 1).reshape(2, 3, 1, 1).astype(np.float32)) 197 x1 = Tensor(np.arange(1 * 3 * 3 * 3).reshape(1, 3, 3, 3).astype(np.float32)) 198 w1 = Tensor(np.arange(2 * 3 * 1 * 1).reshape(2, 3, 1, 1).astype(np.float32)) 206 x2 = Tensor(np.arange(5 * 1 * 2 * 2).reshape(5, 1, 2, 2).astype(np.float32)) 207 w2 = Tensor(np.arange(2 * 1 * 1 * 1).reshape(2, 1, 1, 1).astype(np.float32)) 259 x1 = Tensor(np.arange(1 * 4 * 4 * 1).reshape(1, 4, 4, 1).astype(np.float32)) 260 w1 = Tensor(np.arange(3 * 2 * 2 * 1).reshape(3, 2, 2, 1).astype(np.float32))
|
D | test_tensor_scatter_add.py | 50 arr_input = np.arange(21).reshape(3, 7).astype(np.float32) 58 arr_input = np.arange(24).reshape(4, 2, 3).astype(np.float32) 73 arr_input = np.arange(21).reshape(3, 7).astype(np.float32) 80 arr_input = np.arange(24).reshape(4, 2, 3).astype(np.float32) 88 arr_input = np.arange(25).reshape(5, 5).astype(np.float32) 108 arr_input = np.arange(25).reshape(5, 5).astype(np.float64) 128 arr_input = np.arange(25).reshape(5, 5).astype(np.int32)
|
D | test_add_op.py | 41 Tensor(np.arange(3).reshape(3).astype(nptype)), [3]), name='x1') 46 … Tensor(np.arange(3 * 3 * 3 * 3).reshape(3, 3, 3, 3).astype(nptype)), [3, 3, 3, 3]), name='x2') 48 … Tensor(np.arange(3 * 3 * 3 * 3).reshape(3, 3, 3, 3).astype(nptype)), [3, 3, 3, 3]), name='y2') 51 … Tensor(np.arange(1 * 1 * 3 * 3).reshape(1, 1, 3, 3).astype(nptype)), [1, 1, 3, 3]), name='x3') 53 … Tensor(np.arange(3 * 3 * 3 * 3).reshape(3, 3, 3, 3).astype(nptype)), [3, 3, 3, 3]), name='y3') 185 x1 = Tensor(np.arange(3).reshape(3).astype(nptype)) 188 x2 = Tensor(np.arange(3 * 3 * 3 * 3).reshape(3, 3, 3, 3).astype(nptype)) 189 y2 = Tensor(np.arange(3 * 3 * 3 * 3).reshape(3, 3, 3, 3).astype(nptype))
|
/third_party/mindspore/tests/st/ops/cpu/ |
D | test_matmul.py | 43 input_x = Tensor(np.arange(1 * 3).reshape((1, 3)), mstype.float32) 44 input_y = Tensor(np.arange(3 * 5).reshape((3, 5)), mstype.float32) 57 input_x = Tensor(np.arange(4 * 3).reshape((4, 3)), mstype.float32) 58 input_y = Tensor(np.arange(3 * 5).reshape((3, 5)), mstype.float32) 74 input_x = Tensor(np.arange(3 * 2).reshape((3, 2)), mstype.float32) 75 input_y = Tensor(np.arange(3 * 4).reshape((3, 4)), mstype.float32) 89 input_x = Tensor(np.arange(2 * 3).reshape((2, 3)), mstype.float32) 90 input_y = Tensor(np.arange(5 * 3).reshape((5, 3)), mstype.float32) 104 input_x = Tensor(np.arange(3 * 5).reshape((3, 5)), mstype.float16) 105 input_y = Tensor(np.arange(4 * 3).reshape((4, 3)), mstype.float16)
|
D | test_batch_matmul.py | 45 input_x = Tensor(np.arange(2 * 4 * 1 * 3).reshape((2, 4, 1, 3)), mstype.float32) 46 input_y = Tensor(np.arange(2 * 4 * 3 * 4).reshape((2, 4, 3, 4)), mstype.float32) 66 input_x = Tensor(np.arange(2 * 3 * 2 * 3).reshape((2, 3, 2, 3)), mstype.float32) 67 input_y = Tensor(np.arange(2 * 3 * 3 * 4).reshape((2, 3, 3, 4)), mstype.float32) 91 input_x = Tensor(np.arange(2 * 3 * 3 * 2).reshape((2, 3, 3, 2)), mstype.float32) 92 input_y = Tensor(np.arange(2 * 3 * 3 * 4).reshape((2, 3, 3, 4)), mstype.float32) 116 input_x = Tensor(np.arange(2 * 3 * 2 * 3).reshape((2, 3, 2, 3)), mstype.float32) 117 input_y = Tensor(np.arange(2 * 3 * 4 * 3).reshape((2, 3, 4, 3)), mstype.float32) 141 input_x = Tensor(np.arange(2 * 3 * 3 * 2).reshape((2, 3, 3, 2)), mstype.float16) 142 input_y = Tensor(np.arange(2 * 3 * 4 * 3).reshape((2, 3, 4, 3)), mstype.float16)
|
D | test_transpose_op.py | 34 …self.x_2D = Parameter(initializer(Tensor(np.arange(5 * 6).reshape(5, 6).astype(np.float32)), [5, 6… 38 …self.x_3D = Parameter(initializer(Tensor(np.arange(2 * 2 * 4).reshape(2, 2, 4).astype(np.float32))… 43 initializer(Tensor(np.arange(2 * 3 * 4 * 5).reshape(2, 49 … initializer(Tensor(np.arange(1 * 2 * 3 * 4 * 5).reshape(1, 2, 3, 4, 5).astype(np.float32)), 156 …self.x_2D = Parameter(initializer(Tensor(np.arange(5 * 6).reshape(5, 6).astype(np.int64)), [5, 6]), 160 …self.x_3D = Parameter(initializer(Tensor(np.arange(2 * 2 * 4).reshape(2, 2, 4).astype(np.int64)), … 165 initializer(Tensor(np.arange(2 * 3 * 4 * 5).reshape(2, 171 … initializer(Tensor(np.arange(1 * 2 * 3 * 4 * 5).reshape(1, 2, 3, 4, 5).astype(np.int64)), 278 …self.x_2D = Parameter(initializer(Tensor(np.arange(5 * 6).reshape(5, 6).astype(np.uint8)), [5, 6]), 282 …self.x_3D = Parameter(initializer(Tensor(np.arange(2 * 2 * 4).reshape(2, 2, 4).astype(np.uint8)), … [all …]
|
D | test_addn_op.py | 40 x = np.arange(2 * 3 * 2).reshape((2, 3, 2)) 41 y = np.arange(88, 2 * 3 * 2 + 88).reshape((2, 3, 2)) 64 x = np.arange(2 * 3).reshape((2, 3)) 65 y = np.arange(1, 2 * 3 + 1).reshape((2, 3)) 66 m = np.arange(2, 2 * 3 + 2).reshape((2, 3)) 67 n = np.arange(3, 2 * 3 + 3).reshape((2, 3))
|
D | test_scatter_arithmetic_op.py | 57 updates = Tensor(np.arange(12).reshape((2, 2, 3)).astype(np.float32)) 70 updates = Tensor(np.arange(12).reshape((2, 2, 3)).astype(np.float32)) 85 updates = Tensor(np.arange(96).reshape((2, 2, 2, 3, 4)).astype(np.float32)) 120 updates = Tensor(np.arange(6).reshape((2, 3)).astype(np.float32)) 138 updates = Tensor(np.arange(34, 70).reshape((2, 2, 3, 3)).astype(np.float32)) 152 updates = Tensor(np.arange(12).reshape((2, 2, 3)).astype(np.float16)) 165 updates = Tensor(np.arange(63, 111).reshape((2, 2, 3, 4)).astype(np.float16)) 180 inputx = Tensor(np.flip(np.arange(34, 46).reshape(3, 4).astype(np.float16))) 185 updates = Tensor(np.arange(63, 111).reshape((2, 2, 3, 4)).astype(np.float16)) 199 updates = Tensor(np.arange(63, 111).reshape((2, 2, 3, 4)).astype(np.int32)) [all …]
|
D | test_dot_op.py | 66 …x1_tensor = initializer(Tensor(np.arange(2 * 3 * 4).reshape(2, 3, 4).astype(np.float32)), [2, 3, 4… 67 …x2_tensor = initializer(Tensor(np.arange(1 * 5 * 4 * 2).reshape(1, 5, 4, 2).astype(np.float32)), [… 109 x1_tensor = initializer(Tensor(np.arange(3 * 4).reshape(3, 4).astype(np.float32)), [3, 4]) 110 x2_tensor = initializer(Tensor(np.arange(4 * 5).reshape(4, 5).astype(np.float32)), [4, 5]) 125 …x1_tensor = initializer(Tensor(np.arange(2 * 3 * 4).reshape(2, 3, 4).astype(np.float32)), [2, 3, 4… 126 x2_tensor = initializer(Tensor(np.arange(4 * 5).reshape(4, 5).astype(np.float32)), [4, 5]) 144 x1_tensor = initializer(Tensor(np.arange(4).reshape(4).astype(np.float32)), [4]) 145 …x2_tensor = initializer(Tensor(np.arange(2 * 4 * 5).reshape(2, 4, 5).astype(np.float32)), [2, 4, 5… 155 x1_tensor = initializer(Tensor(np.arange(4).reshape(4).astype(np.float32)), [4]) 156 x2_tensor = initializer(Tensor(np.arange(4 * 4).reshape(4, 4).astype(np.float32)), [4, 4])
|
D | test_split_op.py | 43 input_x = Tensor(np.arange(24).astype(np.int32).reshape((2, 2, 6))) 58 input_x = Tensor(np.arange(24).astype(np.int32).reshape((2, 2, 6))) 75 input_x = Tensor(np.arange(24).astype(np.float32).reshape((2, 2, 6))) 90 input_x = Tensor(np.arange(192).astype(np.float32).reshape((2, 2, 2, 2, 2, 6))) 112 input_x = Tensor(np.arange(192).astype(np.float64).reshape((2, 2, 2, 2, 2, 6))) 134 input_x = Tensor(np.arange(320).astype(np.float16).reshape((2, 2, 2, 2, 2, 10))) 158 input_x = Tensor(np.arange(192).astype(np.int32).reshape((2, 2, 2, 2, 2, 6))) 180 input_x = Tensor(np.arange(192).astype(np.int64).reshape((2, 2, 2, 2, 2, 6))) 202 input_x = Tensor(np.arange(320).astype(np.uint32).reshape((2, 2, 2, 2, 2, 10))) 235 input_x = Tensor(np.arange(1).astype(np.uint32))
|
/third_party/boost/libs/python/test/numpy/ |
D | indexing.py | 15 x = numpy.arange(0,10) 22 x = numpy.arange(0,10) 28 x = numpy.arange(0,10) 34 x = numpy.arange(0,10) 39 x = numpy.arange(9).reshape(3,3) 44 x = numpy.arange(0,10) 48 x = numpy.arange(9).reshape(3,3)
|
/third_party/mindspore/tests/ut/python/pipeline/parse/ |
D | test_partial.py | 38 x = Tensor(np.arange(3).reshape((3,)).astype(np.float32)) 39 y = Tensor(np.arange(3 * 4).reshape((3, 4)).astype(np.float32)) 40 z = Tensor(np.arange(3 * 4 * 5).reshape((3, 4, 5)).astype(np.float32)) 57 x = Tensor(np.arange(3).reshape((3,)).astype(np.float32)) 58 y = Tensor(np.arange(3 * 4).reshape((3, 4)).astype(np.float32)) 59 z = Tensor(np.arange(3 * 4 * 5).reshape((3, 4, 5)).astype(np.float32)) 76 x = Tensor(np.arange(3).reshape((3,)).astype(np.float32)) 77 y = Tensor(np.arange(3 * 4).reshape((3, 4)).astype(np.float32)) 78 z = Tensor(np.arange(3 * 4 * 5).reshape((3, 4, 5)).astype(np.float32)) 96 x = Tensor(np.arange(3).reshape((3,)).astype(np.float32)) [all …]
|
D | test_enumerate.py | 66 self.value = Tensor(np.arange(2 * 3).reshape(2, 3)) 89 x = Tensor(np.arange(4)) 108 x = Tensor(np.arange(4)) 126 x = Tensor(np.arange(2 * 3).reshape(2, 3)) 153 self.value = Tensor(np.arange(2*3).reshape(2, 3)) 181 x = Tensor(np.arange(4)) 199 x = Tensor(np.arange(2 * 3).reshape(2, 3)) 226 self.value = Tensor(np.arange(2 * 3).reshape(2, 3)) 254 x = Tensor(np.arange(4)) 272 x = Tensor(np.arange(2 * 3).reshape(2, 3)) [all …]
|
/third_party/mindspore/tests/ut/python/ops/ |
D | test_tensor_getitem.py | 54 input_np = np.arange(60).reshape(3, 4, 5) 63 input_np = np.arange(60).reshape(3, 4, 5) 72 input_np = np.arange(60).reshape(3, 4, 5) 81 input_np = np.arange(3*4*5*6*7*8).reshape(3, 4, 5, 6, 7, 8) 90 input_np = np.arange(3*4*5*6*7*8).reshape(3, 4, 5, 6, 7, 8) 99 input_np = np.arange(3*4*5*6*7*8).reshape(3, 4, 5, 6, 7, 8) 108 input_np = np.arange(3*4*5*6*7*8).reshape(3, 4, 5, 6, 7, 8) 117 input_np = np.arange(3*4*5*6*7*8).reshape(3, 4, 5, 6, 7, 8)
|
/third_party/mindspore/tests/ut/python/numpy_native/ |
D | test_numpy_ops.py | 105 a = mnp.arange(10) 106 b = mnp.arange(0, 10) 107 c = mnp.arange(0.1, 9.9) 227 'desc_inputs': [Tensor(np.arange(18, dtype=np.int32).reshape(2, 3, 1, 3)), 228 Tensor(np.arange(9, dtype=np.int32).reshape(1, 3, 3))], 232 'desc_inputs': [Tensor(np.arange(9, dtype=np.int32).reshape(3, 3)), 233 Tensor(np.arange(9, dtype=np.int32).reshape(3, 3)),], 242 'desc_inputs': [Tensor(np.arange(9, dtype=np.float32).reshape(3, 3))], 246 'desc_inputs': [Tensor(np.arange(9, dtype=np.float32).reshape(3, 3))], 254 'desc_inputs': [Tensor(np.arange(1, 7, dtype=np.float32).reshape(2, 3))], [all …]
|
/third_party/mindspore/tests/st/ops/ascend/test_tbe_ops/ |
D | test_concat.py | 34 Tensor(np.arange(2 * 2).reshape(2, 2).astype(np.float32)), [2, 2]), name='x1') 36 Tensor(np.arange(2 * 3).reshape(2, 3).astype(np.float32)), [2, 3]), name='x2') 48 print(np.arange(2 * 2).reshape(2, 2)) 49 print(np.arange(2 * 3).reshape(2, 3))
|