| /third_party/mindspore/tests/ut/python/pynative_mode/ops/ |
| D | test_hypermap.py | 56 tensor1 = Tensor(np.array([[1.2, 2.1], [2.2, 3.2]]).astype('float32'))
58 print("test_hypermap_tensor:", mainf(tensor1, tensor2))
71 tensor1 = Tensor(np.array([[1.2, 2.1], [2.2, 3.2]]).astype('float32'))
73 print("test_hypermap_tuple_tensor", mainf((tensor1, tensor1), (tensor2, tensor2)))
78 tensor1 = Tensor(np.array([[1.2, 2.1], [2.2, 3.2]]).astype('float32'))
80 print("test_hypermap_tuple_mix", mainf((tensor1, 1), (tensor2, 2)))
97 tensor1 = Tensor(np.array([[1.2, 2.1], [2.2, 3.2]]).astype('float32'))
99 main_noleaf(tensor1, tensor2)
108 tensor1 = Tensor(np.array([[1.1, 2.1], [2.1, 3.1]]).astype('float32'))
112 main_noleaf((tensor1, tensor3), (tensor2, tensor4))
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| D | test_multitype.py | 51 tensor1 = Tensor(np.array([[1.2, 2.1], [2.2, 3.2]]).astype('float32'))
53 mainf(tensor1, tensor2)
58 tensor1 = Tensor(np.array([[1.2, 2.1], [2.2, 3.2]]).astype('float32'))
59 params1 = Parameter(tensor1, name="params1")
87 tensor1 = Tensor(np.array([[1.2, 2.1], [2.2, 3.2]]).astype('float32'))
89 out = mainf2(tensor1, tensor2)
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| /third_party/mindspore/mindspore/lite/test/ut/nnacl/infer/ |
| D | infer_manager_test.cc | 33 Tensor *tensor1 = new (std::nothrow) Tensor; in TEST_F() local
35 tensor1->set_shape(tensor1_shape); in TEST_F()
37 tensor1->set_data(tensor1_data.data()); in TEST_F()
38 tensor1->set_data_type(kNumberTypeInt32); in TEST_F()
41 inputs.push_back(tensor1); in TEST_F()
107 Tensor *tensor1 = new Tensor; in TEST_F() local
110 tensor1->set_shape(tensor1_shape); in TEST_F()
111 tensor1->set_data(tensor1_data.data()); in TEST_F()
116 inputs.push_back(tensor1); in TEST_F()
152 Tensor *tensor1 = new (std::nothrow) Tensor; in TEST_F() local
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| /third_party/mindspore/mindspore/lite/test/ut/src/ |
| D | scheduler_test.cc | 104 auto tensor1 = std::make_unique<mindspore::schema::TensorT>(); in TEST_F() local
105 tensor1->nodeType = mindspore::lite::NodeType_ValueNode; in TEST_F()
106 tensor1->format = mindspore::schema::Format_NHWC; in TEST_F()
107 tensor1->dataType = mindspore::TypeId::kNumberTypeFloat32; in TEST_F()
108 tensor1->dims = {1, 16, 16, 2}; in TEST_F()
109 tensor1->offset = -1; in TEST_F()
154 meta_graph->allTensors.emplace_back(std::move(tensor1)); in TEST_F()
265 auto tensor1 = std::make_unique<mindspore::schema::TensorT>(); in TEST_F() local
266 tensor1->nodeType = mindspore::lite::NodeType_ValueNode; in TEST_F()
267 tensor1->format = mindspore::schema::Format_NHWC; in TEST_F()
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| D | utils_test.cc | 41 auto tensor1 = std::make_shared<lite::Tensor>(); in TEST_F() local
51 kernel0->set_in_tensors({tensor0.get(), tensor1.get()}); in TEST_F()
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| /third_party/mindspore/mindspore/lite/test/st/ |
| D | mix_data_type_test.cc | 139 auto tensor1 = std::make_unique<mindspore::schema::TensorT>(); in ConstructModel() local
140 tensor1->nodeType = mindspore::lite::NodeType_ValueNode; in ConstructModel()
141 tensor1->format = mindspore::schema::Format_NHWC; in ConstructModel()
142 tensor1->dataType = mindspore::TypeId::kNumberTypeFloat32; in ConstructModel()
143 tensor1->dims = {1, 2, 2, 1}; in ConstructModel()
144 tensor1->offset = -1; in ConstructModel()
145 tensor1->name = "tensor1"; in ConstructModel()
177 meta_graph->allTensors.emplace_back(std::move(tensor1)); in ConstructModel()
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| D | multiple_device_test.cc | 93 auto tensor1 = std::make_unique<mindspore::schema::TensorT>(); in CreateMultyModel1() local
94 tensor1->nodeType = mindspore::lite::NodeType_ValueNode; in CreateMultyModel1()
95 tensor1->format = mindspore::schema::Format_NHWC; in CreateMultyModel1()
96 tensor1->dataType = mindspore::TypeId::kNumberTypeFloat32; in CreateMultyModel1()
97 tensor1->dims = {1, 1, 1, 1}; in CreateMultyModel1()
98 tensor1->offset = -1; in CreateMultyModel1()
99 tensor1->name = "tensor1"; in CreateMultyModel1()
154 meta_graph->allTensors.emplace_back(std::move(tensor1)); in CreateMultyModel1()
197 auto tensor1 = std::make_unique<mindspore::schema::TensorT>(); in CreateMultyModel2() local
198 tensor1->nodeType = mindspore::lite::NodeType_ValueNode; in CreateMultyModel2()
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| /third_party/mindspore/tests/ut/python/utils/ |
| D | test_initializer.py | 153 tensor1 = init.initializer(init.XavierUniform(gain=gain), [20, 22], ms.float32).init_data()
159 …tensor_dict = {tensor1: gain, tensor2: None, tensor3: gain, tensor4: None, tensor5: None, tensor6:…
183 tensor1 = init.initializer(init.HeUniform(), [20, 22], ms.float32)
187 tensors = [tensor1.init_data(), tensor2.init_data(), tensor3.init_data(), tensor4.init_data()]
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| /third_party/mindspore/tests/ut/python/debugger/gpu_tests/ |
| D | test_read_tensors_nonexist_node.py | 38 tensor1 = np.array([32.0, 4096.0], np.float32)
50 tensor_list = [tensor1, tensor2]
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| D | test_read_tensors.py | 39 tensor1 = np.array([32.0, 4096.0], np.float32)
70 tensor_list = [tensor1, tensor2, tensor3, tensor4]
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| D | test_watchpoints.py | 39 tensor1 = np.array([[[-1.2808e-03, 7.7629e-03, 1.9241e-02],
71 tensor_list = [tensor1, tensor2, tensor3, tensor4]
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| /third_party/mindspore/tests/ut/cpp/python_input/gtest_input/optimizer/ |
| D | opt_test.py | 1067 tensor1 = Tensor(np.array([[1.2, 2.1], [2.2, 3.2]]).astype('float32'))
1072 return Mul(tensor1, Mul(tensor2, Sqrt(x)))
1076 return Mul(tensor1, Mul(Sqrt(x), tensor2))
1080 return Mul(Mul(Sqrt(x), tensor2), tensor1)
1084 return Mul(Mul(Sqrt(x), tensor2), tensor1)
1088 return Mul(Sqrt(x), Mul(tensor1, tensor2))
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| /third_party/mindspore/mindspore/ccsrc/frontend/optimizer/ |
| D | cse.cc | 187 auto tensor1 = GetValueNode<tensor::TensorPtr>(inp1_j); in CheckReplace() local
189 if (tensor1->ValueEqual(*tensor2)) { in CheckReplace()
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| /third_party/mindspore/tests/ut/python/parameter_feature/ |
| D | test_parameter.py | 51 tensor1 = Tensor(np.full((2, 3), 2).astype(np.float32))
54 assert np.all(net(tensor1, tensor2).asnumpy() == tensor1.asnumpy())
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| /third_party/mindspore/mindspore/ccsrc/backend/optimizer/somas/ |
| D | somas.cc | 1203 for (auto tensor1 : tensors_list_) { in Assign() local
1204 auto ones_num = reuse_matrix_[tensor1->GetId()].CountOnesNum(); in Assign()
1205 tensor1->num_constraints_ = tensors_num - ones_num; in Assign()
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| /third_party/mindspore/mindspore/ccsrc/backend/optimizer/trt_pass/ |
| D | trt_op_converter.cc | 581 nvinfer1::ITensor *tensor1 = ToTensor(&inputs[0], shape1, context); in MS_TRT_CONVERTER_FUNC_REG() local
583 …auto *layer = context->network()->addMatrixMultiply(*tensor1, trt_transpose1, *tensor2, trt_transp… in MS_TRT_CONVERTER_FUNC_REG()
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