1 /** 2 * Copyright 2020 Huawei Technologies Co., Ltd 3 * 4 * Licensed under the Apache License, Version 2.0 (the "License"); 5 * you may not use this file except in compliance with the License. 6 * You may obtain a copy of the License at 7 * 8 * http://www.apache.org/licenses/LICENSE-2.0 9 * 10 * Unless required by applicable law or agreed to in writing, software 11 * distributed under the License is distributed on an "AS IS" BASIS, 12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 * See the License for the specific language governing permissions and 14 * limitations under the License. 15 */ 16 #include <iostream> 17 #include <memory> 18 #include "common/common_test.h" 19 #include "pipeline/jit/parse/python_adapter.h" 20 #include "pipeline/jit/parse/data_converter.h" 21 #include "frontend/operator/ops.h" 22 #include "pipeline/pynative/pynative_execute.h" 23 #include "utils/ms_context.h" 24 #include "utils/utils.h" 25 26 namespace py = pybind11; 27 using pybind11::literals::operator"" _a; 28 using Tensor = mindspore::tensor::Tensor; 29 using TensorPtr = mindspore::tensor::TensorPtr; 30 31 namespace mindspore { 32 namespace pynative { 33 class TestPynativeExecute : public UT::Common { 34 public: 35 TestPynativeExecute() {} 36 }; 37 38 inline ValuePtr PyAttrValue(const py::object &obj) { 39 ValuePtr converted_ret; 40 bool converted = parse::ConvertData(obj, &converted_ret); 41 if (!converted) { 42 MS_LOG(EXCEPTION) << "attribute convert error with type:" << std::string(py::str(obj)); 43 } 44 return converted_ret; 45 } 46 47 OpExecInfoPtr ConstructOpExecInfo() { 48 py::str op_name = "Conv2D"; 49 py::object tensor_py_module = py::module::import("mindspore.common.tensor").attr("Tensor"); 50 py::object np_py_module = py::module::import("numpy"); 51 py::object np_ones = np_py_module.attr("ones"); 52 py::object np_float32 = np_py_module.attr("float32"); 53 py::tuple weight_dim = py::make_tuple(64, 3, 3, 3); 54 py::object weight = tensor_py_module(np_float32(np_ones(weight_dim))); 55 py::tuple op_params = py::make_tuple(weight); 56 py::tuple inputs_dim = py::make_tuple(1, 3, 6, 6); 57 py::object input = tensor_py_module(np_float32(np_ones(inputs_dim))); 58 py::tuple op_inputs = py::make_tuple(input, weight); 59 60 py::tuple kernel_size = py::make_tuple(3, 3); 61 py::dict op_attrs = py::dict("out_channel"_a = 64, "kernel_size"_a = kernel_size, "mode"_a = 1, "pad_mode"_a = "same", 62 "stride"_a = 1, "dilation"_a = 1, "group"_a = 1, "data_format"_a = kOpFormat_NCHW); 63 64 auto conv_obj = prim::GetPythonOps("conv2d_prim", "gtest_input.pynative"); 65 py::none py_none; 66 py::args args = py::make_tuple(conv_obj, op_name, op_inputs); 67 py::list args_input = args[PY_INPUTS]; 68 return PynativeExecutor::GetInstance()->forward_executor()->GenerateOpExecInfo(args); 69 } 70 71 TEST_F(TestPynativeExecute, TestCreateContext) { 72 auto ctx3 = MsContext::GetInstance(); 73 ASSERT_EQ(ctx3->backend_policy(), "vm"); 74 ASSERT_EQ(ctx3->get_param<std::string>(MS_CTX_DEVICE_TARGET), "CPU"); 75 76 ctx3->set_backend_policy("ge_only"); 77 ctx3->set_param<std::string>(MS_CTX_DEVICE_TARGET, "GPU"); 78 auto ctx4 = MsContext::GetInstance(); 79 80 ASSERT_EQ(ctx3.get(), ctx4.get()); 81 ASSERT_EQ(ctx4->backend_policy(), "ge_only"); 82 ASSERT_EQ(ctx4->get_param<std::string>(MS_CTX_DEVICE_TARGET), "GPU"); 83 } 84 85 TEST_F(TestPynativeExecute, TestDefaultContext) { 86 auto ctx = MsContext::GetInstance(); 87 88 ASSERT_EQ(std::string(ctx->backend_policy()), "ge_only"); 89 90 auto ctx2 = MsContext::GetInstance(); 91 92 ASSERT_EQ(ctx.get(), ctx2.get()); 93 } 94 95 } // namespace pynative 96 } // namespace mindspore 97