# Copyright 2020 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ """ test_tuple_slice """ import numpy as np import pytest from mindspore import Tensor from mindspore.nn import Cell import mindspore.ops.operations as P from ....mindspore_test_framework.mindspore_test import mindspore_test from ....mindspore_test_framework.pipeline.forward.compile_forward \ import pipeline_for_compile_forward_ge_graph_for_case_by_case_config from ....mindspore_test_framework.pipeline.forward.verify_exception \ import pipeline_for_verify_exception_for_case_by_case_config class NetWork_1(Cell): """ NetWork_1 definition """ def __init__(self): super(NetWork_1, self).__init__() self.addN = P.AddN() def construct(self, tensor_tuple): tensor_tuple_slice0 = tensor_tuple[:] tensor_tuple_slice1 = tensor_tuple[:3] tensor_tuple_slice2 = tensor_tuple[1:] tensor_tuple_slice3 = tensor_tuple[2:5:1] sum0 = self.addN(tensor_tuple_slice0) sum1 = self.addN(tensor_tuple_slice1) sum2 = self.addN(tensor_tuple_slice2) sum3 = self.addN(tensor_tuple_slice3) ret = sum0 + sum1 + sum2 + sum3 return ret class NetWork_2(Cell): """ NetWork_2 definition """ def __init__(self): super(NetWork_2, self).__init__() self.addN = P.AddN() def construct(self, tensor_tuple): tensor_tuple_slice0 = tensor_tuple[::-1] tensor_tuple_slice1 = tensor_tuple[-1::-1] tensor_tuple_slice2 = tensor_tuple[:-4:-1] tensor_tuple_slice3 = tensor_tuple[-6:3] tensor_tuple_slice4 = tensor_tuple[-1:-6:-2] sum0 = self.addN(tensor_tuple_slice0) sum1 = self.addN(tensor_tuple_slice1) sum2 = self.addN(tensor_tuple_slice2) sum3 = self.addN(tensor_tuple_slice3) sum4 = self.addN(tensor_tuple_slice4) ret = sum0 + sum1 + sum2 + sum3 + sum4 return ret class NetWork_3(Cell): """ NetWork_3 definition """ def __init__(self): super(NetWork_3, self).__init__() self.addN = P.AddN() def construct(self, tensor_tuple, start, stop, step=1): tensor_tuple_slice0 = tensor_tuple[start:stop:step] res = self.addN(tensor_tuple_slice0) return res test_cases = [ ('SlicePositive', { 'block': NetWork_1(), 'desc_inputs': [(Tensor(np.ones([2, 3, 4], np.int32)), Tensor(np.zeros([2, 3, 4], np.int32)), Tensor(np.ones([2, 3, 4], np.int32)), Tensor(np.ones([2, 3, 4], np.int32)), Tensor(np.zeros([2, 3, 4], np.int32)), Tensor(np.ones([2, 3, 4], np.int32)))], }), ('SliceNegative', { 'block': NetWork_2(), 'desc_inputs': [(Tensor(np.ones([2, 3, 4], np.int32)), Tensor(np.zeros([2, 3, 4], np.int32)), Tensor(np.ones([2, 3, 4], np.int32)), Tensor(np.ones([2, 3, 4], np.int32)), Tensor(np.zeros([2, 3, 4], np.int32)), Tensor(np.ones([2, 3, 4], np.int32)))], }), ] test_cases_for_verify_exception = [ ('SliceStartCross', { 'block': (NetWork_3(), {'exception': RuntimeError}), 'desc_inputs': [*(Tensor(np.ones([2, 3, 4], np.int32)), Tensor(np.zeros([2, 3, 4], np.int32)), Tensor(np.ones([2, 3, 4], np.int32)))], }), ('SliceStepZero', { 'block': (NetWork_3(), {'exception': RuntimeError}), 'desc_inputs': [*(Tensor(np.ones([2, 3, 4], np.int32)), Tensor(np.zeros([2, 3, 4], np.int32)), Tensor(np.ones([2, 3, 4], np.int32)))], }), ] @mindspore_test(pipeline_for_compile_forward_ge_graph_for_case_by_case_config) def test_compile(): return test_cases @mindspore_test(pipeline_for_verify_exception_for_case_by_case_config) def test_check_exception(): return test_cases_for_verify_exception