forked from mindspore-Ecosystem/mindspore
change error log
This commit is contained in:
lianliguang
parent
33800c7f31
commit
efabace125
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@ -1003,7 +1003,13 @@ int64_t CheckSliceMember(const AbstractBasePtr &member, int64_t default_value, c
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return default_value;
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}
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MS_LOG(EXCEPTION) << "The argument of SliceMember operator must be a Scalar or None, but got " << member->ToString();
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if (member->isa<abstract::AbstractTensor>()) {
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MS_EXCEPTION(TypeError)
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<< "The argument of SliceMember operator must be a Scalar or None or constant Tensor, but got a variable Tensor";
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}
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MS_EXCEPTION(TypeError)
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<< "The argument of SliceMember operator must be a Scalar or None or constant Tensor, but got "
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<< member->BuildType()->ToString();
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}
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void GenerateTupleSliceParameter(const abstract::AbstractSequencePtr &tuple, const AbstractSlicePtr &slice,
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@ -194,7 +194,7 @@ class SequenceSlice : public MetaFuncGraph {
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: MetaFuncGraph(name), prim_(prim), get_item_(get_item) {}
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~SequenceSlice() override = default;
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MS_DECLARE_PARENT(SequenceSlice, MetaFuncGraph)
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FuncGraphPtr GenerateFuncGraph(const AbstractBasePtrList &args_spec_list) override;
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FuncGraphPtr GenerateFuncGraph(const AbstractBasePtrList &args_spec_list) final;
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friend bool operator==(const SequenceSlice &lhs, const SequenceSlice &rhs) { return lhs.name_ == rhs.name_; }
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virtual std::pair<abstract::AbstractSequencePtr, abstract::AbstractSlicePtr> CheckArgs(
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const AbstractBasePtrList &args_spec_list) = 0;
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@ -1149,7 +1149,7 @@ EvalResultPtr GetEvaluatedValueForBuiltinTypeAttrOrMethod(const AnalysisEnginePt
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if (require.empty()) {
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require = pipeline::Resource::GetAttrPtr(data_type->type_id(), item_name);
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if (require.empty()) {
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MS_LOG(EXCEPTION) << "Not supported to get attribute item name:\'" << item_name << "\' of a type["
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MS_LOG(EXCEPTION) << "MindSpore not support to get attribute \'" << item_name << "\' of a type["
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<< data_type->ToString() << "]";
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}
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require_type = REQUIRE_TYPE::ATTR;
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@ -338,11 +338,11 @@ AbstractBasePtr InferImplCTCGreedyDecoder(const AnalysisEnginePtr &, const Primi
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AbstractBasePtr InferImplPad(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
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const AbstractBasePtrList &args_spec_list) {
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MS_EXCEPTION_IF_NULL(primitive);
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const std::string op_name = primitive->name();
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CheckArgsSize(op_name, args_spec_list, 1);
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auto arg = CheckArg<AbstractTensor>(op_name, args_spec_list, 0);
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auto input_shp = arg->shape()->shape();
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MS_EXCEPTION_IF_NULL(primitive);
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auto padding_attr = primitive->GetAttr("paddings");
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MS_EXCEPTION_IF_NULL(padding_attr);
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if (!padding_attr->isa<ValueTuple>()) {
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@ -21,6 +21,7 @@ from ...components.function.compile_block import CompileBlockBC
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from ...components.function.run_block import RunBlockBC
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from ...components.function_inputs_policy.cartesian_product_on_id_for_function_inputs import IdCartesianProductFIPC
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from ...components.inputs.generate_inputs_from_shape import GenerateFromShapeDC
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from ...components.inputs.get_inputs_from_config import IdentityDC
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# pylint: disable=W0105
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"""
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@ -61,3 +62,7 @@ pipeline_for_compile_forward_ge_graph_for_case_by_case_config = [MeFacadeFC, Gen
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pipeline_for_compile_forward_ge_graph_for_case_by_case_config_exception = [MeFacadeFC, GenerateFromShapeDC, RunBlockBC,
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IdCartesianProductFIPC]
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pipeline_for_compile_forward_ge_graph_for_case_by_case_config_input_list = [MeFacadeFC, RunBlockBC,
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IdCartesianProductFIPC, IdentityEC,
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IdentityDC]
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@ -0,0 +1,204 @@
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# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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""" test_list_slice """
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import numpy as np
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import mindspore.ops.operations as P
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from mindspore import Tensor
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from mindspore.nn import Cell
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from ....mindspore_test_framework.mindspore_test import mindspore_test
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from ....mindspore_test_framework.pipeline.forward.compile_forward \
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import pipeline_for_compile_forward_ge_graph_for_case_by_case_config_input_list
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from ....mindspore_test_framework.pipeline.forward.verify_exception \
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import pipeline_for_verify_exception_for_case_by_case_config
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class NetWork_1(Cell):
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""" NetWork_1 definition """
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def __init__(self):
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super(NetWork_1, self).__init__()
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self.addN = P.AddN()
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self.index_0 = Tensor(3)
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self.index_1 = Tensor([5])
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self.index_3 = Tensor([True])
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def construct(self, tensor_list):
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tensor_list_slice0 = tensor_list[:]
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tensor_list_slice1 = tensor_list[:self.index_0]
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tensor_list_slice2 = tensor_list[self.index_3:]
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tensor_list_slice3 = tensor_list[2:self.index_1:True]
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sum0 = self.addN(tensor_list_slice0)
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sum1 = self.addN(tensor_list_slice1)
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sum2 = self.addN(tensor_list_slice2)
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sum3 = self.addN(tensor_list_slice3)
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ret = sum0 + sum1 + sum2 + sum3
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return ret
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class NetWork_2(Cell):
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""" NetWork_2 definition """
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def __init__(self):
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super(NetWork_2, self).__init__()
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self.addN = P.AddN()
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self.step = Tensor([-1])
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self.index_0 = Tensor(-6)
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def construct(self, tensor_list):
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tensor_list_slice0 = tensor_list[::self.step]
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tensor_list_slice1 = tensor_list[-1::-1]
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tensor_list_slice2 = tensor_list[:-4:-1]
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tensor_list_slice3 = tensor_list[self.index_0:3]
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tensor_list_slice4 = tensor_list[-1:-6:-2]
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sum0 = self.addN(tensor_list_slice0)
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sum1 = self.addN(tensor_list_slice1)
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sum2 = self.addN(tensor_list_slice2)
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sum3 = self.addN(tensor_list_slice3)
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sum4 = self.addN(tensor_list_slice4)
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ret = sum0 + sum1 + sum2 + sum3 + sum4
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return ret
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class NetWorkSliceStepZero(Cell):
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""" NetWorkSliceStepZero definition """
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def __init__(self):
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super(NetWorkSliceStepZero, self).__init__()
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self.start = 0
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self.stop = 3
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self.step = 0
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def construct(self, tensor_list):
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tensor_list_slice = tensor_list[self.start:self.stop:self.step]
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return tensor_list_slice
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class NetWorkOutOfBounds(Cell):
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""" NetWork_3 definition """
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def __init__(self):
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super(NetWorkOutOfBounds, self).__init__()
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self.index = 100
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def construct(self, tensor_list):
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return tensor_list[self.index]
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class NetWorkTensorSizeGreaterThanTwo(Cell):
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""" NetWork_3 definition """
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def __init__(self):
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super(NetWorkTensorSizeGreaterThanTwo, self).__init__()
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self.index_0 = Tensor([2, 3])
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def construct(self, tensor_list):
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return tensor_list[1:self.index_0]
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class NetWorkTensorDtypeFloat(Cell):
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""" NetWork_3 definition """
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def __init__(self):
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super(NetWorkTensorDtypeFloat, self).__init__()
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self.index_0 = Tensor([2.1])
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def construct(self, tensor_list):
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return tensor_list[1:self.index_0]
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class NewWorkSliceVarTensorError(Cell):
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""" error Network definition """
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def __init__(self):
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super(NewWorkSliceVarTensorError, self).__init__()
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self.index_0 = Tensor(2)
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def construct(self, tensor_list, y):
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x = y + self.index_0
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return tensor_list[1:x]
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test_cases = [
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('SlicePositive', {
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'block': NetWork_1(),
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'desc_inputs': [[Tensor(np.ones([2, 3, 4], np.int32)),
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Tensor(np.zeros([2, 3, 4], np.int32)),
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Tensor(np.ones([2, 3, 4], np.int32)),
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Tensor(np.ones([2, 3, 4], np.int32)),
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Tensor(np.zeros([2, 3, 4], np.int32)),
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Tensor(np.ones([2, 3, 4], np.int32))]],
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}),
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('SliceNegative', {
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'block': NetWork_2(),
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'desc_inputs': [[Tensor(np.ones([2, 3, 4], np.int32)),
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Tensor(np.zeros([2, 3, 4], np.int32)),
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Tensor(np.ones([2, 3, 4], np.int32)),
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Tensor(np.ones([2, 3, 4], np.int32)),
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Tensor(np.zeros([2, 3, 4], np.int32)),
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Tensor(np.ones([2, 3, 4], np.int32))]],
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}),
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]
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test_cases_for_verify_exception = [
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('SliceStepZero', {
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'block': (NetWorkSliceStepZero(), {'exception': ValueError}),
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'desc_inputs': [[Tensor(np.ones([2, 3, 4], np.int32)),
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Tensor(np.zeros([2, 3, 4], np.int32)),
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Tensor(np.ones([2, 3, 4], np.int32))]],
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}),
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('SliceOutOfBounds', {
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'block': (NetWorkOutOfBounds(), {'exception': IndexError}),
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'desc_inputs': [[Tensor(np.ones([2, 3, 4], np.int32)),
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Tensor(np.zeros([2, 3, 4], np.int32)),
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Tensor(np.ones([2, 3, 4], np.int32))]],
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}),
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('SliceTensorSizeGreaterThanTwo', {
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'block': (NetWorkTensorSizeGreaterThanTwo(), {'exception': TypeError}),
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'desc_inputs': [[Tensor(np.ones([2, 3, 4], np.int32)),
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Tensor(np.zeros([2, 3, 4], np.int32)),
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Tensor(np.ones([2, 3, 4], np.int32))]],
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}),
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('SliceTensorDtypeFloat', {
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'block': (NetWorkTensorDtypeFloat(), {'exception': TypeError}),
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'desc_inputs': [[Tensor(np.ones([2, 3, 4], np.int32)),
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Tensor(np.zeros([2, 3, 4], np.int32)),
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Tensor(np.ones([2, 3, 4], np.int32))]],
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}),
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('NewWorkSliceVarTensorError', {
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'block': (NewWorkSliceVarTensorError(), {'exception': TypeError}),
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'desc_inputs': [[Tensor(np.ones([2, 3, 4], np.int32)),
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Tensor(np.zeros([2, 3, 4], np.int32)),
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Tensor(np.ones([2, 3, 4], np.int32))], Tensor(1)],
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}),
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]
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@mindspore_test(pipeline_for_compile_forward_ge_graph_for_case_by_case_config_input_list)
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def test_compile():
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"""
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Feature: test list slice
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Description: test list slice positive and negative
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Expectation: success
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"""
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return test_cases
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@mindspore_test(pipeline_for_verify_exception_for_case_by_case_config)
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def test_check_exception():
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"""
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Feature: test list getitem exception
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Description: test list getitem exception
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Expectation: throw errors
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"""
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return test_cases_for_verify_exception
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