From: @peilin-wang Reviewed-by: @liangchenghui,@youui Signed-off-by: @liangchenghuitags/v1.1.0
| @@ -729,62 +729,6 @@ AbstractBasePtr InferImplReshape(const AnalysisEnginePtr &, const PrimitivePtr & | |||||
| return ret; | return ret; | ||||
| } | } | ||||
| AbstractBasePtr InferImplExpandDims(const AnalysisEnginePtr &, const PrimitivePtr &primitive, | |||||
| const AbstractBasePtrList &args_spec_list) { | |||||
| const std::string op_name = primitive->name(); | |||||
| CheckArgsSize(op_name, args_spec_list, 2); | |||||
| auto x = CheckArg<AbstractTensor>(op_name, args_spec_list, 0); | |||||
| MS_EXCEPTION_IF_NULL(x); | |||||
| MS_EXCEPTION_IF_NULL(x->shape()); | |||||
| ShapeVector x_shape = x->shape()->shape(); | |||||
| ShapeVector x_shape_min = x->shape()->min_shape(); | |||||
| if (x_shape_min.empty()) { | |||||
| x_shape_min = x_shape; | |||||
| } | |||||
| ShapeVector x_shape_max = x->shape()->max_shape(); | |||||
| if (x_shape_max.empty()) { | |||||
| x_shape_max = x_shape; | |||||
| } | |||||
| int64_t value = 0; | |||||
| if (args_spec_list[1]->isa<AbstractTensor>()) { // axis is Tensor | |||||
| auto axis = CheckArg<AbstractTensor>(op_name, args_spec_list, 1); | |||||
| auto axis_value = axis->BuildValue(); | |||||
| if (!axis_value->isa<tensor::Tensor>()) { | |||||
| MS_LOG(EXCEPTION) << axis_value << " axis_value should be tensor, but got " << axis_value->type_name(); | |||||
| } | |||||
| auto axis_tensor = axis_value->cast<tensor::TensorPtr>(); | |||||
| value = *(static_cast<int64_t *>(axis_tensor->data_c())); | |||||
| } else if (args_spec_list[1]->isa<AbstractScalar>()) { // axis is Scalar | |||||
| auto axis = CheckArg<AbstractScalar>(op_name, args_spec_list, 1); | |||||
| MS_EXCEPTION_IF_NULL(axis); | |||||
| value = GetValue<int64_t>(axis->BuildValue()); | |||||
| } else { | |||||
| MS_LOG(EXCEPTION) << "axis incorrect type in ExpandDims"; | |||||
| } | |||||
| if (value < -(SizeToInt(x_shape.size()) + 1) || value > SizeToInt(x_shape.size())) { | |||||
| MS_LOG(EXCEPTION) << " axis value shoud be in range [-intput_x.dim-1,input_x.dim], but axis value is" << value | |||||
| << " and input_x.dim is" << x_shape.size(); | |||||
| } | |||||
| if (value < 0) { | |||||
| value = value + SizeToInt(x_shape.size()) + 1; | |||||
| } | |||||
| ShapeVector shape; | |||||
| shape.insert(shape.end(), x_shape.begin(), x_shape.end()); | |||||
| shape.insert(shape.begin() + value, 1); | |||||
| ShapeVector shape_min; | |||||
| shape_min.insert(shape_min.end(), x_shape_min.begin(), x_shape_min.end()); | |||||
| shape_min.insert(shape_min.begin() + value, 1); | |||||
| ShapeVector shape_max; | |||||
| shape_max.insert(shape_max.end(), x_shape_max.begin(), x_shape_max.end()); | |||||
| shape_max.insert(shape_max.begin() + value, 1); | |||||
| auto ret = std::make_shared<AbstractTensor>(x->element(), std::make_shared<Shape>(shape, shape_min, shape_max)); | |||||
| return ret; | |||||
| } | |||||
| AbstractBasePtr InferImplSplit(const AnalysisEnginePtr &, const PrimitivePtr &primitive, | AbstractBasePtr InferImplSplit(const AnalysisEnginePtr &, const PrimitivePtr &primitive, | ||||
| const AbstractBasePtrList &args_spec_list) { | const AbstractBasePtrList &args_spec_list) { | ||||
| const std::string op_name = primitive->name(); | const std::string op_name = primitive->name(); | ||||
| @@ -492,6 +492,32 @@ AbstractBasePtr InferImplCast(const AnalysisEnginePtr &, const PrimitivePtr &pri | |||||
| return ret; | return ret; | ||||
| } | } | ||||
| AbstractBasePtr InferImplExpandDims(const AnalysisEnginePtr &, const PrimitivePtr &primitive, | |||||
| const AbstractBasePtrList &args_spec_list) { | |||||
| const std::string op_name = primitive->name(); | |||||
| CheckArgsSize(op_name, args_spec_list, 1); | |||||
| auto x = CheckArg<AbstractTensor>(op_name, args_spec_list, 0); | |||||
| MS_EXCEPTION_IF_NULL(x); | |||||
| MS_EXCEPTION_IF_NULL(x->shape()); | |||||
| std::vector<int64_t> shape; | |||||
| std::vector<int64_t> x_shape = x->shape()->shape(); | |||||
| shape.insert(shape.end(), x_shape.begin(), x_shape.end()); | |||||
| auto axis = primitive->GetAttr("axis"); | |||||
| auto value = GetValue<int64_t>(axis); | |||||
| if (value < -(SizeToInt(x_shape.size()) + 1) || value > SizeToInt(x_shape.size())) { | |||||
| MS_LOG(EXCEPTION) << " axis value shoud be in range [-intput_x.dim-1,input_x.dim], but axis value is" << value | |||||
| << " and input_x.dim is" << x_shape.size(); | |||||
| } | |||||
| if (value < 0) { | |||||
| value = value + SizeToInt(x_shape.size()) + 1; | |||||
| } | |||||
| shape.insert(shape.begin() + value, 1); | |||||
| auto ret = std::make_shared<AbstractTensor>(x->element(), std::make_shared<Shape>(shape)); | |||||
| return ret; | |||||
| } | |||||
| AbstractBasePtr InferImplGpuConvertToDynamicShape(const AnalysisEnginePtr &, const PrimitivePtr &primitive, | AbstractBasePtr InferImplGpuConvertToDynamicShape(const AnalysisEnginePtr &, const PrimitivePtr &primitive, | ||||
| const AbstractBasePtrList &args_spec_list) { | const AbstractBasePtrList &args_spec_list) { | ||||
| const std::string &op_name = primitive->name(); | const std::string &op_name = primitive->name(); | ||||
| @@ -118,7 +118,7 @@ def _check_infer_attr_reduce(axis, keep_dims, prim_name): | |||||
| validator.check_value_type('axis[%d]' % index, value, [int], prim_name) | validator.check_value_type('axis[%d]' % index, value, [int], prim_name) | ||||
| class ExpandDims(PrimitiveWithCheck): | |||||
| class ExpandDims(PrimitiveWithInfer): | |||||
| """ | """ | ||||
| Adds an additional dimension at the given axis. | Adds an additional dimension at the given axis. | ||||
| @@ -156,13 +156,29 @@ class ExpandDims(PrimitiveWithCheck): | |||||
| """Initialize ExpandDims""" | """Initialize ExpandDims""" | ||||
| self.init_prim_io_names(inputs=['x', 'axis'], outputs=['output']) | self.init_prim_io_names(inputs=['x', 'axis'], outputs=['output']) | ||||
| def __check__(self, x, axis): | |||||
| def __infer__(self, x, axis): | |||||
| validator.check_subclass("x", x['dtype'], mstype.tensor, self.name) | validator.check_subclass("x", x['dtype'], mstype.tensor, self.name) | ||||
| validator.check_subclass("axis", axis['dtype'], mstype.int_, self.name) | |||||
| x_shape = list(x['shape']) | x_shape = list(x['shape']) | ||||
| axis_v = axis['value'] | axis_v = axis['value'] | ||||
| rank = len(x_shape) | rank = len(x_shape) | ||||
| validator.check_int_range(axis_v, -rank - 1, rank, Rel.INC_BOTH, 'axis', self.name) | validator.check_int_range(axis_v, -rank - 1, rank, Rel.INC_BOTH, 'axis', self.name) | ||||
| value = None | |||||
| if x['value'] is not None: | |||||
| value = x['value'].asnumpy() | |||||
| value = np.expand_dims(value, axis_v) | |||||
| value = Tensor(value) | |||||
| if axis_v < 0: | |||||
| axis_v = rank + 1 + axis_v | |||||
| x_shape.insert(axis_v, 1) | |||||
| out = {'shape': x_shape, | |||||
| 'dtype': x['dtype'], | |||||
| 'value': value} | |||||
| if 'min_shape' in x and 'max_shape' in x: | |||||
| out['min_shape'] = x['min_shape'] | |||||
| out['min_shape'].insert(axis_v, 1) | |||||
| out['max_shape'] = x['max_shape'] | |||||
| out['max_shape'].insert(axis_v, 1) | |||||
| return out | |||||
| class DType(PrimitiveWithInfer): | class DType(PrimitiveWithInfer): | ||||