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!15244 Add logsoftmax C++ infer. 

From: @liangzhibo
Reviewed-by: @zh_qh,@ginfung,@ginfung,@zh_qh
Signed-off-by: @zh_qh,@zh_qh
This commit is contained in:
mindspore-ci-bot 2021-04-16 14:26:53 +08:00 committed by Gitee
parent b30264b9d7 c83ae2f294
commit 44c3fce818
5 changed files with 22 additions and 41 deletions
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2
mindspore/core/abstract/infer_functions.h
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@ -304,8 +304,6 @@ AbstractBasePtr InferImplArgMaxWithValue(const AnalysisEnginePtr &, const Primit
const AbstractBasePtrList &args_spec_list);
AbstractBasePtr InferImplSparseSoftmaxCrossEntropyWithLogits(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
const AbstractBasePtrList &args_spec_list);
AbstractBasePtr InferImplDType(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
const AbstractBasePtrList &args_spec_list);
AbstractBasePtr InferImplLoad(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
const AbstractBasePtrList &args_spec_list);
AbstractBasePtr InferImplAssign(const AnalysisEnginePtr &, const PrimitivePtr &primitive,

16
mindspore/core/abstract/prim_others.cc
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@ -545,22 +545,6 @@ AbstractBasePtr InferImplGpuConvertToDynamicShape(const AnalysisEnginePtr &, con
return std::make_shared<AbstractTensor>(input->element(), shape);
}
AbstractBasePtr InferImplDType(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
const AbstractBasePtrList &args_spec_list) {
MS_EXCEPTION_IF_NULL(primitive);
auto op_name = primitive->name();
CheckArgsSize(op_name, args_spec_list, 1);
MS_EXCEPTION_IF_NULL(args_spec_list[0]);
auto type = args_spec_list[0]->BuildType();
MS_EXCEPTION_IF_NULL(type);
auto tensor_type = type->cast<TensorTypePtr>();
MS_EXCEPTION_IF_NULL(tensor_type);
auto value = tensor_type->element();
auto abstract = std::make_shared<abstract::AbstractType>(value);
abstract->set_value(value);
return abstract;
}
AbstractBasePtr InferImplLoad(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
const AbstractBasePtrList &args_spec_list) {
// Inputs: Ref/Tensor, universal

31
mindspore/core/ops/log_softmax.cc
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@ -34,22 +34,33 @@ void LogSoftmax::Init(const int64_t axis) { this->set_axis(axis); }
abstract::ShapePtr LogSoftmaxInferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
MS_EXCEPTION_IF_NULL(primitive);
auto LogSoftmax_prim = primitive->cast<PrimLogSoftmaxPtr>();
MS_EXCEPTION_IF_NULL(LogSoftmax_prim);
auto op_name = LogSoftmax_prim->name();
auto axis = LogSoftmax_prim->get_axis();
auto in_shape = CheckAndConvertUtils::ConvertShapePtrToShape("input_shape", input_args[0]->GetShapeTrack(), op_name);
auto op_name = primitive->name();
auto axis = GetValue<int64_t>(primitive->GetAttr(kAxis));
CheckAndConvertUtils::CheckInteger("log_softmax infer", input_args.size(), kEqual, 1, op_name);
MS_EXCEPTION_IF_NULL(input_args[0]);
auto shape_map = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[0]->BuildShape());
if (shape_map.empty()) {
// Scalar input, has no shape
return std::make_shared<abstract::Shape>(std::vector<int64_t>());
}
auto in_shape = shape_map[kShape];
auto min_shape = shape_map[kMinShape];
auto max_shape = shape_map[kMaxShape];
auto rank = SizeToLong(in_shape.size());
CheckAndConvertUtils::CheckInRange<int64_t>("axis", axis, kIncludeLeft, {-rank, rank}, op_name);
if (min_shape.size() != 0 && max_shape.size() != 0) {
return std::make_shared<abstract::Shape>(in_shape, min_shape, max_shape);
}
return std::make_shared<abstract::Shape>(in_shape);
}
TypePtr LogSoftmaxInferType(const PrimitivePtr &prim, const std::vector<AbstractBasePtr> &input_args) {
if (std::any_of(input_args.begin(), input_args.end(), [](const AbstractBasePtr &a) { return a == nullptr; })) {
MS_LOG(EXCEPTION) << "nullptr";
}
MS_EXCEPTION_IF_NULL(prim);
auto op_name = prim->name();
CheckAndConvertUtils::CheckInteger("log_softmax infer", input_args.size(), kEqual, 1, op_name);
MS_EXCEPTION_IF_NULL(input_args[0]);
const std::set<TypePtr> valid_types = {kFloat16, kFloat32};
return CheckAndConvertUtils::CheckTensorTypeValid("x", input_args[0]->BuildType(), valid_types, prim->name());
return CheckAndConvertUtils::CheckTensorTypeValid("x", input_args[0]->BuildType(), valid_types, op_name);
}
AbstractBasePtr LogSoftmaxInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
@ -57,6 +68,6 @@ AbstractBasePtr LogSoftmaxInfer(const abstract::AnalysisEnginePtr &, const Primi
return std::make_shared<abstract::AbstractTensor>(LogSoftmaxInferType(primitive, input_args),
LogSoftmaxInferShape(primitive, input_args)->shape());
}
REGISTER_PRIMITIVE_C(kNameLogSoftmax, LogSoftmax);
REGISTER_PRIMITIVE_EVAL_IMPL(LogSoftmax, prim::kPrimLogSoftmax, LogSoftmaxInfer, nullptr, true);
} // namespace ops
} // namespace mindspore

3
mindspore/core/ops/log_softmax.h
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@ -37,9 +37,6 @@ class LogSoftmax : public PrimitiveC {
void set_axis(const int64_t axis);
int64_t get_axis() const;
};
AbstractBasePtr LogSoftmaxInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
const std::vector<AbstractBasePtr> &input_args);
using PrimLogSoftmaxPtr = std::shared_ptr<LogSoftmax>;
} // namespace ops
} // namespace mindspore

11
mindspore/ops/operations/nn_ops.py
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@ -178,7 +178,7 @@ class Softmax(Primitive):
validator.check_value_type("item of axis", item, [int], self.name)
class LogSoftmax(PrimitiveWithInfer):
class LogSoftmax(Primitive):
r"""
Log Softmax activation function.
@ -220,15 +220,6 @@ class LogSoftmax(PrimitiveWithInfer):
def __init__(self, axis=-1):
validator.check_value_type("axis", axis, [int], self.name)
def infer_shape(self, logits):
rank = len(logits)
validator.check_int_range(self.axis, -rank, rank, Rel.INC_LEFT, 'axis', self.name)
return logits
def infer_dtype(self, logits):
validator.check_tensor_dtype_valid("logits", logits, (mstype.float16, mstype.float32), self.name)
return logits
class Softplus(Primitive):
r"""