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Add bprop mindir for array ops

This commit is contained in:
yujianfeng 2022-11-03 15:28:00 +08:00
parent 47e0db0c53
commit e99a43d9d6
102 changed files with 2217 additions and 1033 deletions
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17
mindspore/ccsrc/frontend/optimizer/ad/bprop_utils.cc
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@ -91,6 +91,7 @@ std::pair<std::string, std::string> GetBpropHashAndFilePath(const py::function &
}
// Get the hash of the function.
auto bprop_str = GetBpropString(realpath.value(), prim_name);
MS_LOG(DEBUG) << "bprop string: " << bprop_str;
// Get the relative path of the function.
auto filepath = realpath.value();
static std::string bprop_dir = GetBpropDir();
@ -190,11 +191,8 @@ void OptimizeBpropFromMindIR(const FuncGraphPtr &fg, const pipeline::ResourceBas
EliminateParameterSelf(fg, res, prim);
opt::irpass::BpropMindIRPassLib irpass;
std::vector<opt::SubstitutionPtr> opt_list{irpass.get_multitype_ops_};
(void)opt_list.emplace_back(irpass.get_class_type_);
(void)opt_list.emplace_back(irpass.get_meta_fg_);
(void)opt_list.emplace_back(irpass.get_primal_attr_);
std::vector<opt::SubstitutionPtr> opt_list{irpass.get_constexpr_ops_, irpass.get_class_type_, irpass.get_meta_fg_,
irpass.get_primal_attr_, irpass.get_sub_func_graph_};
opt::OptPassGroupMap map({
{"bprop_mindir_opt", opt::OptPassConfig(opt_list)},
});
@ -211,6 +209,7 @@ FuncGraphPtr LiftParameter(const FuncGraphPtr &func_graph) {
auto bprop_fg = GetValueNode<FuncGraphPtr>(func_graph->output());
MS_EXCEPTION_IF_NULL(bprop_fg);
for (auto &p : bprop_fg->parameters()) {
TraceGuard trace_guard(std::make_shared<TraceCopy>(p->debug_info()));
auto new_p = func_graph->add_parameter();
mng->Replace(p, new_p);
}
@ -223,7 +222,9 @@ FuncGraphPtr LiftParameter(const FuncGraphPtr &func_graph) {
FuncGraphPtr RemovePyObj(const FuncGraphPtr &func_graph, const pipeline::ResourceBasePtr &res) {
opt::irpass::BpropMindIRPassLib irpass;
opt::OptPassGroupMap map({
{"remove_class_type", opt::OptPassConfig({irpass.remote_class_type_})},
{"remove_class_type", opt::OptPassConfig({irpass.class_type_resolve_})},
{"resolve_do_signature_prim", opt::OptPassConfig({irpass.do_signature_resolve_})},
{"remove_resolve", opt::OptPassConfig({irpass.resolve_node_resolve_})},
});
opt::OptimizerPtr export_mindir_opt =
opt::Optimizer::MakeOptimizer("export_mindir_opt", res, map, false, false, false);
@ -234,7 +235,7 @@ FuncGraphPtr RemovePyObj(const FuncGraphPtr &func_graph, const pipeline::Resourc
} // namespace
#ifndef _WIN32
void ExportBpropToMindir(const py::object &obj) {
void ExportBpropToMindir(const py::object &obj, bool force_update = false) {
if (!py::isinstance<py::str>(obj)) {
MS_LOG(EXCEPTION) << "The python obj " << py::str(obj) << " to be exported to mindir should be a string";
}
@ -252,7 +253,7 @@ void ExportBpropToMindir(const py::object &obj) {
MS_LOG(EXCEPTION) << "Fail to get the file path of bprop for " << prim_name;
}
// If the bprop file hash has not changed, we don't need to export a new mindir.
if (CheckBpropUpToDate(prim_name, bprop_hash_and_filepath.first)) {
if (!force_update && CheckBpropUpToDate(prim_name, bprop_hash_and_filepath.first)) {
MS_LOG(WARNING) << "The hash of bprop function of primitive " << prim_name
<< " is not changed, we will not export a new mindir.";
return;

2
mindspore/ccsrc/frontend/optimizer/ad/bprop_utils.h
View File

@ -25,7 +25,7 @@ namespace ad {
#ifndef _WIN32
// For the bprop mindir generator.
// Given an operator name, export a mindir file from its bprop defined in python.
void ExportBpropToMindir(const py::object &obj);
void ExportBpropToMindir(const py::object &obj, bool force_update);
// For the bprop mindir check.
// Given an operator name, check whether its mindir file can be loaded and up to date.
bool CheckMindir(const py::object &obj);

43
mindspore/ccsrc/frontend/optimizer/irpass.cc
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@ -50,11 +50,14 @@
#include "frontend/optimizer/irpass/call_graph_tuple_transform.h"
#include "frontend/optimizer/irpass/recompute_prepare.h"
#include "frontend/optimizer/irpass/real_op_eliminate.h"
#include "frontend/optimizer/irpass/bprop_get_multitype_ops.h"
#include "frontend/optimizer/irpass/bprop_get_class_type.h"
#include "frontend/optimizer/irpass/bprop_get_meta_fg.h"
#include "frontend/optimizer/irpass/bprop_get_primal_attr.h"
#include "frontend/optimizer/irpass/bprop_remove_class_type.h"
#include "mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/get_constexpr_ops.h"
#include "mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/get_class_type.h"
#include "mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/get_meta_fg.h"
#include "mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/get_primal_attr.h"
#include "mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/get_sub_func_graph.h"
#include "mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/class_type_resolve.h"
#include "mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/do_signature_resolve.h"
#include "mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/resolve_node_resolve.h"
namespace mindspore {
namespace opt {
@ -273,24 +276,26 @@ MetaUnpackPrepareLib::MetaUnpackPrepareLib() {
}
BpropMindIRPassLib::BpropMindIRPassLib() {
get_multitype_ops_ = MakeSubstitution(
std::make_shared<BpropGetMultitypeOps>(), "bprop_get_multitype_ops",
{std::make_shared<Primitive>("S-Prim-negative"), std::make_shared<Primitive>("S-Prim-zeros_like_leaf"),
std::make_shared<Primitive>("S-Prim-getitem"), std::make_shared<Primitive>("S-Prim-mul"),
std::make_shared<Primitive>("S-Prim-logical_not"), std::make_shared<Primitive>("S-Prim-in"),
std::make_shared<Primitive>("S-Prim-less"), std::make_shared<Primitive>("S-Prim-add")});
get_constexpr_ops_ =
MakeSubstitution(std::make_shared<GetConstexprOps>(), "get_constexpr_ops", IsValueNode<prim::DoSignaturePrimitive>);
get_class_type_ =
MakeSubstitution(std::make_shared<BpropGetClassType>(), "bprop_get_class_type", IsValueNode<MindIRClassType>);
get_class_type_ = MakeSubstitution(std::make_shared<GetClassType>(), "get_class_type", IsValueNode<MindIRClassType>);
get_meta_fg_ =
MakeSubstitution(std::make_shared<BpropGetMetaFg>(), "bprop_get_class_type", IsValueNode<MindIRMetaFuncGraph>);
get_meta_fg_ = MakeSubstitution(std::make_shared<GetMetaFg>(), "get_meta_fg", IsValueNode<MindIRMetaFuncGraph>);
get_primal_attr_ =
MakeSubstitution(std::make_shared<BpropGetPrimalAttr>(), "bprop_get_primal_attr", {prim::kPrimGetAttr});
get_primal_attr_ = MakeSubstitution(std::make_shared<GetPrimalAttr>(), "get_primal_attr", {prim::kPrimGetAttr});
remote_class_type_ = MakeSubstitution(std::make_shared<BpropRemoveClassType>(), "bprop_remove_primal_attr",
IsValueNode<parse::ClassType>);
get_sub_func_graph_ =
MakeSubstitution(std::make_shared<GetSubFuncGraph>(), "get_sub_func_graph", {prim::kPrimResolve});
class_type_resolve_ =
MakeSubstitution(std::make_shared<ClassTypeResolve>(), "class_type_resolve", IsValueNode<parse::ClassType>);
do_signature_resolve_ =
MakeSubstitution(std::make_shared<DoSignatureResolve>(), "do_signature_resolve", IsCNodeDoSignature);
resolve_node_resolve_ =
MakeSubstitution(std::make_shared<ResolveNodeResolve>(), "resolve_node_resolve", {prim::kPrimResolve});
}
} // namespace irpass
} // namespace opt

16
mindspore/ccsrc/frontend/optimizer/irpass.h
View File

@ -181,11 +181,14 @@ class BpropMindIRPassLib {
public:
BpropMindIRPassLib();
~BpropMindIRPassLib() = default;
SubstitutionPtr get_multitype_ops_;
SubstitutionPtr get_constexpr_ops_;
SubstitutionPtr get_class_type_;
SubstitutionPtr get_meta_fg_;
SubstitutionPtr get_primal_attr_;
SubstitutionPtr remote_class_type_;
SubstitutionPtr get_sub_func_graph_;
SubstitutionPtr class_type_resolve_;
SubstitutionPtr do_signature_resolve_;
SubstitutionPtr resolve_node_resolve_;
};
// predicate functions
@ -248,6 +251,15 @@ inline bool IsCNodeSwitch(const AnfNodePtr &node) {
}
return false;
}
// check if the cnode is a do_signature cnode
inline bool IsCNodeDoSignature(const AnfNodePtr &node) {
auto cnode = dyn_cast_ptr<CNode>(node);
if (cnode == nullptr) {
return false;
}
return IsValueNode<prim::DoSignaturePrimitive>(cnode->input(0));
}
} // namespace irpass
} // namespace opt
} // namespace mindspore

48
mindspore/ccsrc/frontend/optimizer/irpass/bprop_get_meta_fg.h
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@ -1,48 +0,0 @@
/**
* Copyright 2022 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.
*/
#ifndef MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_GET_META_FG_H
#define MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_GET_META_FG_H
#include <string>
#include <memory>
#include "frontend/optimizer/optimizer.h"
#include "frontend/optimizer/irpass.h"
#include "frontend/optimizer/anf_visitor.h"
namespace mindspore {
namespace opt {
namespace irpass {
class BpropGetMetaFg : public AnfVisitor {
AnfNodePtr operator()(const OptimizerPtr &, const AnfNodePtr &node) override {
if (!IsValueNode<MindIRMetaFuncGraph>(node)) {
return nullptr;
}
static mindspore::HashMap<std::string, MetaFuncGraphPtr> meta_fgs{
{"unpack_call", std::make_shared<prim::UnpackCall>("unpack_call")},
};
auto meta_fg_name = GetValueNode<MindIRMetaFuncGraphPtr>(node)->name();
auto iter = meta_fgs.find(meta_fg_name);
if (iter == meta_fgs.end()) {
return nullptr;
}
return NewValueNode(iter->second);
}
};
} // namespace irpass
} // namespace opt
} // namespace mindspore
#endif // MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_GET_META_FG_H

74
mindspore/ccsrc/frontend/optimizer/irpass/bprop_get_multitype_ops.h
View File

@ -1,74 +0,0 @@
/**
* Copyright 2022 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.
*/
#ifndef MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_GET_MULTITYPE_OPS_H
#define MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_GET_MULTITYPE_OPS_H
#include <utility>
#include <string>
#include <vector>
#include <algorithm>
#include "frontend/optimizer/optimizer.h"
#include "frontend/optimizer/irpass.h"
#include "frontend/optimizer/anf_visitor.h"
namespace mindspore {
namespace opt {
namespace irpass {
class BpropGetMultitypeOps : public AnfVisitor {
public:
AnfNodePtr operator()(const OptimizerPtr &, const AnfNodePtr &node) override {
static mindspore::HashMap<std::string, std::pair<std::string, std::string>> multitype_ops{
{"S-Prim-zeros_like_leaf", {"zeros_like", ""}},
{"S-Prim-getitem", {"getitem", "mindspore.ops.composite.multitype_ops.getitem_impl"}},
{"S-Prim-negative", {"negative", "mindspore.ops.composite.multitype_ops.negative_impl"}},
{"S-Prim-mul", {"mul", "mindspore.ops.composite.multitype_ops.mul_impl"}},
{"S-Prim-logical_not", {"logical_not", "mindspore.ops.composite.multitype_ops.logic_not_impl"}},
{"S-Prim-in", {"in_", "mindspore.ops.composite.multitype_ops.in_impl"}},
{"S-Prim-less", {"less", "mindspore.ops.composite.multitype_ops.less_impl"}},
{"S-Prim-add", {"add", "mindspore.ops.composite.multitype_ops.add_impl"}},
};
auto fg = node->func_graph();
if (fg == nullptr) {
return nullptr;
}
auto cnode = node->cast_ptr<CNode>();
MS_EXCEPTION_IF_NULL(cnode);
auto &inputs = cnode->inputs();
if (inputs.empty()) {
return nullptr;
}
auto prim = GetValueNode<PrimitivePtr>(inputs[0]);
MS_EXCEPTION_IF_NULL(prim);
auto iter = multitype_ops.find(prim->name());
if (iter == multitype_ops.end()) {
return nullptr;
}
ValuePtr python_ops;
if (!iter->second.second.empty()) {
python_ops = prim::GetPythonOps(iter->second.first, iter->second.second);
} else {
python_ops = prim::GetPythonOps(iter->second.first);
}
std::vector<AnfNodePtr> new_inputs{NewValueNode(python_ops)};
(void)std::copy(inputs.begin() + 1, inputs.end(), std::back_inserter(new_inputs));
return fg->NewCNode(new_inputs);
}
};
} // namespace irpass
} // namespace opt
} // namespace mindspore
#endif // MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_GET_MULTITYPE_OPS_H

9
mindspore/ccsrc/frontend/optimizer/irpass/bprop_remove_class_type.h → mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/class_type_resolve.h
View File

@ -14,8 +14,8 @@
* limitations under the License.
*/
#ifndef MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_REMOVE_CLASS_TYPE_H
#define MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_REMOVE_CLASS_TYPE_H
#ifndef MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_CLASS_TYPE_RESOLVE_H
#define MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_CLASS_TYPE_RESOLVE_H
#include <string>
#include <memory>
@ -26,7 +26,8 @@
namespace mindspore {
namespace opt {
namespace irpass {
class BpropRemoveClassType : public AnfVisitor {
class ClassTypeResolve : public AnfVisitor {
public:
AnfNodePtr operator()(const OptimizerPtr &, const AnfNodePtr &node) override {
if (!IsValueNode<parse::ClassType>(node)) {
return nullptr;
@ -38,4 +39,4 @@ class BpropRemoveClassType : public AnfVisitor {
} // namespace irpass
} // namespace opt
} // namespace mindspore
#endif // MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_REMOVE_CLASS_TYPE_H
#endif // MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_CLASS_TYPE_RESOLVE_H

76
mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/do_signature_resolve.h Normal file
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@ -0,0 +1,76 @@
/**
* Copyright 2022 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.
*/
#ifndef MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_DO_SIGNATURE_RESOLVE_H
#define MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_DO_SIGNATURE_RESOLVE_H
#include <string>
#include <memory>
#include <vector>
#include <algorithm>
#include "frontend/optimizer/optimizer.h"
#include "frontend/optimizer/irpass.h"
#include "frontend/optimizer/anf_visitor.h"
namespace mindspore {
namespace opt {
namespace irpass {
class DoSignatureResolve : public AnfVisitor {
public:
AnfNodePtr operator()(const OptimizerPtr &optimizer, const AnfNodePtr &node) override {
auto cnode = dyn_cast_ptr<CNode>(node);
if (cnode == nullptr) {
return nullptr;
}
auto prim_py = dyn_cast_ptr<PrimitivePy>(GetValueWithoutDoSignature(cnode->input(0)));
if (prim_py == nullptr) {
return nullptr;
}
auto prim_py_obj = prim_py->GetPyObj();
// Resolve constexpr function
if (py::hasattr(prim_py_obj, "fn")) {
py::object fn = py::getattr(prim_py_obj, "fn");
if (!fn || py::isinstance<py::none>(fn)) {
return nullptr;
}
if (!py::hasattr(fn, "__module__") || !py::hasattr(fn, "__name__")) {
return nullptr;
}
auto module = py::getattr(fn, "__module__");
auto name = py::getattr(fn, "__name__");
prim_py->AddAttr("constexpr_module", MakeValue(py::cast<std::string>(module)));
prim_py->AddAttr("constexpr_name", MakeValue(py::cast<std::string>(name)));
return nullptr;
}
// Convert the primitive with python infer or check function to class type
if (py::hasattr(prim_py_obj, "__infer__") || py::hasattr(prim_py_obj, "__check__")) {
auto class_type = py::str(py::getattr(prim_py_obj, "__class__")).cast<std::string>();
auto mindir_class_type =
NewValueNode(std::make_shared<MindIRClassType>(std::string(class_type.begin() + 1, class_type.end() - 1)));
auto fg = node->func_graph();
MS_EXCEPTION_IF_NULL(fg);
const auto &inputs = cnode->inputs();
std::vector<AnfNodePtr> new_inputs{fg->NewCNode({mindir_class_type})};
(void)std::copy(inputs.begin() + 1, inputs.end(), std::back_inserter(new_inputs));
return fg->NewCNode(new_inputs);
}
return nullptr;
}
};
} // namespace irpass
} // namespace opt
} // namespace mindspore
#endif // MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_DO_SIGNATURE_RESOLVE_H

23
mindspore/ccsrc/frontend/optimizer/irpass/bprop_get_class_type.h → mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/get_class_type.h
View File

@ -14,8 +14,8 @@
* limitations under the License.
*/
#ifndef MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_GET_CLASS_TYPE_H
#define MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_GET_CLASS_TYPE_H
#ifndef MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_CLASS_TYPE_H
#define MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_CLASS_TYPE_H
#include <string>
#include <memory>
@ -26,17 +26,24 @@
namespace mindspore {
namespace opt {
namespace irpass {
class BpropGetClassType : public AnfVisitor {
class GetClassType : public AnfVisitor {
public:
AnfNodePtr operator()(const OptimizerPtr &, const AnfNodePtr &node) override {
if (!IsValueNode<MindIRClassType>(node)) {
return nullptr;
}
auto class_path = GetValueNode<MindIRClassTypePtr>(node)->name();
std::string sub_str = ".";
auto class_name_pos =
std::find_end(class_path.begin(), class_path.end(), sub_str.begin(), sub_str.end()) - class_path.begin();
auto package = std::string(class_path.begin(), class_path.begin() + class_name_pos);
auto class_name = std::string(class_path.begin() + class_name_pos + 1, class_path.end());
std::string package;
std::string class_name;
auto class_name_pos = std::find_end(class_path.begin(), class_path.end(), sub_str.begin(), sub_str.end());
if (class_name_pos == class_path.end()) {
package = "builtins";
class_name = class_path;
} else {
package = std::string(class_path.begin(), class_name_pos);
class_name = std::string(class_name_pos + 1, class_path.end());
}
auto module = python_adapter::GetPyModule(package);
if (!module || py::isinstance<py::none>(module)) {
MS_LOG(EXCEPTION) << "Can not get python module: " << package;
@ -48,4 +55,4 @@ class BpropGetClassType : public AnfVisitor {
} // namespace irpass
} // namespace opt
} // namespace mindspore
#endif // MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_GET_CLASS_TYPE_H
#endif // MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_CLASS_TYPE_H

63
mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/get_constexpr_ops.h Normal file
View File

@ -0,0 +1,63 @@
/**
* Copyright 2022 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.
*/
#ifndef MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_CONSTEXPR_OPS_H
#define MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_CONSTEXPR_OPS_H
#include <utility>
#include <string>
#include <vector>
#include <algorithm>
#include <memory>
#include "frontend/optimizer/optimizer.h"
#include "frontend/optimizer/irpass.h"
#include "frontend/optimizer/anf_visitor.h"
namespace mindspore {
namespace opt {
namespace irpass {
class GetConstexprOps : public AnfVisitor {
public:
AnfNodePtr operator()(const OptimizerPtr &, const AnfNodePtr &node) override {
auto prim = dyn_cast_ptr<Primitive>(GetValueWithoutDoSignature(node));
if (prim == nullptr) {
return nullptr;
}
auto module_value = prim->GetAttr("constexpr_module");
if (module_value == nullptr) {
return nullptr;
}
auto package = GetValue<std::string>(module_value);
auto class_name = GetValue<std::string>(prim->GetAttr("constexpr_name"));
auto module = python_adapter::GetPyModule(package);
if (!module || py::isinstance<py::none>(module)) {
MS_LOG(EXCEPTION) << "Can not get python module: " << package;
}
auto attr = module.attr(class_name.c_str());
auto prim_adapter = attr.cast<PrimitivePyAdapterPtr>();
MS_EXCEPTION_IF_NULL(prim_adapter);
auto new_prim = prim_adapter->attached_primitive();
if (new_prim == nullptr) {
new_prim = std::make_shared<PrimitivePy>(attr, prim_adapter);
prim_adapter->set_attached_primitive(new_prim);
}
return NewValueNode(std::make_shared<prim::DoSignaturePrimitive>(new_prim->name(), new_prim));
}
};
} // namespace irpass
} // namespace opt
} // namespace mindspore
#endif // MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_CONSTEXPR_OPS_H

90
mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/get_meta_fg.h Normal file
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@ -0,0 +1,90 @@
/**
* Copyright 2022 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.
*/
#ifndef MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_META_FG_H
#define MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_META_FG_H
#include <string>
#include <memory>
#include <utility>
#include "frontend/optimizer/optimizer.h"
#include "frontend/optimizer/irpass.h"
#include "frontend/optimizer/anf_visitor.h"
namespace mindspore {
namespace opt {
namespace irpass {
class GetMetaFg : public AnfVisitor {
public:
AnfNodePtr operator()(const OptimizerPtr &, const AnfNodePtr &node) override {
static mindspore::HashMap<std::string, std::pair<std::string, std::string>> multitype_ops{
{"zeros_like_leaf", {"zeros_like", ""}},
{"getitem", {"getitem", "mindspore.ops.composite.multitype_ops.getitem_impl"}},
{"negative", {"negative", "mindspore.ops.composite.multitype_ops.negative_impl"}},
{"mul", {"mul", "mindspore.ops.composite.multitype_ops.mul_impl"}},
{"logical_not", {"logical_not", "mindspore.ops.composite.multitype_ops.logic_not_impl"}},
{"in", {"in_", "mindspore.ops.composite.multitype_ops.in_impl"}},
{"less", {"less", "mindspore.ops.composite.multitype_ops.less_impl"}},
{"greater", {"greater", "mindspore.ops.composite.multitype_ops.greater_impl"}},
{"add", {"add", "mindspore.ops.composite.multitype_ops.add_impl"}},
{"sub", {"sub", "mindspore.ops.composite.multitype_ops.sub_impl"}},
{"dout_cast", {"dout_cast", "mindspore.ops._grad.grad_array_ops"}},
{"equal", {"equal", "mindspore.ops.composite.multitype_ops.equal_impl"}},
{"floordiv", {"floordiv", "mindspore.ops.composite.multitype_ops.floordiv_impl"}},
};
static mindspore::HashMap<std::string, MetaFuncGraphPtr> meta_fgs{
{"unpack_call", std::make_shared<prim::UnpackCall>("unpack_call")},
};
if (!IsValueNode<MindIRMetaFuncGraph>(node)) {
return nullptr;
}
auto meta_fg_name = GetValueNode<MindIRMetaFuncGraphPtr>(node)->name();
meta_fg_name = GetHyperMapOpsName(meta_fg_name);
// meta func_graph
auto meta_fgs_iter = meta_fgs.find(meta_fg_name);
if (meta_fgs_iter != meta_fgs.end()) {
return NewValueNode(meta_fgs_iter->second);
}
// multitype func_graph
auto multitype_ops_iter = multitype_ops.find(meta_fg_name);
if (multitype_ops_iter == multitype_ops.end()) {
return nullptr;
}
ValuePtr python_ops;
if (!multitype_ops_iter->second.second.empty()) {
python_ops = prim::GetPythonOps(multitype_ops_iter->second.first, multitype_ops_iter->second.second);
} else {
python_ops = prim::GetPythonOps(multitype_ops_iter->second.first);
}
return NewValueNode(python_ops);
}
// hyper_map[xxx] -> xxx
static std::string GetHyperMapOpsName(const std::string &meta_fg_name) {
static constexpr char kHyperMapPrefix[] = "hyper_map";
static size_t prefix_len = strlen(kHyperMapPrefix);
if (meta_fg_name.compare(0, prefix_len, kHyperMapPrefix) != 0) {
return meta_fg_name;
}
constexpr auto offset = 2;
auto op_name = meta_fg_name.substr(prefix_len + 1, meta_fg_name.length() - prefix_len - offset);
return op_name;
}
};
} // namespace irpass
} // namespace opt
} // namespace mindspore
#endif // MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_META_FG_H

8
mindspore/ccsrc/frontend/optimizer/irpass/bprop_get_primal_attr.h → mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/get_primal_attr.h
View File

@ -14,8 +14,8 @@
* limitations under the License.
*/
#ifndef MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_GET_PRIMAL_ATTR_H
#define MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_GET_PRIMAL_ATTR_H
#ifndef MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_PRIMAL_ATTR_H
#define MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_PRIMAL_ATTR_H
#include <string>
#include "frontend/optimizer/optimizer.h"
@ -25,7 +25,7 @@
namespace mindspore {
namespace opt {
namespace irpass {
class BpropGetPrimalAttr : public AnfVisitor {
class GetPrimalAttr : public AnfVisitor {
public:
AnfNodePtr operator()(const OptimizerPtr &, const AnfNodePtr &node) override {
Reset();
@ -72,4 +72,4 @@ class BpropGetPrimalAttr : public AnfVisitor {
} // namespace irpass
} // namespace opt
} // namespace mindspore
#endif // MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_GET_PRIMAL_ATTR_H
#endif // MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_PRIMAL_ATTR_H

83
mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/get_sub_func_graph.h Normal file
View File

@ -0,0 +1,83 @@
/**
* Copyright 2022 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.
*/
#ifndef MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_SUB_FUNC_GRAPH_H
#define MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_SUB_FUNC_GRAPH_H
#include <string>
#include <memory>
#include "frontend/optimizer/optimizer.h"
#include "frontend/optimizer/irpass.h"
#include "frontend/optimizer/anf_visitor.h"
namespace mindspore {
namespace opt {
namespace irpass {
class GetSubFuncGraph : public AnfVisitor {
public:
AnfNodePtr operator()(const OptimizerPtr &, const AnfNodePtr &node) override {
Reset();
AnfVisitor::Match(prim::kPrimResolve, {IsVNode, IsVNode})(node);
if (!is_match_) {
return nullptr;
}
auto module = python_adapter::GetPyModule(name_space_);
if (!module || py::isinstance<py::none>(module)) {
MS_LOG(EXCEPTION) << "Can not get python module: " << name_space_;
}
auto func_obj = module.attr(symbol_.c_str());
ValuePtr convert_result = nullptr;
bool converted = parse::ConvertData(func_obj, &convert_result);
if (!converted) {
MS_LOG(EXCEPTION) << "Failed to convert data for " << py::str(func_obj);
}
if (!convert_result->isa<FuncGraph>()) {
MS_LOG(EXCEPTION) << "The result of convert should be a func_graph, but got " << convert_result->ToString();
}
return NewValueNode(convert_result);
}
void Visit(const ValueNodePtr &vnode) override {
if (IsValueNode<MindIRNameSpace>(vnode)) {
auto mindir_name_space = GetValueNode<MindIRNameSpacePtr>(vnode);
MS_EXCEPTION_IF_NULL(mindir_name_space);
name_space_ = mindir_name_space->name_space();
} else if (IsValueNode<MindIRSymbol>(vnode)) {
auto mindir_symbol = GetValueNode<MindIRSymbolPtr>(vnode);
MS_EXCEPTION_IF_NULL(mindir_symbol);
symbol_ = mindir_symbol->symbol();
}
if (!name_space_.empty() && !symbol_.empty()) {
is_match_ = true;
}
}
void Reset() {
is_match_ = false;
name_space_.clear();
symbol_.clear();
}
private:
bool is_match_{false};
std::string name_space_;
std::string symbol_;
};
} // namespace irpass
} // namespace opt
} // namespace mindspore
#endif // MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_GET_CLASS_TYPE_H

79
mindspore/ccsrc/frontend/optimizer/irpass/bprop_mindir/resolve_node_resolve.h Normal file
View File

@ -0,0 +1,79 @@
/**
* Copyright 2022 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.
*/
#ifndef MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_RESOLVE_NODE_RESOLVE_H
#define MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_RESOLVE_NODE_RESOLVE_H
#include <string>
#include <memory>
#include "frontend/optimizer/optimizer.h"
#include "frontend/optimizer/irpass.h"
#include "frontend/optimizer/anf_visitor.h"
namespace mindspore {
namespace opt {
namespace irpass {
class ResolveNodeResolve : public AnfVisitor {
public:
AnfNodePtr operator()(const OptimizerPtr &, const AnfNodePtr &node) override {
Reset();
AnfVisitor::Match(prim::kPrimResolve, {IsVNode, IsVNode})(node);
if (!is_match_) {
return nullptr;
}
py::module mod = python_adapter::GetPyModule(parse::PYTHON_MOD_PARSE_MODULE);
auto symbol_obj = python_adapter::CallPyModFn(mod, parse::PYTHON_MOD_RESOLVE_FUNCTION, obj_, symbol_);
auto module_str = py::str(getattr(symbol_obj, "__module__")).cast<std::string>();
auto name_str = py::str(getattr(symbol_obj, "__name__")).cast<std::string>();
auto mindir_name_space = std::make_shared<MindIRNameSpace>(module_str);
auto mindir_symbol = std::make_shared<MindIRSymbol>(name_str);
auto fg = node->func_graph();
MS_EXCEPTION_IF_NULL(fg);
return fg->NewCNode(
{node->cast_ptr<CNode>()->input(0), NewValueNode(mindir_name_space), NewValueNode(mindir_symbol)});
}
void Visit(const ValueNodePtr &vnode) override {
if (IsValueNode<parse::NameSpace>(vnode)) {
auto name_space = GetValueNode<parse::NameSpacePtr>(vnode);
MS_EXCEPTION_IF_NULL(name_space);
obj_ = name_space->obj();
} else if (IsValueNode<parse::Symbol>(vnode)) {
auto symbol_value = GetValueNode<parse::SymbolPtr>(vnode);
MS_EXCEPTION_IF_NULL(symbol_value);
symbol_ = symbol_value->symbol();
}
if (!py::isinstance<py::none>(obj_) && !symbol_.empty()) {
is_match_ = true;
}
}
void Reset() {
is_match_ = false;
symbol_.clear();
obj_ = py::none();
}
private:
bool is_match_{false};
py::object obj_{py::none()};
std::string symbol_;
};
} // namespace irpass
} // namespace opt
} // namespace mindspore
#endif // MINDSPORE_CCSRC_FRONTEND_OPTIMIZER_IRPASS_BPROP_MINDIR_RESOLVE_NODE_RESOLVE_H

3
mindspore/ccsrc/frontend/optimizer/opt.cc
View File

@ -95,7 +95,8 @@ static inline bool isTraversable(const AnfNodePtr &node) {
MS_EXCEPTION_IF_NULL(value_node);
const auto &value = value_node->value();
return (value != nullptr) && (value->isa<FuncGraph>() || value->isa<RefKey>() || value->isa<MindIRClassType>() ||
value->isa<MindIRMetaFuncGraph>() || value->isa<parse::ClassType>());
value->isa<MindIRMetaFuncGraph>() || value->isa<parse::ClassType>() ||
value->isa<prim::DoSignaturePrimitive>());
}
static AnfNodePtr DoTransform(const OptimizerPtr &optimizer, const AnfNodePtr &node,

11
mindspore/ccsrc/pipeline/jit/parse/resolve.cc
View File

@ -278,6 +278,17 @@ AnfNodePtr ConvertObjectToNode(const AnfNodePtr &origin_node, const py::object &
MS_LOG(ERROR) << "Convert data failed";
return nullptr;
}
// For the bprop which is loaded from mindir file, the sub function should be resolved after loading.
if (common::GetEnv("MS_DEV_EXPORT_BPROP_MINDIR") == "1" && IsPrimitiveCNode(origin_node, prim::kPrimResolve)) {
auto name_space = GetValueNode<NameSpacePtr>(origin_node->cast<CNodePtr>()->input(1));
MS_EXCEPTION_IF_NULL(name_space);
auto obj_type = data_converter::GetObjType(obj);
if (obj_type == RESOLVE_TYPE_FUNCTION && convert_result->isa<FuncGraph>() &&
name_space->module() != RESOLVE_NAMESPACE_NAME_COMMON_OPS) {
return origin_node;
}
}
bool interpret_without_internal =
(IsPrimitiveCNode(origin_node, prim::kPrimPyInterpret) && !origin_node->interpret_internal_type()) ||
origin_node->interpret();

46
mindspore/ccsrc/transform/express_ir/mindir_exporter.cc
View File

@ -138,6 +138,7 @@ class IrExportBuilder {
bool SetAbstractToNodeProto(const CNodePtr &node, mind_ir::NodeProto *const node_proto);
bool SetAbstractToNodeProto(const abstract::AbstractBasePtr &abstract, mind_ir::AttributeProto *const attr_proto);
bool SetValueToAttributeProto(const ValuePtr &value, mind_ir::AttributeProto *const attr_proto);
bool SetNamedValueToAttributeProto(const ValuePtr &value, mind_ir::AttributeProto *const attr_proto);
bool SetTypeToAttributeProto(const ValuePtr &value, mind_ir::AttributeProto *const attr_proto);
bool SetScalarToAttributeProto_ir(const ValuePtr &value, mind_ir::AttributeProto *const attr_proto) const;
bool SetScalarToAttributeProtoForInt_ir(const ValuePtr &value, mind_ir::AttributeProto *const attr_proto) const;
@ -713,7 +714,13 @@ std::string IrExportBuilder::GetOpTypeName(const AnfNodePtr &node) {
if (IsValueNode<Primitive>(node)) {
PrimitivePtr prim = GetValueNode<PrimitivePtr>(node);
MS_EXCEPTION_IF_NULL(prim);
type_name = "REF::" + GetPrimitiveUniqueName(prim);
auto do_sign_prim = prim->cast_ptr<prim::DoSignaturePrimitive>();
if (do_sign_prim != nullptr && do_sign_prim->function() != nullptr &&
do_sign_prim->function()->isa<MetaFuncGraph>()) {
type_name = "REF::MetaFuncGraph::" + do_sign_prim->function()->cast_ptr<MetaFuncGraph>()->name();
} else {
type_name = "REF::" + GetPrimitiveUniqueName(prim);
}
} else if (IsValueNode<FuncGraph>(node)) {
FuncGraphPtr fg = GetValueNode<FuncGraphPtr>(node);
MS_EXCEPTION_IF_NULL(fg);
@ -1023,6 +1030,30 @@ bool IrExportBuilder::SetTypeToAttributeProto(const ValuePtr &value, mind_ir::At
return true;
}
bool IrExportBuilder::SetNamedValueToAttributeProto(const ValuePtr &value, mind_ir::AttributeProto *const attr_proto) {
if (value->isa<None>()) {
attr_proto->set_type(mind_ir::AttributeProto_AttributeType_NONE);
MS_LOG(DEBUG) << "Attr string: " << value->type_name();
} else if (value->isa<MindIRClassType>()) {
attr_proto->set_type(mind_ir::AttributeProto_AttributeType_CLASS_TYPE);
auto class_type = GetValue<MindIRClassTypePtr>(value)->name();
// class 'XXX' -> XXX
constexpr int64_t path_begin_index = 7;
auto str = std::string(class_type.begin() + path_begin_index, class_type.end() - 1);
attr_proto->set_s(str);
} else if (value->isa<MindIRNameSpace>()) {
attr_proto->set_type(mind_ir::AttributeProto_AttributeType_NAME_SPACE);
attr_proto->set_s(GetValue<MindIRNameSpacePtr>(value)->name_space());
} else if (value->isa<MindIRSymbol>()) {
attr_proto->set_type(mind_ir::AttributeProto_AttributeType_SYMBOL);
attr_proto->set_s(GetValue<MindIRSymbolPtr>(value)->symbol());
} else {
MS_LOG(ERROR) << "Unsupported named type: " << value->type_name();
return false;
}
return true;
}
bool IrExportBuilder::SetValueToAttributeProto(const ValuePtr &value, mind_ir::AttributeProto *const attr_proto) {
if (value == nullptr || attr_proto == nullptr) {
MS_LOG(EXCEPTION) << "ValuePtr or AttributeProto is null!";
@ -1045,8 +1076,10 @@ bool IrExportBuilder::SetValueToAttributeProto(const ValuePtr &value, mind_ir::A
MS_LOG(DEBUG) << "Attr string: " << value->type_name();
} else if (value->isa<tensor::Tensor>()) {
return SetTensorToAttributeProto(value, attr_proto);
} else if (value->isa<None>()) {
attr_proto->set_type(mind_ir::AttributeProto_AttributeType_NONE);
} else if (value->isa<Named>()) {
return SetNamedValueToAttributeProto(value, attr_proto);
} else if (value->isa<TypeNull>()) {
attr_proto->set_type(mind_ir::AttributeProto_AttributeType_TYPE_NULL);
MS_LOG(DEBUG) << "Attr string: " << value->type_name();
} else if (value->isa<Monad>()) {
if (value->isa<UMonad>()) {
@ -1057,13 +1090,6 @@ bool IrExportBuilder::SetValueToAttributeProto(const ValuePtr &value, mind_ir::A
MS_LOG(ERROR) << "Unsupported Monad type: " << value->type_name();
return false;
}
} else if (value->isa<MindIRClassType>()) {
attr_proto->set_type(mind_ir::AttributeProto_AttributeType_CLASS_TYPE);
auto class_type = GetValue<MindIRClassTypePtr>(value)->name();
// class 'XXX' -> XXX
constexpr int64_t path_begin_index = 7;
auto str = std::string(class_type.begin() + path_begin_index, class_type.end() - 1);
attr_proto->set_s(str);
} else {
MS_LOG(ERROR) << "Unsupported type: " << value->type_name();
return false;

34
mindspore/core/ir/named.h
View File

@ -152,26 +152,44 @@ class MS_CORE_API Ellipsis final : public Named {
};
GVAR_DEF(NamedPtr, kEllipsis, std::make_shared<Ellipsis>());
/// \brief MindIRClassType defines the class type loaded from MindIR.
class MS_CORE_API MindIRClassType final : public Named {
class MindIRClassType final : public Named {
public:
/// \brief The default constructor for MindIRClassType.
explicit MindIRClassType(const std::string &class_type) : Named(class_type) {}
/// \brief The destructor of MindIRClassType.
~MindIRClassType() override = default;
MS_DECLARE_PARENT(MindIRClassType, Named);
};
using MindIRClassTypePtr = std::shared_ptr<MindIRClassType>;
/// \brief MindIRMetaFuncGraph defines the meta func_graph loaded from MindIR.
class MS_CORE_API MindIRMetaFuncGraph final : public Named {
class MindIRMetaFuncGraph final : public Named {
public:
/// \brief The default constructor for MindIRMetaFuncGraph.
explicit MindIRMetaFuncGraph(const std::string &name) : Named(name) {}
/// \brief The destructor of MindIRMetaFuncGraph.
~MindIRMetaFuncGraph() override = default;
MS_DECLARE_PARENT(MindIRMetaFuncGraph, Named);
};
using MindIRMetaFuncGraphPtr = std::shared_ptr<MindIRMetaFuncGraph>;
class MindIRNameSpace final : public Named {
public:
explicit MindIRNameSpace(const std::string &name_space) : Named(name_space), name_space_(name_space) {}
~MindIRNameSpace() override = default;
MS_DECLARE_PARENT(MindIRNameSpace, Named);
const std::string &name_space() const { return name_space_; }
private:
std::string name_space_;
};
using MindIRNameSpacePtr = std::shared_ptr<MindIRNameSpace>;
class MindIRSymbol final : public Named {
public:
explicit MindIRSymbol(const std::string &symbol) : Named(symbol), symbol_(symbol) {}
~MindIRSymbol() override = default;
MS_DECLARE_PARENT(MindIRSymbol, Named);
const std::string &symbol() const { return symbol_; }
private:
std::string symbol_;
};
using MindIRSymbolPtr = std::shared_ptr<MindIRSymbol>;
} // namespace mindspore
#endif // MINDSPORE_CORE_IR_NAMED_H_

44
mindspore/core/load_mindir/anf_model_parser.cc
View File

@ -45,7 +45,6 @@ std::map<std::string, tensor::TensorPtr> MSANFModelParser::load_tensor_map_;
namespace {
static constexpr char kConstantValueNode[] = "Constant";
static constexpr char kDoSignaturePrimitivePrefix[] = "S-Prim-";
static constexpr char kHyperMapPrefix[] = "hyper_map";
enum ParseForm : int {
FORM_PARSE_TYPE = 0,
@ -1042,6 +1041,14 @@ bool MSANFModelParser::ObtainValueNodeInNoneForm(const std::string &value_node_n
return true;
}
bool MSANFModelParser::ObtainValueNodeInTypeNullForm(const std::string &value_node_name) {
auto new_value_node = NewValueNode(kTypeNull);
MS_EXCEPTION_IF_NULL(new_value_node);
new_value_node->set_abstract(kTypeNull->ToAbstract());
anfnode_build_map_[value_node_name] = new_value_node;
return true;
}
bool MSANFModelParser::ObtainValueNodeInMonadForm(const std::string &value_node_name,
const mind_ir::AttributeProto &attr_proto) {
const std::string &ref_attr_name = attr_proto.ref_attr_name();
@ -1244,6 +1251,24 @@ bool MSANFModelParser::GetAttrValueForValueNodeWithType(const std::string &value
anfnode_build_map_[value_node_name] = new_value_node;
break;
}
case mind_ir::AttributeProto_AttributeType_TYPE_NULL: {
(void)ObtainValueNodeInTypeNullForm(value_node_name);
break;
}
case mind_ir::AttributeProto_AttributeType_NAME_SPACE: {
auto name_space = static_cast<std::string>(attr_proto.s());
auto mindir_name_space = std::make_shared<MindIRNameSpace>(name_space);
new_value_node = NewValueNode(mindir_name_space);
anfnode_build_map_[value_node_name] = new_value_node;
break;
}
case mind_ir::AttributeProto_AttributeType_SYMBOL: {
auto symbol = static_cast<std::string>(attr_proto.s());
auto mindir_symbol = std::make_shared<MindIRSymbol>(symbol);
new_value_node = NewValueNode(mindir_symbol);
anfnode_build_map_[value_node_name] = new_value_node;
break;
}
default: {
ValuePtr value = ObtainCNodeAttrInSingleScalarForm(attr_proto);
if (value == nullptr) {
@ -1348,19 +1373,6 @@ mindspore::HashMap<std::string, abstract::AbstractBasePtr> MSANFModelParser::Get
return kv;
}
// S-Prim-xxx or S-Prim-hyper_map[xxx] -> xxx
static std::string GetDoSignaturePrimitiveName(const std::string &node_type) {
// Remove `S-Prim-` prefix.
auto prim_name = node_type.substr(strlen(kDoSignaturePrimitivePrefix));
if (prim_name.compare(0, strlen(kHyperMapPrefix), kHyperMapPrefix) != 0) {
return prim_name;
}
// hyper_map[xxx] -> xxx
constexpr auto offset = 2;
auto op_name = prim_name.substr(strlen(kHyperMapPrefix) + 1, (prim_name.length() - strlen(kHyperMapPrefix)) - offset);
return op_name;
}
AnfNodePtr MSANFModelParser::BuildOperatorNode(const mind_ir::NodeProto &node_proto) {
const std::string kOperatorTypeFlag = std::string("REF::");
const size_t kOpTypeFlagSize = kOperatorTypeFlag.length();
@ -1384,7 +1396,7 @@ AnfNodePtr MSANFModelParser::BuildOperatorNode(const mind_ir::NodeProto &node_pr
prim = op_primc_fns[node_type]();
} else {
if (node_type.compare(0, strlen(kDoSignaturePrimitivePrefix), kDoSignaturePrimitivePrefix) == 0) {
auto op_name = GetDoSignaturePrimitiveName(node_type);
auto op_name = node_type.substr(strlen(kDoSignaturePrimitivePrefix));
prim = std::make_shared<prim::DoSignaturePrimitive>(op_name, std::make_shared<Primitive>(op_name));
MS_EXCEPTION_IF_NULL(prim);
prim->set_instance_name(op_name);
@ -1851,7 +1863,7 @@ bool MSANFModelParser::BuildPrimitiveNode(const mind_ir::PrimitiveProto &primiti
prim = it->second();
} else {
if (prim_type.compare(0, strlen(kDoSignaturePrimitivePrefix), kDoSignaturePrimitivePrefix) == 0) {
auto op_name = GetDoSignaturePrimitiveName(prim_type);
auto op_name = prim_type.substr(strlen(kDoSignaturePrimitivePrefix));
prim = std::make_shared<prim::DoSignaturePrimitive>(op_name, std::make_shared<Primitive>(op_name));
MS_EXCEPTION_IF_NULL(prim);
prim->set_instance_name(op_name);

1
mindspore/core/load_mindir/anf_model_parser.h
View File

@ -120,6 +120,7 @@ class MSANFModelParser {
bool GetAttrValueForValueNodeWithType(const std::string &value_node_name, const mind_ir::AttributeProto &attr_proto);
bool ObtainValueNodeInTypeForm(const string &value_node_name, const mind_ir::TensorProto &attr_tensor);
bool ObtainValueNodeInNoneForm(const std::string &value_node_name);
bool ObtainValueNodeInTypeNullForm(const std::string &value_node_name);
bool ObtainValueNodeInMonadForm(const std::string &value_node_name, const mind_ir::AttributeProto &attr_proto);
ValuePtr ObtainValueInSequenceForm(const mind_ir::AttributeProto &attr_proto);
ValuePtr ObtainValueInDictionaryForm(const mind_ir::AttributeProto &attr_proto);

3
mindspore/core/proto/mind_ir.proto
View File

@ -42,6 +42,9 @@ message AttributeProto {
COO_TENSOR = 31;
ROW_TENSOR = 32;
CLASS_TYPE = 33;
NAME_SPACE = 34;
SYMBOL = 35;
TYPE_NULL = 36;
}
optional string name = 1;
optional float f = 2;

36
mindspore/python/mindspore/ops/bprop_mindir/ApproximateEqual_bprop.mindir
View File

@ -1,19 +1,19 @@
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,get_bprop_approximate_equal.94:[Parameter]96*.
,get_bprop_approximate_equal.94:[Parameter]98*/
-get_bprop_approximate_equal.94:[Parameter]102*/
-get_bprop_approximate_equal.94:[Parameter]1032-
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28
mindspore/python/mindspore/ops/bprop_mindir/Argmax_bprop.mindir
View File

@ -1,15 +1,15 @@
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28
mindspore/python/mindspore/ops/bprop_mindir/Argmin_bprop.mindir
View File

@ -1,15 +1,15 @@
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36
mindspore/python/mindspore/ops/bprop_mindir/AssignAdd_bprop.mindir
View File

@ -1,19 +1,19 @@
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%get_bprop_assign_add.66:[Parameter]74*'
%get_bprop_assign_add.66:[Parameter]752%
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36
mindspore/python/mindspore/ops/bprop_mindir/AssignSub_bprop.mindir
View File

@ -1,19 +1,19 @@
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%get_bprop_assign_sub.76:[Parameter]84*'
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mindspore/python/mindspore/ops/bprop_mindir/Assign_bprop.mindir
View File

@ -1,17 +1,17 @@
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mindspore/python/mindspore/ops/bprop_mindir/BNTrainingReduce_bprop.mindir
View File

@ -1,15 +1,15 @@
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mindspore/python/mindspore/ops/bprop_mindir/Broadcast_bprop.mindir
View File

@ -1,12 +1,13 @@
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mindspore/python/mindspore/ops/bprop_mindir/Cast_bprop.mindir Normal file
View File

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mindspore/python/mindspore/ops/bprop_mindir/DType_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/Depend_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/DropoutDoMask_bprop.mindir
View File

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mindspore/python/mindspore/ops/bprop_mindir/DropoutGenMask_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/DynamicShape_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/GatherD_bprop.mindir Normal file
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mindspore/python/mindspore/ops/bprop_mindir/GreaterEqual_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/Greater_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/IsInf_bprop.mindir
View File

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mindspore/python/mindspore/ops/bprop_mindir/IsNan_bprop.mindir
View File

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mindspore/python/mindspore/ops/bprop_mindir/LessEqual_bprop.mindir
View File

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mindspore/python/mindspore/ops/bprop_mindir/Less_bprop.mindir
View File

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mindspore/python/mindspore/ops/bprop_mindir/LinSpace_bprop.mindir
View File

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mindspore/python/mindspore/ops/bprop_mindir/Load_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/LogicalAnd_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/LogicalNot_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/LogicalOr_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/MatMul_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/Maximum_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/NotEqual_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/OneHot_bprop.mindir
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@ -1,27 +1,27 @@
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mindspore/python/mindspore/ops/bprop_mindir/OnesLike_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/Padding_bprop.mindir Normal file
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mindspore/python/mindspore/ops/bprop_mindir/Range_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/Rank_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/ReLUV2_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/ReLU_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/ReduceAll_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/ReduceAny_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/ReluGrad_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/Reshape_bprop.mindir Normal file
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mindspore/python/mindspore/ops/bprop_mindir/ReverseV2_bprop.mindir Normal file
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mindspore/python/mindspore/ops/bprop_mindir/Round_bprop.mindir
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mindspore/python/mindspore/ops/bprop_mindir/Select_bprop.mindir
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21
mindspore/python/mindspore/ops/bprop_mindir/generate_mindir.py
View File

@ -24,18 +24,19 @@ from mindspore._c_expression import _export_bprop_mindir
from mindspore.ops._grad.grad_base import bprop_getters, bprops
logging.getLogger().setLevel(logging.INFO)
os.environ['MS_DEV_EXPORT_BPROP_MINDIR'] = '1'
def run_generate(bprop_mindir_install_dir, bprop_map):
def run_generate(bprop_mindir_install_dir, bprop_map, force_update):
for op_name in bprop_map.keys():
if not isinstance(op_name, str):
continue
if os.path.isfile(os.path.join(bprop_mindir_install_dir, op_name + "_bprop.mindir")):
_export_bprop_mindir(op_name)
_export_bprop_mindir(op_name, force_update)
def run_generate_with_op_name(op_name):
_export_bprop_mindir(op_name)
def run_generate_with_op_name(op_name, force_update):
_export_bprop_mindir(op_name, force_update)
if __name__ == "__main__":
@ -48,6 +49,9 @@ if __name__ == "__main__":
help="The name of the operator whose bprop is to be transformed to mindir file. If not \
specified, it will generate all the mindir files of bprop which has already been transform \
to mindir. Default: None.")
parser.add_argument('--force', type=bool, default=False,
help="Whether to force to generate mindir file of a bprop function regardless of nothing \
changed. Default: False.")
args_opt = parser.parse_args()
# mindspore/ops/_grad/__init__.py
@ -79,12 +83,13 @@ if __name__ == "__main__":
shutil.copy(file_path, bprop_installed_dir)
logging.info("copied: %s", file_path)
force = args_opt.force
op = args_opt.op
if op is None:
run_generate(bprop_mindir_export_dir, bprop_getters)
run_generate(bprop_mindir_export_dir, bprops)
run_generate(bprop_mindir_export_dir, bprop_getters, force)
run_generate(bprop_mindir_export_dir, bprops, force)
else:
run_generate_with_op_name(op)
run_generate_with_op_name(op, force)
# If the specified bprop source directory is not on the mindspore installed path,
# copy the generated mindir files to the mindir directory relative to the specified path.
@ -103,3 +108,5 @@ if __name__ == "__main__":
else:
logging.info("The new bprop mindir files has been generated in the path \"%s\", "
"copy the *.mindir to your mindspore path or PYTHONPATH if necessary.", bprop_mindir_export_dir)
del os.environ['MS_DEV_EXPORT_BPROP_MINDIR']

21
mindspore/python/mindspore/ops/bprop_mindir/stop_gradient_bprop.mindir
View File

@ -1,12 +1,11 @@
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S-Prim-MakeTuple:3S-Prim-MakeTupleh

1
mindspore/python/mindspore/ops/primitive.py
View File

@ -771,6 +771,7 @@ def constexpr(fn=None, get_instance=True, name=None, reuse_result=True, check=Tr
op_name = name if name else fn.__name__
PrimitiveWithInfer.__init__(self, op_name)
self.set_const_prim(True)
self.fn = fn
if not reuse_result:
self.add_prim_attr('forbid_reuse_result', True)

22
mindspore/python/mindspore/ops/vm_impl_registry.py
View File

@ -23,8 +23,28 @@ from __future__ import absolute_import
from __future__ import division
from mindspore.ops._register_for_op import Registry
from mindspore.ops.primitive import Primitive
vm_impl_registry = Registry()
class VmImplRegistry(Registry):
"""Registry class for registry functions for vm_impl on Primitive or string."""
def register(self, prim):
"""register the function."""
def deco(fn):
"""Decorate the function."""
if isinstance(prim, str):
self[prim] = fn
elif issubclass(prim, Primitive):
self[id(prim)] = fn
self[prim.__name__] = fn
return fn
return deco
vm_impl_registry = VmImplRegistry()
"""
Register the python primitive debug implementation function of a primitive operator.

242
tests/ut/python/optimizer/test_bprop_mindir.py
View File

@ -18,7 +18,6 @@ import os
import numpy as np
import mindspore.nn as nn
from mindspore import context
from mindspore import Tensor, Parameter
from mindspore.ops import operations as P
import mindspore.ops.functional as F
@ -28,6 +27,7 @@ from mindspore.common.initializer import initializer
import mindspore.ops._grad as g
from mindspore.ops._grad.grad_base import bprop_getters, bprops
from mindspore._c_expression import _check_bprop_mindir
from mindspore import mutable
class Net(nn.Cell):
@ -506,7 +506,6 @@ def test_switch():
Description: Compile the backward graph for the switch op.
Expectation: Load the bprop mindir successfully.
"""
context.set_context(mode=context.PYNATIVE_MODE)
class SwitchNet(nn.Cell):
def construct(self, x, y):
@ -652,3 +651,242 @@ def test_relu_v2():
relu_v2 = Net(P.ReLUV2())
grad = GradNet(relu_v2)
grad.compile(x)
def test_cast():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the cast op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor(np.array([1.0]), mstype.float32)
cast = Net(P.Cast())
grad = GradNet(cast)
grad.compile(x, mstype.int32)
def test_split():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the split op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor(np.array([[1, 1, 1, 1], [2, 2, 2, 2]]), mstype.int32)
split = Net(P.Split(1, 2))
grad = GradNet(split)
grad.compile(x)
def test_reshape():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the reshape op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]), mstype.float32)
reshape = Net(P.Reshape())
grad = GradNet(reshape)
grad.compile(x, (3, 2))
def test_expand_dims():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the expand_dims op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor(np.array([[2, 2], [2, 2]]), mstype.float32)
expand_dims = Net(P.ExpandDims())
grad = GradNet(expand_dims)
grad.compile(x, 0)
def test_squeeze():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the squeeze op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor(np.ones(shape=[3, 2, 1]), mstype.float32)
squeeze = Net(P.Squeeze(2))
grad = GradNet(squeeze)
grad.compile(x)
def test_flatten():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the flatten op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor(np.ones(shape=[1, 2, 3, 4]), mstype.float32)
flatten = Net(P.Flatten())
grad = GradNet(flatten)
grad.compile(x)
def test_tile():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the tile op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor(np.array([[1, 2], [3, 4]]), mstype.float32)
tile = Net(P.Tile())
grad = GradNet(tile)
grad.compile(x, (2, 3))
def test_embedding_lookup():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the embedding_lookup op.
Expectation: Load the bprop mindir successfully.
"""
input_params = Tensor(np.array([[8, 9], [10, 11], [12, 13], [14, 15]]), mstype.float32)
input_indices = Tensor(np.array([[5, 2], [8, 5]]), mstype.int32)
offset = 4
embedding_lookup = Net(P.EmbeddingLookup())
grad = GradNet(embedding_lookup)
grad.compile(input_params, input_indices, offset)
def test_padding():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the padding op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor(np.array([[8], [10]]), mstype.float32)
padding = Net(P.Padding(4))
grad = GradNet(padding)
grad.compile(x)
def test_transpose():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the transpose op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor(np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]), mstype.float32)
perm = (0, 2, 1)
transpose = Net(P.Transpose())
grad = GradNet(transpose)
grad.compile(x, perm)
def test_concat():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the concat op.
Expectation: Load the bprop mindir successfully.
"""
x1 = Tensor(np.array([[0, 1], [2, 1]]).astype(np.float32))
x2 = Tensor(np.array([[0, 1], [2, 1]]).astype(np.float32))
concat = Net(P.Concat())
grad = GradNet(concat)
grad.compile(mutable((x1, x2)))
def test_slice():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the slice op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor(np.array([[[1, 1, 1], [2, 2, 2]],
[[3, 3, 3], [4, 4, 4]],
[[5, 5, 5], [6, 6, 6]]]).astype(np.int32))
slice_net = Net(P.Slice())
grad = GradNet(slice_net)
grad.compile(x, (1, 0, 0), (1, 1, 3))
def test_gather():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the gather op.
Expectation: Load the bprop mindir successfully.
"""
input_params = Tensor(np.array([1, 2, 3, 4, 5, 6, 7]), mstype.float32)
input_indices = Tensor(np.array([0, 2, 4, 2, 6]), mstype.int32)
gather = Net(P.Gather())
grad = GradNet(gather)
grad.compile(input_params, input_indices, 0)
def test_gather_d():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the gather_d op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor(np.array([[1, 2], [3, 4]]), mstype.int32)
index = Tensor(np.array([[0, 0], [1, 0]]), mstype.int32)
gather_d = Net(P.GatherD())
grad = GradNet(gather_d)
grad.compile(x, 1, index)
def test_sort():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the sort op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor(np.array([[8, 2, 1], [5, 9, 3], [4, 6, 7]]), mstype.float16)
sort = Net(P.Sort())
grad = GradNet(sort)
grad.compile(x)
def test_reverse_v2():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the reverse_v2 op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor(np.array([[1, 2, 3, 4], [5, 6, 7, 8]]), mstype.int32)
reverse_v2 = Net(P.ReverseV2(axis=[1]))
grad = GradNet(reverse_v2)
grad.compile(x)
def test_unstack():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the unstack op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor(np.array([[1, 1, 1, 1], [2, 2, 2, 2]]))
unstack = Net(P.Unstack())
grad = GradNet(unstack)
grad.compile(x)
def test_strided_slice():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the strided_slice op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor([[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]],
[[5, 5, 5], [6, 6, 6]]], mstype.float32)
strided_slice = Net(P.StridedSlice())
grad = GradNet(strided_slice)
grad.compile(x, (1, 0, 2), (3, 1, 3), (1, 1, 1))
def test_strided_slice_grad():
"""
Feature: Bprop pre-compilation.
Description: Compile the backward graph for the strided_slice_grad op.
Expectation: Load the bprop mindir successfully.
"""
x = Tensor([[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]],
[[5, 5, 5], [6, 6, 6]]], mstype.float32)
strided_slice = Net(P.StridedSlice())
grad = GradNet(strided_slice)
second_grad = GradNet(grad)
second_grad.compile(x, (1, 0, 2), (3, 1, 3), (1, 1, 1))

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