sy00000
/
mindspore
forked from OSSInnovation/mindspore
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

!14442 fix codex 

From: @lianliguang
Reviewed-by: @zhoufeng54,@chujinjin
Signed-off-by: @chujinjin
This commit is contained in:
mindspore-ci-bot 2021-03-31 16:34:27 +08:00 committed by Gitee
parent 47c6d91762 9b94b6f8ed
commit 36dbb2690e
10 changed files with 139 additions and 106 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

51
mindspore/ccsrc/backend/optimizer/ascend/format_type/convert_cast_format.cc
View File

@ -18,6 +18,8 @@
#include <memory>
#include <string>
#include <unordered_map>
#include <utility>
#include <vector>
#include "backend/session/anf_runtime_algorithm.h"
#include "backend/optimizer/common/helper.h"
@ -73,26 +75,7 @@ void ConvertCastFormat::ChangeCastFormat(const CNodePtr &cast_node, const FuncGr
AnfAlgo::SetNodeAttr(kAttrVisited, MakeValue(true), cast_node);
auto used_cast_node_list = GetRealNodeUsedList(func_graph, cast_node);
MS_EXCEPTION_IF_NULL(used_cast_node_list);
std::unordered_map<string, size_t> format_counter;
for (const auto &node_info : *used_cast_node_list) {
MS_EXCEPTION_IF_NULL(node_info.first);
auto cast_out_node = node_info.first->cast<CNodePtr>();
MS_EXCEPTION_IF_NULL(cast_out_node);
size_t input_num = AnfAlgo::GetInputTensorNum(cast_out_node);
for (size_t index = 0; index < input_num; ++index) {
if (AnfAlgo::VisitKernelWithReturnType(AnfAlgo::GetInputNode(cast_out_node->cast<CNodePtr>(), index), 0).first !=
cast_node) {
continue;
}
auto format = AnfAlgo::GetInputFormat(cast_out_node, index);
auto it = format_counter.find(format);
if (it == format_counter.end()) {
format_counter[format] = 1;
} else {
it->second++;
}
}
}
std::unordered_map<string, size_t> format_counter = CalculateFormat(used_cast_node_list, cast_node);
auto cast_input_format = AnfAlgo::GetPrevNodeOutputFormat(cast_node, 0);
string convert_format = kOpFormat_DEFAULT;
if (cast_input_format == kOpFormat_DEFAULT) {
@ -121,5 +104,33 @@ void ConvertCastFormat::ChangeCastFormat(const CNodePtr &cast_node, const FuncGr
SetCastFormat(cast_node, convert_format);
}
}
std::unordered_map<string, size_t> ConvertCastFormat::CalculateFormat(
const std::shared_ptr<std::vector<std::pair<AnfNodePtr, int>>> &used_cast_node_list,
const CNodePtr &cast_node) const {
MS_EXCEPTION_IF_NULL(used_cast_node_list);
MS_EXCEPTION_IF_NULL(cast_node);
std::unordered_map<string, size_t> format_counter;
for (const auto &node_info : *used_cast_node_list) {
MS_EXCEPTION_IF_NULL(node_info.first);
auto cast_out_node = node_info.first->cast<CNodePtr>();
MS_EXCEPTION_IF_NULL(cast_out_node);
size_t input_num = AnfAlgo::GetInputTensorNum(cast_out_node);
for (size_t index = 0; index < input_num; ++index) {
if (AnfAlgo::VisitKernelWithReturnType(AnfAlgo::GetInputNode(cast_out_node->cast<CNodePtr>(), index), 0).first !=
cast_node) {
continue;
}
auto format = AnfAlgo::GetInputFormat(cast_out_node, index);
auto it = format_counter.find(format);
if (it == format_counter.end()) {
format_counter[format] = 1;
} else {
it->second++;
}
}
}
return format_counter;
}
} // namespace opt
} // namespace mindspore

7
mindspore/ccsrc/backend/optimizer/ascend/format_type/convert_cast_format.h
View File

@ -17,6 +17,10 @@
#define MINDSPORE_CCSRC_BACKEND_OPTIMIZER_ASCEND_FORMAT_TYPE_CONVERT_CAST_FORMAT_H_
#include <string>
#include <unordered_map>
#include <utility>
#include <memory>
#include <vector>
#include "backend/optimizer/common/optimizer.h"
@ -30,6 +34,9 @@ class ConvertCastFormat : public PatternProcessPass {
const AnfNodePtr Process(const FuncGraphPtr &func_graph, const AnfNodePtr &, const EquivPtr &) const override;
private:
std::unordered_map<string, size_t> CalculateFormat(
const std::shared_ptr<std::vector<std::pair<AnfNodePtr, int>>> &used_cast_node_list,
const CNodePtr &cast_node) const;
void ChangeCastFormat(const CNodePtr &cast_node, const FuncGraphPtr &func_graph) const;
void SetCastFormat(const CNodePtr &cast_node, const string &format) const;
};

20
mindspore/ccsrc/backend/optimizer/ascend/format_type/deal_ref_trans_and_cast.cc
View File

@ -143,18 +143,22 @@ CNodePtr DealRefTransAndCast::AddAdditionalToRefOutput(const FuncGraphPtr &func_
}
// insert depend
if (origin_format != cur_format || origin_type != cur_type) {
std::vector<AnfNodePtr> depend_nodes;
if (get_item.get() != nullptr) {
depend_nodes = std::vector<AnfNodePtr>{NewValueNode(prim::kPrimDepend), get_item, final_node};
} else {
depend_nodes = std::vector<AnfNodePtr>{NewValueNode(prim::kPrimDepend), cnode, final_node};
}
final_node = func_graph->NewCNode(depend_nodes);
final_node = MakeDependency(get_item, final_node, cnode, func_graph);
MS_LOG(INFO) << "DealRefTranshwAndCast add denpend, op debug info is " << final_node->DebugString();
}
return final_node;
}
CNodePtr DealRefTransAndCast::MakeDependency(const CNodePtr &get_item, const CNodePtr &final_node,
const CNodePtr &cnode, const FuncGraphPtr &func_graph) const {
std::vector<AnfNodePtr> depend_nodes;
if (get_item != nullptr) {
depend_nodes = std::vector<AnfNodePtr>{NewValueNode(prim::kPrimDepend), get_item, final_node};
} else {
depend_nodes = std::vector<AnfNodePtr>{NewValueNode(prim::kPrimDepend), cnode, final_node};
}
return func_graph->NewCNode(depend_nodes);
}
CNodePtr DealRefTransAndCast::DealRefForMultipleOutput(const FuncGraphPtr &func_graph, const CNodePtr &cnode,
const std::shared_ptr<kernel::OpInfo> &op_info) const {
MS_EXCEPTION_IF_NULL(op_info);

2
mindspore/ccsrc/backend/optimizer/ascend/format_type/deal_ref_trans_and_cast.h
View File

@ -33,6 +33,8 @@ class DealRefTransAndCast : public TransDataSplit {
const AnfNodePtr Process(const FuncGraphPtr &, const AnfNodePtr &, const EquivPtr &) const override;
private:
CNodePtr MakeDependency(const CNodePtr &getitem, const CNodePtr &final_node, const CNodePtr &cnode,
const FuncGraphPtr &func_graph) const;
CNodePtr SplitTransdataIfNotSupported(const FuncGraphPtr &func_graph, const CNodePtr &cnode) const;
void DealBroadCastAsRef(const FuncGraphPtr &func_graph, const CNodePtr &cnode) const;
CNodePtr DealRefSigleOutput(const FuncGraphPtr &func_graph, const CNodePtr &cnode,

1
mindspore/ccsrc/common/trans.h
View File

@ -97,7 +97,6 @@ const std::map<std::string, FormatTransfer> kTransFormatMapOfHostToDevice{
{kOpFormat_NC1HWC0, NchwToNc1hwc0}, {kOpFormat_C1HWNCoC0, NchwToC1hwncoc0},
{kOpFormat_FRACTAL_Z_C04, NchwToFracZc04}, {kOpFormat_NC1HWC0_C04, NchwToNc1hwc04},
{kOpFormat_NDC1HWC0, NcdhwToNdc1hwc0}, {kOpFormat_FRACTAL_Z_3D, NcdhwToFracZ3D}};
} // namespace trans
} // namespace mindspore

48
mindspore/ccsrc/pybind_api/ir/primitive_py.cc
View File

@ -182,32 +182,36 @@ void PrimitivePy::CheckHookConsistency(const py::object &grad_out, const py::obj
}
}
BaseRef PrimitivePy::RunBpropHookFunction(const py::tuple &py_args) const {
SyncData(py_args);
auto size = py_args.size();
py::tuple input_args(size - 2);
for (size_t i = 0; i < size - 2; ++i) {
input_args[i] = py_args[i];
}
py::tuple convert_args(py_args.size());
ConvertCTensorToPyTensor(py_args, &convert_args);
auto inst = pynative::PynativeExecutor::GetInstance();
MS_EXCEPTION_IF_NULL(inst);
try {
MS_LOG(DEBUG) << "Run bprop function start";
inst->NewGraph(hook_, input_args.cast<py::args>());
py::object grads_obj = hook_(*convert_args);
py::tuple grads = check_bprop_out(grads_obj, py_args);
inst->EndGraph(hook_, grads_obj, input_args.cast<py::args>());
MS_LOG(DEBUG) << "Run bprop function end";
return std::make_shared<PyObjectRef>(grads);
} catch (std::exception &bt) {
inst->ClearRes();
std::rethrow_exception(std::current_exception());
}
}
BaseRef PrimitivePy::RunHookFunction(const VectorRef &args) const {
py::tuple py_args = ConvertDatatoPyTuple(args);
bool is_bprop = this->HasAttr(kBpropAttrName);
if (is_bprop) {
SyncData(py_args);
auto size = py_args.size();
py::tuple input_args(size - 2);
for (size_t i = 0; i < size - 2; ++i) {
input_args[i] = py_args[i];
}
py::tuple convert_args(py_args.size());
ConvertCTensorToPyTensor(py_args, &convert_args);
auto inst = pynative::PynativeExecutor::GetInstance();
MS_EXCEPTION_IF_NULL(inst);
try {
MS_LOG(DEBUG) << "Run bprop function start";
inst->NewGraph(hook_, input_args.cast<py::args>());
py::object grads_obj = hook_(*convert_args);
py::tuple grads = check_bprop_out(grads_obj, py_args);
inst->EndGraph(hook_, grads_obj, input_args.cast<py::args>());
MS_LOG(DEBUG) << "Run bprop function end";
return std::make_shared<PyObjectRef>(grads);
} catch (std::exception &bt) {
inst->ClearRes();
std::rethrow_exception(std::current_exception());
}
return RunBpropHookFunction(py_args);
}
SyncData(py_args[2]);
bool is_cell = this->HasAttr(kCellHookAttrName);

1
mindspore/ccsrc/pybind_api/ir/primitive_py.h
View File

@ -55,6 +55,7 @@ class PrimitivePy : public Primitive {
void set_hook(const py::function &hook) { hook_ = hook; }
py::function hook() const { return hook_; }
BaseRef RunHookFunction(const VectorRef &args) const override;
BaseRef RunBpropHookFunction(const py::tuple &py_args) const;
BaseRef RunComputeFunction(const VectorRef &args) const override;
py::object RunPyComputeFunction(const py::tuple &py_args) const;
bool HasComputeFunction() const;

56
mindspore/core/ops/conv2d.cc
View File

@ -28,29 +28,8 @@
namespace mindspore {
namespace ops {
namespace {
abstract::ShapePtr Conv2dInferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
MS_EXCEPTION_IF_NULL(primitive);
auto prim_name = primitive->name();
CheckAndConvertUtils::CheckInRange<size_t>("conv2d_infer", input_args.size(), kIncludeBoth, {2, 3}, prim_name);
auto x_shape = CheckAndConvertUtils::ConvertShapePtrToShape("x_shape", input_args[0]->BuildShape(), prim_name);
auto w_shape = CheckAndConvertUtils::ConvertShapePtrToShape("w_shape", input_args[1]->BuildShape(), prim_name);
auto format = Format(GetValue<int64_t>(primitive->GetAttr(kFormat)));
if (format == NHWC) {
x_shape = {x_shape[0], x_shape[3], x_shape[1], x_shape[2]};
w_shape = {w_shape[0], w_shape[3], w_shape[1], w_shape[2]};
}
CheckAndConvertUtils::CheckInteger("weight rank", w_shape.size(), kEqual, 4, prim_name);
CheckAndConvertUtils::CheckInteger("x rank", x_shape.size(), kEqual, 4, prim_name);
CheckAndConvertUtils::Check("x_shape[1] / group", x_shape[1] / GetValue<int64_t>(primitive->GetAttr(kGroup)), kEqual,
"w_shape[1]", w_shape[1], prim_name);
auto out_channel = GetValue<int64_t>(primitive->GetAttr(kOutChannel));
CheckAndConvertUtils::Check("out_channel", out_channel, kEqual, "w_shape[0]", w_shape[0], prim_name);
std::vector<int64_t> temp_w;
std::copy(w_shape.begin() + 2, w_shape.end(), std::back_inserter(temp_w));
CheckAndConvertUtils::Check("kernel_size", GetValue<std::vector<int64_t>>(primitive->GetAttr(kKernelSize)), kEqual,
"w_shape[2:4]", temp_w, prim_name);
std::vector<int64_t> SetPadList(const PrimitivePtr &primitive, const std::vector<int64_t> &w_shape,
const std::vector<int64_t> &x_shape, const int64_t &out_channel) {
auto kernel_size_h = w_shape[2];
auto kernel_size_w = w_shape[3];
auto stride = GetValue<std::vector<int64_t>>(primitive->GetAttr(kStride));
@ -92,13 +71,36 @@ abstract::ShapePtr Conv2dInferShape(const PrimitivePtr &primitive, const std::ve
h_out = floor(h_out);
w_out = floor(w_out);
}
CheckAndConvertUtils::CheckInteger("pad_size", pad_list.size(), kEqual, 4, prim_name);
primitive->AddAttr(kPadList, MakeValue(CheckAndConvertUtils::CheckPositiveVector(kPad, pad_list, prim_name)));
CheckAndConvertUtils::CheckInteger("pad_size", pad_list.size(), kEqual, 4, primitive->name());
primitive->AddAttr(kPadList, MakeValue(CheckAndConvertUtils::CheckPositiveVector(kPad, pad_list, primitive->name())));
std::vector<int64_t> out_shape = {x_shape[0], out_channel, h_out, w_out};
return out_shape;
}
abstract::ShapePtr Conv2dInferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
MS_EXCEPTION_IF_NULL(primitive);
auto prim_name = primitive->name();
CheckAndConvertUtils::CheckInRange<size_t>("conv2d_infer", input_args.size(), kIncludeBoth, {2, 3}, prim_name);
auto x_shape = CheckAndConvertUtils::ConvertShapePtrToShape("x_shape", input_args[0]->BuildShape(), prim_name);
auto w_shape = CheckAndConvertUtils::ConvertShapePtrToShape("w_shape", input_args[1]->BuildShape(), prim_name);
auto format = Format(GetValue<int64_t>(primitive->GetAttr(kFormat)));
if (format == NHWC) {
out_shape = {x_shape[0], h_out, w_out, out_channel};
x_shape = {x_shape[0], x_shape[3], x_shape[1], x_shape[2]};
w_shape = {w_shape[0], w_shape[3], w_shape[1], w_shape[2]};
}
CheckAndConvertUtils::CheckInteger("weight rank", w_shape.size(), kEqual, 4, prim_name);
CheckAndConvertUtils::CheckInteger("x rank", x_shape.size(), kEqual, 4, prim_name);
CheckAndConvertUtils::Check("x_shape[1] / group", x_shape[1] / GetValue<int64_t>(primitive->GetAttr(kGroup)), kEqual,
"w_shape[1]", w_shape[1], prim_name);
auto out_channel = GetValue<int64_t>(primitive->GetAttr(kOutChannel));
CheckAndConvertUtils::Check("out_channel", out_channel, kEqual, "w_shape[0]", w_shape[0], prim_name);
std::vector<int64_t> temp_w;
std::copy(w_shape.begin() + 2, w_shape.end(), std::back_inserter(temp_w));
CheckAndConvertUtils::Check("kernel_size", GetValue<std::vector<int64_t>>(primitive->GetAttr(kKernelSize)), kEqual,
"w_shape[2:4]", temp_w, prim_name);
auto out_shape = SetPadList(primitive, w_shape, x_shape, out_channel);
if (format == NHWC) {
out_shape = {out_shape[0], out_shape[3], out_shape[1], out_shape[2]};
}
return std::make_shared<abstract::Shape>(out_shape);
}

56
mindspore/core/ops/grad/conv2d_backprop_input.cc
View File

@ -23,32 +23,8 @@
namespace mindspore {
namespace ops {
AbstractBasePtr Conv2DBackpropInputInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
const std::vector<AbstractBasePtr> &input_args) {
MS_EXCEPTION_IF_NULL(primitive);
auto prim_name = primitive->name();
CheckAndConvertUtils::CheckInteger("input number", input_args.size(), kEqual, 3, prim_name);
for (const auto &item : input_args) {
MS_EXCEPTION_IF_NULL(item);
}
auto doutput = input_args[0];
auto x_size = input_args[2];
auto x_size_value = x_size->GetValueTrack();
MS_EXCEPTION_IF_NULL(x_size);
auto x_size_v = GetValue<std::vector<int64_t>>(x_size_value);
// infer dtype
auto dtype = doutput->BuildType();
if (!dtype->isa<TensorType>()) {
MS_LOG(EXCEPTION) << "Conv2DBackpropInputInfer doutput must be tensor but got" << dtype->ToString();
}
auto input_tensor_type = dtype->cast<TensorTypePtr>();
MS_EXCEPTION_IF_NULL(input_tensor_type);
auto element = input_tensor_type->element();
// infer shape
auto dout_shape = doutput->BuildShape();
MS_EXCEPTION_IF_NULL(doutput);
auto dout_shapeptr = dout_shape->cast<abstract::ShapePtr>();
auto dout_shape_norm = dout_shapeptr->shape();
void SetPadList(const PrimitivePtr &primitive, const std::vector<int64_t> &dout_shape_norm,
const std::vector<int64_t> &x_size_v) {
auto kernel_size = GetValue<std::vector<int64_t>>(primitive->GetAttr(kKernelSize));
auto stride = GetValue<std::vector<int64_t>>(primitive->GetAttr(kStride));
auto dilation = GetValue<std::vector<int64_t>>(primitive->GetAttr(kStride));
@ -76,6 +52,34 @@ AbstractBasePtr Conv2DBackpropInputInfer(const abstract::AnalysisEnginePtr &, co
pad_list = GetValue<std::vector<int64_t>>(primitive->GetAttr(kPad));
}
primitive->AddAttr(kPadList, MakeValue(pad_list));
}
AbstractBasePtr Conv2DBackpropInputInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
const std::vector<AbstractBasePtr> &input_args) {
MS_EXCEPTION_IF_NULL(primitive);
auto prim_name = primitive->name();
CheckAndConvertUtils::CheckInteger("input number", input_args.size(), kEqual, 3, prim_name);
for (const auto &item : input_args) {
MS_EXCEPTION_IF_NULL(item);
}
auto doutput = input_args[0];
auto x_size = input_args[2];
auto x_size_value = x_size->GetValueTrack();
MS_EXCEPTION_IF_NULL(x_size);
auto x_size_v = GetValue<std::vector<int64_t>>(x_size_value);
// infer dtype
auto dtype = doutput->BuildType();
if (!dtype->isa<TensorType>()) {
MS_LOG(EXCEPTION) << "Conv2DBackpropInputInfer doutput must be tensor but got" << dtype->ToString();
}
auto input_tensor_type = dtype->cast<TensorTypePtr>();
MS_EXCEPTION_IF_NULL(input_tensor_type);
auto element = input_tensor_type->element();
// infer shape
auto dout_shape = doutput->BuildShape();
MS_EXCEPTION_IF_NULL(doutput);
auto dout_shapeptr = dout_shape->cast<abstract::ShapePtr>();
auto dout_shape_norm = dout_shapeptr->shape();
SetPadList(primitive, dout_shape_norm, x_size_v);
return std::make_shared<abstract::AbstractTensor>(element, std::make_shared<abstract::Shape>(x_size_v));
}

3
mindspore/core/ops/max_pool.cc
View File

@ -102,8 +102,7 @@ abstract::ShapePtr InferShape(const PrimitivePtr &primitive, const std::vector<A
CheckAndConvertUtils::CheckInteger("x_rank", in_shape.size(), kEqual, 4, op_name);
auto kernel_size = GetValue<std::vector<int64_t>>(primitive->GetAttr(kKernelSize));
auto pad_mode_value = (primitive->GetAttr(kPadMode));
PadMode pad_mode = PAD;
pad_mode = PadMode(GetValue<int64_t>(pad_mode_value));
PadMode pad_mode = PadMode(GetValue<int64_t>(pad_mode_value));
auto batch = in_shape[0];
auto channel = in_shape[1];
auto in_h = in_shape[2];