mindspore-Ecosystem
/
mindspore
21
0
Fork 27
Code Issues Pull Requests 6 Projects Releases Wiki Activity

!37788 告警清理 

Merge pull request !37788 from qiuzhongya/master
This commit is contained in:
i-robot 2022-07-13 02:35:46 +00:00 committed by Gitee
parent f02f317e3d 611afd8cf8
commit b1c4038a5b
No known key found for this signature in database
GPG Key ID: 173E9B9CA92EEF8F
9 changed files with 20 additions and 55 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
mindspore/ccsrc/plugin/device/ascend/kernel/hccl/hccl_kernel.cc
View File

@ -322,7 +322,7 @@ bool HcclKernel::Launch(const std::vector<AddressPtr> &inputs, const std::vector
op_info.outputPtr = outputs[0]->addr;
op_info.dataType = static_cast<HcclDataType>(data_type);
op_info.opType = static_cast<HcclReduceOp>(op_type_);
op_info.root = IntToUint(root_id_);
op_info.root = root_id_;
op_info.count = hccl_count_;
auto callback = [this](HcclResult status) {

1
mindspore/ccsrc/plugin/device/ascend/kernel/hccl/hcom_receive.h
View File

@ -19,6 +19,7 @@
#include <memory>
#include <vector>
#include "plugin/device/ascend/kernel/hccl/hccl_kernel.h"
namespace mindspore {

4
mindspore/ccsrc/plugin/device/ascend/kernel/hccl/hcom_util.cc
View File

@ -158,7 +158,7 @@ bool HcomUtil::GetHcomCount(const AnfNodePtr &anf_node, const vector<HcclDataTyp
}
size_t actual_input_size = input_size;
if (common::AnfAlgo::HasNodeAttr(kAttrFusion, cnode) &&
common::AnfAlgo::GetNodeAttr<int64_t>(anf_node, kAttrFusion)) {
common::AnfAlgo::GetNodeAttr<int64_t>(anf_node, kAttrFusion) != 0) {
actual_input_size = (input_size + align_size - 1 + filled_size) / align_size * align_size;
}
block_size = static_cast<uint64_t>(actual_input_size / LongToSize(rank_size));
@ -219,7 +219,7 @@ bool HcomUtil::GetHcomRootId(const AnfNodePtr &anf_node, uint32_t *root_id) {
auto primitive = common::AnfAlgo::GetCNodePrimitive(anf_node);
MS_EXCEPTION_IF_NULL(primitive);
if (primitive->GetAttr(kAttrRootRank) != nullptr) {
*root_id = (uint32_t)GetValue<int64_t>(primitive->GetAttr(kAttrRootRank));
*root_id = static_cast<uint32_t>(GetValue<int64_t>(primitive->GetAttr(kAttrRootRank)));
} else {
MS_LOG(ERROR) << "HcomUtil::Get HCOM_ATTR_ROOT_INDEX fail, not support!";
return false;

2
mindspore/ccsrc/plugin/device/ascend/kernel/hccl/hcom_util.h
View File

@ -58,7 +58,7 @@ static map<HcclDataType, uint32_t> kConstOpHcomDataTypeSizeMap = {
class HcomUtil {
public:
static bool GetKernelInputShape(const AnfNodePtr &anf_node, vector<ShapeVector> *hccl_kernel_shape_list);
static bool GetKernelInputShape(const AnfNodePtr &anf_node, vector<ShapeVector> *hccl_kernel_intput_shape_list);
static bool GetKernelOutputShape(const AnfNodePtr &anf_node, vector<ShapeVector> *hccl_kernel_shape_list);
static ::HcclDataType ConvertHcclType(TypeId type_id);
static bool GetHcomDataType(const AnfNodePtr &anf_node, vector<HcclDataType> *data_type_list);

11
mindspore/ccsrc/plugin/device/ascend/kernel/host/dynamic_broadcast_gradient_args_kernel.cc
View File

@ -144,14 +144,13 @@ std::vector<int64_t> GetInputShape(const CNodePtr &cnode, size_t index) {
x_shape_value->set_device_address(address_x, false);
x_shape_value->data_sync();
auto x_value = reinterpret_cast<int64_t *>(x_shape_value->data_c());
auto x_value = static_cast<int64_t *>(x_shape_value->data_c());
MS_EXCEPTION_IF_NULL(x_value);
std::vector<int64_t> input_shape = {x_value, x_value + x_num};
return input_shape;
}
size_t SetOutputValue(const CNodePtr &cnode, const std::vector<std::vector<int64_t>> &grad_reduce_idx, size_t index,
size_t input_num) {
size_t SetOutputValue(const CNodePtr &cnode, const std::vector<std::vector<int64_t>> &grad_reduce_idx, size_t index) {
std::vector<int64_t> output;
size_t out_size = grad_reduce_idx[index].size();
for (size_t k = 0; k < out_size; ++k) {
@ -188,7 +187,7 @@ size_t SetOutputValue(const CNodePtr &cnode, const std::vector<std::vector<int64
}
} // namespace
void DynamicBroadcastGradientArgsKernelMod::Execute() {
void DynamicBroadcastGradientArgsKernelMod::Execute() const {
MS_LOG(INFO) << "Execute DynamicBroadcastGradientArgsKernel Start";
auto node = anf_node_.lock();
MS_EXCEPTION_IF_NULL(node);
@ -205,8 +204,8 @@ void DynamicBroadcastGradientArgsKernelMod::Execute() {
input_shapes[1] = GetInputShape(cnode, 1);
auto grad_reduce_idx = CalculateOutput(input_shapes);
auto r0_size = SetOutputValue(cnode, grad_reduce_idx, 0, input_shapes[0].size());
auto r1_size = SetOutputValue(cnode, grad_reduce_idx, 1, input_shapes[1].size());
auto r0_size = SetOutputValue(cnode, grad_reduce_idx, 0);
auto r1_size = SetOutputValue(cnode, grad_reduce_idx, 1);
ShapeVector r0_shp{SizeToLong(r0_size)};
ShapeVector r1_shp{SizeToLong(r1_size)};

5
mindspore/ccsrc/plugin/device/ascend/kernel/host/dynamic_broadcast_gradient_args_kernel.h
View File

@ -15,9 +15,10 @@
*/
#ifndef MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_HOST_DYNAMIC_BROADCAST_GRADIENT_ARGS_KERNEL_H_
#define MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_HOST_DYNAMIC_BROADCAST_GRADIENT_ARGS_KERNEL_H_
#include <vector>
#include <memory>
#include <string>
#include <vector>
#include "plugin/device/ascend/kernel/host/host_kernel_mod.h"
namespace mindspore {
@ -30,7 +31,7 @@ class DynamicBroadcastGradientArgsKernelMod : public HostKernelMod {
const std::vector<AddressPtr> &outputs, void *stream_ptr) override;
private:
void Execute();
void Execute() const;
};
MS_HOST_REG_KERNEL(DynamicBroadcastGradientArgs, DynamicBroadcastGradientArgsKernelMod);
} // namespace kernel

46
mindspore/ccsrc/plugin/device/ascend/kernel/host/dynamic_shape_kernel.cc
View File

@ -23,7 +23,7 @@
namespace mindspore {
namespace kernel {
void TensorShapeKernelMod::Execute() {
void TensorShapeKernelMod::Execute() const {
MS_LOG(INFO) << "Execute TensorShapeKernel Start";
auto node = anf_node_.lock();
MS_EXCEPTION_IF_NULL(node);
@ -64,50 +64,16 @@ void TensorShapeKernelMod::Execute() {
if (!ret) {
MS_LOG(EXCEPTION) << "Sync stream error!";
}
output_addr->SyncHostToDevice(output_shape, LongToSize(output_tensor_for_sync->data().nbytes()),
output_tensor_for_sync->data_type(), output_tensor_for_sync->data_c(),
output_tensor_for_sync->device_info().host_format_);
if (!output_addr->SyncHostToDevice(output_shape, LongToSize(output_tensor_for_sync->data().nbytes()),
output_tensor_for_sync->data_type(), output_tensor_for_sync->data_c(),
output_tensor_for_sync->device_info().host_format_)) {
MS_LOG(EXCEPTION) << "TensorShapeKernel SyncHostToDevice failed.";
}
}
MS_LOG(INFO) << "Execute TensorShapeKernel End";
}
void TensorShapeKernelMod::Execute(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &outputs) {
MS_LOG(INFO) << "Execute TensorShapeKernel Start";
auto node = anf_node_.lock();
MS_EXCEPTION_IF_NULL(node);
auto cnode = node->cast<CNodePtr>();
MS_EXCEPTION_IF_NULL(cnode);
auto input_num = common::AnfAlgo::GetInputTensorNum(cnode);
if (input_num != 1) {
MS_LOG(EXCEPTION) << "Op [" << cnode->DebugString() << "] has invalid input num, should be 1, but got " << input_num
<< trace::DumpSourceLines(cnode);
}
auto prev_output_shape = common::AnfAlgo::GetPrevNodeOutputInferShape(cnode, 0);
std::vector<int64_t> output_shape = {SizeToLong(prev_output_shape.size())};
auto output_type = TypeId::kNumberTypeInt64;
auto output_tensor_for_sync = std::make_shared<tensor::Tensor>(output_type, output_shape);
MS_EXCEPTION_IF_NULL(output_tensor_for_sync);
auto data_ptr = static_cast<int64_t *>(output_tensor_for_sync->data_c());
for (size_t i = 0; i < prev_output_shape.size(); ++i) {
MS_LOG(INFO) << "DEBUG prev_output_shape[" << i << "]:" << prev_output_shape[i];
*(data_ptr + i) = prev_output_shape[i];
}
if (outputs.empty()) {
MS_LOG(EXCEPTION) << "Output address of DynamicShape is empty";
}
auto status = rtMemcpyAsync(outputs[0]->addr, outputs[0]->size, output_tensor_for_sync->data_c(),
LongToSize(output_tensor_for_sync->data().nbytes()), RT_MEMCPY_HOST_TO_DEVICE, stream_);
if (status != RT_ERROR_NONE) {
MS_LOG(EXCEPTION) << "Execute TensorShapeKernel rtMemcpyAsync failed!";
}
MS_LOG(INFO) << "Execute TensorShapeKernel End";
}
bool TensorShapeKernelMod::Launch(const std::vector<AddressPtr> &, const std::vector<AddressPtr> &,
const std::vector<AddressPtr> &, void *stream_ptr) {
auto node = anf_node_.lock();

3
mindspore/ccsrc/plugin/device/ascend/kernel/host/dynamic_shape_kernel.h
View File

@ -30,8 +30,7 @@ class TensorShapeKernelMod : public HostKernelMod {
const std::vector<AddressPtr> &outputs, void *stream_ptr) override;
private:
void Execute();
void Execute(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &outputs);
void Execute() const;
};
MS_HOST_REG_KERNEL(DynamicShape, TensorShapeKernelMod);
MS_HOST_REG_KERNEL(TensorShape, TensorShapeKernelMod);

1
mindspore/ccsrc/plugin/device/ascend/kernel/host/host_kernel_metadata.h
View File

@ -17,7 +17,6 @@
#ifndef MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_HOST_HOST_KERNEL_META_DATA_H_
#define MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_HOST_HOST_KERNEL_META_DATA_H_
#include <string>
#include <vector>
#include <memory>
#include "kernel/kernel_build_info.h"