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modified: concat_offset_kernel.cc

Browse Source 
modified:   gather_v2_kernel.cc
	modified:   strided_slice_kernel.cc
pull/1204/head
zhaoxinxin 4 years ago
parent 56ff720fac
commit 5acba13261
3 changed files with 23 additions and 23 deletions
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12
ge/host_kernels/concat_offset_kernel.cc
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@ -33,7 +33,7 @@ const int kNumOne = 1;
} // namespace } // namespace
Status ConcatOffsetKernel::Compute(const OpDescPtr op_desc_ptr, const vector<ConstGeTensorPtr> &input, Status ConcatOffsetKernel::Compute(const OpDescPtr op_desc_ptr, const vector<ConstGeTensorPtr> &input,
vector<GeTensorPtr> &v_output) { vector<GeTensorPtr> &v_output) {
GELOGI("ConcatOffsetKernel in."); GELOGD("ConcatOffsetKernel in");
if (op_desc_ptr == nullptr) { if (op_desc_ptr == nullptr) {
GELOGE(PARAM_INVALID, "input opdesc is nullptr."); GELOGE(PARAM_INVALID, "input opdesc is nullptr.");
return PARAM_INVALID; return PARAM_INVALID;
@ -41,7 +41,7 @@ Status ConcatOffsetKernel::Compute(const OpDescPtr op_desc_ptr, const vector<Con
// validate attrs // validate attrs
int N = 0; int N = 0;
if (!(AttrUtils::GetInt(op_desc_ptr, "N", N))) { if (!(AttrUtils::GetInt(op_desc_ptr, "N", N))) {
GELOGW("Attr %s does not exist.", "N"); GELOGW("Attr %s does not exist", "N");
return NOT_CHANGED; return NOT_CHANGED;
} }
// follow IR def, the first input is concat_dim // follow IR def, the first input is concat_dim
@ -50,7 +50,7 @@ Status ConcatOffsetKernel::Compute(const OpDescPtr op_desc_ptr, const vector<Con
int32_t concat_dim = *(const_cast<int32_t *>(reinterpret_cast<const int32_t *>(input_0->GetData().data()))); int32_t concat_dim = *(const_cast<int32_t *>(reinterpret_cast<const int32_t *>(input_0->GetData().data())));
// validate inputs // validate inputs
if ((static_cast<int>(input.size()) != (N + kNumOne)) || (input.size() <= kConcatOffsetInputIndexOne)) { if ((static_cast<int>(input.size()) != (N + kNumOne)) || (input.size() <= kConcatOffsetInputIndexOne)) {
GELOGW("The number of input for concat offset must be equal to %d, and must be more than one.", (N + kNumOne)); GELOGW("The number of input for concat offset must be equal to %d, and must be more than one", (N + kNumOne));
return NOT_CHANGED; return NOT_CHANGED;
} }
@ -61,7 +61,7 @@ Status ConcatOffsetKernel::Compute(const OpDescPtr op_desc_ptr, const vector<Con
GELOGW("Concat dim is bigger than the size of output_shape."); GELOGW("Concat dim is bigger than the size of output_shape.");
return NOT_CHANGED; return NOT_CHANGED;
} }
GELOGI("Output shape size is %ld", output_size); GELOGI("Output shape size is %ld.", output_size);
int32_t offset = 0; int32_t offset = 0;
if (output_size < 0) { if (output_size < 0) {
GELOGE(FAILED, "Index is negative."); GELOGE(FAILED, "Index is negative.");
@ -86,7 +86,7 @@ Status ConcatOffsetKernel::Compute(const OpDescPtr op_desc_ptr, const vector<Con
output_ptr->MutableTensorDesc().SetShape(output_shape); output_ptr->MutableTensorDesc().SetShape(output_shape);
GE_IF_BOOL_EXEC(output_ptr->SetData(reinterpret_cast<uint8_t *>(buf.get()), GE_IF_BOOL_EXEC(output_ptr->SetData(reinterpret_cast<uint8_t *>(buf.get()),
static_cast<size_t>(sizeof(DT_INT32) * output_size)) != GRAPH_SUCCESS, static_cast<size_t>(sizeof(DT_INT32) * output_size)) != GRAPH_SUCCESS,
GELOGW("set data failed"); GELOGW("set data failed.");
return NOT_CHANGED); return NOT_CHANGED);
v_output.push_back(output_ptr); v_output.push_back(output_ptr);
// caculate offset // caculate offset
@ -99,7 +99,7 @@ Status ConcatOffsetKernel::Compute(const OpDescPtr op_desc_ptr, const vector<Con
} }
offset += input_dim; offset += input_dim;
} }
GELOGI("ConcatOffsetKernel success."); GELOGD("ConcatOffsetKernel success");
return SUCCESS; return SUCCESS;
} }
REGISTER_KERNEL(CONCATOFFSET, ConcatOffsetKernel); REGISTER_KERNEL(CONCATOFFSET, ConcatOffsetKernel);

12
ge/host_kernels/gather_v2_kernel.cc
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@ -208,7 +208,7 @@ Status GatherV2Kernel::GenData(const int64_t data_num, ConstGeTensorPtr tensor_x
ret = ProcessAxis3<T>(tensor_x, output); ret = ProcessAxis3<T>(tensor_x, output);
break; break;
default: default:
GELOGI("Only support 4 dims and below but input axis is %ld.", axis); GELOGI("Only support 4 dims and below but input axis is %ld", axis);
return NOT_CHANGED; return NOT_CHANGED;
} }
return ret; return ret;
@ -267,7 +267,7 @@ Status GatherV2Kernel::Process(int64_t axis, DataType data_type, ConstGeTensorPt
ret = GenData<uint64_t>(data_num, input_tensor_ptr, axis, output_ptr); ret = GenData<uint64_t>(data_num, input_tensor_ptr, axis, output_ptr);
break; break;
default: default:
GELOGI("GatherV2Kernel does not support this Data type:%s.", TypeUtils::DataTypeToSerialString(data_type).c_str()); GELOGI("GatherV2Kernel does not support this Data type:%s", TypeUtils::DataTypeToSerialString(data_type).c_str());
return NOT_CHANGED; return NOT_CHANGED;
} }
return ret; return ret;
@ -330,13 +330,13 @@ Status GatherV2Kernel::Check(const OpDescPtr &op_desc_ptr, const vector<ConstGeT
auto axis_shape = tensor2->GetTensorDesc().GetShape(); auto axis_shape = tensor2->GetTensorDesc().GetShape();
// axis must be scalar // axis must be scalar
if (axis_shape.GetDimNum() != 0) { if (axis_shape.GetDimNum() != 0) {
GELOGW("axis must be scalar but its shape is %zu.", axis_shape.GetDimNum()); GELOGW("axis must be scalar but its shape is %zu", axis_shape.GetDimNum());
return NOT_CHANGED; return NOT_CHANGED;
} }
auto axis_data_type = tensor2->GetTensorDesc().GetDataType(); auto axis_data_type = tensor2->GetTensorDesc().GetDataType();
bool is_valid_axis_data_type = axis_data_type == DT_INT32 || axis_data_type == DT_INT64; bool is_valid_axis_data_type = axis_data_type == DT_INT32 || axis_data_type == DT_INT64;
if (!is_valid_axis_data_type) { if (!is_valid_axis_data_type) {
GELOGW("axis datatype must be DT_INT32 or DT_INT64."); GELOGW("axis datatype must be DT_INT32 or DT_INT64");
return NOT_CHANGED; return NOT_CHANGED;
} }
@ -442,13 +442,13 @@ Status GatherV2Kernel::Compute(const OpDescPtr op_desc_ptr, const vector<ConstGe
auto ret_y = CalcStride(ystride_, y_shape); auto ret_y = CalcStride(ystride_, y_shape);
ret = (ret_x == SUCCESS && ret_y == SUCCESS) ? SUCCESS : NOT_CHANGED; ret = (ret_x == SUCCESS && ret_y == SUCCESS) ? SUCCESS : NOT_CHANGED;
if (ret != SUCCESS) { if (ret != SUCCESS) {
GELOGE(ret, "CalcStride Failed."); GELOGE(ret, "CalcStride Failed");
return ret; return ret;
} }
ret = Process(axis, x_data_type, tensor0, output_ptr); ret = Process(axis, x_data_type, tensor0, output_ptr);
if (ret != SUCCESS) { if (ret != SUCCESS) {
GELOGE(ret, "GenData failed, data_type: %s.", TypeUtils::DataTypeToSerialString(x_data_type).c_str()); GELOGE(ret, "GenData failed, data_type: %s", TypeUtils::DataTypeToSerialString(x_data_type).c_str());
return ret; return ret;
} }

22
ge/host_kernels/strided_slice_kernel.cc
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@ -45,7 +45,7 @@ bool IsEllipsisMaskValid(const GeTensorDescPtr &input_desc, const uint32_t ellip
++ellipsis_num; ++ellipsis_num;
} }
if (ellipsis_num > 1) { if (ellipsis_num > 1) {
GELOGW("Only one non-zero bit is allowed in ellipsis_mask"); GELOGW("Only one non-zero bit is allowed in ellipsis_mask.");
return false; return false;
} }
} }
@ -100,7 +100,7 @@ Status StridedSliceKernel::Compute(const ge::OpDescPtr attr, const std::vector<g
std::vector<int64_t> output_dims; std::vector<int64_t> output_dims;
std::vector<int64_t> stride_vec; std::vector<int64_t> stride_vec;
if (InitParamWithAttrs(input, input_dims, begin_vec, output_dims, stride_vec) != SUCCESS) { if (InitParamWithAttrs(input, input_dims, begin_vec, output_dims, stride_vec) != SUCCESS) {
GELOGW("Init param with mask attrs failed.Ignore kernel"); GELOGW("Init param with mask attrs failed.Ignore kernel.");
return NOT_CHANGED; return NOT_CHANGED;
} }
@ -114,7 +114,7 @@ Status StridedSliceKernel::Compute(const ge::OpDescPtr attr, const std::vector<g
auto output_tensor_desc = attr->GetOutputDesc(0); auto output_tensor_desc = attr->GetOutputDesc(0);
GeTensorPtr output_ptr = MakeShared<GeTensor>(output_tensor_desc); GeTensorPtr output_ptr = MakeShared<GeTensor>(output_tensor_desc);
if (output_ptr == nullptr) { if (output_ptr == nullptr) {
GELOGE(MEMALLOC_FAILED, "MakeShared GeTensor failed, node name %s", attr->GetName().c_str()); GELOGE(MEMALLOC_FAILED, "MakeShared GeTensor failed, node name %s.", attr->GetName().c_str());
return NOT_CHANGED; return NOT_CHANGED;
} }
auto ret = OpUtils::SetOutputSliceData(data, static_cast<int64_t>(data_size), data_type, input_dims, begin_vec, auto ret = OpUtils::SetOutputSliceData(data, static_cast<int64_t>(data_size), data_type, input_dims, begin_vec,
@ -138,7 +138,7 @@ Status StridedSliceKernel::Compute(const ge::OpDescPtr attr, const std::vector<g
} }
Status StridedSliceKernel::CheckAndGetAttr(const OpDescPtr &attr) { Status StridedSliceKernel::CheckAndGetAttr(const OpDescPtr &attr) {
if (attr == nullptr) { if (attr == nullptr) {
GELOGE(PARAM_INVALID, "input opdescptr is nullptr"); GELOGE(PARAM_INVALID, "input opdescptr is nullptr.");
return PARAM_INVALID; return PARAM_INVALID;
} }
// Get all op attr value of strided_slice // Get all op attr value of strided_slice
@ -159,7 +159,7 @@ Status StridedSliceKernel::CheckAndGetAttr(const OpDescPtr &attr) {
} }
Status StridedSliceKernel::CheckInputParam(const std::vector<ConstGeTensorPtr> &input) { Status StridedSliceKernel::CheckInputParam(const std::vector<ConstGeTensorPtr> &input) {
if (input.size() != kStridedSliceInputSize) { if (input.size() != kStridedSliceInputSize) {
GELOGE(PARAM_INVALID, "The number of input for strided slice must be %zu", kStridedSliceInputSize); GELOGE(PARAM_INVALID, "The number of input for strided slice must be %zu.", kStridedSliceInputSize);
return PARAM_INVALID; return PARAM_INVALID;
} }
@ -178,7 +178,7 @@ Status StridedSliceKernel::CheckInputParam(const std::vector<ConstGeTensorPtr> &
auto stride_tensor_desc = begin_tensor->GetTensorDesc(); auto stride_tensor_desc = begin_tensor->GetTensorDesc();
if (begin_tensor_desc.GetDataType() != end_tensor_desc.GetDataType() || if (begin_tensor_desc.GetDataType() != end_tensor_desc.GetDataType() ||
end_tensor_desc.GetDataType() != stride_tensor_desc.GetDataType()) { end_tensor_desc.GetDataType() != stride_tensor_desc.GetDataType()) {
GELOGW("Data type of StridedSlice OP(begin,end,strides) must be same"); GELOGW("Data type of StridedSlice OP(begin,end,strides) must be same.");
return PARAM_INVALID; return PARAM_INVALID;
} }
if (kIndexNumberType.find(begin_tensor_desc.GetDataType()) == kIndexNumberType.end()) { if (kIndexNumberType.find(begin_tensor_desc.GetDataType()) == kIndexNumberType.end()) {
@ -190,7 +190,7 @@ Status StridedSliceKernel::CheckInputParam(const std::vector<ConstGeTensorPtr> &
auto x_data_type = weight0->GetTensorDesc().GetDataType(); auto x_data_type = weight0->GetTensorDesc().GetDataType();
auto x_data_size = GetSizeByDataType(x_data_type); auto x_data_size = GetSizeByDataType(x_data_type);
if (x_data_size < 0) { if (x_data_size < 0) {
GELOGW("Data type of x input %s is not supported", TypeUtils::DataTypeToSerialString(x_data_type).c_str()); GELOGW("Data type of x input %s is not supported.", TypeUtils::DataTypeToSerialString(x_data_type).c_str());
return PARAM_INVALID; return PARAM_INVALID;
} }
size_t weight0_size = weight0->GetData().size() / x_data_size; size_t weight0_size = weight0->GetData().size() / x_data_size;
@ -198,12 +198,12 @@ Status StridedSliceKernel::CheckInputParam(const std::vector<ConstGeTensorPtr> &
size_t end_data_size = end_tensor->GetData().size(); size_t end_data_size = end_tensor->GetData().size();
size_t stride_data_size = stride_tensor->GetData().size(); size_t stride_data_size = stride_tensor->GetData().size();
if ((weight0_size == 0) || (begin_data_size == 0) || (end_data_size == 0) || (stride_data_size == 0)) { if ((weight0_size == 0) || (begin_data_size == 0) || (end_data_size == 0) || (stride_data_size == 0)) {
GELOGW("Data size of inputs is 0"); GELOGW("Data size of inputs is 0.");
return PARAM_INVALID; return PARAM_INVALID;
} }
// check dim size // check dim size
if (!((begin_data_size == end_data_size) && (end_data_size == stride_data_size))) { if (!((begin_data_size == end_data_size) && (end_data_size == stride_data_size))) {
GELOGW("The sizes of begin, end and stride is not supported"); GELOGW("The sizes of begin, end and stride is not supported.");
return PARAM_INVALID; return PARAM_INVALID;
} }
return SUCCESS; return SUCCESS;
@ -254,7 +254,7 @@ Status StridedSliceKernel::InitParamWithAttrs(const std::vector<ConstGeTensorPtr
begin_i, end_i, stride_i, x_dims.at(i)); begin_i, end_i, stride_i, x_dims.at(i));
auto ret = MaskCal(i, begin_i, end_i, x_dims.at(i)); auto ret = MaskCal(i, begin_i, end_i, x_dims.at(i));
if (ret != SUCCESS) { if (ret != SUCCESS) {
GELOGW("MaskCal failed, because of data overflow"); GELOGW("MaskCal failed, because of data overflow.");
return NOT_CHANGED; return NOT_CHANGED;
} }
int64_t dim_final; int64_t dim_final;
@ -273,7 +273,7 @@ void StridedSliceKernel::ExpandDimsWithNewAxis(const ConstGeTensorPtr &begin_ten
vector<int64_t> &x_dims) { vector<int64_t> &x_dims) {
auto begin_data_type_size = GetSizeByDataType(begin_tensor->GetTensorDesc().GetDataType()); auto begin_data_type_size = GetSizeByDataType(begin_tensor->GetTensorDesc().GetDataType());
if (begin_data_type_size == 0) { if (begin_data_type_size == 0) {
GELOGW("Param begin_data_type_size should not be zero"); GELOGW("Param begin_data_type_size should not be zero.");
return; return;
} }
size_t begin_vec_size = begin_tensor->GetData().size() / begin_data_type_size; size_t begin_vec_size = begin_tensor->GetData().size() / begin_data_type_size;

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