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CI测试不review update matmul_kernel.cc [phi_ops] #78765

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4dcde94
update matmul_kernel.cc
co63oc Apr 23, 2026
9678b2e
fix
co63oc Apr 23, 2026
e03dfe7
fix
co63oc Apr 23, 2026
41f6b3c
fix
co63oc Apr 23, 2026
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16 changes: 7 additions & 9 deletions paddle/phi/core/tensor_utils.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -994,7 +994,7 @@ template phi::dtype::complex<double> GetValue(const DenseTensor* x);
template <typename T>
std::vector<T> GetVectorFromTensor(const DenseTensor* x) {
std::vector<T> vec_new_data;
if (phi::TransToProtoVarType(x->dtype()) == ProtoDataType::INT32) {
if (x->dtype() == DataType::INT32) {
auto* data = x->data<int>();
DenseTensor cpu_attr_tensor;
if (x->place().GetType() != phi::AllocationType::CPU) {
Expand All @@ -1004,7 +1004,7 @@ std::vector<T> GetVectorFromTensor(const DenseTensor* x) {
data = cpu_attr_tensor.data<int>();
}
vec_new_data = std::vector<T>(data, data + x->numel());
} else if (phi::TransToProtoVarType(x->dtype()) == ProtoDataType::INT64) {
} else if (x->dtype() == DataType::INT64) {
auto* data = x->data<int64_t>();
DenseTensor cpu_attr_tensor;
if (x->place().GetType() != phi::AllocationType::CPU) {
Expand All @@ -1018,7 +1018,7 @@ std::vector<T> GetVectorFromTensor(const DenseTensor* x) {
} else {
PADDLE_THROW(common::errors::InvalidArgument(
"The dtype of Tensor must be int32 or int64, but received: %s",
phi::TransToProtoVarType(x->dtype())));
x->dtype()));
}
return vec_new_data;
}
Expand Down Expand Up @@ -1046,20 +1046,18 @@ std::vector<T> _GetVectorFromTensor(const DenseTensor* x) {

template <>
std::vector<float> GetVectorFromTensor<float>(const DenseTensor* x) {
if (phi::TransToProtoVarType(x->dtype()) != ProtoDataType::FP32) {
if (x->dtype() != DataType::FLOAT32) {
PADDLE_THROW(common::errors::InvalidArgument(
"The dtype of Tensor must be float32, but received: %s",
phi::TransToProtoVarType(x->dtype())));
"The dtype of Tensor must be float32, but received: %s", x->dtype()));
}
return _GetVectorFromTensor<float>(x);
}

template <>
std::vector<double> GetVectorFromTensor<double>(const DenseTensor* x) {
if (phi::TransToProtoVarType(x->dtype()) != ProtoDataType::FP64) {
if (x->dtype() != DataType::FLOAT64) {
PADDLE_THROW(common::errors::InvalidArgument(
"The dtype of Tensor must be float64, but received: %s",
phi::TransToProtoVarType(x->dtype())));
"The dtype of Tensor must be float64, but received: %s", x->dtype()));
}
return _GetVectorFromTensor<double>(x);
}
Expand Down
7 changes: 4 additions & 3 deletions paddle/phi/infermeta/multiary.cc
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Expand Up @@ -2849,11 +2849,12 @@ void FusionGroupInferMeta(const std::vector<const MetaTensor*>& ins,
}

for (size_t j = 0; j < num_outs; ++j) {
if (outs_dtype[j] == phi::TransToProtoVarType(DataType::FLOAT16)) {
DataType out_dtype = TransToPhiDataType(outs_dtype[j]);
if (out_dtype == DataType::FLOAT16) {
outs[j]->set_dtype(DataType::FLOAT16);
} else if (outs_dtype[j] == phi::TransToProtoVarType(DataType::FLOAT32)) {
} else if (out_dtype == DataType::FLOAT32) {
outs[j]->set_dtype(DataType::FLOAT32);
} else if (outs_dtype[j] == phi::TransToProtoVarType(DataType::FLOAT64)) {
} else if (out_dtype == DataType::FLOAT64) {
outs[j]->set_dtype(DataType::FLOAT64);
}
}
Expand Down
4 changes: 2 additions & 2 deletions paddle/phi/kernels/cpu/pyramid_hash_kernel.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -228,8 +228,8 @@ void CPUPyramidHashOPKernel(const Context& dev_ctx,
if (iter != iter_end) {
exit(1);
}
auto weight_type = TransToProtoVarType(_blobs_0->dtype());
if (_is_training == 0 && weight_type != ProtoDataType::INT8) {
auto weight_type = _blobs_0->dtype();
if (_is_training == 0 && weight_type != DataType::INT8) {
funcs::axpy_noadd(
top_data, top_data, top->dims()[0] * top->dims()[1], _drop_out_percent);
}
Expand Down
28 changes: 12 additions & 16 deletions paddle/phi/kernels/cpu/tdm_sampler_kernel.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -262,9 +262,9 @@ void TDMSamplerKernel(const Context &dev_ctx,
DenseTensor *out,
DenseTensor *labels,
DenseTensor *mask) {
const auto &input_type = TransToProtoVarType(x.dtype());
const auto &input_type = x.dtype();
bool input_type_match =
input_type == ProtoDataType::INT32 || input_type == ProtoDataType::INT64;
input_type == DataType::INT32 || input_type == DataType::INT64;
PADDLE_ENFORCE_EQ(input_type_match,
true,
common::errors::InvalidArgument(
Expand All @@ -274,9 +274,9 @@ void TDMSamplerKernel(const Context &dev_ctx,
DataTypeToString(DataType::INT32),
DataTypeToString(DataType::INT64)));

const auto &travel_type = TransToProtoVarType(travel.dtype());
bool travel_type_match = travel_type == ProtoDataType::INT32 ||
travel_type == ProtoDataType::INT64;
const auto &travel_type = travel.dtype();
bool travel_type_match =
travel_type == DataType::INT32 || travel_type == DataType::INT64;
PADDLE_ENFORCE_EQ(travel_type_match,
true,
common::errors::InvalidArgument(
Expand All @@ -286,9 +286,9 @@ void TDMSamplerKernel(const Context &dev_ctx,
DataTypeToString(DataType::INT32),
DataTypeToString(DataType::INT64)));

const auto &layer_type = TransToProtoVarType(layer.dtype());
const auto &layer_type = layer.dtype();
bool layer_type_match =
layer_type == ProtoDataType::INT32 || layer_type == ProtoDataType::INT64;
layer_type == DataType::INT32 || layer_type == DataType::INT64;
PADDLE_ENFORCE_EQ(layer_type_match,
true,
common::errors::InvalidArgument(
Expand All @@ -305,10 +305,9 @@ void TDMSamplerKernel(const Context &dev_ctx,
DataTypeToString(travel.dtype()),
DataTypeToString(layer.dtype())));

auto output_type = static_cast<ProtoDataType>(dtype);
auto output_type = TransToPhiDataType(dtype);

if (travel_type == ProtoDataType::INT32 &&
output_type == ProtoDataType::INT32) {
if (travel_type == DataType::INT32 && output_type == DataType::INT32) {
TDMSamplerInner<T, Context, int, int>(dev_ctx,
x,
travel,
Expand All @@ -320,8 +319,7 @@ void TDMSamplerKernel(const Context &dev_ctx,
out,
labels,
mask);
} else if (travel_type == ProtoDataType::INT64 &&
output_type == ProtoDataType::INT32) {
} else if (travel_type == DataType::INT64 && output_type == DataType::INT32) {
TDMSamplerInner<T, Context, int64_t, int>(dev_ctx,
x,
travel,
Expand All @@ -333,8 +331,7 @@ void TDMSamplerKernel(const Context &dev_ctx,
out,
labels,
mask);
} else if (travel_type == ProtoDataType::INT32 &&
output_type == ProtoDataType::INT64) {
} else if (travel_type == DataType::INT32 && output_type == DataType::INT64) {
TDMSamplerInner<T, Context, int, int64_t>(dev_ctx,
x,
travel,
Expand All @@ -346,8 +343,7 @@ void TDMSamplerKernel(const Context &dev_ctx,
out,
labels,
mask);
} else if (travel_type == ProtoDataType::INT64 &&
output_type == ProtoDataType::INT64) {
} else if (travel_type == DataType::INT64 && output_type == DataType::INT64) {
TDMSamplerInner<T, Context, int64_t, int64_t>(dev_ctx,
x,
travel,
Expand Down
35 changes: 16 additions & 19 deletions paddle/phi/kernels/fusion/gpu/fusion_group_kernel.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -28,15 +28,14 @@ static void MutableMultiTypeData(std::vector<DenseTensor*>* var,
const std::vector<int>& data_type,
const DeviceContext& dev_ctx) {
for (size_t i = 0; i < var->size(); i++) {
if (data_type[i] == phi::TransToProtoVarType(phi::DataType::FLOAT32)) {
DataType dtype = TransToPhiDataType(data_type[i]);
if (dtype == DataType::FLOAT32) {
dev_ctx.template Alloc<float>((*var)[i],
(*var)[i]->numel() * sizeof(float));
} else if (data_type[i] ==
phi::TransToProtoVarType(phi::DataType::FLOAT16)) {
dev_ctx.template Alloc<phi::float16>(
(*var)[i], (*var)[i]->numel() * sizeof(phi::float16));
} else if (data_type[i] ==
phi::TransToProtoVarType(phi::DataType::FLOAT64)) {
} else if (dtype == DataType::FLOAT16) {
dev_ctx.template Alloc<float16>((*var)[i],
(*var)[i]->numel() * sizeof(float16));
} else if (dtype == DataType::FLOAT64) {
dev_ctx.template Alloc<double>((*var)[i],
(*var)[i]->numel() * sizeof(double));
}
Expand Down Expand Up @@ -66,25 +65,23 @@ void FusionGroupKernel(const Context& dev_ctx,
args.push_back(&n);
std::vector<const void*> ptrs(num_ins + num_outs);
for (size_t i = 0; i < num_ins; ++i) {
if (inputs_dtype[i] == phi::TransToProtoVarType(phi::DataType::FLOAT16)) {
ptrs[i] = ins[i]->data<phi::float16>();
} else if (inputs_dtype[i] ==
phi::TransToProtoVarType(phi::DataType::FLOAT32)) {
DataType input_dtype = TransToPhiDataType(inputs_dtype[i]);
if (input_dtype == DataType::FLOAT16) {
ptrs[i] = ins[i]->data<float16>();
} else if (input_dtype == DataType::FLOAT32) {
ptrs[i] = ins[i]->data<float>();
} else if (inputs_dtype[i] ==
phi::TransToProtoVarType(phi::DataType::FLOAT64)) {
} else if (input_dtype == DataType::FLOAT64) {
ptrs[i] = ins[i]->data<double>();
}
args.push_back(&ptrs[i]);
}
for (size_t j = 0; j < num_outs; ++j) {
if (outs_dtype[j] == phi::TransToProtoVarType(phi::DataType::FLOAT16)) {
ptrs[num_ins + j] = outs[j]->data<phi::float16>();
} else if (outs_dtype[j] ==
phi::TransToProtoVarType(phi::DataType::FLOAT32)) {
DataType out_dtype = TransToPhiDataType(outs_dtype[j]);
if (out_dtype == DataType::FLOAT16) {
ptrs[num_ins + j] = outs[j]->data<float16>();
} else if (out_dtype == DataType::FLOAT32) {
ptrs[num_ins + j] = outs[j]->data<float>();
} else if (outs_dtype[j] ==
phi::TransToProtoVarType(phi::DataType::FLOAT64)) {
} else if (out_dtype == DataType::FLOAT64) {
ptrs[num_ins + j] = outs[j]->data<double>();
}
args.push_back(&ptrs[num_ins + j]);
Expand Down
5 changes: 2 additions & 3 deletions paddle/phi/kernels/fusion/onednn/fusion_gru_kernel.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -489,14 +489,13 @@ void RunKernel(const phi::OneDNNContext& dev_ctx,
std::shared_ptr<dnnl::memory> h0_memory_p, weight_h_memory_p,
weight_x_memory_p;

if (phi::TransToProtoVarType(weight_h.dtype()) == phi::ProtoDataType::FP32) {
if (weight_h.dtype() == DataType::FLOAT32) {
h0_memory_p = handler.template AcquireH0Memory<float>(h0.get_ptr());
weight_x_memory_p =
handler.template AcquireWeightXMemory<float>(&weight_x, origin_mode);
weight_h_memory_p =
handler.template AcquireWeightHMemory<float>(&weight_h, origin_mode);
} else if (phi::TransToProtoVarType(weight_h.dtype()) ==
phi::ProtoDataType::BF16) {
} else if (weight_h.dtype() == DataType::BFLOAT16) {
h0_memory_p = handler.template AcquireH0Memory<phi::bfloat16>(h0.get_ptr());
weight_x_memory_p = handler.template AcquireWeightXMemory<phi::bfloat16>(
&weight_x, origin_mode);
Expand Down
4 changes: 2 additions & 2 deletions paddle/phi/kernels/onednn/matmul_kernel.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -449,9 +449,9 @@ std::shared_ptr<MulPrimitiveFactory<XT, YT, OT>> GetPrimitiveFactory(
const DenseTensor *input_y,
const engine &onednn_engine) {
std::string key = funcs::CreateKey(dev_ctx,
phi::TransToProtoVarType(input_x->dtype()),
TransToProtoVarType(input_x->dtype()),
vectorize(input_x->dims()),
phi::TransToProtoVarType(input_y->dtype()),
TransToProtoVarType(input_y->dtype()),
vectorize(input_y->dims()),
dev_ctx.GetOutputsName("Out")[0]);
key = funcs::ExtendKeyWithThreadInfoIfNeeded(dev_ctx, key);
Expand Down
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