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remove some [-Wunused-parameter]warning and WITH_DISTRIBUTE flag #53532

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Merged
merged 2 commits into from
May 9, 2023
Merged

remove some [-Wunused-parameter]warning and WITH_DISTRIBUTE flag #53532

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c6559bd
test,test=develop
Galaxy1458 May 5, 2023
f06f0fd
test,test=develop
Galaxy1458 May 5, 2023
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11 changes: 6 additions & 5 deletions paddle/fluid/distributed/ps/table/common_graph_table.h
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Expand Up @@ -511,7 +511,7 @@ class GraphTable : public Table {
}
virtual ~GraphTable();

virtual void *GetShard(size_t shard_idx) { return 0; }
virtual void *GetShard(size_t shard_idx UNUSED) { return 0; }

static int32_t sparse_local_shard_num(uint32_t shard_num,
uint32_t server_num) {
Expand Down Expand Up @@ -624,15 +624,16 @@ class GraphTable : public Table {
Node *find_node(GraphTableType table_type, int idx, uint64_t id);
Node *find_node(GraphTableType table_type, uint64_t id);

virtual int32_t Pull(TableContext &context) { return 0; } // NOLINT
virtual int32_t Push(TableContext &context) { return 0; } // NOLINT
virtual int32_t Pull(TableContext &context UNUSED) { return 0; } // NOLINT
virtual int32_t Push(TableContext &context UNUSED) { return 0; } // NOLINT

virtual int32_t clear_nodes(GraphTableType table_type, int idx);
virtual void Clear() {}
virtual int32_t Flush() { return 0; }
virtual int32_t Shrink(const std::string &param) { return 0; }
virtual int32_t Shrink(const std::string &param UNUSED) { return 0; }
// 指定保存路径
virtual int32_t Save(const std::string &path, const std::string &converter) {
virtual int32_t Save(const std::string &path UNUSED,
const std::string &converter UNUSED) {
return 0;
}
virtual int32_t InitializeShard() { return 0; }
Expand Down
4 changes: 1 addition & 3 deletions paddle/fluid/framework/CMakeLists.txt
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Expand Up @@ -928,9 +928,7 @@ if(WITH_DISTRIBUTE)
fleet_executor)
endif()
elseif(WITH_PSLIB)
set(DISTRIBUTE_COMPILE_FLAGS
"-Wno-non-virtual-dtor -Wno-error=non-virtual-dtor -Wno-error=delete-non-virtual-dtor"
)
set(DISTRIBUTE_COMPILE_FLAGS "")
if(CMAKE_CXX_COMPILER_VERSION VERSION_GREATER 7.0)
set(DISTRIBUTE_COMPILE_FLAGS "${DISTRIBUTE_COMPILE_FLAGS} -faligned-new")
endif()
Expand Down
2 changes: 1 addition & 1 deletion paddle/phi/backends/onednn/onednn_reuse.h
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Expand Up @@ -1178,7 +1178,7 @@ class ReductionOneDNNHandler
const dnnl::engine engine,
Place cpu_place,
const DenseTensor* x,
const DenseTensor* out,
const DenseTensor* out UNUSED,
std::vector<int64_t> out_tz,
const dnnl::primitive_attr& attrs = NULL)
: OneDNNHandlerNoCachingT<T, dnnl::reduction>(engine, cpu_place) {
Expand Down
5 changes: 3 additions & 2 deletions paddle/phi/core/utils/unroll_array_ops.h
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Expand Up @@ -87,7 +87,8 @@ struct UnrollCompare {
template <size_t kStart, size_t kEnd>
struct UnrollCompare<kStart, kEnd, true> {
template <typename T>
HOSTDEVICE inline constexpr static bool Run(const T *d1, const T *d2) {
HOSTDEVICE inline constexpr static bool Run(const T *d1 UNUSED,
const T *d2 UNUSED) {
return true;
}
};
Expand All @@ -104,7 +105,7 @@ struct UnrollProduct {
template <size_t kStart, size_t kEnd>
struct UnrollProduct<kStart, kEnd, true> {
template <typename T>
HOSTDEVICE inline constexpr static T Run(const T *d) {
HOSTDEVICE inline constexpr static T Run(const T *d UNUSED) {
return 1;
}
};
Expand Down
2 changes: 1 addition & 1 deletion paddle/phi/kernels/complex_kernel.h
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Expand Up @@ -58,7 +58,7 @@ template <
std::enable_if_t<!std::is_same<T, phi::dtype::complex<float>>::value &&
!std::is_same<T, phi::dtype::complex<double>>::value,
bool> = true>
DenseTensor Conj(const Context& dev_ctx, const DenseTensor& x) {
DenseTensor Conj(const Context& dev_ctx UNUSED, const DenseTensor& x) {
return x;
}

Expand Down
2 changes: 1 addition & 1 deletion paddle/phi/kernels/cpu/cross_entropy_grad_kernel.cc
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Expand Up @@ -30,7 +30,7 @@ void CrossEntropyWithSoftmaxGradCPUKernel(const CPUContext& dev_ctx,
const DenseTensor& loss_grad,
bool soft_label,
bool use_softmax,
bool numeric_stable_mode,
bool numeric_stable_mode UNUSED,
int ignore_index,
int axis,
DenseTensor* logits_grad) {
Expand Down
6 changes: 3 additions & 3 deletions paddle/phi/kernels/cpu/full_kernel.cc
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Expand Up @@ -32,17 +32,17 @@ template <typename T, typename Context>
void FullKernel(const Context& dev_ctx,
const IntArray& shape,
const Scalar& val,
DataType dtype,
DataType dtype UNUSED,
DenseTensor* out) {
out->Resize(phi::make_ddim(shape.GetData()));
FullValue<T>(dev_ctx, out, val.to<T>());
}

template <typename T, typename Context>
void FullLikeKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& x UNUSED,
const Scalar& val,
DataType dtype,
DataType dtype UNUSED,
DenseTensor* out) {
auto value = val.to<double>();
using CommonType = typename std::common_type<
Expand Down
2 changes: 1 addition & 1 deletion paddle/phi/kernels/cpu/graph_send_recv_funcs.h
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Expand Up @@ -25,7 +25,7 @@ namespace phi {

template <typename T>
struct GraphSendRecvSumFunctor {
void operator()(const bool& first_flag,
void operator()(const bool& first_flag UNUSED,
const DenseTensor& src_slice,
DenseTensor* dst_slice) {
auto eigen_src = phi::EigenVector<T>::Flatten(src_slice);
Expand Down
2 changes: 1 addition & 1 deletion paddle/phi/kernels/full_kernel.cc
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Expand Up @@ -21,7 +21,7 @@ namespace phi {
template <typename T, typename Context>
void FullBatchSizeLikeKernel(const Context& dev_ctx,
const DenseTensor& x,
const std::vector<int>& shape,
const std::vector<int>& shape UNUSED,
const Scalar& val,
DataType dtype,
int x_batch_size_dim,
Expand Down
4 changes: 2 additions & 2 deletions paddle/phi/kernels/funcs/gather_scatter_functor.cc
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Expand Up @@ -181,11 +181,11 @@ void cpu_scatter_mul_kernel(phi::DenseTensor self,
}

template <typename tensor_t, typename index_t>
void cpu_scatter_input_grad_kernel(phi::DenseTensor self,
void cpu_scatter_input_grad_kernel(phi::DenseTensor self UNUSED,
int dim,
const phi::DenseTensor& index,
phi::DenseTensor output,
const phi::DeviceContext& ctx) {
const phi::DeviceContext& ctx UNUSED) {
auto* index_data = index.data<index_t>();
auto* output_data = output.data<tensor_t>();

Expand Down
2 changes: 1 addition & 1 deletion paddle/phi/kernels/funcs/math_function.cc
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Expand Up @@ -92,7 +92,7 @@ DEFINE_CPU_TRANS(6);

template <typename DeviceContext, typename T>
void TransposeNormal<DeviceContext, T>::operator()(
const DeviceContext& context,
const DeviceContext& context UNUSED,
const phi::DenseTensor& in,
phi::DenseTensor* out,
const std::vector<int>& axis) {
Expand Down
2 changes: 1 addition & 1 deletion paddle/phi/kernels/funcs/reduce_functor.h
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Expand Up @@ -41,7 +41,7 @@ struct FrobeniusNormGradFunctor {
DX* dx,
DY* dy,
const Dim& dim,
int size) {
int size UNUSED) {
dx->device(place) = y->broadcast(dim);
dx->device(place) = *dx + dx->constant(1e-12f);
dx->device(place) = (*x / *dx) * (dy->broadcast(dim));
Expand Down
4 changes: 2 additions & 2 deletions paddle/phi/kernels/funcs/segment_pooling.cc
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Expand Up @@ -31,7 +31,7 @@ class SegmentPoolFunctor<phi::CPUContext, T, IndexT> {
const DenseTensor& input,
const DenseTensor& segments,
DenseTensor* output,
DenseTensor* index,
DenseTensor* index UNUSED,
const std::string pooltype = "SUM") {
const IndexT* segment_ids = segments.data<IndexT>();
auto curent_id = segment_ids[0];
Expand Down Expand Up @@ -90,7 +90,7 @@ class SegmentPoolGradFunctor<phi::CPUContext, T, IndexT> {
const DenseTensor& out_grad,
const DenseTensor& segments,
DenseTensor* in_grad,
const paddle::optional<DenseTensor>& index,
const paddle::optional<DenseTensor>& index UNUSED,
const std::string pooltype = "SUM") {
const IndexT* segment_ids = segments.data<IndexT>();
auto& place = *dev_ctx.eigen_device();
Expand Down
2 changes: 1 addition & 1 deletion paddle/phi/kernels/funcs/unique_functor.h
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Expand Up @@ -190,7 +190,7 @@ static void UniqueFlattendTensor(const Context& context,
}

template <typename Context, typename ForwardIt, typename InT, typename IndexT>
static ForwardIt UniqueDimImpl(const Context& context,
static ForwardIt UniqueDimImpl(const Context& context UNUSED,
ForwardIt first,
ForwardIt last,
const std::vector<IndexT>& sorted_indices_vec,
Expand Down
2 changes: 1 addition & 1 deletion paddle/phi/kernels/impl/gumbel_softmax_kernel_impl.h
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Expand Up @@ -27,7 +27,7 @@ namespace phi {

template <typename Context, typename T, int64_t Rank>
struct ArgMaxFunctor {
void operator()(const Context& ctx,
void operator()(const Context& ctx UNUSED,
const DenseTensor& in,
DenseTensor* index_tensor,
const int64_t& axis) {
Expand Down
4 changes: 2 additions & 2 deletions paddle/phi/kernels/impl/lerp_grad_kernel_impl.h
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Expand Up @@ -21,8 +21,8 @@ namespace phi {

template <typename Context, typename T, size_t D>
static void LerpGradFunction(const Context& ctx,
const DenseTensor& x,
const DenseTensor& y,
const DenseTensor& x UNUSED,
const DenseTensor& y UNUSED,
const DenseTensor& weight,
const DenseTensor& out,
const DenseTensor& out_grad,
Expand Down
2 changes: 1 addition & 1 deletion paddle/phi/kernels/reverse_kernel.cc
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Expand Up @@ -23,7 +23,7 @@ namespace phi {
template <typename T, typename Context>
void ReverseArrayKernel(const Context& dev_ctx,
const TensorArray& x,
const IntArray& axis,
const IntArray& axis UNUSED,
TensorArray* out) {
PADDLE_ENFORCE_EQ(
x.size(),
Expand Down
2 changes: 1 addition & 1 deletion paddle/phi/kernels/sparse/cpu/full_kernel.cc
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Expand Up @@ -34,7 +34,7 @@ template <typename T, typename Context>
void FullLikeCooKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const Scalar& val,
DataType dtype,
DataType dtype UNUSED,
SparseCooTensor* out) {
phi::Copy<Context>(dev_ctx,
x.non_zero_indices(),
Expand Down
4 changes: 2 additions & 2 deletions paddle/phi/kernels/sparse/sparse_utils_kernel.h
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Expand Up @@ -144,14 +144,14 @@ DenseTensor CsrToDense(const Context& dev_ctx, const SparseCsrTensor& x) {
}

template <typename T, typename Context>
void ValuesCooKernel(const Context& dev_ctx,
void ValuesCooKernel(const Context& dev_ctx UNUSED,
const SparseCooTensor& x,
DenseTensor* out) {
*out = x.non_zero_elements();
}

template <typename T, typename Context>
void ValuesCsrKernel(const Context& dev_ctx,
void ValuesCsrKernel(const Context& dev_ctx UNUSED,
const SparseCsrTensor& x,
DenseTensor* out) {
*out = x.non_zero_elements();
Expand Down