@@ -32,10 +32,10 @@ torch::Tensor broadcast(torch::Tensor src, torch::Tensor other, int64_t dim) {
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return src;
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}
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- std::tuple<torch::Tensor, torch ::optional<torch::Tensor>>
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+ std::tuple<torch::Tensor, std ::optional<torch::Tensor>>
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scatter_fw (torch::Tensor src, torch::Tensor index, int64_t dim,
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- torch ::optional<torch::Tensor> optional_out,
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- torch ::optional<int64_t > dim_size, std::string reduce) {
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+ std ::optional<torch::Tensor> optional_out,
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+ std ::optional<int64_t > dim_size, std::string reduce) {
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if (src.device ().is_cuda ()) {
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#ifdef WITH_CUDA
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return scatter_cuda (src, index , dim, optional_out, dim_size, reduce);
@@ -55,8 +55,8 @@ class ScatterSum : public torch::autograd::Function<ScatterSum> {
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public:
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static variable_list forward (AutogradContext *ctx, Variable src,
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Variable index, int64_t dim,
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- torch ::optional<Variable> optional_out,
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- torch ::optional<int64_t > dim_size) {
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+ std ::optional<Variable> optional_out,
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+ std ::optional<int64_t > dim_size) {
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dim = dim < 0 ? src.dim () + dim : dim;
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ctx->saved_data [" dim" ] = dim;
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ctx->saved_data [" src_shape" ] = src.sizes ();
@@ -84,8 +84,8 @@ class ScatterMul : public torch::autograd::Function<ScatterMul> {
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public:
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static variable_list forward (AutogradContext *ctx, Variable src,
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Variable index, int64_t dim,
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- torch ::optional<Variable> optional_out,
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- torch ::optional<int64_t > dim_size) {
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+ std ::optional<Variable> optional_out,
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+ std ::optional<int64_t > dim_size) {
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dim = dim < 0 ? src.dim () + dim : dim;
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ctx->saved_data [" dim" ] = dim;
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ctx->saved_data [" src_shape" ] = src.sizes ();
@@ -116,8 +116,8 @@ class ScatterMean : public torch::autograd::Function<ScatterMean> {
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public:
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static variable_list forward (AutogradContext *ctx, Variable src,
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Variable index, int64_t dim,
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- torch ::optional<Variable> optional_out,
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- torch ::optional<int64_t > dim_size) {
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+ std ::optional<Variable> optional_out,
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+ std ::optional<int64_t > dim_size) {
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dim = dim < 0 ? src.dim () + dim : dim;
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ctx->saved_data [" dim" ] = dim;
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ctx->saved_data [" src_shape" ] = src.sizes ();
@@ -131,7 +131,7 @@ class ScatterMean : public torch::autograd::Function<ScatterMean> {
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auto ones = torch::ones (old_index.sizes (), src.options ());
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result = scatter_fw (ones, old_index,
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old_index.dim () <= dim ? old_index.dim () - 1 : dim,
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- torch ::nullopt, out.size (dim), " sum" );
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+ std ::nullopt, out.size (dim), " sum" );
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auto count = std::get<0 >(result);
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count.masked_fill_ (count < 1 , 1 );
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count = broadcast (count, out, dim);
@@ -164,8 +164,8 @@ class ScatterMin : public torch::autograd::Function<ScatterMin> {
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public:
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static variable_list forward (AutogradContext *ctx, Variable src,
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Variable index, int64_t dim,
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- torch ::optional<Variable> optional_out,
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- torch ::optional<int64_t > dim_size) {
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+ std ::optional<Variable> optional_out,
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+ std ::optional<int64_t > dim_size) {
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dim = dim < 0 ? src.dim () + dim : dim;
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ctx->saved_data [" dim" ] = dim;
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ctx->saved_data [" src_shape" ] = src.sizes ();
@@ -200,8 +200,8 @@ class ScatterMax : public torch::autograd::Function<ScatterMax> {
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public:
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static variable_list forward (AutogradContext *ctx, Variable src,
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Variable index, int64_t dim,
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- torch ::optional<Variable> optional_out,
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- torch ::optional<int64_t > dim_size) {
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+ std ::optional<Variable> optional_out,
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+ std ::optional<int64_t > dim_size) {
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dim = dim < 0 ? src.dim () + dim : dim;
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ctx->saved_data [" dim" ] = dim;
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ctx->saved_data [" src_shape" ] = src.sizes ();
@@ -234,37 +234,37 @@ class ScatterMax : public torch::autograd::Function<ScatterMax> {
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SCATTER_API torch::Tensor
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scatter_sum (torch::Tensor src, torch::Tensor index, int64_t dim,
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- torch ::optional<torch::Tensor> optional_out,
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- torch ::optional<int64_t > dim_size) {
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+ std ::optional<torch::Tensor> optional_out,
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+ std ::optional<int64_t > dim_size) {
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return ScatterSum::apply (src, index , dim, optional_out, dim_size)[0 ];
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}
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SCATTER_API torch::Tensor
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scatter_mul (torch::Tensor src, torch::Tensor index, int64_t dim,
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- torch ::optional<torch::Tensor> optional_out,
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- torch ::optional<int64_t > dim_size) {
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+ std ::optional<torch::Tensor> optional_out,
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+ std ::optional<int64_t > dim_size) {
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return ScatterMul::apply (src, index , dim, optional_out, dim_size)[0 ];
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}
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SCATTER_API torch::Tensor
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scatter_mean (torch::Tensor src, torch::Tensor index, int64_t dim,
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- torch ::optional<torch::Tensor> optional_out,
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- torch ::optional<int64_t > dim_size) {
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+ std ::optional<torch::Tensor> optional_out,
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+ std ::optional<int64_t > dim_size) {
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return ScatterMean::apply (src, index , dim, optional_out, dim_size)[0 ];
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}
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SCATTER_API std::tuple<torch::Tensor, torch::Tensor>
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scatter_min (torch::Tensor src, torch::Tensor index, int64_t dim,
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- torch ::optional<torch::Tensor> optional_out,
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- torch ::optional<int64_t > dim_size) {
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+ std ::optional<torch::Tensor> optional_out,
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+ std ::optional<int64_t > dim_size) {
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auto result = ScatterMin::apply (src, index , dim, optional_out, dim_size);
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return std::make_tuple (result[0 ], result[1 ]);
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}
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SCATTER_API std::tuple<torch::Tensor, torch::Tensor>
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scatter_max (torch::Tensor src, torch::Tensor index, int64_t dim,
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- torch ::optional<torch::Tensor> optional_out,
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- torch ::optional<int64_t > dim_size) {
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+ std ::optional<torch::Tensor> optional_out,
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+ std ::optional<int64_t > dim_size) {
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auto result = ScatterMax::apply (src, index , dim, optional_out, dim_size);
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return std::make_tuple (result[0 ], result[1 ]);
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}
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