support multiply inputs and outputs (#36851)

* initial tensor design & sign kernel demo

* add move constructor for meta & add lodtensor

* add dirs & sign xpu kernel

* add mean cpu&cuda kernel impl

* move sign & mean xpu & npu kernel

* add selected_rows basic impl

* refactor design, BaseTensor to DenseTensor, etc.

* add scale mkldnn kernel

* polish xpu & npu impl details

* fix mkldnn reuse compile failed

* change tensor operation lib name

* rename util filename

* add more comments

* change TensorImplInterface to TensorInterface

* add kernel key and factory

* remove MKLDNNTensorMeta, add MKLDNNDenseTensor

* change XXDeviceContext to XXContext

* add base kernel registrar utils & test on sign

* replace boost::any by paddle::any

* fix several ci failed

* fix npu compile error

* add ordered map util

* fix multiple ordered_map compile errors

* move dev into include dir

* support sign op in static op run

* fix static op run error

* fix new executor compile failed

* add dygraph branch & remove sign_op.h

* fix test_infer_no_need_buffer_slots

* fix rocm compile link error

* fix unitybuild error & clear glog

* fix npu compile failed

* skip quant trans test

* fix part windows compile problem

* fix xpu enforce error

* fix inference test failed

* remove ordered_map to solve quant failed

* fix part of rcom compile faild

* add more register kernels

* revert scale kernel temporarily

* fix code format error

* add new kernel registrar marco

* rename top to tcmpt

* revert xpu, npu, mkldnn impl & remove op def

* add kernel args parse functor to auto parse args

* revert some change & add scale kernels

* add op proto in dygraph kernelcontext building

* polish kernel dispatch logic & nameing rule

* fix scale kernel match error

* fix scale test failed

* add mean API and unittest

* test mean api success

* add branch to solve compiled error

* skip clang format error

* add mean skip rule in op_library

* add dot kernel, api and unittest (#6)

* remove old kernel and add symbol link

* fix dot compiled failed

* add merco for module declare

* fix npu and xpu compile error

* revert sign, mean, scale, dot kernel removing

* add comment for keeping old kernel impl

* fix mutable_data error

* fix bfloat16 conflit

* fix inference undef error

* adapt to msvc compile rules

* polish comment for template inst

* add cmake template instantiation for win

* fix backend to place device id bug

* fix ifdef error

* Op2functor (#7)

* add kernel args maker class

* make args maker non-const

* remove debug log

* modify codes by review options

* split constructPrKernelContext function

* fix output name bug

* fix test_mean_op test_sign_op failed

* fill_any_like kernel refactor (#10)

* fill_any_like kernel refactor

* remove useless code of full_like c++ api

* skip dtype for fill_any_like

* add attrs for kernel key constrcut

* add use_pt_kernel Flags to control whether to use pt kernel (#13)

* add use_pt_kernel Flags to control whether to use pt kernel

* change the default value to true for cheking pt kernels

* fix mutable_data cuda place error

* move high level apis into hapi

* remove selectedrows adapting temporarily

* Support Scalar in Tensor Compute Library (#14)

* fill_any_like kernel refactor

* remove useless code of full_like c++ api

* Support Scalar in Tensor Compute Library

* add scalar in dygraph and static graph mode

* keep the basic type for attr, instead of using scalar for all

* merge the code

* remove mkldnn tensor & polish details

* use flat_hash_map and small_vector in kernel factory

* Refactor flatten kernel (#12)

* refactor flatten kernel

* update infershape function

* fix compile bugs

* fix bugs when merge

* fix compiler bugs

* fix bugs when run test_flatten_api

* fix bugs when run test

* Revert "use flat_hash_map and small_vector in kernel factory"

This reverts commit 23091495cfdd3df8cc1be592d30f09ea66a7c72b.

* Move cpu, cuda and other device code into kernels (#15)

* fill_any_like kernel refactor

* remove useless code of full_like c++ api

* Support Scalar in Tensor Compute Library

* add scalar in dygraph and static graph mode

* keep the basic type for attr, instead of using scalar for all

* merge the code

* start refactor matmul

* move cpu, cuda and other device modules into kernels

* merge code

* polish code in operator.cc

* Perfect unitests (#16)

* perfect unittest

* update license

* replace with flat_hash_map, small_vector (#19)

* fix small_vector build error on windows platform

* replace with flat_hash_map, small_vector

* remove todo

* Perfect unitests (#20)

* perfect unittest

* update license

* fix bug when run tcmpt_utils_test

* refactor execution adapting impl

* fix insert conflit

* Fix CI bug of test_yolov3 (#21)

* fill_any_like kernel refactor

* remove useless code of full_like c++ api

* Support Scalar in Tensor Compute Library

* add scalar in dygraph and static graph mode

* keep the basic type for attr, instead of using scalar for all

* merge the code

* start refactor matmul

* move cpu, cuda and other device modules into kernels

* merge code

* polish code in operator.cc

* Fix CI bug of test_yolov3

* add the tensor base class, test=develop (#17)

* update the tensor base class, test=develop

* remove two funcs, test=develop

* update the error msg, test=develop
Co-authored-by: NChen Weihang <chenweihang@baidu.com>

* [no-verify] commit backend and tensor signature changes

* Rename tcmpt to pten (#23)

* rename tcmpt to pten

* update omitted files for rename to pten

* update omitted file for rename to pten

* remove k of all enum var

* remove kernel_instantiate (#26)

* remove symbols and spatial_tensor

* change common to functions

* readd share tensor impl methods

* add a candidate dense tensor class, test=develop (#28)

* change all Pt to Pten

* resolve conflit with xiaowei

* Op2functor opt1 (#27)

* replace to small vector and change to const &

* add std::move
Co-authored-by: NChen Weihang <chenweihang@baidu.com>

* polish kernel factory and kernel registry

* fix operator test error msg mismatch

* remove tensor signature and backend set member

* move scalar and polish enforce

* revert dtype layout change to fix error

* fix enum operator override error

* add several base unittests

* add pten utils tests

* polish some details

* Dev/op2func refactor 3 (#30)

* add a candidate dense tensor class, test=develop

* remove TensorBase::backend(), test=develop

* remove some ops, test=develop

* cherry-pick the pr of tensor meta, test=develop

* moves the dense tensor and some ops, test=develop

* update the linalg operator, test=develop

* update other operators, test=develop

* fix errors, test=develop

* fix bugs, test=develop

* try to resolve the problem of windows ci, test=develop

* updates codes, test=develop

* fix the tensor_utils.cc, test=develop

* modify the dense tensor, test=develop

* fix the data type, test=develop
Co-authored-by: Nshixiaowei02 <39303645+Shixiaowei02@users.noreply.github.com>

* polish some details

* polish kernel signature details

* fix a bug about offsets of the tensor, test=develop (#31)
Co-authored-by: Nshixiaowei02 <39303645+Shixiaowei02@users.noreply.github.com>

* support multiply inputs and outputs

* rm attrs {}

* fix multioutputs bug

* merge develop

* remove unsed header file

* add missing & in const reference

* modify inputAt, outputAt to inputBetween, outputBetween
Co-authored-by: NChen Weihang <chenweihang@baidu.com>
Co-authored-by: Nzyfncg <1370305206@qq.com>
Co-authored-by: NYuanRisheng <yuanrisheng@baidu.com>
Co-authored-by: N石晓伟 <39303645+Shixiaowei02@users.noreply.github.com>

paddle/pten/core/kernel_context.h

@@ -52,37 +52,37 @@ class KernelContext {
   }
 
   void EmplaceBackInput(std::shared_ptr<TensorBase> input) {
+    int index = inputs_.size();
     inputs_.emplace_back(std::move(input));
     // Record the start and end index of the input
-    int index = inputs_.size();
     input_range_.emplace_back(std::pair<int, int>(index, index + 1));
   }
 
   void EmplaceBackInputs(
-      paddle::SmallVector<std::shared_ptr<TensorBase>> inputs) {
+      const paddle::SmallVector<std::shared_ptr<TensorBase>>& inputs) {
+    int index = inputs_.size();
     for (auto in : inputs) {
-      inputs_.emplace_back(in);
+      inputs_.emplace_back(std::move(in));
     }
     // Record the start and end index of the input
-    int index = inputs_.size();
     input_range_.emplace_back(
         std::pair<int, int>(index, index + inputs.size()));
   }
 
   void EmplaceBackOutput(std::shared_ptr<TensorBase> output) {
+    int index = outputs_.size();
     outputs_.emplace_back(std::move(output));
     // Record the start and end index of the input
-    int index = outputs_.size();
     output_range_.emplace_back(std::pair<int, int>(index, index + 1));
   }
 
   void EmplaceBackOutputs(
-      paddle::SmallVector<std::shared_ptr<TensorBase>> outputs) {
+      const paddle::SmallVector<std::shared_ptr<TensorBase>>& outputs) {
+    int index = outputs_.size();
     for (auto out : outputs) {
-      outputs_.emplace_back(out);
+      outputs_.emplace_back(std::move(out));
     }
     // Record the start and end index of the input
-    int index = outputs_.size();
     output_range_.emplace_back(
         std::pair<int, int>(index, index + outputs.size()));
   }
@@ -96,11 +96,40 @@ class KernelContext {
     return static_cast<const TensorType&>(*(inputs_.at(idx)));
   }
 
+  template <typename TensorType>
+  std::vector<TensorType> InputBetween(size_t start, size_t end) const {
+    std::vector<TensorType> v;
+    for (size_t i = start; i < end; ++i) {
+      auto t = std::dynamic_pointer_cast<TensorType>(inputs_.at(i));
+      v.emplace_back(std::move(*t.get()));
+    }
+
+    return v;
+  }
+
+  const std::pair<int, int>& InputRangeAt(size_t idx) const {
+    return input_range_.at(idx);
+  }
+
+  const std::pair<int, int>& OutputRangeAt(size_t idx) const {
+    return output_range_.at(idx);
+  }
+
   template <typename TensorType>
   TensorType* MutableOutputAt(size_t idx) {
     return static_cast<TensorType*>(outputs_.at(idx).get());
   }
 
+  template <typename TensorType>
+  std::vector<TensorType*> MutableOutputBetween(size_t start, size_t end) {
+    std::vector<TensorType*> v;
+    for (size_t i = start; i < end; ++i) {
+      v.emplace_back(static_cast<TensorType*>(outputs_.at(i).get()));
+    }
+
+    return v;
+  }
+
   template <typename AttrType>
   AttrType AttrAt(size_t idx) const {
     try {

paddle/pten/core/kernel_registry.h

@@ -62,9 +62,17 @@ struct KernelArgsParseFunctor<Return_ (*)(Args_...)> {
       } else if (arg_type == std::type_index(typeid(const DenseTensor&))) {
         args_def->AppendInput(
             default_key.backend(), default_tensor_layout, default_key.dtype());
+      } else if (arg_type ==
+                 std::type_index(typeid(const std::vector<DenseTensor>&))) {
+        args_def->AppendInput(
+            default_key.backend(), default_tensor_layout, default_key.dtype());
       } else if (arg_type == std::type_index(typeid(DenseTensor*))) {
         args_def->AppendOutput(
             default_key.backend(), default_tensor_layout, default_key.dtype());
+      } else if (arg_type ==
+                 std::type_index(typeid(std::vector<DenseTensor*>))) {
+        args_def->AppendOutput(
+            default_key.backend(), default_tensor_layout, default_key.dtype());
       } else {
         // Attribute deal with
         // TODO(chenweihang): now here allow any types of attribute, maybe

paddle/pten/core/kernel_utils.h

@@ -79,7 +79,30 @@ using XPUContext = paddle::platform::XPUDeviceContext;
                     "Kernel's Input should appear before Attributes."); \
       static_assert(out_idx == 0,                                       \
                     "Kernel's Input should appear before Outputs.");    \
-      const tensor_type& arg = ctx->InputAt<tensor_type>(in_idx);       \
+      const std::pair<int, int> range = ctx->InputRangeAt(in_idx);      \
+      const tensor_type& arg = ctx->InputAt<tensor_type>(range.first);  \
+      KernelCallHelper<Tail...>::                                       \
+          template Compute<dev_ctx_idx, in_idx + 1, attr_idx, out_idx>( \
+              ctx, pargs..., arg);                                      \
+    }                                                                   \
+  }
+
+#define PT_SPECIALIZE_KernelCallHelper_FOR_MULTI_INPUT(tensor_type)     \
+  template <typename... Tail>                                           \
+  struct KernelCallHelper<const std::vector<tensor_type>&, Tail...> {   \
+    template <int dev_ctx_idx,                                          \
+              int in_idx,                                               \
+              int attr_idx,                                             \
+              int out_idx,                                              \
+              typename... PreviousArgs>                                 \
+    static void Compute(KernelContext* ctx, PreviousArgs&... pargs) {   \
+      static_assert(attr_idx == 0,                                      \
+                    "Kernel's Input should appear before Attributes."); \
+      static_assert(out_idx == 0,                                       \
+                    "Kernel's Input should appear before Outputs.");    \
+      const std::pair<int, int> range = ctx->InputRangeAt(in_idx);      \
+      std::vector<tensor_type> arg = std::move(                         \
+          ctx->InputBetween<tensor_type>(range.first, range.second));   \
       KernelCallHelper<Tail...>::                                       \
           template Compute<dev_ctx_idx, in_idx + 1, attr_idx, out_idx>( \
               ctx, pargs..., arg);                                      \
@@ -104,20 +127,39 @@ using XPUContext = paddle::platform::XPUDeviceContext;
     }                                                                     \
   }
 
-#define PT_SPECIALIZE_KernelCallHelper_FOR_OUTPUT(tensor_type)          \
-  template <typename... Tail>                                           \
-  struct KernelCallHelper<tensor_type*, Tail...> {                      \
-    template <int dev_ctx_idx,                                          \
-              int in_idx,                                               \
-              int attr_idx,                                             \
-              int out_idx,                                              \
-              typename... PreviousArgs>                                 \
-    static void Compute(KernelContext* ctx, PreviousArgs&... pargs) {   \
-      tensor_type* arg = ctx->MutableOutputAt<tensor_type>(out_idx);    \
-      KernelCallHelper<Tail...>::                                       \
-          template Compute<dev_ctx_idx, in_idx, attr_idx, out_idx + 1>( \
-              ctx, pargs..., arg);                                      \
-    }                                                                   \
+#define PT_SPECIALIZE_KernelCallHelper_FOR_OUTPUT(tensor_type)           \
+  template <typename... Tail>                                            \
+  struct KernelCallHelper<tensor_type*, Tail...> {                       \
+    template <int dev_ctx_idx,                                           \
+              int in_idx,                                                \
+              int attr_idx,                                              \
+              int out_idx,                                               \
+              typename... PreviousArgs>                                  \
+    static void Compute(KernelContext* ctx, PreviousArgs&... pargs) {    \
+      const std::pair<int, int> range = ctx->OutputRangeAt(out_idx);     \
+      tensor_type* arg = ctx->MutableOutputAt<tensor_type>(range.first); \
+      KernelCallHelper<Tail...>::                                        \
+          template Compute<dev_ctx_idx, in_idx, attr_idx, out_idx + 1>(  \
+              ctx, pargs..., arg);                                       \
+    }                                                                    \
+  }
+
+#define PT_SPECIALIZE_KernelCallHelper_FOR_MULTI_OUTPUT(tensor_type)          \
+  template <typename... Tail>                                                 \
+  struct KernelCallHelper<std::vector<tensor_type*>, Tail...> {               \
+    template <int dev_ctx_idx,                                                \
+              int in_idx,                                                     \
+              int attr_idx,                                                   \
+              int out_idx,                                                    \
+              typename... PreviousArgs>                                       \
+    static void Compute(KernelContext* ctx, PreviousArgs&... pargs) {         \
+      const std::pair<int, int> range = ctx->OutputRangeAt(out_idx);          \
+      std::vector<tensor_type*> arg = std::move(                              \
+          ctx->MutableOutputBetween<tensor_type>(range.first, range.second)); \
+      KernelCallHelper<Tail...>::                                             \
+          template Compute<dev_ctx_idx, in_idx, attr_idx, out_idx + 1>(       \
+              ctx, pargs..., arg);                                            \
+    }                                                                         \
   }
 
 template <typename T>
@@ -152,6 +194,7 @@ struct KernelImpl<Return (*)(Args...), kernel_fn> {
   /* Input Helpers */
 
   PT_SPECIALIZE_KernelCallHelper_FOR_INPUT(DenseTensor);
+  PT_SPECIALIZE_KernelCallHelper_FOR_MULTI_INPUT(DenseTensor);
   // TODO(chenweihang): adapt SelectedRows
   // PT_SPECIALIZE_KernelCallHelper_FOR_INPUT(SelectedRowsTensor);
 
@@ -168,6 +211,7 @@ struct KernelImpl<Return (*)(Args...), kernel_fn> {
   /* Output Helpers */
 
   PT_SPECIALIZE_KernelCallHelper_FOR_OUTPUT(DenseTensor);
+  PT_SPECIALIZE_KernelCallHelper_FOR_MULTI_OUTPUT(DenseTensor);
   // TODO(chenweihang): adapt SelectedRows
   // PT_SPECIALIZE_KernelCallHelper_FOR_OUTPUT(SelectedRowsTensor);
 

paddle/pten/hapi/lib/kernel_dispatch.h

@@ -122,6 +122,14 @@ struct KernelKeyParser : ArgsIterator<KernelKeyParser> {
     key_set.dtype = x.type();
   }
 
+  void operator()(const std::vector<Tensor>& x) {
+    key_set.backend_set =
+        key_set.backend_set | detail::GetTensorBackendSet(x[0]);
+    // TODO(chenweihang): selecte multi layout and dtype
+    key_set.layout = x[0].layout();
+    key_set.dtype = x[0].type();
+  }
+
   // skip other type args, these args don't used in kernel selection
   template <typename T>
   void operator()(const T& x) {