[CustomOP Optional Inplace] Custom operator supports inplace optional…

… vector Tensor input (#52421) * [CustomOP Optional Inplace] Custom operator supports inplace optional vector Tensor input * uncomment unittest codes
PaddlePaddle · Apr 3, 2023 · 59c9d75 · 59c9d75
1 parent 0b60f28
commit 59c9d75
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Showing 6 changed files with 493 additions and 75 deletions.
diff --git a/paddle/fluid/framework/custom_operator.cc b/paddle/fluid/framework/custom_operator.cc
@@ -833,7 +833,11 @@ static void RunInferDtypeFunc(
       auto in_name = inplace_reverse_map.at(out_name);
       // make sure ctx has valid inplace optional outputs
       if (ctx->HasOutput(out_name)) {
-        ctx->SetOutputDataTypes(out_name, ctx->GetInputDataTypes(in_name));
+        size_t size = ctx->InputSize(in_name);
+        for (size_t i = 0; i < size; ++i) {
+          auto dtype = ctx->GetInputDataType(in_name, i);
+          ctx->SetOutputDataType(out_name, dtype, i);
+        }
       } else {
         PADDLE_ENFORCE(
             detail::IsOptionalVar(out_name),

diff --git a/paddle/phi/api/ext/op_meta_info.h b/paddle/phi/api/ext/op_meta_info.h
@@ -120,6 +120,8 @@ class PADDLE_API CustomOpKernelContext {
   std::vector<Tensor> InputsBetween(size_t start, size_t end) const;
   Tensor& MutableInputAt(size_t idx);
   paddle::optional<Tensor> OptionalInputAt(size_t idx);
+  paddle::optional<std::vector<Tensor>> OptionalInputsBetween(size_t start,
+                                                              size_t end);
   const std::vector<paddle::any>& Attrs() const { return attrs_; }
   const std::vector<std::pair<size_t, size_t>>& InputRange() {
     return input_range_;
@@ -294,6 +296,34 @@ struct KernelFuncImpl<Return (*)(Args...), impl_fn> {
     }
   };
 
+  // Handle args for inplace vector<Tensor> case
+  template <typename... Tail>
+  struct ComputeCallHelper<std::vector<Tensor>&, Tail...> {
+    template <int in_idx, int attr_idx, int out_idx, typename... PreviousArgs>
+    static void Compute(CustomOpKernelContext* ctx, PreviousArgs&... pargs) {
+      auto& range = ctx->InputRangeAt(in_idx);
+      auto arg = ctx->InputsBetween(range.first, range.second);
+      ComputeCallHelper<
+          Tail...>::template Compute<in_idx + 1, attr_idx, out_idx>(ctx,
+                                                                    pargs...,
+                                                                    arg);
+    }
+  };
+
+  // Handle args for optional inplace vector<Tensor> case
+  template <typename... Tail>
+  struct ComputeCallHelper<paddle::optional<std::vector<Tensor>>&, Tail...> {
+    template <int in_idx, int attr_idx, int out_idx, typename... PreviousArgs>
+    static void Compute(CustomOpKernelContext* ctx, PreviousArgs&... pargs) {
+      auto& range = ctx->InputRangeAt(in_idx);
+      auto arg = ctx->OptionalInputsBetween(range.first, range.second);
+      ComputeCallHelper<
+          Tail...>::template Compute<in_idx + 1, attr_idx, out_idx>(ctx,
+                                                                    pargs...,
+                                                                    arg);
+    }
+  };
+
   PD_SPECIALIZE_ComputeCallHelper(bool);
   PD_SPECIALIZE_ComputeCallHelper(int);
   PD_SPECIALIZE_ComputeCallHelper(float);
@@ -358,20 +388,6 @@ struct KernelFuncImpl<Return (*)(Args...), impl_fn> {
     }
   };
 
-  // Handle args for inplace vector<Tensor> case
-  template <typename... Tail>
-  struct ComputeCallHelper<std::vector<Tensor>&, Tail...> {
-    template <int in_idx, int attr_idx, int out_idx, typename... PreviousArgs>
-    static void Compute(CustomOpKernelContext* ctx, PreviousArgs&... pargs) {
-      auto& range = ctx->InputRangeAt(in_idx);
-      auto arg = ctx->InputsBetween(range.first, range.second);
-      ComputeCallHelper<
-          Tail...>::template Compute<in_idx + 1, attr_idx, out_idx>(ctx,
-                                                                    pargs...,
-                                                                    arg);
-    }
-  };
-
   template <int out_idx, typename T>
   struct ComputeReturnHelper;
 

diff --git a/paddle/phi/api/lib/op_meta_info.cc b/paddle/phi/api/lib/op_meta_info.cc
@@ -110,6 +110,18 @@ paddle::optional<Tensor> CustomOpKernelContext::OptionalInputAt(size_t idx) {
   return paddle::make_optional<paddle::Tensor>(inputs_.at(idx));
 }
 
+paddle::optional<std::vector<Tensor>>
+CustomOpKernelContext::OptionalInputsBetween(size_t start, size_t end) {
+  std::vector<Tensor> rlt;
+  for (size_t i = start; i < end; ++i) {
+    if (!inputs_.at(i).is_initialized()) {
+      return paddle::none;
+    }
+    rlt.emplace_back(inputs_.at(i));
+  }
+  return paddle::make_optional<std::vector<Tensor>>(rlt);
+}
+
 Tensor* CustomOpKernelContext::MutableOutputAt(size_t idx) {
   return &(outputs_.at(idx));
 }

diff --git a/python/paddle/utils/cpp_extension/extension_utils.py b/python/paddle/utils/cpp_extension/extension_utils.py
@@ -1057,6 +1057,22 @@ def _gen_output_content(
         if out_idx in inplace_reverse_idx:
             in_idx = inplace_reverse_idx[out_idx]
         if (
+            in_idx != -1
+            and "@VECTOR" in in_names[in_idx]
+            and "@OPTIONAL" in in_names[in_idx]
+        ):
+            # inplace optional vector<Tensor> output case
+            lower_in_names = in_names[in_idx].split("@")[0].lower()
+            dynamic_content += f"""
+{indent}if {lower_in_names} is not None:
+{indent}    outs['{out_name}'] = [core.eager.Tensor() for _ in range(len({lower_in_names}))]
+{indent}else:
+{indent}    outs['{out_name}'] = core.eager.Tensor()
+{indent}ctx.add_outputs(outs['{out_name}'])"""
+            static_content += f"""
+{indent}if {lower_in_names} is not None:
+{indent}    outs['{out_name}'] = [helper.create_variable(dtype='float32') for _ in range(len({lower_in_names}))]"""
+        elif (
             in_idx != -1 and "@VECTOR" in in_names[in_idx]
         ):  # inplace vector<Tensor> output case
             lower_in_names = in_names[in_idx].split("@")[0].lower()

diff --git a/test/custom_op/custom_optional.cc b/test/custom_op/custom_optional.cc
@@ -300,3 +300,116 @@ PD_BUILD_GRAD_OP(custom_optional_inplace_add)
                      paddle::Grad(paddle::Optional("Y"))}})
     .SetKernelFn(PD_KERNEL(AddOptionalInplaceBackward))
     .SetInferShapeFn(PD_INFER_SHAPE(AddOptionalInplaceBackwardInferShape));
+
+/*
+if (y) {
+  outX = 2 * x + y[1...n];
+  outY[i] = x + y[i];
+} else {
+  outX = 2 * x;
+  outY = None;
+}
+*/
+std::vector<paddle::Tensor> AddOptionalInplaceVectorForward(
+    const paddle::Tensor& x,
+    paddle::optional<std::vector<paddle::Tensor>>& y) {  // NOLINT
+  PD_CHECK(x.place() == paddle::PlaceType::kCPU, "x must be a CPU Tensor.");
+  paddle::Tensor outX = paddle::zeros(x.shape(), x.dtype(), x.place());
+
+  PD_DISPATCH_FLOATING_TYPES(
+      x.type(), "AddOptionalInplaceVectorForward", ([&] {
+        add_two_pointers<data_t>(
+            x.data<data_t>(), x.data<data_t>(), outX.data<data_t>(), x.size());
+        if (y) {
+          for (size_t i = 0; i < y->size(); ++i) {
+            add_one_pointer<data_t>(
+                y->at(i).data<data_t>(), outX.data<data_t>(), outX.size());
+            add_one_pointer<data_t>(
+                x.data<data_t>(), y->at(i).data<data_t>(), x.size());
+          }
+        }
+      }));
+  // No need to return y, because we set it as inplace input.
+  return {outX};
+}
+
+std::vector<paddle::DataType> AddOptionalInplaceVectorInferDtype(
+    const paddle::DataType& x_dtype,
+    const paddle::optional<std::vector<paddle::DataType>>& y_dtype) {
+  return {x_dtype};
+}
+
+std::vector<std::vector<int64_t>> AddOptionalInplaceVectorInferShape(
+    const std::vector<int64_t>& x_shape,
+    const paddle::optional<std::vector<std::vector<int64_t>>>& y_shape) {
+  return {x_shape};
+}
+
+/*
+if (outy_grad) {
+  x_grad = outX_grad * 2 + outY_grad[1...n];
+  y_grad[i] = outX_grad + outY_grad[i];
+} else {
+  x_grad = outX_grad * 2;
+  y_grad = None;
+}
+*/
+std::vector<paddle::Tensor> AddOptionalInplaceVectorBackward(
+    const paddle::Tensor& x,
+    const paddle::optional<std::vector<paddle::Tensor>>& y,
+    const paddle::Tensor& outx_grad,
+    paddle::optional<std::vector<paddle::Tensor>>& outy_grad) {  // NOLINT
+  PD_CHECK(x.place() == paddle::PlaceType::kCPU, "x must be a CPU Tensor.");
+
+  paddle::Tensor x_grad = paddle::zeros(x.shape(), x.dtype(), x.place());
+
+  PD_DISPATCH_FLOATING_TYPES(
+      outx_grad.type(), "AddOptionalInplaceVectorBackward", ([&] {
+        add_two_pointers<data_t>(outx_grad.data<data_t>(),
+                                 outx_grad.data<data_t>(),
+                                 x_grad.data<data_t>(),
+                                 x_grad.size());
+        if (outy_grad) {
+          for (size_t i = 0; i < outy_grad->size(); ++i) {
+            add_one_pointer<data_t>(outy_grad->at(i).data<data_t>(),
+                                    x_grad.data<data_t>(),
+                                    x_grad.size());
+            add_one_pointer<data_t>(outx_grad.data<data_t>(),
+                                    outy_grad->at(i).data<data_t>(),
+                                    outx_grad.size());
+          }
+        }
+      }));
+
+  return {x_grad};
+}
+
+std::vector<std::vector<int64_t>> AddOptionalInplaceVectorBackwardInferShape(
+    const std::vector<int64_t>& x_shape,
+    const paddle::optional<std::vector<std::vector<int64_t>>>& y_shape,
+    const std::vector<int64_t>& x_grad_shape,
+    const paddle::optional<std::vector<std::vector<int64_t>>>& y_grad_shape) {
+  return {x_shape};
+}
+
+PD_BUILD_OP(custom_optional_inplace_add_vec)
+    .Inputs({"X", paddle::Optional(paddle::Vec("Y"))})
+    .Outputs({"OutX", paddle::Optional(paddle::Vec("OutY"))})
+    .SetInplaceMap({{paddle::Optional(paddle::Vec("Y")),
+                     paddle::Optional(paddle::Vec("OutY"))}})
+    .SetKernelFn(PD_KERNEL(AddOptionalInplaceVectorForward))
+    .SetInferShapeFn(PD_INFER_SHAPE(AddOptionalInplaceVectorInferShape))
+    .SetInferDtypeFn(PD_INFER_DTYPE(AddOptionalInplaceVectorInferDtype));
+
+PD_BUILD_GRAD_OP(custom_optional_inplace_add_vec)
+    .Inputs({"X",
+             paddle::Optional(paddle::Vec("Y")),
+             paddle::Grad("OutX"),
+             paddle::Grad(paddle::Optional(paddle::Vec("OutY")))})
+    .Outputs({paddle::Grad("X"),
+              paddle::Grad(paddle::Optional(paddle::Vec("Y")))})
+    .SetInplaceMap({{paddle::Grad(paddle::Optional(paddle::Vec("OutY"))),
+                     paddle::Grad(paddle::Optional(paddle::Vec("Y")))}})
+    .SetKernelFn(PD_KERNEL(AddOptionalInplaceVectorBackward))
+    .SetInferShapeFn(
+        PD_INFER_SHAPE(AddOptionalInplaceVectorBackwardInferShape));