From 17b8335bbbb1f0c420b0da6a776d9c9aae872381 Mon Sep 17 00:00:00 2001
From: jiangcheng <thisjiang@qq.com>
Date: Wed, 23 Mar 2022 11:03:22 +0800
Subject: [PATCH] fix cinn graph may hasn't input problem (#40814)

---
 .../operators/cinn/cinn_instruction_run_op.cc | 51 ++++++++++++++++++-
 paddle/fluid/operators/cinn/cinn_launch_op.cc |  9 ++--
 2 files changed, 56 insertions(+), 4 deletions(-)

diff --git a/paddle/fluid/operators/cinn/cinn_instruction_run_op.cc b/paddle/fluid/operators/cinn/cinn_instruction_run_op.cc
index edf854a9c95..8139530b809 100644
--- a/paddle/fluid/operators/cinn/cinn_instruction_run_op.cc
+++ b/paddle/fluid/operators/cinn/cinn_instruction_run_op.cc
@@ -24,7 +24,9 @@ class CinnInstructionRunOp : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
   void InferShape(framework::InferShapeContext* ctx) const override {
-    OP_INOUT_CHECK(ctx->HasInputs(kX), "Input", kX, "CinnInstructionRun");
+    // The cinn-graph may hasn't input for CINN now support fill_constant,
+    // and its all inputs may generated by fill_constant instead of by fetch.
+    // OP_INOUT_CHECK(ctx->HasInputs(kX), "Input", kX, "CinnInstructionRun");
     OP_INOUT_CHECK(ctx->HasOutputs(kOutputs), "Output", kOutputs,
                    "CinnInstructionRun");
     const CinnCompiledObject& compiled_object =
@@ -43,6 +45,53 @@ class CinnInstructionRunOp : public framework::OperatorWithKernel {
                    });
     ctx->SetOutputsDim(kOutputs, output_dims);
   }
+
+ protected:
+  framework::OpKernelType GetExpectedKernelType(
+      const framework::ExecutionContext& ctx) const override {
+    // Why we need override GetExpectedKernelType?
+    // A cinn-graph may has no inpute var, if we use the base function,
+    // it will check wheter input tensors is initialized. Here we rewrite
+    // the function so that we can infer kernel type by output date type.
+    if (ctx.InputSize(kX)) {
+      // if the instruction has input, infer kernel type by input date type:
+      return OperatorWithKernel::GetExpectedKernelType(ctx);
+    }
+
+    // Else infer kernel type by output date type:
+    // The `OutputVar` will check wheter the kOutputs iff has one output var
+    const framework::Variable* var = ctx.OutputVar(kOutputs);
+    PADDLE_ENFORCE_NE(
+        var, nullptr,
+        platform::errors::InvalidArgument(
+            "The cinn_instruction_run Op's Output Variable should not empty."));
+
+    const framework::Tensor* tensor = nullptr;
+    if (var->IsType<framework::Tensor>()) {
+      tensor = &var->Get<framework::Tensor>();
+    } else if (var->IsType<framework::LoDTensor>()) {
+      tensor = &var->Get<framework::LoDTensor>();
+    } else if (var->IsType<phi::SelectedRows>()) {
+      tensor = &(var->Get<phi::SelectedRows>().value());
+    } else if (var->IsType<framework::LoDTensorArray>()) {
+      auto t_arr = &var->Get<framework::LoDTensorArray>();
+      PADDLE_ENFORCE_EQ(t_arr->size(), 1UL,
+                        platform::errors::InvalidArgument(
+                            "The cinn_instruction_run Op should just has One "
+                            "Output when Input empty."));
+      tensor = &(t_arr->front());
+    }
+
+    PADDLE_ENFORCE_NE(
+        tensor, nullptr,
+        platform::errors::InvalidArgument(
+            "The cinn_instruction_run Op's Output Tensor should not empty."));
+
+    VLOG(4) << "The tensor [" << ctx.OutputName(kOutputs) << "]'s dtype is "
+            << paddle::framework::DataType2String(tensor->dtype());
+    auto output_type = paddle::framework::TransToProtoVarType(tensor->dtype());
+    return framework::OpKernelType(output_type, ctx.device_context());
+  }
 };
 
 class CinnInstructionRunOpMaker : public framework::OpProtoAndCheckerMaker {
diff --git a/paddle/fluid/operators/cinn/cinn_launch_op.cc b/paddle/fluid/operators/cinn/cinn_launch_op.cc
index d918b7216c4..5d006a947be 100644
--- a/paddle/fluid/operators/cinn/cinn_launch_op.cc
+++ b/paddle/fluid/operators/cinn/cinn_launch_op.cc
@@ -87,9 +87,12 @@ class CinnLaunchOp : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
   void InferShape(framework::InferShapeContext* ctx) const override {
-    OP_INOUT_CHECK(ctx->HasInputs(kX) || ctx->HasInputs(kNoNeedBufferX),
-                   "Input", string::format_string("%s|%s", kX, kNoNeedBufferX),
-                   "CinnLaunchOp");
+    // The cinn-graph may hasn't input for CINN now support fill_constant,
+    // and its all inputs may generated by fill_constant instead of by fetch.
+    // OP_INOUT_CHECK(ctx->HasInputs(kX) || ctx->HasInputs(kNoNeedBufferX),
+    //                "Input", string::format_string("%s|%s", kX,
+    //                kNoNeedBufferX),
+    //                "CinnLaunchOp");
     OP_INOUT_CHECK(ctx->HasOutputs(kOutputs), "Output", kOutputs,
                    "CinnLaunchOp");
   }
-- 
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