[hybrid] seed and dropout op support force-cpu (#35820)

* [HIP] fix op not support AMD GPU bug, the flag PADDLE_WITH_ROCM is invalid

* [HIP] fix op not support AMD GPU bug, the flag PADDLE_WITH_ROCM is invalid

* [HIP] fix op not support AMD GPU bug

* [hybrid] seed and dropout op support force-cpu

* [hybrid] seed and dropout op support force-cpu

* [hybrid] seed and dropout op support force-cpu

* [hybrid] seed and dropout op support force-cpu

* [hybrid] seed and dropout op support force-cpu

* [hybrid] fix seed ci failed issue

* add AsExtra for force_cpu of seed op

paddle/fluid/operators/dropout_impl.cu.h

@@ -205,6 +205,9 @@ void DropoutFwGPUKernelDriver(const platform::CUDADeviceContext& dev_ctx,
       TensorCopySync(*seed, platform::CPUPlace(), &seed_cpu_tensor);
       seed_data = static_cast<uint64_t>(seed_cpu_tensor.data<int>()[0]);
       increment = offset;
+    } else if (seed && platform::is_cpu_place(seed->place())) {
+      seed_data = *(seed->data<int>());
+      increment = offset;
     } else if (gen_cuda->GetIsInitPy() && (!is_fix_seed)) {
       auto seed_offset = gen_cuda->IncrementOffset(offset);
       seed_data = seed_offset.first;

paddle/fluid/operators/dropout_op.cc

@@ -42,6 +42,19 @@ class DropoutOp : public framework::OperatorWithKernel {
     return framework::OpKernelType(
         OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace());
   }
+
+  framework::OpKernelType GetKernelTypeForVar(
+      const std::string& var_name, const Tensor& tensor,
+      const framework::OpKernelType& expected_kernel_type) const override {
+    if (var_name == "Seed") {
+      VLOG(10) << "var_name:" << var_name
+               << " does not need to transform in dropout op";
+      return expected_kernel_type;
+    }
+
+    return framework::OpKernelType(expected_kernel_type.data_type_,
+                                   tensor.place(), tensor.layout());
+  }
 };
 
 class DropoutOpMaker : public framework::OpProtoAndCheckerMaker {

paddle/fluid/operators/seed_op.cc

@@ -39,6 +39,12 @@ class SeedOpMaker : public framework::OpProtoAndCheckerMaker {
   void Make() override {
     AddOutput("Out", "The output of seed op.");
     AddAttr<int>("seed", "Dropout random seed.").SetDefault(0);
+    AddAttr<bool>("force_cpu",
+                  "(bool, default false) Force fill output variable to cpu "
+                  "memory. Otherwise, fill output variable to the running "
+                  "device")
+        .SetDefault(false)
+        .AsExtra();
     AddComment(R"DOC(
 Seed Operator.
 )DOC");
@@ -55,3 +61,15 @@ REGISTER_OPERATOR(
     paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>);
 REGISTER_OP_CPU_KERNEL(
     seed, ops::CPUSeedKernel<paddle::platform::CPUDeviceContext, int>);
+
+/* ==========================  register checkpoint ===========================*/
+REGISTER_OP_VERSION(seed)
+    .AddCheckpoint(
+        R"ROC(
+             Upgrade seed add a new attribute [force_cpu])ROC",
+        paddle::framework::compatible::OpVersionDesc().NewAttr(
+            "force_cpu",
+            "If true, Force fill output variable to cpu."
+            "memory. Otherwise, fill output variable to the running "
+            "device",
+            false));

paddle/fluid/operators/seed_op.cu

@@ -12,6 +12,7 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
+#include "paddle/fluid/operators/math/math_function.h"
 #include "paddle/fluid/operators/seed_op.h"
 
 namespace paddle {
@@ -20,10 +21,10 @@ namespace operators {
 template <typename Place, typename T>
 class GPUSeedKernel : public framework::OpKernel<T> {
  public:
-  void Compute(const framework::ExecutionContext& context) const override {
-    auto* out = context.Output<Tensor>("Out");
-    auto* out_data = out->mutable_data<T>(context.GetPlace());
+  void Compute(const framework::ExecutionContext &context) const override {
+    auto *out = context.Output<Tensor>("Out");
     int user_seed = context.Attr<int>("seed");
+    auto force_cpu = context.Attr<bool>("force_cpu");
     std::random_device rnd;
     int seed;
     if (user_seed != 0) {
@@ -31,11 +32,24 @@ class GPUSeedKernel : public framework::OpKernel<T> {
     } else {
       seed = rnd();
     }
-    auto target_gpu_place =
-        BOOST_GET_CONST(platform::CUDAPlace, context.GetPlace());
-    auto stream = context.cuda_device_context().stream();
-    memory::Copy(target_gpu_place, out_data, platform::CPUPlace(), &seed,
-                 sizeof(int), stream);
+
+    bool cpu_place = force_cpu || context.GetPlace() == platform::CPUPlace();
+    if (cpu_place) {
+      platform::DeviceContextPool &pool =
+          platform::DeviceContextPool::Instance();
+      auto &dev_ctx = *pool.Get(context.GetPlace());
+      out->mutable_data<T>(platform::CPUPlace());
+      math::SetConstant<platform::CPUDeviceContext, T> functor;
+      functor(reinterpret_cast<const platform::CPUDeviceContext &>(dev_ctx),
+              out, static_cast<T>(seed));
+    } else {
+      auto *out_data = out->mutable_data<T>(context.GetPlace());
+      auto target_gpu_place =
+          BOOST_GET_CONST(platform::CUDAPlace, context.GetPlace());
+      auto stream = context.cuda_device_context().stream();
+      memory::Copy(target_gpu_place, out_data, platform::CPUPlace(), &seed,
+                   sizeof(int), stream);
+    }
   }
 };
 

paddle/fluid/operators/seed_op.h

@@ -14,6 +14,7 @@
 #pragma once
 
 #include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace operators {

python/paddle/fluid/backward.py

@@ -197,13 +197,18 @@ class ProgramStats(object):
             if op.desc.has_attr(op_device_attr_name):
                 op_device = op.desc.attr(op_device_attr_name)
 
+            # Setting the force_cpu of seed to true will make the output of seed in cpu memory, 
+            # reduce the synchronous copy from GPU to CPU in dropout, and reduce the communication hang
             added_op = self.block._insert_op(
                 index=op.idx,
                 type='seed',
                 inputs={},
                 outputs={'Out': [added_var]},
-                attrs={'seed': seed,
-                       'op_device': op_device})
+                attrs={
+                    'seed': seed,
+                    'op_device': op_device,
+                    'force_cpu': True
+                })
             self.ops.insert(op_idx, added_op)
             # modify dropout op desc so that it accept a seed var as input
             op.desc.set_input("Seed", [var_unique_name])

python/paddle/fluid/tests/unittests/test_dropout_op.py

@@ -232,6 +232,75 @@ class TestFP16DropoutOp2(TestFP16DropoutOp):
         self.fix_seed = False
 
 
+class TestDropoutOpWithSeedOnCPUPlace(unittest.TestCase):
+    def test_seed_cpu_place(self):
+        paddle.enable_static()
+        main_program = Program()
+        with program_guard(main_program):
+            seed_input_name = "tensor@SeedInput"
+            x_var_name = "tensor@X"
+            x_out_var = "tensor@XOut"
+
+            mask_var_name = "tensor@Mask"
+            seed_input_var = main_program.global_block().create_var(
+                name=seed_input_name,
+                shape=[1],
+                dtype='int32',
+                persistable=False,
+                stop_gradient=True)
+            x_out_var = main_program.global_block().create_var(
+                name=x_out_var,
+                shape=[40, 40],
+                dtype='float32',
+                persistable=False,
+                stop_gradient=True)
+            x_var = main_program.global_block().create_var(
+                name=x_var_name,
+                shape=[40, 40],
+                dtype='float32',
+                persistable=False,
+                stop_gradient=True)
+            mask_var = main_program.global_block().create_var(
+                name=mask_var_name,
+                shape=[1],
+                dtype='int',
+                persistable=False,
+                stop_gradient=True)
+
+            main_program.global_block().append_op(
+                type="fill_constant",
+                outputs={"Out": x_var_name},
+                attrs={
+                    "shape": [40, 40],
+                    "dtype": x_var.dtype,
+                    "value": 1.0,
+                    "place_type": 0
+                })
+            main_program.global_block().append_op(
+                type='seed',
+                inputs={},
+                outputs={'Out': seed_input_var},
+                attrs={'seed': 1,
+                       'force_cpu': True})
+            main_program.global_block().append_op(
+                type='dropout',
+                inputs={'X': x_var,
+                        'Seed': seed_input_var},
+                attrs={'dropout_prob': 0.},
+                outputs={'Out': x_out_var,
+                         'Mask': mask_var})
+            place = fluid.CPUPlace()
+            if core.is_compiled_with_cuda():
+                place = fluid.CUDAPlace(0)
+            exe = fluid.Executor(place)
+            x_out, mask_out = exe.run(
+                main_program,
+                feed={},
+                fetch_list=[x_out_var.name, mask_var.name])
+            x_in_np = np.ones([40, 40]).astype("float32")
+            self.assertTrue(np.allclose(x_out, x_in_np))
+
+
 class TestDropoutOpError(unittest.TestCase):
     def test_errors(self):
         with program_guard(Program(), Program()):

python/paddle/fluid/tests/unittests/test_seed_op.py

@@ -25,7 +25,7 @@ class TestSeedOpFixSeed(OpTest):
         self.op_type = "seed"
         self.inputs = {}
         self.attrs = {"seed": 123}
-        self.outputs = {"Out": np.asarray((123)).astype('int32')}
+        self.outputs = {"Out": np.asarray((123)).astype('int')}
 
     def test_check_output(self):
         self.check_output()
@@ -36,7 +36,7 @@ class TestSeedOpDiffSeed(OpTest):
         self.op_type = "seed"
         self.inputs = {}
         self.attrs = {"seed": 0}
-        self.outputs = {"Out": np.asarray((123)).astype('int32')}
+        self.outputs = {"Out": np.asarray((123)).astype('int')}
 
     def test_check_output(self):
         self.check_output(no_check_set=["Out"])