add send and recv ops (#28590)

* update, test=develop

paddle/fluid/operators/collective/recv_v2_op.cc

+/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/fluid/operators/collective/recv_v2_op.h"
+#include <string>
+
+namespace paddle {
+namespace operators {
+
+class RecvOpV2 : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext* ctx) const override {
+    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "Recv_V2");
+    int peer = ctx->Attrs().Get<int>("peer");
+    int ring_id = ctx->Attrs().Get<int>("ring_id");
+    PADDLE_ENFORCE_GE(
+        peer, 0,
+        platform::errors::InvalidArgument(
+            "The peer (%d) for recv_v2 op must be non-negative.", peer));
+    PADDLE_ENFORCE_GE(
+        ring_id, 0,
+        platform::errors::InvalidArgument(
+            "The ring_id (%d) for recv_v2 op must be non-negative.", ring_id));
+    auto out_shape = ctx->Attrs().Get<std::vector<int>>("out_shape");
+    PADDLE_ENFORCE_GE(out_shape.size(), 1,
+                      platform::errors::InvalidArgument(
+                          "The size of the output shape must be greater than 0 "
+                          "but the value given is %d.",
+                          out_shape.size()));
+    ctx->SetOutputDim("Out", framework::make_ddim(out_shape));
+  }
+
+ protected:
+  framework::OpKernelType GetExpectedKernelType(
+      const framework::ExecutionContext& ctx) const override {
+    int dtype = ctx.Attr<int>("dtype");
+    framework::proto::VarType::Type type =
+        framework::proto::VarType::Type(dtype);
+    return framework::OpKernelType(type, ctx.GetPlace());
+  }
+};
+
+class RecvOpV2Maker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() {
+    AddOutput("Out", "(Tensor) tensor to receive.");
+    AddAttr<int>("ring_id", "(int default 0) nccl communication ring id.")
+        .SetDefault(0);
+    AddAttr<int>("peer", "(int default 0) rank id for sender.").SetDefault(0);
+    AddAttr<int>("dtype", "(int default 5('float32')) data type of tensor.")
+        .SetDefault(5);
+    AddAttr<std::vector<int>>("out_shape", "shape of the output tensor.")
+        .SetDefault(std::vector<int>());
+    AddAttr<bool>(
+        "use_calc_stream",
+        "(bool default false) eject CUDA operations to calculation stream.")
+        .SetDefault(false);
+    AddComment(R"DOC(
+Recv Operator
+
+Reference: https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/usage/p2p.html#sendrecv
+)DOC");
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OP_WITHOUT_GRADIENT(recv_v2, ops::RecvOpV2, ops::RecvOpV2Maker);
+
+REGISTER_OP_CPU_KERNEL(recv_v2, ops::RecvOpV2CPUKernel<float>,
+                       ops::RecvOpV2CPUKernel<double>,
+                       ops::RecvOpV2CPUKernel<int>,
+                       ops::RecvOpV2CPUKernel<int64_t>,
+                       ops::RecvOpV2CPUKernel<plat::float16>);

paddle/fluid/operators/collective/recv_v2_op.cu.cc

+/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/fluid/operators/collective/recv_v2_op.h"
+
+#if defined(PADDLE_WITH_NCCL)
+#include "paddle/fluid/platform/collective_helper.h"
+#include "paddle/fluid/platform/nccl_helper.h"
+#endif
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+class RecvOpV2CUDAKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext &ctx) const override {
+    int rid = ctx.Attr<int>("ring_id");
+    PADDLE_ENFORCE_GE(
+        rid, 0,
+        platform::errors::InvalidArgument(
+            "The ring_id (%d) for recv_v2 op must be non-negative.", rid));
+
+    int peer = ctx.Attr<int>("peer");
+    PADDLE_ENFORCE_GE(
+        peer, 0,
+        platform::errors::InvalidArgument(
+            "The peer (%d) for recv_v2 op must be non-negative.", peer));
+
+    auto out = ctx.Output<framework::LoDTensor>("Out");
+    auto out_dims = out->dims();
+    int data_type = ctx.Attr<int>("dtype");
+    framework::proto::VarType::Type type =
+        framework::proto::VarType::Type(data_type);
+
+#if defined(PADDLE_WITH_NCCL) && NCCL_VERSION_CODE >= 2703
+    cudaStream_t stream = nullptr;
+    auto place = ctx.GetPlace();
+    auto comm = platform::NCCLCommContext::Instance().Get(rid, place);
+    if (ctx.Attr<bool>("use_calc_stream")) {
+      auto dev_ctx = platform::DeviceContextPool::Instance().Get(place);
+      stream = static_cast<platform::CUDADeviceContext *>(dev_ctx)->stream();
+    } else {
+      stream = comm->stream();
+    }
+
+    PADDLE_ENFORCE_LT(
+        peer, comm->nranks(),
+        platform::errors::InvalidArgument("The value of peer (%d) you set must "
+                                          "be less than comm->nranks (%d).",
+                                          peer, comm->nranks()));
+    ncclDataType_t dtype = platform::ToNCCLDataType(type);
+
+    // Recv the number of elements to receive first
+    int numel = 0;
+    int *numel_ptr = nullptr;
+    PADDLE_ENFORCE_CUDA_SUCCESS(cudaMalloc(&numel_ptr, sizeof(int)));
+    PADDLE_ENFORCE_CUDA_SUCCESS(
+        platform::dynload::ncclRecv(static_cast<void *>(numel_ptr), 1, ncclInt,
+                                    peer, comm->comm(), stream));
+    PADDLE_ENFORCE_CUDA_SUCCESS(
+        cudaMemcpy(&numel, numel_ptr, sizeof(int), cudaMemcpyDeviceToHost));
+
+    int rest_numel = 1;
+    for (int i = 1; i < out_dims.size(); ++i) {
+      rest_numel = rest_numel * out_dims[i];
+    }
+    out_dims[0] = numel / rest_numel;
+    out->mutable_data<T>(out_dims, place);
+
+    PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclRecv(
+        out->data<T>(), numel, dtype, peer, comm->comm(), stream));
+    VLOG(3) << "rank " << comm->rank() << " recv "
+            << framework::product(out->dims()) << " from " << peer;
+#else
+    PADDLE_THROW(platform::errors::Unavailable(
+        "PaddlePaddle should be compiled with NCCL and "
+        "NCCL version >= 2.7.3 is needed."));
+#endif
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OP_CUDA_KERNEL(recv_v2, ops::RecvOpV2CUDAKernel<float>,
+                        ops::RecvOpV2CUDAKernel<double>,
+                        ops::RecvOpV2CUDAKernel<int>,
+                        ops::RecvOpV2CUDAKernel<int64_t>,
+                        ops::RecvOpV2CUDAKernel<plat::float16>);

paddle/fluid/operators/collective/recv_v2_op.h

+/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#pragma once
+#include <algorithm>
+#include <utility>
+#include <vector>
+
+#include "paddle/fluid/framework/data_type.h"
+#include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+class RecvOpV2CPUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    PADDLE_THROW(platform::errors::Unavailable(
+        "Do not support recv for cpu kernel now."));
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

paddle/fluid/operators/collective/send_v2_op.cc

+/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/fluid/operators/collective/send_v2_op.h"
+
+namespace paddle {
+namespace operators {
+
+class SendOpV2 : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext* ctx) const override {
+    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "SendV2");
+    int peer = ctx->Attrs().Get<int>("peer");
+    int ring_id = ctx->Attrs().Get<int>("ring_id");
+    PADDLE_ENFORCE_GE(
+        peer, 0,
+        platform::errors::InvalidArgument(
+            "The peer (%d) for send_v2 op must be non-negative.", peer));
+    PADDLE_ENFORCE_GE(
+        ring_id, 0,
+        platform::errors::InvalidArgument(
+            "The ring_id (%d) for send_v2 op must be non-negative.", ring_id));
+  }
+
+ protected:
+  framework::OpKernelType GetExpectedKernelType(
+      const framework::ExecutionContext& ctx) const override {
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace());
+  }
+};
+
+class SendOpV2Maker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() {
+    AddInput("X", "(Tensor) tensor to be sent.");
+    AddAttr<int>("ring_id", "(int default 0) nccl communication ring id.")
+        .SetDefault(0);
+    AddAttr<int>("peer", "(int default 0) rank id for receiver.").SetDefault(0);
+    AddAttr<bool>(
+        "use_calc_stream",
+        "(bool default false) eject CUDA operations to calculation stream.")
+        .SetDefault(false);
+    AddComment(R"DOC(
+Send Operator
+
+Reference: https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/usage/p2p.html#sendrecv
+)DOC");
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OP_WITHOUT_GRADIENT(send_v2, ops::SendOpV2, ops::SendOpV2Maker);
+
+REGISTER_OP_CPU_KERNEL(send_v2, ops::SendOpV2CPUKernel<float>,
+                       ops::SendOpV2CPUKernel<double>,
+                       ops::SendOpV2CPUKernel<int>,
+                       ops::SendOpV2CPUKernel<int64_t>,
+                       ops::SendOpV2CPUKernel<plat::float16>);

paddle/fluid/operators/collective/send_v2_op.cu.cc

+/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/fluid/operators/collective/send_v2_op.h"
+
+#if defined(PADDLE_WITH_NCCL)
+#include "paddle/fluid/platform/collective_helper.h"
+#include "paddle/fluid/platform/nccl_helper.h"
+#endif
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+class SendOpV2CUDAKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto x = ctx.Input<framework::LoDTensor>("X");
+    int numel = x->numel();
+
+    int rid = ctx.Attr<int>("ring_id");
+    PADDLE_ENFORCE_GE(
+        rid, 0,
+        platform::errors::InvalidArgument(
+            "The ring_id (%d) for send_v2 op must be non-negative.", rid));
+
+    int peer = ctx.Attr<int>("peer");
+    PADDLE_ENFORCE_GE(
+        peer, 0,
+        platform::errors::InvalidArgument(
+            "The peer (%d) for send_v2 op must be non-negative.", peer));
+    cudaStream_t stream = nullptr;
+    auto place = ctx.GetPlace();
+#if defined(PADDLE_WITH_NCCL) && NCCL_VERSION_CODE >= 2703
+    auto comm = platform::NCCLCommContext::Instance().Get(rid, place);
+    if (ctx.Attr<bool>("use_calc_stream")) {
+      auto dev_ctx = platform::DeviceContextPool::Instance().Get(place);
+      stream = static_cast<platform::CUDADeviceContext*>(dev_ctx)->stream();
+    } else {
+      stream = comm->stream();
+    }
+    PADDLE_ENFORCE_LT(
+        peer, comm->nranks(),
+        platform::errors::InvalidArgument("The value of peer (%d) you set must "
+                                          "be less than comm->nranks (%d).",
+                                          peer, comm->nranks()));
+    ncclDataType_t dtype = platform::ToNCCLDataType(x->type());
+    // Send number of elements to the receiver, as the receiver may have
+    // no information of the Tensor size.
+    int* numel_ptr = nullptr;
+    PADDLE_ENFORCE_CUDA_SUCCESS(cudaMalloc(&numel_ptr, sizeof(int)));
+    PADDLE_ENFORCE_CUDA_SUCCESS(
+        cudaMemcpy(numel_ptr, &numel, sizeof(int), cudaMemcpyHostToDevice));
+
+    PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclSend(
+        numel_ptr, 1, ncclInt, peer, comm->comm(), stream));
+    PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclSend(
+        x->data<T>(), numel, dtype, peer, comm->comm(), stream));
+    VLOG(3) << "rank " << comm->rank() << " send "
+            << framework::product(x->dims()) << " to " << peer;
+#else
+    PADDLE_THROW(platform::errors::Unavailable(
+        "PaddlePaddle should be compiled with NCCL "
+        "and NCCL version >= 2.7.3 is needed."));
+#endif
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OP_CUDA_KERNEL(send_v2, ops::SendOpV2CUDAKernel<float>,
+                        ops::SendOpV2CUDAKernel<double>,
+                        ops::SendOpV2CUDAKernel<int>,
+                        ops::SendOpV2CUDAKernel<int64_t>,
+                        ops::SendOpV2CUDAKernel<plat::float16>);

paddle/fluid/operators/collective/send_v2_op.h

+/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#pragma once
+
+#include <algorithm>
+#include <utility>
+#include <vector>
+
+#include "paddle/fluid/framework/data_type.h"
+#include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+class SendOpV2CPUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    PADDLE_THROW(platform::errors::Unavailable(
+        "Do not support send for cpu kernel now."));
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

python/paddle/fluid/tests/unittests/CMakeLists.txt

@@ -64,6 +64,7 @@ if(NOT WITH_GPU OR WIN32)
     LIST(REMOVE_ITEM TEST_OPS test_broadcast)
     LIST(REMOVE_ITEM TEST_OPS test_collective_reduce)
     LIST(REMOVE_ITEM TEST_OPS test_collective_scatter)
+    LIST(REMOVE_ITEM TEST_OPS test_collective_sendrecv)
     LIST(REMOVE_ITEM TEST_OPS test_reducescatter)
     LIST(REMOVE_ITEM TEST_OPS test_reducescatter_api)
     LIST(REMOVE_ITEM TEST_OPS test_collective_reduce_api)

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

+# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import print_function
+
+import numpy as np
+import argparse
+import os
+import sys
+import signal
+import time
+import socket
+from contextlib import closing
+from six import string_types
+import math
+import paddle
+import paddle.fluid as fluid
+import paddle.fluid.profiler as profiler
+import paddle.fluid.unique_name as nameGen
+from paddle.fluid import core
+import unittest
+from multiprocessing import Process
+import paddle.fluid.layers as layers
+from functools import reduce
+from test_collective_base import TestCollectiveRunnerBase, runtime_main
+
+paddle.enable_static()
+
+
+class TestCollectiveSendRecv(TestCollectiveRunnerBase):
+    def __init__(self):
+        self.global_ring_id = 0
+
+    def get_model(self, main_prog, startup_program):
+        ring_id = self.global_ring_id
+        with fluid.program_guard(main_prog, startup_program):
+            tindata = layers.data(
+                name="tindata", shape=[10, 1000], dtype='float64')
+            if self.rank == 0:
+                main_prog.global_block().append_op(
+                    type="send_v2",
+                    inputs={'X': tindata},
+                    attrs={
+                        'ring_id': ring_id,
+                        'peer': 1,
+                        'use_calc_stream': True
+                    })
+            else:
+                main_prog.global_block().append_op(
+                    type="recv_v2",
+                    outputs={'Out': tindata},
+                    attrs={
+                        'peer': 0,
+                        'ring_id': ring_id,
+                        'dtype': tindata.dtype,
+                        'out_shape': tindata.shape,
+                        'use_calc_stream': True,
+                    })
+            return tindata
+
+
+if __name__ == "__main__":
+    runtime_main(TestCollectiveSendRecv, "sendrecv", 0)

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

@@ -103,6 +103,7 @@ class TestCollectiveRunnerBase(object):
         nranks = 2
         self.initCommunicator(startup_prog, rank, nranks, True,
                               current_endpoint, endpoints)
+        self.rank = rank
         result = self.get_model(train_prog, startup_prog)
         device_id = int(os.getenv("FLAGS_selected_gpus", "0"))
         place = fluid.CUDAPlace(
@@ -268,6 +269,11 @@ class TestDistBase(unittest.TestCase):
             self.assertTrue(
                 np.allclose(
                     tr1_out, need_result2, rtol=1e-05, atol=1e-05))
+        elif col_type == "sendrecv":
+            need_result = input1
+            self.assertTrue(
+                np.allclose(
+                    tr1_out, need_result, rtol=1e-05, atol=1e-05))
         elif col_type == "reduce_slicegather":
             slicesize = input1.shape[0] // 2
             tmp10 = input1[0:slicesize]

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

+#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import print_function
+import unittest
+import numpy as np
+import paddle
+
+from test_collective_base import TestDistBase
+
+paddle.enable_static()
+
+
+class TestSendRecvOp(TestDistBase):
+    def _setup_config(self):
+        pass
+
+    def test_sendrecv(self):
+        self.check_with_place("collective_sendrecv_op.py", "sendrecv")
+
+
+if __name__ == '__main__':
+    unittest.main()