add c_concat and c_split ops (#32486)

* add c_concat op

paddle/fluid/operators/collective/c_concat_op.cc

+/* Copyright (c) 2021 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/c_concat_op.h"
+
+namespace paddle {
+namespace operators {
+
+class CConcatOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext* ctx) const override {
+    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "c_concat");
+    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "c_concat");
+    int nranks = ctx->Attrs().Get<int>("nranks");
+    int rank = ctx->Attrs().Get<int>("rank");
+    int ring_id = ctx->Attrs().Get<int>("ring_id");
+    PADDLE_ENFORCE_GE(nranks, 2, platform::errors::InvalidArgument(
+                                     "The number of ranks (%d) for c_concat "
+                                     "must be greater than 1.",
+                                     nranks));
+    PADDLE_ENFORCE_GE(
+        ring_id, 0,
+        platform::errors::InvalidArgument(
+            "The ring_id (%d) for c_concat must be non-negative.", ring_id));
+    PADDLE_ENFORCE_GE(
+        rank, 0, platform::errors::InvalidArgument(
+                     "The rank (%d) for c_concat must be non-negative.", rank));
+    PADDLE_ENFORCE_LT(rank, nranks,
+                      platform::errors::InvalidArgument(
+                          "The value of rank (%d) for c_concat must "
+                          "be less than that of nranks.",
+                          rank, nranks));
+
+    framework::DDim dim = ctx->GetInputDim("X");
+    dim[dim.size() - 1] = dim[dim.size() - 1] * nranks;
+    if (dim[dim.size() - 1] < 0) dim[dim.size() - 1] = -1;
+    ctx->SetOutputDim("Out", dim);
+  }
+
+ protected:
+  framework::OpKernelType GetExpectedKernelType(
+      const framework::ExecutionContext& ctx) const override {
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace());
+  }
+};
+
+template <typename T>
+class CConcatOpGradMaker : public framework::SingleGradOpMaker<T> {
+ public:
+  using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
+
+ protected:
+  void Apply(GradOpPtr<T> retv) const override {
+    retv->SetType("c_split");
+    retv->SetInput("X", this->OutputGrad("Out"));
+    retv->SetOutput("Out", this->InputGrad("X"));
+    retv->SetAttrMap(this->Attrs());
+  }
+};
+
+class CConcatOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() {
+    AddInput("X", "(Tensor) tensor to be concated.");
+    AddOutput("Out", "(Tensor) the result of concat.");
+    AddAttr<int>("rank", "(int default 0) rank id.").SetDefault(0);
+    AddAttr<int>("nranks", "(int default 1) number of ranks.").SetDefault(1);
+    AddAttr<int>("ring_id", "(int default 0) ring id.").SetDefault(0);
+    AddAttr<bool>(
+        "use_calc_stream",
+        "(bool default true) eject CUDA operations to calculation stream.")
+        .SetDefault(true);
+    AddAttr<bool>("use_model_parallel",
+                  "(bool default true) use this op with model parallel.")
+        .SetDefault(true);
+    AddComment(R"DOC(
+CConcat Operator
+AllGather the tensors on different trainers and concat them along the last dimension.
+)DOC");
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OPERATOR(c_concat, ops::CConcatOp,
+                  ops::CConcatOpGradMaker<paddle::framework::OpDesc>,
+                  ops::CConcatOpGradMaker<paddle::imperative::OpBase>,
+                  ops::CConcatOpMaker);
+
+REGISTER_OP_CPU_KERNEL(c_concat, ops::CConcatOpCPUKernel<float>,
+                       ops::CConcatOpCPUKernel<double>,
+                       ops::CConcatOpCPUKernel<int>,
+                       ops::CConcatOpCPUKernel<int64_t>,
+                       ops::CConcatOpCPUKernel<plat::float16>);

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

+/* Copyright (c) 2021 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 <vector>
+
+#include "paddle/fluid/operators/collective/c_concat_op.h"
+#include "paddle/fluid/operators/math/concat_and_split.h"
+
+#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
+#include "paddle/fluid/platform/collective_helper.h"
+#include "paddle/fluid/platform/nccl_helper.h"
+#endif
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+class CConcatOpCUDAKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto x = ctx.Input<framework::Tensor>("X");
+    auto out = ctx.Output<framework::Tensor>("Out");
+    ncclDataType_t dtype = platform::ToNCCLDataType(x->type());
+
+    int nranks = ctx.Attr<int>("nranks");
+    int rank = ctx.Attr<int>("rank");
+    int rid = ctx.Attr<int>("ring_id");
+    auto place = ctx.GetPlace();
+    PADDLE_ENFORCE_GE(rank, 0,
+                      platform::errors::PreconditionNotMet(
+                          "The value of rank (%d) for c_concat must be "
+                          "greater than or equal to 0.",
+                          rank));
+    PADDLE_ENFORCE_GE(nranks, 2,
+                      platform::errors::PreconditionNotMet(
+                          "The value of nranks (%d) for c_concat must be "
+                          "greater than or equal to 2.",
+                          nranks));
+    PADDLE_ENFORCE_LT(rank, nranks,
+                      platform::errors::PreconditionNotMet(
+                          "The value of rank (%d) for c_concat must be "
+                          "less than that of nranks (%d).",
+                          rank, nranks));
+
+#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
+    auto comm = platform::NCCLCommContext::Instance().Get(rid, place);
+    PADDLE_ENFORCE_EQ(
+        nranks, comm->nranks(),
+        platform::errors::InvalidArgument("nranks: %s should equal to %s",
+                                          nranks, comm->nranks()));
+
+    framework::Tensor temp_out;
+    framework::DDim temp_out_dims = x->dims();
+    temp_out_dims[0] *= nranks;
+    temp_out.mutable_data<T>(temp_out_dims, place);
+    int64_t send_numel = x->numel();
+    const T* send_buff = x->data<T>();
+    T* recv_buff = temp_out.data<T>();
+    gpuStream_t stream = nullptr;
+    auto dev_ctx = platform::DeviceContextPool::Instance().Get(place);
+    stream = static_cast<platform::CUDADeviceContext*>(dev_ctx)->stream();
+
+    PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllGather(
+        send_buff, recv_buff, send_numel, static_cast<ncclDataType_t>(dtype),
+        comm->comm(), stream));
+
+    std::vector<framework::Tensor> inputs;
+    int axis = x->dims().size() - 1;
+    auto out_dims = x->dims();
+    out_dims[out_dims.size() - 1] *= nranks;
+    int rows_per_tensor = x->dims()[0];
+    int offset = 0;
+    for (int i = 0; i < nranks; i++) {
+      framework::Tensor temp = temp_out.Slice(offset, offset + rows_per_tensor);
+      inputs.emplace_back(temp);
+      offset += rows_per_tensor;
+    }
+
+    math::ConcatFunctor<platform::CUDADeviceContext, T> functor;
+    out->mutable_data<T>(out_dims, place);
+    auto& dev_ctx2 = ctx.template device_context<platform::CUDADeviceContext>();
+    functor(dev_ctx2, inputs, axis, out);
+#else
+    PADDLE_THROW(platform::errors::PreconditionNotMet(
+        "PaddlePaddle should compile with GPU."));
+#endif
+  }
+};
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OP_CUDA_KERNEL(c_concat, ops::CConcatOpCUDAKernel<float>,
+                        ops::CConcatOpCUDAKernel<double>,
+                        ops::CConcatOpCUDAKernel<int>,
+                        ops::CConcatOpCUDAKernel<int64_t>,
+                        ops::CConcatOpCUDAKernel<plat::float16>);

paddle/fluid/operators/collective/c_concat_op.h

+/* Copyright (c) 2021 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 CConcatOpCPUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    PADDLE_THROW(platform::errors::Unavailable(
+        "Do not support c_concat for cpu kernel now."));
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

paddle/fluid/operators/collective/c_split_op.cc

+/* Copyright (c) 2021 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/c_split_op.h"
+
+namespace paddle {
+namespace operators {
+
+class CSplitOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext* ctx) const override {
+    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "c_split");
+    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "c_split");
+    int nranks = ctx->Attrs().Get<int>("nranks");
+    int rank = ctx->Attrs().Get<int>("rank");
+    int ring_id = ctx->Attrs().Get<int>("ring_id");
+    PADDLE_ENFORCE_GE(nranks, 2, platform::errors::InvalidArgument(
+                                     "The number of ranks (%d) for c_split "
+                                     "must be greater than 1.",
+                                     nranks));
+    PADDLE_ENFORCE_GE(
+        ring_id, 0,
+        platform::errors::InvalidArgument(
+            "The ring_id (%d) for c_split must be non-negative.", ring_id));
+    PADDLE_ENFORCE_GE(
+        rank, 0, platform::errors::InvalidArgument(
+                     "The rank (%d) for c_split must be non-negative.", rank));
+    PADDLE_ENFORCE_LT(rank, nranks,
+                      platform::errors::InvalidArgument(
+                          "The value of rank (%d) for c_split must "
+                          "be less than that of nranks.",
+                          rank, nranks));
+
+    framework::DDim dim = ctx->GetInputDim("X");
+    dim[dim.size() - 1] = dim[dim.size() - 1] / nranks;
+    if (dim[0] < 0) dim[0] = -1;
+    ctx->SetOutputDim("Out", dim);
+  }
+
+ protected:
+  framework::OpKernelType GetExpectedKernelType(
+      const framework::ExecutionContext& ctx) const override {
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace());
+  }
+};
+
+template <typename T>
+class CSplitOpGradMaker : public framework::SingleGradOpMaker<T> {
+ public:
+  using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
+
+ protected:
+  void Apply(GradOpPtr<T> retv) const override {
+    retv->SetType("c_allgather");
+    retv->SetInput("X", this->OutputGrad("Out"));
+    retv->SetOutput("Out", this->InputGrad("X"));
+    retv->SetAttrMap(this->Attrs());
+  }
+};
+
+class CSplitOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() {
+    AddInput("X", "(Tensor) tensor to be split.");
+    AddOutput("Out", "(Tensor) the result of split.");
+    AddAttr<int>("rank", "(int default 0) rank id.").SetDefault(0);
+    AddAttr<int>("nranks", "(int default 1) number of ranks.").SetDefault(1);
+    AddAttr<int>("ring_id", "(int default 0) ring id.").SetDefault(0);
+    AddAttr<bool>(
+        "use_calc_stream",
+        "(bool default false) eject CUDA operations to calculation stream.")
+        .SetDefault(false);
+    AddAttr<bool>("use_model_parallel",
+                  "(bool default false) use this op with model parallel.")
+        .SetDefault(true);
+    AddComment(R"DOC(
+CSplit Operator
+Split the tensor evenly according to its rank.
+)DOC");
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OPERATOR(c_split, ops::CSplitOp,
+                  ops::CSplitOpGradMaker<paddle::framework::OpDesc>,
+                  ops::CSplitOpGradMaker<paddle::imperative::OpBase>,
+                  ops::CSplitOpMaker);
+
+REGISTER_OP_CPU_KERNEL(c_split, ops::CSplitOpCPUKernel<float>,
+                       ops::CSplitOpCPUKernel<double>,
+                       ops::CSplitOpCPUKernel<int>,
+                       ops::CSplitOpCPUKernel<int64_t>,
+                       ops::CSplitOpCPUKernel<plat::float16>);

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

+/* Copyright (c) 2021 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 <vector>
+
+#include "paddle/fluid/operators/collective/c_split_op.h"
+#include "paddle/fluid/operators/math/concat_and_split.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+class CSplitOpCUDAKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto x = ctx.Input<framework::Tensor>("X");
+    auto out = ctx.Output<framework::Tensor>("Out");
+
+    int nranks = ctx.Attr<int>("nranks");
+    int rank = ctx.Attr<int>("rank");
+    auto place = ctx.GetPlace();
+
+    PADDLE_ENFORCE_GE(rank, 0, platform::errors::PreconditionNotMet(
+                                   "The value of rank (%d) for c_split must be "
+                                   "greater than or equal to 0.",
+                                   rank));
+    PADDLE_ENFORCE_GE(nranks, 2,
+                      platform::errors::PreconditionNotMet(
+                          "The value of nranks (%d) for c_split must be "
+                          "greater than or equal to 2.",
+                          nranks));
+    PADDLE_ENFORCE_LT(rank, nranks,
+                      platform::errors::PreconditionNotMet(
+                          "The value of rank (%d) for c_split must be "
+                          "less than that of nranks (%d).",
+                          rank, nranks));
+
+    auto& dev_ctx = ctx.template device_context<platform::CUDADeviceContext>();
+    std::vector<const framework::Tensor*> shape_refer;
+    std::vector<framework::Tensor*> results;
+    size_t numel = x->numel();
+    auto dims = x->dims();
+    numel /= nranks;
+    int axis = dims.size() - 1;
+    dims[dims.size() - 1] /= nranks;
+    for (int i = 0; i < nranks; i++) {
+      framework::Tensor* out = new framework::Tensor();
+      out->mutable_data<T>(dims, place);
+      shape_refer.emplace_back(out);
+      results.emplace_back(out);
+    }
+
+    math::SplitFunctor<platform::CUDADeviceContext, T> functor;
+    functor(dev_ctx, *x, shape_refer, axis, &results);
+    out->mutable_data<T>(dims, place);
+    paddle::framework::TensorCopySync(*results[rank], out->place(), out);
+  }
+};
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OP_CUDA_KERNEL(c_split, ops::CSplitOpCUDAKernel<float>,
+                        ops::CSplitOpCUDAKernel<double>,
+                        ops::CSplitOpCUDAKernel<int>,
+                        ops::CSplitOpCUDAKernel<int64_t>,
+                        ops::CSplitOpCUDAKernel<plat::float16>);

paddle/fluid/operators/collective/c_split_op.h

+/* Copyright (c) 2021 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 CSplitOpCPUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    PADDLE_THROW(platform::errors::Unavailable(
+        "Do not support c_split for cpu kernel now."));
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

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

@@ -71,6 +71,8 @@ endforeach()
 
 if(((NOT WITH_ROCM) AND (NOT WITH_GPU)) OR WIN32)
     LIST(REMOVE_ITEM TEST_OPS test_c_comm_init_all_op)
+    LIST(REMOVE_ITEM TEST_OPS test_c_concat)
+    LIST(REMOVE_ITEM TEST_OPS test_c_split)
     LIST(REMOVE_ITEM TEST_OPS test_allgather)
     LIST(REMOVE_ITEM TEST_OPS test_allreduce)
     LIST(REMOVE_ITEM TEST_OPS test_broadcast)
@@ -873,6 +875,8 @@ if((WITH_ROCM OR WITH_GPU) AND NOT WIN32)
     set_tests_properties(test_collective_reduce_api PROPERTIES TIMEOUT 120)
     set_tests_properties(test_collective_reduce PROPERTIES TIMEOUT 120)
     set_tests_properties(test_allreduce PROPERTIES TIMEOUT 120)
+    set_tests_properties(test_c_concat PROPERTIES TIMEOUT 120)
+    set_tests_properties(test_c_split PROPERTIES TIMEOUT 120)
     set_tests_properties(test_allgather PROPERTIES TIMEOUT 120)
     set_tests_properties(test_collective_scatter_api PROPERTIES TIMEOUT 120)
     set_tests_properties(test_collective_barrier_api PROPERTIES TIMEOUT 120)

python/paddle/fluid/tests/unittests/collective_concat_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
+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 TestCollectiveConcat(TestCollectiveRunnerBase):
+    def __init__(self):
+        self.global_ring_id = 0
+
+    def get_model(self, main_prog, startup_program):
+        ring_id = 0
+        nranks = 2
+        with fluid.program_guard(main_prog, startup_program):
+            tindata = layers.data(
+                name="tindata", shape=[10, 1000], dtype='float32')
+            toutdata = main_prog.current_block().create_var(
+                name="outofconcat",
+                dtype='float32',
+                type=core.VarDesc.VarType.LOD_TENSOR,
+                persistable=False,
+                stop_gradient=False)
+            main_prog.global_block().append_op(
+                type="c_concat",
+                inputs={'X': tindata},
+                attrs={
+                    'ring_id': ring_id,
+                    'rank': self.rank,
+                    'nranks': nranks
+                },
+                outputs={'Out': toutdata})
+            return toutdata
+
+
+if __name__ == "__main__":
+    runtime_main(TestCollectiveConcat, "concat", 0)

python/paddle/fluid/tests/unittests/collective_split_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
+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 TestCollectiveAllGather(TestCollectiveRunnerBase):
+    def __init__(self):
+        self.global_ring_id = 0
+
+    def get_model(self, main_prog, startup_program):
+        ring_id = 0
+        nranks = 2
+        with fluid.program_guard(main_prog, startup_program):
+            tindata = layers.data(
+                name="tindata", shape=[10, 1000], dtype='float32')
+            toutdata = main_prog.current_block().create_var(
+                name="outofsplit",
+                dtype='float32',
+                type=core.VarDesc.VarType.LOD_TENSOR,
+                persistable=False,
+                stop_gradient=False)
+            main_prog.global_block().append_op(
+                type="c_split",
+                inputs={'X': tindata},
+                attrs={
+                    'ring_id': ring_id,
+                    'rank': self.rank,
+                    'nranks': nranks
+                },
+                outputs={'Out': toutdata})
+            return toutdata
+
+
+if __name__ == "__main__":
+    runtime_main(TestCollectiveAllGather, "split", 0)

python/paddle/fluid/tests/unittests/test_c_concat.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 TestConcatOp(TestDistBase):
+    def _setup_config(self):
+        pass
+
+    def test_concat(self, col_type="concat"):
+        self.check_with_place("collective_concat_op.py", col_type)
+
+
+if __name__ == '__main__':
+    unittest.main()

python/paddle/fluid/tests/unittests/test_c_split.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 TestSplitOp(TestDistBase):
+    def _setup_config(self):
+        pass
+
+    def test_split(self, col_type="split"):
+        self.check_with_place("collective_split_op.py", col_type)
+
+
+if __name__ == '__main__':
+    unittest.main()

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

@@ -284,5 +284,22 @@ class TestDistBase(unittest.TestCase):
             need_result2 = np.concatenate((tmp20, tmp21), axis=1)
             self.assertTrue(np.allclose(tr0_out, need_result1))
             self.assertTrue(np.allclose(tr1_out, need_result2))
+        elif col_type == "concat":
+            need_result = np.concatenate((input1, input2), axis=1)
+            self.assertTrue(
+                np.allclose(
+                    tr0_out, need_result, rtol=1e-05, atol=1e-05))
+            self.assertTrue(
+                np.allclose(
+                    tr1_out, need_result, rtol=1e-05, atol=1e-05))
+        elif col_type == "split":
+            need_result1 = np.split(input1, 2, axis=1)[0]
+            need_result2 = np.split(input2, 2, axis=1)[1]
+            self.assertTrue(
+                np.allclose(
+                    tr0_out, need_result1, rtol=1e-05, atol=1e-05))
+            self.assertTrue(
+                np.allclose(
+                    tr1_out, need_result2, rtol=1e-05, atol=1e-05))
         else:
             pass