add alltoall api (#32507)

* add alltoall api, test=develop

paddle/fluid/operators/collective/alltoall_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/alltoall_op.h"
+
+namespace paddle {
+namespace operators {
+
+class AllToAllOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext* ctx) const override {
+    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "AllToAll");
+    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "AllToAll");
+    int ring_id = ctx->Attrs().Get<int>("ring_id");
+    PADDLE_ENFORCE_GE(
+        ring_id, 0,
+        platform::errors::InvalidArgument(
+            "The ring_id (%d) for alltoall op must be non-negative.", ring_id));
+    framework::DDim dim = ctx->GetInputDim("X");
+    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());
+  }
+};
+
+class AllToAllOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() {
+    AddInput("X", "(Tensor) tensor send.");
+    AddOutput("Out", "(Tensor) the result of alltoall.");
+    AddAttr<int>("ring_id", "(int default 0) nccl communication ring id.")
+        .SetDefault(0);
+    AddAttr<bool>(
+        "use_calc_stream",
+        "(bool default false) eject CUDA operations to calculation stream.")
+        .SetDefault(false);
+    AddComment(R"DOC(
+AllToAll Operator
+Scatter tensors from all participators to all participators.
+)DOC");
+  }
+};
+
+template <typename T>
+class AllToAllOpGradMaker : public framework::SingleGradOpMaker<T> {
+ public:
+  using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
+
+ protected:
+  void Apply(GradOpPtr<T> retv) const override {
+    retv->SetType("alltoall");
+    retv->SetInput("X", this->OutputGrad("Out"));
+    retv->SetOutput("Out", this->InputGrad("X"));
+    retv->SetAttrMap(this->Attrs());
+  }
+};
+
+DECLARE_INPLACE_OP_INFERER(AllToAllInplaceInferer, {"X", "Out"});
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OPERATOR(alltoall, ops::AllToAllOp, ops::AllToAllOpMaker,
+                  ops::AllToAllOpGradMaker<paddle::framework::OpDesc>,
+                  ops::AllToAllOpGradMaker<paddle::imperative::OpBase>,
+                  ops::AllToAllInplaceInferer)
+
+REGISTER_OP_CPU_KERNEL(alltoall, ops::AllToAllOpCPUKernel<float>,
+                       ops::AllToAllOpCPUKernel<double>,
+                       ops::AllToAllOpCPUKernel<int>,
+                       ops::AllToAllOpCPUKernel<int64_t>,
+                       ops::AllToAllOpCPUKernel<plat::float16>);

paddle/fluid/operators/collective/alltoall_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 "paddle/fluid/operators/collective/alltoall_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 AllToAllOpCUDAKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+#if defined(PADDLE_WITH_NCCL)
+#if NCCL_VERSION_CODE >= 2703
+    auto x = ctx.Input<framework::LoDTensor>("X");
+    auto out = ctx.Output<framework::LoDTensor>("Out");
+    int send_numel = x->numel();
+    ncclDataType_t dtype = platform::ToNCCLDataType(x->type());
+
+    int ring_id = ctx.Attr<int>("ring_id");
+    PADDLE_ENFORCE_GE(
+        ring_id, 0,
+        platform::errors::InvalidArgument(
+            "The ring_id (%d) for alltoall op must be non-negative.", ring_id));
+    auto place = ctx.GetPlace();
+    auto comm = platform::NCCLCommContext::Instance().Get(ring_id, place);
+    int nranks = comm->nranks();
+
+    cudaStream_t stream = nullptr;
+    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();
+    }
+
+    framework::DDim x_dims = x->dims();
+    framework::DDim out_dims(x_dims);
+    PADDLE_ENFORCE_EQ(
+        x_dims[0] % nranks, 0,
+        platform::errors::InvalidArgument(
+            "The first dimension size (%d) of the input tensor must be "
+            "divisible by the number of ranks (%d).",
+            x_dims[0], nranks));
+    auto send_buf = x->data<T>();
+    auto recv_buf = out->mutable_data<T>(out_dims, place);
+    size_t offset = 0;
+    send_numel /= nranks;
+    PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclGroupStart());
+    for (auto i = 0; i < nranks; ++i) {
+      PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclSend(
+          send_buf + offset, send_numel, dtype, i, comm->comm(), stream));
+      PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclRecv(
+          recv_buf + offset, send_numel, dtype, i, comm->comm(), stream));
+      offset += send_numel;
+    }
+    PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclGroupEnd());
+#else
+    PADDLE_THROW(
+        platform::errors::Unavailable("NCCL version >= 2.7.3 is needed."));
+#endif
+#else
+    PADDLE_THROW(
+        platform::errors::Unavailable("PaddlePaddle should compile with GPU."));
+#endif
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OP_CUDA_KERNEL(alltoall, ops::AllToAllOpCUDAKernel<float>,
+                        ops::AllToAllOpCUDAKernel<double>,
+                        ops::AllToAllOpCUDAKernel<int>,
+                        ops::AllToAllOpCUDAKernel<int64_t>,
+                        ops::AllToAllOpCUDAKernel<plat::float16>);

paddle/fluid/operators/collective/alltoall_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"
+
+#if defined(PADDLE_WITH_GLOO)
+#include "paddle/fluid/framework/fleet/gloo_wrapper.h"
+#endif
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+class AllToAllOpCPUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    PADDLE_THROW(platform::errors::Unavailable(
+        "Do not support alltoall for cpu kernel now."));
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

python/paddle/distributed/collective.py

@@ -36,6 +36,7 @@ __all__ = [
     'scatter',
     'barrier',
     'split',
+    'alltoall',
     'ReduceOp',
     'send',
     'recv',
@@ -1178,6 +1179,77 @@ def split(x,
         return linear_out
 
 
+def alltoall(in_tensor_list, out_tensor_list, group=None, use_calc_stream=True):
+    """
+    Scatter tensors in in_tensor_list to all participators and gather the result tensors in out_tensor_list.
+    Args:
+        in_tensor_list (list): A list of input Tensors. Every element in the list must be a Tensor whose data type
+            should be float16, float32, float64, int32 or int64.
+        out_tensor_list (Tensor): A list of output Tensors. The data type of its elements should be the same as the
+            data type of the input Tensors.
+        group (Group, optional): The group instance return by new_group or None for global default group. Default: None.
+        use_calc_stream (bool, optional): Wether to use calculation stream (True) or communication stream. Default: True.
+    Returns:
+        None.
+    Examples:
+        .. code-block:: python
+            # required: distributed
+            import numpy as np
+            import paddle
+            from paddle.distributed import init_parallel_env
+            init_parallel_env()
+            out_tensor_list = []
+            if paddle.distributed.ParallelEnv().rank == 0:
+                np_data1 = np.array([[1, 2, 3], [4, 5, 6]])
+                np_data2 = np.array([[7, 8, 9], [10, 11, 12]])
+            else:
+                np_data1 = np.array([[13, 14, 15], [16, 17, 18]])
+                np_data2 = np.array([[19, 20, 21], [22, 23, 24]])
+            data1 = paddle.to_tensor(np_data1)
+            data2 = paddle.to_tensor(np_data2)
+            paddle.distributed.all_to_all([data1, data2], out_tensor_list)
+            # out for rank 0: [[[1, 2, 3], [4, 5, 6]], [[13, 14, 15], [16, 17, 18]]]
+            # out for rank 1: [[[7, 8, 9], [10, 11, 12]], [[19, 20, 21], [22, 23, 24]]]
+    """
+    if group is not None and not group.is_member():
+        return
+
+    ring_id = 0 if group is None else group.id
+    op_type = 'alltoall'
+    temp = paddle.concat(in_tensor_list, axis=0)
+    helper = LayerHelper(op_type, **locals())
+    nranks = len(in_tensor_list)
+    out = helper.create_variable_for_type_inference(
+        dtype=in_tensor_list[0].dtype)
+    if in_dygraph_mode():
+        core.ops.alltoall_(temp, 'use_calc_stream', use_calc_stream, 'ring_id',
+                           ring_id)
+    else:
+        if not isinstance(in_tensor_list, list):
+            raise ValueError("The type of 'in_tensor_list' for all_to_all "
+                             "should be list.")
+        for elem in in_tensor_list:
+            check_variable_and_dtype(
+                elem, 'in_tensor_list',
+                ['float16', 'float32', 'float64', 'int32', 'int64'],
+                'all_to_all')
+        if not isinstance(out_tensor_list, list):
+            raise ValueError("The type of 'out_tensor_list' for all_to_all "
+                             "should be list.")
+        if len(out_tensor_list) != 0:
+            raise ValueError("The 'out_tensor_list' for all_to_all "
+                             "must be an empty list.")
+        helper.append_op(
+            type=op_type,
+            inputs={'X': [temp]},
+            outputs={'Out': [out]},
+            attrs={
+                'ring_id': group,
+                'use_calc_stream': use_calc_stream,
+            })
+    out_tensor_list.extend(paddle.split(out, nranks, 0))
+
+
 def send(tensor, dst=0, group=None, use_calc_stream=True):
     """
     Send a tensor to the receiver.

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

@@ -96,6 +96,7 @@ if(((NOT WITH_ROCM) AND (NOT WITH_GPU)) OR WIN32)
     LIST(REMOVE_ITEM TEST_OPS test_new_group_api)
     LIST(REMOVE_ITEM TEST_OPS test_collective_broadcast_api)
     LIST(REMOVE_ITEM TEST_OPS test_collective_allgather_api)
+    LIST(REMOVE_ITEM TEST_OPS test_collective_alltoall_api)
     LIST(REMOVE_ITEM TEST_OPS test_collective_sendrecv_api)
     LIST(REMOVE_ITEM TEST_OPS test_collective_wait)
     LIST(REMOVE_ITEM TEST_OPS test_memcpy_op)
@@ -872,6 +873,7 @@ if(WITH_DISTRIBUTE AND WITH_GPU AND WITH_NCCL)
 endif()
 if((WITH_ROCM OR WITH_GPU) AND NOT WIN32)
     set_tests_properties(test_collective_allgather_api PROPERTIES TIMEOUT 120)
+    set_tests_properties(test_collective_alltoall_api PROPERTIES TIMEOUT 120)
     set_tests_properties(test_collective_sendrecv_api PROPERTIES TIMEOUT 120)
     set_tests_properties(test_collective_broadcast_api PROPERTIES TIMEOUT 120)
     set_tests_properties(test_collective_allreduce_api PROPERTIES TIMEOUT 120)
@@ -907,6 +909,7 @@ if((WITH_ROCM OR WITH_GPU) AND NOT WIN32)
         test_new_group_api
         test_collective_broadcast_api
         test_collective_allgather_api
+        test_collective_alltoall_api
         PROPERTIES LABELS "RUN_TYPE=DIST")
 endif()
 if(WITH_GPU OR WITH_ROCM)

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

+# 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.
+
+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_api_base import TestCollectiveAPIRunnerBase, runtime_main
+
+paddle.enable_static()
+
+
+class TestCollectiveAllToAllAPI(TestCollectiveAPIRunnerBase):
+    def __init__(self):
+        self.global_ring_id = 0
+
+    def get_model(self, main_prog, startup_program, rank):
+        with fluid.program_guard(main_prog, startup_program):
+            tindata = layers.data(
+                name="tindata", shape=[10, 1000], dtype='float32')
+            tindata = paddle.split(tindata, 2, axis=0)
+            tout_data = []
+            paddle.distributed.alltoall(tindata, tout_data)
+            return tout_data
+
+
+if __name__ == "__main__":
+    runtime_main(TestCollectiveAllToAllAPI, "alltoall")

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

+#   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.
+
+from __future__ import print_function
+import unittest
+import numpy as np
+import paddle
+
+from test_collective_api_base import TestDistBase
+
+paddle.enable_static()
+
+
+class TestCollectiveAllToAllAPI(TestDistBase):
+    def _setup_config(self):
+        pass
+
+    def test_alltoall_nccl(self):
+        self.check_with_place("collective_alltoall_api.py", "alltoall", "nccl")
+
+
+if __name__ == '__main__':
+    unittest.main()

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

@@ -277,6 +277,19 @@ class TestDistBase(unittest.TestCase):
             self.assertTrue(
                 np.allclose(
                     result_data, need_result, rtol=1e-05, atol=1e-05))
+        elif col_type == "alltoall":
+            need_result1 = np.vstack((input1[0:input1.shape[0] // 2, :],
+                                      input2[0:input2.shape[0] // 2, :]))
+            need_result2 = np.vstack((input1[input1.shape[0] // 2:, :],
+                                      input2[input2.shape[0] // 2:, :]))
+            tr0_out = np.vstack(tr0_out)
+            tr1_out = np.vstack(tr1_out)
+            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))
         elif col_type == "sendrecv":
             result_data = tr1_out[0]
             self.assertTrue(