support lodtensorarray for send/recv

paddle/fluid/operators/collective/recv_v2_op.cc

@@ -34,21 +34,26 @@ class RecvOpV2 : public framework::OperatorWithKernel {
         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()));
-    for (size_t i = 0; i < out_shape.size(); ++i) {
-      PADDLE_ENFORCE_GE(out_shape[i], 1,
-                        platform::errors::InvalidArgument(
-                            "The shape attribute for recv_v2 must be set "
-                            "explicitly, but the %dth element is %d which "
-                            "is less than 1.",
-                            i, out_shape[i]));
+
+    if (ctx->GetOutputsVarType("Out").front() ==
+        framework::proto::VarType::LOD_TENSOR) {
+      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()));
+      for (size_t i = 0; i < out_shape.size(); ++i) {
+        PADDLE_ENFORCE_GE(out_shape[i], 1,
+                          platform::errors::InvalidArgument(
+                              "The shape attribute for recv_v2 must be set "
+                              "explicitly, but the %dth element is %d which "
+                              "is less than 1.",
+                              i, out_shape[i]));
+      }
+      ctx->SetOutputDim("Out", framework::make_ddim(out_shape));
     }
-    ctx->SetOutputDim("Out", framework::make_ddim(out_shape));
   }
 
  protected:

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

@@ -40,13 +40,6 @@ class RecvOpV2CUDAKernel : public framework::OpKernel<T> {
         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();
-    auto numel = out->numel();
-    int data_type = ctx.Attr<int>("dtype");
-    framework::proto::VarType::Type type =
-        framework::proto::VarType::Type(data_type);
-
     gpuStream_t stream = nullptr;
     auto place = ctx.GetPlace();
     auto comm = platform::NCCLCommContext::Instance().Get(rid, place);
@@ -56,14 +49,40 @@ class RecvOpV2CUDAKernel : public framework::OpKernel<T> {
     } 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()));
-    out->mutable_data<T>(out_dims, place);
+
+    int data_type = ctx.Attr<int>("dtype");
+    framework::proto::VarType::Type type =
+        framework::proto::VarType::Type(data_type);
     ncclDataType_t dtype = platform::ToNCCLDataType(type);
+
+    auto *out_var = ctx.OutputVar("Out");
+    if (out_var->IsType<framework::LoDTensorArray>()) {
+      auto out_array = out_var->GetMutable<framework::LoDTensorArray>();
+      for (size_t idx = 0; idx < out_array->size(); ++idx) {
+        VLOG(3) << "LodTensorArray: idx(" << idx << ")";
+        auto out = &out_array->at(idx);
+        auto out_dims = out->dims();
+        out->mutable_data<T>(out_dims, place, 0);
+        auto numel = out->numel();
+        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;
+      }
+      return;
+    }
+
+    auto out_shape = ctx.Attr<std::vector<int>>("out_shape");
+    auto out = ctx.Output<framework::LoDTensor>("Out");
+    auto out_dims = out->dims();
+    auto numel = out->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 "

paddle/fluid/operators/collective/send_v2_op.cc

@@ -38,6 +38,16 @@ class SendOpV2 : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
+    const framework::Variable* var = ctx.InputVar("X");
+    if (var->IsType<framework::LoDTensorArray>()) {
+      auto t_arr = var->Get<framework::LoDTensorArray>();
+      // NOTE(sandyhouse): Support an empty tensor array as Input.
+      // And set the kernel type is float.
+      if (t_arr.size() == 0) {
+        return framework::OpKernelType(framework::proto::VarType::FP32,
+                                       ctx.device_context());
+      }
+    }
     return framework::OpKernelType(
         OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace());
   }

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

@@ -28,9 +28,6 @@ class SendOpV2CUDAKernel : public framework::OpKernel<T> {
   void Compute(const framework::ExecutionContext& ctx) const override {
 #if (defined(PADDLE_WITH_RCCL) || defined(PADDLE_WITH_NCCL)) && \
     NCCL_VERSION_CODE >= 2703
-    auto x = ctx.Input<framework::LoDTensor>("X");
-    int numel = x->numel();
-
     int rid = ctx.Attr<int>("ring_id");
     PADDLE_ENFORCE_GE(
         rid, 0,
@@ -56,6 +53,25 @@ class SendOpV2CUDAKernel : public framework::OpKernel<T> {
         platform::errors::InvalidArgument("The value of peer (%d) you set must "
                                           "be less than comm->nranks (%d).",
                                           peer, comm->nranks()));
+
+    auto* x_var = ctx.InputVar("X");
+    if (x_var->IsType<framework::LoDTensorArray>()) {
+      auto& x_array = x_var->Get<framework::LoDTensorArray>();
+      for (size_t idx = 0; idx < x_array.size(); idx++) {
+        VLOG(3) << "LodTensorArray: idx(" << idx << ")";
+        auto& x = x_array.at(idx);
+        int numel = x.numel();
+        ncclDataType_t dtype = platform::ToNCCLDataType(x.type());
+        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;
+      }
+      return;
+    }
+    auto x = ctx.Input<framework::LoDTensor>("X");
+    int numel = x->numel();
+
     ncclDataType_t dtype = platform::ToNCCLDataType(x->type());
     PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclSend(
         x->data<T>(), numel, dtype, peer, comm->comm(), stream));

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

@@ -0,0 +1,95 @@
+# 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',
+                append_batch_size=False)
+            if self.rank == 0:
+                data1 = fluid.layers.assign(
+                    np.array(
+                        [[0, 1, 2]], dtype='float32'))
+                data2 = fluid.layers.assign(
+                    np.array(
+                        [[3, 4, 5]], dtype='float32'))
+            elif self.rank == 1:
+                data1 = fluid.layers.assign(
+                    np.array(
+                        [[3, 4, 5]], dtype='float32'))
+                data2 = fluid.layers.assign(
+                    np.array(
+                        [[0, 1, 2]], dtype='float32'))
+            tensor_array = fluid.layers.create_array(dtype='float32')
+            i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
+            fluid.layers.array_write(data1, i, tensor_array)
+            fluid.layers.array_write(data2, i + 1, tensor_array)
+            if self.rank == 0:
+                main_prog.global_block().append_op(
+                    type="send_v2",
+                    inputs={'X': tensor_array},
+                    attrs={
+                        'ring_id': ring_id,
+                        'peer': 1,
+                        'use_calc_stream': True
+                    })
+            else:
+                main_prog.global_block().append_op(
+                    type="recv_v2",
+                    outputs={'Out': tensor_array},
+                    attrs={
+                        'peer': 0,
+                        'ring_id': ring_id,
+                        'dtype': data1.dtype,
+                        'out_shape': [1, 3],
+                        'use_calc_stream': True,
+                    })
+            return tensor_array
+
+
+if __name__ == "__main__":
+    runtime_main(TestCollectiveSendRecv, "sendrecv_array", 0)

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

@@ -215,7 +215,7 @@ def check_with_place(self,
             "PYTHONPATH": os.getenv("PYTHONPATH", ""),
             "LD_LIBRARY_PATH": os.getenv("LD_LIBRARY_PATH", ""),
             "LD_PRELOAD": os.getenv("LD_PRELOAD", ""),
-            "GLOG_v": "0",
+            "GLOG_v": "3",
             "NCCL_P2P_DISABLE": "1"
         }
         required_envs.update(need_envs)
@@ -300,5 +300,14 @@ def check_with_place(self,
             self.assertTrue(
                 np.allclose(
                     tr1_out, need_result2, rtol=1e-05, atol=1e-05))
+        elif col_type == "sendrecv_array":
+            need_result1 = np.array([[0, 1, 2]])
+            need_result2 = np.array([[3, 4, 5]])
+            self.assertTrue(
+                np.allclose(
+                    tr1_out[0][0], need_result1, rtol=1e-05, atol=1e-05))
+            self.assertTrue(
+                np.allclose(
+                    tr1_out[0][1], need_result2, rtol=1e-05, atol=1e-05))
         else:
             pass

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

@@ -29,6 +29,10 @@ def _setup_config(self):
     def test_sendrecv(self):
         self.check_with_place("collective_sendrecv_op.py", "sendrecv")
 
+    def test_sendrecv_array(self):
+        self.check_with_place("collective_sendrecv_op_array.py",
+                              "sendrecv_array")
+
 
 if __name__ == '__main__':
     unittest.main()