Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into fix_dist_resnet_ut_in_py36

test=develop

cmake/operators.cmake

@@ -109,7 +109,8 @@ function(op_library TARGET)
 
     # Define operators that don't need pybind here.
     foreach(manual_pybind_op "compare_op" "logical_op" "nccl_op"
-"tensor_array_read_write_op" "tensorrt_engine_op" "conv_fusion_op")
+"tensor_array_read_write_op" "tensorrt_engine_op" "conv_fusion_op"
+"fusion_transpose_flatten_concat_op")
         if ("${TARGET}" STREQUAL "${manual_pybind_op}")
             set(pybind_flag 1)
         endif()

paddle/fluid/framework/CMakeLists.txt

@@ -117,7 +117,7 @@ cc_library(op_info SRCS op_info.cc DEPS attribute framework_proto)
 cc_library(shape_inference SRCS shape_inference.cc DEPS ddim attribute device_context)
 
 if (NOT WIN32)
-cc_library(transfer_scope_cache SRCS transfer_scope_cache.cc DEPS scope framework_proto)
+cc_library(transfer_scope_cache SRCS transfer_scope_cache.cc DEPS scope framework_proto device_context)
 cc_library(operator SRCS operator.cc DEPS op_info device_context tensor scope glog
     shape_inference data_transform lod_tensor profiler transfer_scope_cache)
 else()

paddle/fluid/framework/transfer_scope_cache.cc

@@ -17,16 +17,28 @@
 namespace paddle {
 namespace framework {
 
+// Holds all the transfer scope across the process.
 std::unordered_map<size_t, Scope*>& global_transfer_data_cache() {
-  thread_local auto* x = new std::unordered_map<size_t, Scope*>;
+  typedef std::unordered_map<size_t, Scope*> map_t;
+  thread_local std::unique_ptr<map_t> x(new map_t);
   return *x;
 }
 
+// Holds all the transfer scope for this thread.
 std::unordered_set<Scope*>& global_transfer_scope_cache() {
-  thread_local auto* x = new std::unordered_set<Scope*>;
+  typedef std::unordered_set<Scope*> set_t;
+  thread_local std::unique_ptr<set_t> x(new set_t);
   return *x;
 }
 
+// Try to create a transfer scope. If one cached scope has match the
+// requirement, just return that one.
+// Inputs:
+// @type0: the source kernel type.
+// @type1: the target kernel type.
+// @scope: the execution scope of this op.
+// Returns: A scope used to hold the transfer data across the different kernel
+// type.
 Scope* TryCreateTransferScope(OpKernelType type0, OpKernelType type1,
                               const Scope* scope) {
   Scope* new_scope{nullptr};
@@ -46,27 +58,5 @@ Scope* TryCreateTransferScope(OpKernelType type0, OpKernelType type1,
   return new_scope;
 }
 
-void RemoveKidsFromTransferScopeCache(Scope* scope) {
-  auto it = global_transfer_scope_cache().find(scope);
-  if (it != global_transfer_scope_cache().end()) {
-    global_transfer_scope_cache().erase(it);
-  }
-  for (auto* s : scope->kids()) {
-    auto it = global_transfer_scope_cache().find(s);
-    if (it != global_transfer_scope_cache().end()) {
-      global_transfer_scope_cache().erase(it);
-    }
-  }
-
-  // remove global transfer data cache
-  auto& cache = global_transfer_data_cache();
-  for (auto it = cache.begin(); it != cache.end();) {
-    if (it->second == scope)
-      it = cache.erase(it);
-    else
-      it++;
-  }
-}
-
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/operators/fused/CMakeLists.txt

 include(operators)
-register_operators()
+register_operators(EXCLUDES fusion_transpose_flatten_concat_op)
+if (WITH_GPU)
+  op_library(fusion_transpose_flatten_concat_op)
+  file(APPEND ${pybind_file} "USE_CUDA_ONLY_OP(fusion_transpose_flatten_concat);\n")
+endif()

paddle/fluid/operators/fused/fusion_transpose_flatten_concat_op.cc

+/* Copyright (c) 2016 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/fused/fusion_transpose_flatten_concat_op.h"
+#include <string>
+#include <vector>
+#include "paddle/fluid/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+
+using framework::Tensor;
+
+class TransposeFlattenConcatFusionOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext *ctx) const override {
+    PADDLE_ENFORCE_GE(ctx->Inputs("X").size(), 1UL,
+                      "Inputs(X) of ConcatOp should be empty.");
+    PADDLE_ENFORCE(ctx->HasOutput("Out"),
+                   "Output(Out) of ConcatOp should not be null.");
+
+    auto ins = ctx->GetInputsDim("X");
+    const size_t n = ins.size();
+    PADDLE_ENFORCE_GT(n, 0, "Input tensors count should > 0.");
+
+    std::vector<int> trans_axis =
+        ctx->Attrs().Get<std::vector<int>>("trans_axis");
+    int flatten_axis = ctx->Attrs().Get<int>("flatten_axis");
+    int concat_axis = ctx->Attrs().Get<int>("concat_axis");
+
+    size_t x_rank = ins[0].size();
+    size_t trans_axis_size = trans_axis.size();
+    PADDLE_ENFORCE_EQ(x_rank, trans_axis_size,
+                      "The input tensor's rank(%d) "
+                      "should be equal to the permutation axis's size(%d)",
+                      x_rank, trans_axis_size);
+
+    auto dims0 =
+        GetFlattenShape(flatten_axis, GetPermuteShape(trans_axis, ins[0]));
+    std::vector<int> out_dims(dims0);
+    for (size_t i = 1; i < n; i++) {
+      auto dimsi =
+          GetFlattenShape(flatten_axis, GetPermuteShape(trans_axis, ins[i]));
+      for (int j = 0; j < static_cast<int>(dims0.size()); j++) {
+        if (j == concat_axis) {
+          out_dims[concat_axis] += dimsi[j];
+        } else {
+          PADDLE_ENFORCE_EQ(out_dims[j], dimsi[j],
+                            "After flatting, the %d-th dim should be save "
+                            "except the specify axis.",
+                            j);
+        }
+      }
+    }
+    if (out_dims[concat_axis] < 0) {
+      out_dims[concat_axis] = -1;
+    }
+    ctx->SetOutputDim("Out", framework::make_ddim(out_dims));
+  }
+};
+
+class TransposeFlattenConcatFusionOpMaker
+    : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() override {
+    AddInput(
+        "X",
+        "(Tensor) The input tensor, tensors with rank up to 6 are supported.")
+        .AsDuplicable();
+    AddOutput("Out", "(Tensor)The output tensor.");
+    AddAttr<std::vector<int>>(
+        "trans_axis",
+        "(vector<int>) A list of values, and the size of the list should be "
+        "the same with the input tensor rank. This operator permutes the input "
+        "tensor's axes according to the values given.");
+    AddAttr<int>("flatten_axis",
+                 "(int)"
+                 "Indicate up to which input dimensions (exclusive) should be"
+                 "flattened to the outer dimension of the output. The value"
+                 "for axis must be in the range [0, R], where R is the rank of"
+                 "the input tensor. When axis = 0, the shape of the output"
+                 "tensor is (1, (d_0 X d_1 ... d_n), where the shape of the"
+                 "input tensor is (d_0, d_1, ... d_n).");
+    AddAttr<int>("concat_axis",
+                 "The axis along which the input tensors will be concatenated. "
+                 "It should be 0 or 1, since the tensor is 2D after flatting.");
+    AddComment(R"DOC(
+
+
+)DOC");
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OPERATOR(fusion_transpose_flatten_concat,
+                  ops::TransposeFlattenConcatFusionOp,
+                  ops::TransposeFlattenConcatFusionOpMaker,
+                  paddle::framework::EmptyGradOpMaker);

paddle/fluid/operators/fused/fusion_transpose_flatten_concat_op.cu.cc

+/* Copyright (c) 2016 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/fused/fusion_transpose_flatten_concat_op.h"
+#include <vector>
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/platform/cudnn_helper.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+using CudnnDataType = platform::CudnnDataType<T>;
+
+template <typename T>
+class TransposeFlattenConcatFusionKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto ins = ctx.MultiInput<framework::Tensor>("X");
+    auto* out = ctx.Output<framework::Tensor>("Out");
+    out->mutable_data<T>(ctx.GetPlace());
+    auto odims = out->dims();
+
+    std::vector<int> trans_axis = ctx.Attr<std::vector<int>>("trans_axis");
+    int flatten_axis = ctx.Attr<int>("flatten_axis");
+    int concat_axis = ctx.Attr<int>("concat_axis");
+
+    int rank = ins[0]->dims().size();
+    // use at least 4D in cudnnTransformTensor
+    int max_dim = rank < 4 ? 4 : rank;
+    std::vector<int> stride_x(max_dim, 0);
+    std::vector<int> stride_y(max_dim, 0);
+    std::vector<int> dims_y(max_dim, 0);
+
+    cudnnTensorDescriptor_t in_desc;
+    cudnnTensorDescriptor_t out_desc;
+    CUDNN_ENFORCE(platform::dynload::cudnnCreateTensorDescriptor(&in_desc));
+    CUDNN_ENFORCE(platform::dynload::cudnnCreateTensorDescriptor(&out_desc));
+    cudnnDataType_t cudnn_dtype = CudnnDataType<T>::type;
+
+    auto& dev_ctx = ctx.template device_context<platform::CUDADeviceContext>();
+    auto handle = dev_ctx.cudnn_handle();
+
+    T* odata = out->data<T>();
+    for (size_t k = 0; k < ins.size(); ++k) {
+      auto perm_shape = GetPermuteShape(trans_axis, ins[k]->dims());
+      int osize = 1;
+      auto idims = ins[k]->dims();
+      for (int i = 0; i < rank; i++) {
+        stride_x[i] = 1;
+        for (int j = trans_axis[i] + 1; j < rank; j++) {
+          stride_x[i] *= idims[j];
+        }
+        dims_y[i] = perm_shape[i];
+        osize *= perm_shape[i];
+      }
+      stride_y[rank - 1] = 1;
+      for (int i = rank - 2; i >= 0; i--) {
+        if (((i + 1) == flatten_axis) && (concat_axis == 1)) {
+          stride_y[i] = odims[1];
+        } else {
+          stride_y[i] = stride_y[i + 1] * perm_shape[i + 1];
+        }
+      }
+
+      // Since concat is aftern flatten, the output is 2D tensor.
+      // If concat_axis is 0, each input's permutated tensor is continuous.
+      // If concat_axis is 1, the stride of 0-th dim of each input's
+      // permutated tensor is odims()[1].
+
+      for (int i = rank; i < max_dim; i++) {
+        stride_x[i] = 1;
+        stride_y[i] = 1;
+        dims_y[i] = 1;
+      }
+
+      CUDNN_ENFORCE(platform::dynload::cudnnSetTensorNdDescriptor(
+          in_desc, cudnn_dtype, max_dim, dims_y.data(), stride_x.data()));
+      CUDNN_ENFORCE(platform::dynload::cudnnSetTensorNdDescriptor(
+          out_desc, cudnn_dtype, max_dim, dims_y.data(), stride_y.data()));
+
+      CUDNN_ENFORCE(platform::dynload::cudnnTransformTensor(
+          handle, CudnnDataType<T>::kOne(), in_desc,
+          static_cast<const void*>(ins[k]->data<T>()),
+          CudnnDataType<T>::kZero(), out_desc, static_cast<void*>(odata)));
+      if (concat_axis == 0) {
+        odata += osize;
+      } else {
+        auto flat_shape = GetFlattenShape(flatten_axis, perm_shape);
+        odata += flat_shape[1];
+      }
+    }
+    CUDNN_ENFORCE(platform::dynload::cudnnDestroyTensorDescriptor(in_desc));
+    CUDNN_ENFORCE(platform::dynload::cudnnDestroyTensorDescriptor(out_desc));
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OP_CUDA_KERNEL(fusion_transpose_flatten_concat,
+                        ops::TransposeFlattenConcatFusionKernel<float>,
+                        ops::TransposeFlattenConcatFusionKernel<double>);

paddle/fluid/operators/fused/fusion_transpose_flatten_concat_op.h

+/* Copyright (c) 2016 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 <string>
+#include <vector>
+#include "paddle/fluid/framework/ddim.h"
+
+namespace paddle {
+namespace operators {
+
+inline std::vector<int32_t> GetPermuteShape(const std::vector<int>& axis,
+                                            const framework::DDim& in_dims) {
+  std::vector<int32_t> out_dims(in_dims.size());
+  for (size_t i = 0; i < axis.size(); i++) {
+    out_dims[i] = in_dims[axis[i]];
+  }
+  return out_dims;
+}
+
+inline std::vector<int32_t> GetFlattenShape(const int axis,
+                                            const std::vector<int>& in_dims) {
+  int64_t outer = 1, inner = 1;
+  for (int i = 0; i < static_cast<int>(in_dims.size()); ++i) {
+    if (i < axis) {
+      outer *= in_dims[i];
+    } else {
+      inner *= in_dims[i];
+    }
+  }
+  std::vector<int32_t> out_shape(2);
+  out_shape[0] = outer;
+  out_shape[1] = inner;
+  return out_shape;
+}
+
+}  // namespace operators
+}  // namespace paddle

python/paddle/fluid/tests/unittests/test_fusion_transpose_flatten_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 unittest
+import numpy as np
+from op_test import OpTest
+import paddle.fluid.core as core
+
+
+class TestFusionTransposeFlattenConcationOp(OpTest):
+    def setUp(self):
+        self.init_test_case()
+        self.op_type = "fusion_transpose_flatten_concat"
+
+        ins = []
+        flats = []
+        for i in range(len(self.shapes)):
+            in_shape = self.shapes[i]
+            a = np.random.random(in_shape).astype("float32")
+            ins.append(("x%d" % i, a))
+
+            b = a.transpose(self.trans_axis)
+            flat_shape = (np.prod(b.shape[:self.flatten_axis]),
+                          np.prod(b.shape[self.flatten_axis:]))
+            c = b.reshape(flat_shape)
+            flats.append(c)
+        out = np.concatenate(flats, axis=self.concat_axis)
+
+        self.inputs = {'X': ins}
+        self.attrs = {
+            'trans_axis': list(self.trans_axis),
+            'flatten_axis': self.flatten_axis,
+            'concat_axis': self.concat_axis
+        }
+        self.outputs = {'Out': out}
+
+    def test_check_output(self):
+        if core.is_compiled_with_cuda():
+            place = core.CUDAPlace(0)
+            self.check_output_with_place(place, 1e-6)
+        else:
+            pass
+
+    def init_test_case(self):
+        self.shapes = [(3, 4, 17, 17), (3, 8, 7, 7), (3, 12, 5, 5)]
+        self.trans_axis = (0, 2, 3, 1)
+        self.flatten_axis = 1
+        self.concat_axis = 1
+
+
+class TestCase1(TestFusionTransposeFlattenConcationOp):
+    def init_test_case(self):
+        self.shapes = [(3, 4, 18, 17), (3, 8, 18, 7), (6, 12, 9, 5)]
+        self.trans_axis = (0, 2, 3, 1)
+        self.flatten_axis = 2
+        self.concat_axis = 1
+
+
+class TestCase2(TestFusionTransposeFlattenConcationOp):
+    def init_test_case(self):
+        self.shapes = [(3, 8, 20, 17), (3, 8, 19, 17), (3, 8, 40, 17)]
+        self.trans_axis = (0, 2, 3, 1)
+        self.flatten_axis = 2
+        self.concat_axis = 0
+
+
+class TestCase3(TestFusionTransposeFlattenConcationOp):
+    def init_test_case(self):
+        self.shapes = [(3, 8, 20, 17), (3, 8, 19, 17), (3, 8, 40, 17)]
+        self.trans_axis = (0, 3, 2, 1)
+        self.flatten_axis = 1
+        self.concat_axis = 1
+
+
+class TestCase4(TestFusionTransposeFlattenConcationOp):
+    def init_test_case(self):
+        self.shapes = [(3, 8, 9, 17), (8, 3, 9, 17), (4, 6, 9, 17)]
+        self.trans_axis = (0, 2, 1, 3)
+        self.flatten_axis = 3
+        self.concat_axis = 1
+
+
+class TestCase5(TestFusionTransposeFlattenConcationOp):
+    def init_test_case(self):
+        self.shapes = [(3, 8, 9, 17, 2), (3, 8, 2, 17, 9), (3, 17, 9, 8, 2)]
+        self.trans_axis = (0, 2, 1, 4, 3)
+        self.flatten_axis = 1
+        self.concat_axis = 1
+
+
+if __name__ == '__main__':
+    unittest.main()