Merge branch 'tttt' of https://github.com/gangliao/Paddle into python-test

.gitignore

@@ -24,4 +24,5 @@ cmake-build-*
 python/paddle/v2/framework/core.so
 CMakeFiles
 cmake_install.cmake
-
+paddle/.timestamp
+python/paddlepaddle.egg-info/

Dockerfile

@@ -64,7 +64,7 @@ RUN pip install --upgrade pip && \
     pip install -U sphinx-rtd-theme==0.1.9 recommonmark && \
     pip install pre-commit 'requests==2.9.2' 'ipython==5.3.0' && \
     pip install 'ipykernel==4.6.0' 'jupyter==1.0.0' && \
-    pip install rarfile
+    pip install opencv-python rarfile 'scipy>=0.19.0' 'nltk>=3.2.2'
 
 # To fix https://github.com/PaddlePaddle/Paddle/issues/1954, we use
 # the solution in https://urllib3.readthedocs.io/en/latest/user-guide.html#ssl-py2

paddle/framework/CMakeLists.txt

@@ -35,6 +35,11 @@ py_proto_compile(framework_py_proto SRCS attribute.proto op_proto.proto op_desc.
 # Generate an empty __init__.py to make framework_py_proto as a valid python module.
 add_custom_target(framework_py_proto_init ALL COMMAND ${CMAKE_COMMAND} -E touch __init__.py)
 add_dependencies(framework_py_proto framework_py_proto_init)
+add_custom_command(TARGET framework_py_proto POST_BUILD
+    COMMAND ${CMAKE_COMMAND} -E make_directory ${PROJ_ROOT}/python/paddle/v2/framework/proto
+    COMMAND cp *.py ${PROJ_ROOT}/python/paddle/v2/framework/proto/
+    COMMENT "Copy generated python proto into directory paddle/v2/framework/proto."
+    WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR})
 
 cc_library(backward SRCS backward.cc DEPS net_op)
 cc_test(backward_test SRCS backward_test.cc DEPS backward)

paddle/framework/backward.cc

@@ -133,8 +133,9 @@ std::shared_ptr<OperatorBase> BackwardRecursive(
     std::shared_ptr<OperatorBase> grad_op = OpRegistry::CreateGradOp(forwardOp);
     for (std::string& grad_input : grad_op->inputs_) {
       if (no_grad_names.count(grad_input)) {
-        std::string prefix =
+        // +1 for \0
-            grad_input.substr(0, grad_input.size() - kGradVarSuffix.size());
+        std::string prefix = grad_input.substr(
+            0, grad_input.size() - sizeof(kGradVarSuffix) / sizeof(char) + 1);
         grad_input = prefix + kZeroVarSuffix;
 
         // If part of input gradient of that operator is not calculated, fill
@@ -167,7 +168,7 @@ std::shared_ptr<OperatorBase> Backward(
   std::unordered_set<std::string> no_grad_names;
   no_grad_names.reserve(no_grad_vars.size());
 
-  no_grad_names.insert(kEmptyVarName + kGradVarSuffix);
+  no_grad_names.insert(std::string(kEmptyVarName) + kGradVarSuffix);
 
   for (auto& name : no_grad_vars) {
     no_grad_names.insert(name + kGradVarSuffix);

paddle/framework/backward_test.cc

@@ -171,10 +171,10 @@ TEST(Backward, simple_op_grad) {
   ASSERT_EQ(4UL, gop->inputs_.size());
   ASSERT_EQ(f::kEmptyVarName, gop->inputs_[0]);
   ASSERT_EQ("rowwise_add_grad", gop->type_);
-  ASSERT_EQ("X" + f::kGradVarSuffix, gop->outputs_[0]);
+  ASSERT_EQ(f::GradVarName("X"), gop->outputs_[0]);
-  ASSERT_EQ("b" + f::kGradVarSuffix, gop->outputs_[1]);
+  ASSERT_EQ(f::GradVarName("b"), gop->outputs_[1]);
 
-  ASSERT_EQ("X" + f::kGradVarSuffix, gop->Output("X" + f::kGradVarSuffix));
+  ASSERT_EQ(f::GradVarName("X"), gop->Output(f::GradVarName("X")));
 }
 
 TEST(Backward, simple_op_not_need_grad) {
@@ -182,7 +182,7 @@ TEST(Backward, simple_op_not_need_grad) {
   ASSERT_NE(fwd, nullptr);
   auto gop = f::Backward(*fwd, {"X"});
   ASSERT_EQ(std::find(gop->outputs_.begin(), gop->outputs_.end(),
-                      "X" + f::kGradVarSuffix),
+                      f::GradVarName("X")),
             gop->outputs_.end());
 
   auto no_input_gop = f::Backward(*fwd, {"X", "b"});
@@ -250,18 +250,18 @@ TEST(Backward, net_input_of_network_not_need_grad) {
   all_output.erase(f::kEmptyVarName);
 
   for (auto &out : {"W1", "b1", "hidden0", "W2", "b2"}) {
-    ASSERT_NE(all_output.find(out + f::kGradVarSuffix), all_output.end());
+    ASSERT_NE(all_output.find(f::GradVarName(out)), all_output.end());
   }
 
   // Not Generated X
-  ASSERT_EQ(all_output.find("X" + f::kGradVarSuffix), all_output.end());
+  ASSERT_EQ(all_output.find(f::GradVarName("X")), all_output.end());
 
   ASSERT_EQ(2UL, bwd_net->ops_.size());
   ASSERT_TRUE(bwd_net->ops_[1]->IsNetOp());
   auto first_fc_grad = static_cast<ops::NetOp *>(bwd_net->ops_[1].get());
   ASSERT_EQ(3UL, first_fc_grad->ops_.size());
   ASSERT_EQ(f::kEmptyVarName,
-            first_fc_grad->ops_[2]->Output("A" + f::kGradVarSuffix));
+            first_fc_grad->ops_[2]->Output(f::GradVarName("A")));
 }
 
 TEST(Backward, net_shared_weight) {
@@ -313,15 +313,15 @@ TEST(Backward, op_part_of_output_are_not_need) {
   ASSERT_EQ(1UL, fill_zero.inputs_.size());
   ASSERT_EQ("Z", fill_zero.inputs_[0]);
   ASSERT_EQ(1UL, fill_zero.outputs_.size());
-  ASSERT_EQ("Z" + f::kZeroVarSuffix, fill_zero.outputs_[0]);
+  ASSERT_EQ(std::string("Z") + f::kZeroVarSuffix, fill_zero.outputs_[0]);
 
   auto &d_many_out = *net->ops_[1];
   ASSERT_EQ("many_output_op_grad", d_many_out.type_);
   ASSERT_EQ(1UL + 2UL + 2UL, d_many_out.inputs_.size());  // I/O/OG
-  ASSERT_EQ("Z" + f::kZeroVarSuffix, d_many_out.Input("z" + f::kGradVarSuffix));
+  ASSERT_EQ(std::string("Z") + f::kZeroVarSuffix,
-  ASSERT_EQ("Y" + f::kGradVarSuffix, d_many_out.Input("y" + f::kGradVarSuffix));
+            d_many_out.Input(f::GradVarName("z")));
-  ASSERT_EQ("X" + f::kGradVarSuffix,
+  ASSERT_EQ(f::GradVarName("Y"), d_many_out.Input(f::GradVarName("y")));
-            d_many_out.Output("x" + f::kGradVarSuffix));
+  ASSERT_EQ(f::GradVarName("X"), d_many_out.Output(f::GradVarName("x")));
 }
 
 TEST(Backward, op_part_of_input_are_not_need) {
@@ -331,10 +331,9 @@ TEST(Backward, op_part_of_input_are_not_need) {
   ASSERT_EQ(grad_mul.type_, "mul_grad");
   ASSERT_EQ(grad_mul.inputs_.size(), 2UL + 1UL + 1UL);
   ASSERT_EQ(grad_mul.outputs_.size(), 2UL);
-  ASSERT_EQ(grad_mul.Output("A" + f::kGradVarSuffix), f::kEmptyVarName);
+  ASSERT_EQ(grad_mul.Output(f::GradVarName("A")), f::kEmptyVarName);
-  ASSERT_EQ(grad_mul.Output("B" + f::kGradVarSuffix), "b" + f::kGradVarSuffix);
+  ASSERT_EQ(grad_mul.Output(f::GradVarName("B")), f::GradVarName("b"));
-  ASSERT_EQ(grad_mul.Input("Out" + f::kGradVarSuffix),
+  ASSERT_EQ(grad_mul.Input(f::GradVarName("Out")), f::GradVarName("out"));
-            "out" + f::kGradVarSuffix);
   ASSERT_EQ(grad_mul.Input("A"), "a");
   ASSERT_EQ(grad_mul.Input("B"), "b");
   ASSERT_EQ(grad_mul.Input("Out"), "out");

paddle/framework/grad_op_builder_test.cc

@@ -83,21 +83,19 @@ TEST(GradOpBuilder, MutiInOut) {
   EXPECT_EQ(grad_test_op->Input("Out1"), "out1");
   EXPECT_EQ(grad_test_op->Inputs("Out2_mult"),
             std::vector<std::string>({"out2_1", "out2_2"}));
-  EXPECT_EQ(grad_test_op->Input("Out1" + f::kGradVarSuffix),
+  EXPECT_EQ(grad_test_op->Input(f::GradVarName("Out1")),
-            "out1" + f::kGradVarSuffix);
+            f::GradVarName("out1"));
-  EXPECT_EQ(grad_test_op->Inputs("Out2_mult" + f::kGradVarSuffix),
+  EXPECT_EQ(grad_test_op->Inputs(f::GradVarName("Out2_mult")),
             std::vector<std::string>(
-                {"out2_1" + f::kGradVarSuffix, "out2_2" + f::kGradVarSuffix}));
+                {f::GradVarName("out2_1"), f::GradVarName("out2_2")}));
 
   ASSERT_EQ(grad_test_op->outputs_.size(), 5UL);
-  EXPECT_EQ(grad_test_op->Output("In1" + f::kGradVarSuffix),
+  EXPECT_EQ(grad_test_op->Output(f::GradVarName("In1")), f::GradVarName("in1"));
-            "in1" + f::kGradVarSuffix);
+  EXPECT_EQ(grad_test_op->Outputs(f::GradVarName("In2_mult")),
-  EXPECT_EQ(grad_test_op->Outputs("In2_mult" + f::kGradVarSuffix),
+            std::vector<std::string>({f::GradVarName("in2_1"),
-            std::vector<std::string>({"in2_1" + f::kGradVarSuffix,
+                                      f::GradVarName("in2_2"),
-                                      "in2_2" + f::kGradVarSuffix,
+                                      f::GradVarName("in2_3")}));
-                                      "in2_3" + f::kGradVarSuffix}));
+  EXPECT_EQ(grad_test_op->Output(f::GradVarName("In3")), f::GradVarName("in3"));
-  EXPECT_EQ(grad_test_op->Output("In3" + f::kGradVarSuffix),
-            "in3" + f::kGradVarSuffix);
 }
 
 TEST(GradOpBuilder, IOIgnoredInGradient) {
@@ -119,19 +117,18 @@ TEST(GradOpBuilder, IOIgnoredInGradient) {
   EXPECT_EQ(grad_test_op->Inputs("Out1_mult"),
             std::vector<std::string>({"out1_1", "out1_2"}));
   EXPECT_EQ(grad_test_op->Input("Out2"), f::kEmptyVarName);
-  EXPECT_EQ(grad_test_op->Inputs("Out1_mult" + f::kGradVarSuffix),
+  EXPECT_EQ(grad_test_op->Inputs(f::GradVarName("Out1_mult")),
             std::vector<std::string>(
-                {"out1_1" + f::kGradVarSuffix, "out1_2" + f::kGradVarSuffix}));
+                {f::GradVarName("out1_1"), f::GradVarName("out1_2")}));
-  EXPECT_EQ(grad_test_op->Input("Out2" + f::kGradVarSuffix),
+  EXPECT_EQ(grad_test_op->Input(f::GradVarName("Out2")),
-            "out2" + f::kGradVarSuffix);
+            f::GradVarName("out2"));
 
   ASSERT_EQ(grad_test_op->outputs_.size(), 5UL);
-  EXPECT_EQ(grad_test_op->Output("In1" + f::kGradVarSuffix),
+  EXPECT_EQ(grad_test_op->Output(f::GradVarName("In1")), f::GradVarName("in1"));
-            "in1" + f::kGradVarSuffix);
+  EXPECT_EQ(grad_test_op->Outputs(f::GradVarName("In2_mult")),
-  EXPECT_EQ(grad_test_op->Outputs("In2_mult" + f::kGradVarSuffix),
             std::vector<std::string>(
-                {"in2_1" + f::kGradVarSuffix, "in2_2" + f::kGradVarSuffix}));
+                {f::GradVarName("in2_1"), f::GradVarName("in2_2")}));
-  EXPECT_EQ(grad_test_op->Outputs("In3_mult" + f::kGradVarSuffix),
+  EXPECT_EQ(grad_test_op->Outputs(f::GradVarName("In3_mult")),
             std::vector<std::string>(
-                {"in3_1" + f::kGradVarSuffix, "in3_2" + f::kGradVarSuffix}));
+                {f::GradVarName("in3_1"), f::GradVarName("in3_2")}));
 }

paddle/framework/operator.h

@@ -33,19 +33,19 @@ namespace paddle {
 namespace framework {
 
 /// If a variable is a empty variable, that name will be used.
-const std::string kEmptyVarName = "@EMPTY@";
+constexpr char kEmptyVarName[] = "@EMPTY@";
 
 /// If a variable is a temporary variable, that name will be set in Python,
 /// but it will be convert to a unique name in scope after OpCreator.
-const std::string kTempVarName = "@TEMP@";
+constexpr char kTempVarName[] = "@TEMP@";
 
 /// If a variable's name has a certain suffix, it means that the
 /// variable is the gradient of another varibale.
 /// e.g. Variable "x@GRAD" is the gradient of varibale "x".
-const std::string kGradVarSuffix = "@GRAD";
+constexpr char kGradVarSuffix[] = "@GRAD";
 
 /// Variables with this suffix are supposed to be filled up with zeros.
-const std::string kZeroVarSuffix = "@ZERO";
+constexpr char kZeroVarSuffix[] = "@ZERO";
 
 inline std::string GradVarName(const std::string& var_name) {
   return var_name + kGradVarSuffix;

paddle/operators/mean_op.cc

@@ -41,7 +41,7 @@ class MeanOpMaker : public framework::OpProtoAndCheckerMaker {
 class MeanGradOp : public framework::OperatorWithKernel {
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {
-    ctx.Output<Tensor>("X" + framework::kGradVarSuffix)
+    ctx.Output<Tensor>(framework::GradVarName("X"))
         ->Resize(ctx.Input<Tensor>("X")->dims());
   }
 };

paddle/operators/mean_op.h

@@ -48,10 +48,10 @@ template <typename Place, typename T>
 class MeanGradKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext& context) const override {
-    auto OG = context.Input<Tensor>("Out" + framework::kGradVarSuffix);
+    auto OG = context.Input<Tensor>(framework::GradVarName("Out"));
     PADDLE_ENFORCE(framework::product(OG->dims()) == 1,
                    "Mean Gradient should be scalar");
-    auto IG = context.Output<Tensor>("X" + framework::kGradVarSuffix);
+    auto IG = context.Output<Tensor>(framework::GradVarName("X"));
     IG->mutable_data<T>(context.GetPlace());
 
     T ig_size = (T)framework::product(IG->dims());

paddle/platform/enforce.h

@@ -15,11 +15,12 @@ limitations under the License. */
 #pragma once
 
 #include <execinfo.h>
-#include <paddle/string/printf.h>
 #include <iomanip>
 #include <sstream>
 #include <stdexcept>
 #include <string>
+#include "paddle/string/printf.h"
+#include "paddle/string/to_string.h"
 
 #ifndef PADDLE_ONLY_CPU
 
@@ -194,8 +195,8 @@ inline void throw_on_error(T e) {
 #define __PADDLE_BINARY_COMPARE(__VAL0, __VAL1, __CMP, __INV_CMP, ...)        \
   PADDLE_ENFORCE(__VAL0 __CMP __VAL1,                                         \
                  "enforce %s " #__CMP " %s failed, %s " #__INV_CMP " %s\n%s", \
-                 #__VAL0, #__VAL1, std::to_string(__VAL0),                    \
+                 #__VAL0, #__VAL1, paddle::string::to_string(__VAL0),         \
-                 std::to_string(__VAL1),                                      \
+                 paddle::string::to_string(__VAL1),                           \
                  paddle::string::Sprintf("" __VA_ARGS__));
 
 }  // namespace platform

paddle/platform/enforce_test.cc

@@ -9,6 +9,8 @@ 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 <array>
+#include <iostream>
 #include <memory>
 
 #include "gtest/gtest.h"
@@ -83,7 +85,7 @@ TEST(ENFORCE_NE, FAIL) {
   } catch (paddle::platform::EnforceNotMet error) {
     caught_exception = true;
     EXPECT_TRUE(HasPrefix(StringPiece(error.what()),
-                          "enforce 1.0 != 1UL failed, 1.000000 == 1"))
+                          "enforce 1.0 != 1UL failed, 1 == 1"))
         << error.what() << " does not have expected prefix";
   }
   EXPECT_TRUE(caught_exception);
@@ -176,3 +178,39 @@ TEST(ENFORCE_NOT_NULL, FAIL) {
   }
   EXPECT_TRUE(caught_exception);
 }
+
+struct Dims {
+  size_t dims_[4];
+
+  bool operator==(const Dims& o) const {
+    for (size_t i = 0; i < 4; ++i) {
+      if (dims_[i] != o.dims_[i]) return false;
+    }
+    return true;
+  }
+};
+
+std::ostream& operator<<(std::ostream& os, const Dims& d) {
+  for (size_t i = 0; i < 4; ++i) {
+    if (i == 0) {
+      os << "[";
+    }
+    os << d.dims_[i];
+    if (i == 4 - 1) {
+      os << "]";
+    } else {
+      os << ", ";
+    }
+  }
+  return os;
+}
+
+TEST(ENFORCE_USER_DEFINED_CLASS, EQ) {
+  Dims a{{1, 2, 3, 4}}, b{{1, 2, 3, 4}};
+  PADDLE_ENFORCE_EQ(a, b);
+}
+
+TEST(ENFORCE_USER_DEFINED_CLASS, NE) {
+  Dims a{{1, 2, 3, 4}}, b{{5, 6, 7, 8}};
+  ASSERT_THROW(PADDLE_ENFORCE_EQ(a, b), paddle::platform::EnforceNotMet);
+}

paddle/scripts/docker/build.sh

@@ -74,11 +74,11 @@ cat <<EOF
 Running unit tests ...
 ========================================
 EOF
+    ctest --output-on-failure
     # make install should also be test when unittest
     make install -j `nproc`
     pip install /usr/local/opt/paddle/share/wheels/*.whl
     paddle version
-    ctest --output-on-failure
 fi
 
 

paddle/string/CMakeLists.txt

@@ -2,3 +2,4 @@ cc_library(stringpiece SRCS piece.cc)
 cc_test(stringpiece_test SRCS piece_test.cc DEPS stringpiece glog gflags)
 
 cc_test(stringprintf_test SRCS printf_test.cc DEPS glog gflags)
+cc_test(to_string_test SRCS to_string_test.cc)

paddle/string/to_string.h

@@ -0,0 +1,40 @@
+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+   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 <sstream>
+#include <string>
+
+namespace paddle {
+namespace string {
+template <typename T>
+inline std::string to_string(T v) {
+  std::ostringstream sout;
+  sout << v;
+  return sout.str();
+}
+
+// Faster std::string/const char* type
+template <>
+inline std::string to_string(std::string v) {
+  return v;
+}
+
+template <>
+inline std::string to_string(const char* v) {
+  return std::string(v);
+}
+
+}  // namespace string
+}  // namespace paddle

paddle/string/to_string_test.cc

@@ -0,0 +1,39 @@
+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+   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/string/to_string.h"
+#include <gtest/gtest.h>
+
+constexpr char kOutputString[] = "User Defined Output";
+class UserDefinedClass {
+public:
+};
+
+std::ostream& operator<<(std::ostream& s, const UserDefinedClass& ins) {
+  s << kOutputString;
+  return s;
+}
+
+TEST(to_string, normal) {
+  using namespace paddle::string;
+  ASSERT_EQ("10", to_string(10));
+  ASSERT_EQ("abc", to_string("abc"));
+  ASSERT_EQ("1.2", to_string(1.2));
+}
+
+TEST(to_string, user_defined) {
+  using namespace paddle::string;
+  UserDefinedClass instance;
+  ASSERT_EQ(kOutputString, to_string(instance));
+}

python/paddle/v2/framework/.gitignore

@@ -0,0 +1 @@
+proto