Merge branch 'develop' into make_network_op

paddle/framework/net_op_test.cc

@@ -69,7 +69,7 @@ TEST(OpKernel, all) {
   net->Run(scope, dev_ctx);
   ASSERT_EQ(2, infer_shape_cnt);
   ASSERT_EQ(2, run_cnt);
-  ASSERT_THROW(net->AddOp(op2), std::runtime_error);
+  ASSERT_THROW(net->AddOp(op2), paddle::platform::EnforceNotMet);
 }
 TEST(AddBackwardOp, TestGradOp) {
   auto net = std::make_shared<PlainNet>();

paddle/framework/op_registry_test.cc

@@ -90,7 +90,7 @@ TEST(OpRegistry, IllegalAttr) {
   bool caught = false;
   try {
     paddle::framework::OpRegistry::CreateOp(op_desc);
-  } catch (std::runtime_error& err) {
+  } catch (paddle::platform::EnforceNotMet err) {
     caught = true;
     std::string msg = "larger_than check fail";
     const char* err_msg = err.what();
@@ -136,7 +136,7 @@ TEST(OpRegistry, CustomChecker) {
   bool caught = false;
   try {
     paddle::framework::OpRegistry::CreateOp(op_desc);
-  } catch (std::runtime_error& err) {
+  } catch (paddle::platform::EnforceNotMet err) {
     caught = true;
     std::string msg = "Attribute 'test_attr' is required!";
     const char* err_msg = err.what();
@@ -154,7 +154,7 @@ TEST(OpRegistry, CustomChecker) {
   caught = false;
   try {
     paddle::framework::OpRegistry::CreateOp(op_desc);
-  } catch (std::runtime_error& err) {
+  } catch (paddle::platform::EnforceNotMet err) {
     caught = true;
     std::string msg = "'test_attr' must be even!";
     const char* err_msg = err.what();
@@ -192,7 +192,7 @@ TEST(ProtoMaker, DuplicatedAttr) {
   pd::OpProto op_proto;
   pd::OpAttrChecker op_checker;
   auto proto_maker = TestAttrProtoMaker(&op_proto, &op_checker);
-  ASSERT_THROW(proto_maker.Validate(), std::runtime_error);
+  ASSERT_THROW(proto_maker.Validate(), paddle::platform::EnforceNotMet);
 }
 
 class TestInOutProtoMaker : public pd::OpProtoAndCheckerMaker {
@@ -208,5 +208,5 @@ TEST(ProtoMaker, DuplicatedInOut) {
   pd::OpProto op_proto;
   pd::OpAttrChecker op_checker;
   auto proto_maker = TestInOutProtoMaker(&op_proto, &op_checker);
-  ASSERT_THROW(proto_maker.Validate(), std::runtime_error);
+  ASSERT_THROW(proto_maker.Validate(), paddle::platform::EnforceNotMet);
 }

paddle/framework/scope.h

@@ -56,7 +56,9 @@ class Scope {
     if (var) {
       return var;
     } else {
-      vars_[name] = std::unique_ptr<Variable>(new Variable());
+      auto ptr = new Variable();
+      name_to_var_[name] = std::unique_ptr<Variable>(ptr);
+      var_to_name_[ptr] = name;
       return GetVariable(name);
     }
   }
@@ -68,8 +70,8 @@ class Scope {
    * from it's parent scope. Return nullptr if not found.
    */
   Variable* GetVariable(const std::string& name) const {
-    auto it = vars_.find(name);
-    if (it != vars_.end()) {
+    auto it = name_to_var_.find(name);
+    if (it != name_to_var_.end()) {
       return it->second.get();
     } else if (parent_ != nullptr) {
       return parent_->GetVariable(name);
@@ -84,12 +86,21 @@ class Scope {
    * Find if there is a Variable in this scope and it's parent scope
    */
   bool HasVariable(const std::string& name) const {
-    return (vars_.find(name) != vars_.end() ||
+    return (name_to_var_.find(name) != name_to_var_.end() ||
             (parent_ && parent_->HasVariable(name)));
   }
 
+  std::string GetVariableName(Variable* const var) const {
+    try {
+      return var_to_name_.at(var);
+    } catch (...) {
+      return "";
+    }
+  }
+
  private:
-  std::unordered_map<std::string, std::unique_ptr<Variable>> vars_;
+  std::unordered_map<Variable*, std::string> var_to_name_;
+  std::unordered_map<std::string, std::unique_ptr<Variable>> name_to_var_;
   std::shared_ptr<Scope> parent_{nullptr};
 };
 

paddle/framework/scope_test.cc

@@ -40,6 +40,11 @@ TEST(Scope, Create) {
   /// already exist.
   Variable* var4 = scope->CreateVariable("a");
   EXPECT_EQ(var4, var2);
+
+  EXPECT_EQ("a", scope->GetVariableName(var4));
+  Scope scope2;
+  auto var = scope2.CreateVariable("tmp");
+  EXPECT_EQ("", scope->GetVariableName(var));
 }
 
 TEST(Scope, Parent) {

paddle/framework/tensor_test.cc

@@ -33,7 +33,7 @@ TEST(Tensor, DataAssert) {
   bool caught = false;
   try {
     src_tensor.data<double>();
-  } catch (std::runtime_error& err) {
+  } catch (paddle::platform::EnforceNotMet err) {
     caught = true;
     std::string msg =
         "Tenosr holds no memory. Call Tensor::mutable_data first.";
@@ -107,7 +107,7 @@ TEST(Tensor, ShareDataWith) {
     bool caught = false;
     try {
       dst_tensor.ShareDataWith<float>(src_tensor);
-    } catch (std::runtime_error& err) {
+    } catch (paddle::platform::EnforceNotMet err) {
       caught = true;
       std::string msg =
           "Tenosr holds no memory. Call Tensor::mutable_data first.";

paddle/platform/enforce.h

@@ -36,6 +36,21 @@ limitations under the License. */
 namespace paddle {
 namespace platform {
 
+struct EnforceNotMet : public std::exception {
+  std::exception_ptr exp_;
+  std::string err_str_;
+
+  EnforceNotMet(std::exception_ptr e, const char* f, int l) : exp_(e) {
+    try {
+      std::rethrow_exception(exp_);
+    } catch (const std::exception& exp) {
+      err_str_ = string::Sprintf("%s at [%s:%d]", exp.what(), f, l);
+    }
+  }
+
+  const char* what() const noexcept { return err_str_.c_str(); }
+};
+
 // Because most enforce conditions would evaluate to true, we can use
 // __builtin_expect to instruct the C++ compiler to generate code that
 // always forces branch prediction of true.
@@ -52,9 +67,7 @@ template <typename... Args>
 inline typename std::enable_if<sizeof...(Args) != 0, void>::type throw_on_error(
     int stat, const Args&... args) {
   if (UNLIKELY(!(stat))) {
-    throw std::runtime_error(
-        string::Sprintf(args...) +
-        string::Sprintf(" at [%s:%s];", __FILE__, __LINE__));
+    throw std::runtime_error(string::Sprintf(args...));
   }
 }
 
@@ -64,12 +77,8 @@ template <typename... Args>
 inline typename std::enable_if<sizeof...(Args) != 0, void>::type throw_on_error(
     cudaError_t e, const Args&... args) {
   if (UNLIKELY(e)) {
-    // clang-format off
-    throw thrust::system_error(
-        e, thrust::cuda_category(),
-        string::Sprintf(args...) +
-        string::Sprintf(" at [%s:%s];", __FILE__, __LINE__));
-    // clang-format on
+    throw thrust::system_error(e, thrust::cuda_category(),
+                               string::Sprintf(args...));
   }
 }
 
@@ -77,12 +86,8 @@ template <typename... Args>
 inline typename std::enable_if<sizeof...(Args) != 0, void>::type throw_on_error(
     curandStatus_t stat, const Args&... args) {
   if (stat != CURAND_STATUS_SUCCESS) {
-    // clang-format off
-    throw thrust::system_error(
-        cudaErrorLaunchFailure, thrust::cuda_category(),
-        string::Sprintf(args...) +
-        string::Sprintf(" at [%s:%s];", __FILE__, __LINE__));
-    // clang-format on
+    throw thrust::system_error(cudaErrorLaunchFailure, thrust::cuda_category(),
+                               string::Sprintf(args...));
   }
 }
 
@@ -92,12 +97,8 @@ inline typename std::enable_if<sizeof...(Args) != 0, void>::type throw_on_error(
   if (stat == CUDNN_STATUS_SUCCESS) {
     return;
   } else {
-    // clang-format off
-    throw std::runtime_error(
-        platform::dynload::cudnnGetErrorString(stat) +
-        string::Sprintf(args...) +
-        string::Sprintf(" at [%s:%s];", __FILE__, __LINE__));
-    // clang-format on
+    throw std::runtime_error(platform::dynload::cudnnGetErrorString(stat) +
+                             string::Sprintf(args...));
   }
 }
 
@@ -126,22 +127,27 @@ inline typename std::enable_if<sizeof...(Args) != 0, void>::type throw_on_error(
   } else if (stat == CUBLAS_STATUS_LICENSE_ERROR) {
     err = "CUBLAS: license error, ";
   }
-  throw std::runtime_error(err + string::Sprintf(args...) +
-                           string::Sprintf(" at [%s:%s];", __FILE__, __LINE__));
+  throw std::runtime_error(err + string::Sprintf(args...));
 }
 
 #endif  // PADDLE_ONLY_CPU
 
 #define PADDLE_THROW(...)                                      \
   do {                                                         \
-    throw std::runtime_error(                                 \
-        string::Sprintf(__VA_ARGS__) +                        \
-        string::Sprintf(" at [%s:%s];", __FILE__, __LINE__)); \
+    throw ::paddle::platform::EnforceNotMet(                   \
+        std::make_exception_ptr(                               \
+            std::runtime_error(string::Sprintf(__VA_ARGS__))), \
+        __FILE__, __LINE__);                                   \
   } while (0)
 
 #define PADDLE_ENFORCE(...)                                             \
   do {                                                                  \
+    try {                                                               \
       ::paddle::platform::throw_on_error(__VA_ARGS__);                  \
+    } catch (...) {                                                     \
+      throw ::paddle::platform::EnforceNotMet(std::current_exception(), \
+                                              __FILE__, __LINE__);      \
+    }                                                                   \
   } while (0)
 
 }  // namespace platform

paddle/platform/enforce_test.cc

@@ -23,7 +23,7 @@ TEST(ENFORCE, FAILED) {
   bool in_catch = false;
   try {
     PADDLE_ENFORCE(false, "Enforce is not ok %d at all", 123);
-  } catch (const std::runtime_error& error) {
+  } catch (paddle::platform::EnforceNotMet error) {
     // your error handling code here
     in_catch = true;
     std::string msg = "Enforce is not ok 123 at all";

paddle/pybind/pybind.cc

@@ -48,6 +48,11 @@ void ExposeOperator(ClassType& m) {
       .def("__str__", &ClassType::type::DebugString);
 }
 
+static size_t UniqueIntegerGenerator() {
+  static std::atomic<size_t> generator;
+  return generator.fetch_add(1);
+}
+
 PYBIND11_PLUGIN(core) {
   py::module m("core", "C++ core of PaddlePaddle");
 
@@ -98,7 +103,8 @@ All parameter, weight, gradient are variables in Paddle.
            py::return_value_policy::reference)
       .def("create_var",
            &pd::Scope::CreateVariable,
-           py::return_value_policy::reference);
+           py::return_value_policy::reference)
+      .def("get_var_name", &pd::Scope::GetVariableName);
 
   //! @note: Be careful! PyBind will return std::string as an unicode, not
   //! Python str. If you want a str object, you should cast them in Python.
@@ -141,10 +147,9 @@ All parameter, weight, gradient are variables in Paddle.
   ExposeOperator(operator_base);
 
   using PlainNetPtr = std::shared_ptr<pd::PlainNet>;
-  py::class_<pd::PlainNet, PlainNetPtr> plain_net(m, "PlainNet");
+  py::class_<pd::PlainNet, PlainNetPtr> net(m, "Net");
 
-  plain_net
-      .def_static("create",
+  net.def_static("create",
                  []() -> std::shared_ptr<pd::PlainNet> {
                    auto retv = std::make_shared<pd::PlainNet>();
                    retv->type_ = "plain_net";
@@ -152,12 +157,14 @@ All parameter, weight, gradient are variables in Paddle.
                  })
       .def("add_op", &pd::PlainNet::AddOp)
       .def("add_op",
-           [](PlainNetPtr& self, const PlainNetPtr& plain_net) -> void {
-             self->AddOp(std::static_pointer_cast<pd::OperatorBase>(plain_net));
+           [](PlainNetPtr& self, const PlainNetPtr& net) -> void {
+             self->AddOp(std::static_pointer_cast<pd::OperatorBase>(net));
            })
       .def("complete_add_op", &pd::PlainNet::CompleteAddOp)
       .def("complete_add_op", [](PlainNetPtr& self) { self->CompleteAddOp(); });
-  ExposeOperator(plain_net);
+  ExposeOperator(net);
+
+  m.def("unique_integer", UniqueIntegerGenerator);
 
   return m.ptr();
 }

python/paddle/trainer/config_parser.py

@@ -2055,8 +2055,7 @@ class BatchNormLayer(LayerBase):
         # Automatically select cudnn_batch_norm for GPU and batch_norm for CPU.
         # Also based on cudnn version.
         use_cudnn = use_gpu and batch_norm_type != "batch_norm" and \
-            ((not parallel_nn) or self.config.device > -1) and \
-            cudnn_version >= 4007
+                ((not parallel_nn) or self.config.device > -1)
         self.layer_type = "cudnn_batch_norm" if use_cudnn else "batch_norm"
         super(BatchNormLayer, self).__init__(
             name, self.layer_type, 0, inputs=inputs, **xargs)

python/paddle/v2/__init__.py

@@ -34,6 +34,7 @@ import minibatch
 import plot
 import image
 import model
+import paddle.trainer.config_parser as cp
 
 __all__ = [
     'optimizer',
@@ -58,6 +59,8 @@ __all__ = [
     'model',
 ]
 
+cp.begin_parse()
+
 
 def init(**kwargs):
     import py_paddle.swig_paddle as api
@@ -73,6 +76,11 @@ def init(**kwargs):
     for key in args_dict.keys():
         args.append('--%s=%s' % (key, str(args_dict[key])))
 
+    if 'use_gpu' in kwargs:
+        cp.g_command_config_args['use_gpu'] = kwargs['use_gpu']
+    assert 'parallel_nn' not in kwargs, ("currently 'parallel_nn' is not "
+                                         "supported in v2 APIs.")
+
     api.initPaddle(*args)
 
 

python/paddle/v2/dataset/mq2007.py

@@ -242,9 +242,9 @@ def gen_list(querylist):
     if not isinstance(querylist, QueryList):
         querylist = QueryList(querylist)
     querylist._correct_ranking_()
-    relevance_score_list = [query.relevance_score for query in querylist]
+    relevance_score_list = [[query.relevance_score] for query in querylist]
     feature_vector_list = [query.feature_vector for query in querylist]
-    yield np.array(relevance_score_list).T, np.array(feature_vector_list)
+    yield np.array(relevance_score_list), np.array(feature_vector_list)
 
 
 def query_filter(querylists):

python/paddle/v2/framework/create_op_creation_methods.py

@@ -220,6 +220,9 @@ def create_op_creation_method(op_proto):
     __impl__.all_input_args = [var.name for var in op_proto.inputs]
     __impl__.all_output_args = [var.name for var in op_proto.outputs]
     __impl__.all_attr_args = [attr.name for attr in op_proto.attrs]
+    __impl__.all_not_temp_output_args = [
+        var.name for var in op_proto.outputs if not var.temporary
+    ]
 
     return __impl__
 

python/paddle/v2/framework/network.py

+import paddle.v2.framework.core as core
+from paddle.v2.framework.create_op_creation_methods import op_creations
+from default_scope_funcs import create_var, get_var, get_cur_scope
+
+__all__ = ['Network']  # Only expose Network
+
+
+class NetworkFunctor(object):
+    """
+    Network Op Creation Function. Used internally in this module.
+    It convert string input to Variable. If it is not created before, just 
+    create in scope.
+    
+    It is a functor object. means the instances are callable.
+    
+    :param func: The op creation function which generated in Python.
+    :param net: The Network instance.
+    """
+
+    def __init__(self, func, net):
+        self.func = func
+        self.net = net
+
+    def __call__(self, *args, **kwargs):
+        if len(args) != 0:
+            raise ValueError("Paddle must use keyword argument")
+        inputs = self.func.all_input_args
+        for ipt in inputs:
+            if ipt in kwargs:
+                var = kwargs[ipt]
+                if isinstance(var, basestring):
+                    var = create_var(var)
+                if not isinstance(var, core.Variable):
+                    raise TypeError(
+                        "Input of op creation must be string or variable")
+
+                kwargs[ipt] = get_cur_scope().get_var_name(var)
+
+        notemp_outputs = self.func.all_not_temp_output_args
+
+        for name in notemp_outputs:
+            if name not in kwargs:
+                kwargs[
+                    name] = self.func.__name__ + "@OUT@%d" % core.unique_integer(
+                    )
+
+        outputs = self.func.all_output_args
+        for opt in outputs:
+            if opt in kwargs:
+                var = kwargs[opt]
+                if isinstance(var, basestring):
+                    var = create_var(var)
+                if not isinstance(var, core.Variable):
+                    raise TypeError(
+                        "Output of op creation must be string or variable")
+                kwargs[opt] = get_cur_scope().get_var_name(var)
+
+        op = self.func(**kwargs)
+
+        self.net.net.add_op(op)
+
+        lst = [get_var(kwargs[opt]) for opt in notemp_outputs]
+        if len(lst) == 1:
+            return lst[0]
+        elif len(lst) == 0:
+            return None
+        else:
+            return lst
+
+
+class Network(object):
+    """
+    The network concept. It avoid user to manually create operator, create 
+    variable, and combine them into a Net. Just use Network.xxx can create the
+    operator, create variables in default scope, and add them into `self.net`.
+    
+    For example:
+    
+    ..  code-block: python
+    
+        net = Network()
+        out = net.add_two(X="a", Y="b")
+        fc_out = net.fc(X="out", W="fc.w")
+        
+        net.run(...)
+    """
+
+    def __init__(self):
+        self.net = core.Net.create()
+        funcs = (func_name for func_name in dir(op_creations)
+                 if not func_name.startswith("__"))
+
+        # TODO(yuyang18): This code can work, but do not generate a good
+        # docstring, try to give a better way generate function in runtime
+        # later.
+        for func_name in funcs:
+            func = getattr(op_creations, func_name)
+            impl = NetworkFunctor(func, self)
+            setattr(self, func_name, impl.__call__)
+        self.__complete_add_op__ = False
+
+    def infer_shape(self):
+        self.complete_add_op()
+        self.net.infer_shape(get_cur_scope())
+
+    def run(self, device_context):
+        self.complete_add_op()
+        self.net.run(get_cur_scope(), device_context)
+
+    def __str__(self):
+        return str(self.net)
+
+    def complete_add_op(self):
+        if not self.__complete_add_op__:
+            self.net.complete_add_op()
+            self.__complete_add_op__ = True
+
+
+if __name__ == '__main__':
+    net = Network()
+    out = net.add_two(X="a", Y="b")
+    fc_out = net.fc(X=out, W="fc.w", b="fc.b", activation="softmax")
+    net.complete_add_op()
+    print net

python/paddle/v2/framework/tests/CMakeLists.txt

@@ -3,7 +3,7 @@ add_python_test(test_framework
     test_scope.py
     test_default_scope_funcs.py
     test_op_creation_methods.py
-    test_plain_net.py
+    test_net.py
     test_tensor.py
     test_fc_op.py
     test_add_two_op.py
@@ -12,4 +12,5 @@ add_python_test(test_framework
     test_mul_op.py
     test_sigmoid_op.py
     test_softmax_op.py
-    test_rowwise_add_op.py)
+    test_rowwise_add_op.py
+    test_network.py)

python/paddle/v2/framework/tests/test_plain_net.py → python/paddle/v2/framework/tests/test_net.py

@@ -5,11 +5,11 @@ import unittest
 
 class TestNet(unittest.TestCase):
     def test_net_all(self):
-        net = core.PlainNet.create()
+        net = core.Net.create()
         op1 = op_creations.add_two(X="X", Y="Y", Out="Out")
         net.add_op(op1)
 
-        net2 = core.PlainNet.create()
+        net2 = core.Net.create()
         net2.add_op(op_creations.fc(X="X", W="w", Y="fc.out"))
         net2.complete_add_op(True)
         net.add_op(net2)

python/paddle/v2/framework/tests/test_network.py

+from paddle.v2.framework.network import Network
+import paddle.v2.framework.core as core
+import unittest
+
+
+class TestNet(unittest.TestCase):
+    def test_net_all(self):
+        net = Network()
+        out = net.add_two(X="X", Y="Y")
+        fc_out = net.fc(X=out, W="w")
+        net.complete_add_op()
+        self.assertTrue(isinstance(fc_out, core.Variable))
+        self.assertEqual(
+            '''Op(plain_net), inputs:(@EMPTY@, X, Y, w), outputs:(@TEMP@fc@0, add_two@OUT@0, fc@OUT@1).
+    Op(add_two), inputs:(X, Y), outputs:(add_two@OUT@0).
+    Op(fc), inputs:(add_two@OUT@0, w, @EMPTY@), outputs:(fc@OUT@1, @TEMP@fc@0).
+        Op(mul), inputs:(add_two@OUT@0, w), outputs:(@TEMP@fc@0).
+        Op(sigmoid), inputs:(@TEMP@fc@0), outputs:(fc@OUT@1).
+''', str(net))
+
+        net2 = Network()
+        tmp = net2.add_two(X="X", Y="Y")
+        self.assertTrue(isinstance(tmp, core.Variable))
+        net2.complete_add_op()
+        self.assertEqual(
+            '''Op(plain_net), inputs:(X, Y), outputs:(add_two@OUT@2).
+    Op(add_two), inputs:(X, Y), outputs:(add_two@OUT@2).
+''', str(net2))
+
+
+if __name__ == '__main__':
+    unittest.main()

python/paddle/v2/layer.py

@@ -324,6 +324,3 @@ def parse_network(output_layers, extra_layers=None):
 
 def get_layer(name):
     return config_base.__layer_map__.get(name)
-
-
-cp.begin_parse()