test=develop, polish code and merge conflict

paddle/fluid/framework/operator.cc

@@ -1073,7 +1073,8 @@ Scope* OperatorWithKernel::PrepareData(
 
 proto::VarType::Type OperatorWithKernel::IndicateDataType(
     const ExecutionContext& ctx) const {
-  int data_type = -1;
+  proto::VarType::Type defaut_data_type = static_cast<proto::VarType::Type>(-1);
+  proto::VarType::Type data_type = defaut_data_type;
   for (auto& input : this->inputs_) {
     const std::vector<const Variable*> vars = ctx.MultiInputVar(input.first);
     for (size_t i = 0; i < vars.size(); ++i) {
@@ -1090,18 +1091,19 @@ proto::VarType::Type OperatorWithKernel::IndicateDataType(
         if (t != nullptr) {
           PADDLE_ENFORCE(t->IsInitialized(), "Input %s(%lu)is not initialized",
                          input.first, i);
-          int tmp = static_cast<int>(t->type());
+          proto::VarType::Type tmp = t->type();
           PADDLE_ENFORCE(
-              tmp == data_type || data_type == -1,
+              tmp == data_type || data_type == defaut_data_type,
               "DataType of Paddle Op %s must be the same. Get (%d) != (%d)",
-              Type(), data_type, tmp);
+              Type(), DataTypeToString(data_type), DataTypeToString(tmp));
           data_type = tmp;
         }
       }
     }
   }
-  PADDLE_ENFORCE(data_type != -1, "DataType should be indicated by input");
-  return static_cast<proto::VarType::Type>(data_type);
+  PADDLE_ENFORCE(data_type != defaut_data_type,
+                 "DataType should be indicated by input");
+  return data_type;
 }
 
 OpKernelType OperatorWithKernel::GetExpectedKernelType(

paddle/fluid/framework/tensor_impl.h

@@ -25,7 +25,8 @@ inline const T* Tensor::data() const {
   check_memory_size();
   bool valid =
       std::is_same<T, void>::value || type_ == DataTypeTrait<T>::DataType;
-  PADDLE_ENFORCE(valid, "Tensor holds the wrong type, it holds %d", type_);
+  PADDLE_ENFORCE(valid, "Tensor holds the wrong type, it holds %d",
+                 DataTypeToString(type_));
 
   return reinterpret_cast<const T*>(
       reinterpret_cast<uintptr_t>(holder_->ptr()) + offset_);

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

@@ -1,48 +0,0 @@
-# Copyright (c) 2019 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 paddle.fluid as fluid
-from paddle.fluid.imperative.nn import EMBEDDING
-import paddle.fluid.framework as framework
-from paddle.fluid.optimizer import SGDOptimizer
-from paddle.fluid.imperative.base import to_variable
-import numpy as np
-
-
-class Split_test(fluid.imperative.Layer):
-    def __init__(self):
-        super(Split_test, self).__init__()
-
-    def _build_once(self, input):
-        pass
-
-    def forward(self, input):
-        out = fluid.layers.split(input, num_or_sections=4, dim=-1)
-        return out
-
-
-class TestImperativePtbRnn(unittest.TestCase):
-    def test_spilt(self):
-        with fluid.imperative.guard():
-            inp = to_variable(np.arange(160).reshape(4, 40).astype('float32'))
-            st = Split_test()
-            out = st(inp)
-            print(out)
-
-
-if __name__ == '__main__':
-    unittest.main()