Refine java api, add write_to_array and read_from_array op

src/common/log.h

@@ -85,18 +85,18 @@ struct Print {
 
  private:
   void print(LogLevel level) {
-    buffer_ << std::endl;
+    // buffer_ << std::endl;
     if (level == kLOG_ERROR) {
-      std::cerr << buffer_.str();
+      std::cerr << buffer_.str() << std::endl;
     } else {
-      std::cout << buffer_.str();
+      std::cout << buffer_.str() << std::endl;
     }
   }
   std::ostringstream buffer_;
 };
 
 struct ToLog {
-  ToLog(LogLevel level = kLOG_DEBUG, const std::string &info = "")
+  explicit ToLog(LogLevel level = kLOG_DEBUG, const std::string &info = "")
       : level_(level) {
     unsigned blanks =
         (unsigned)(level > kLOG_DEBUG ? (level - kLOG_DEBUG) * 4 : 1);

src/common/types.cpp

@@ -81,6 +81,8 @@ const char *G_OP_TYPE_LOGICAL_AND = "logical_and";
 const char *G_OP_TYPE_LOGICAL_OR = "logical_or";
 const char *G_OP_TYPE_LOGICAL_NOT = "logical_not";
 const char *G_OP_TYPE_LOGICAL_XOR = "logical_xor";
+const char *G_OP_TYPE_WRITE_TO_ARRAY = "write_to_array";
+const char *G_OP_TYPE_READ_FROM_ARRAY = "read_from_array";
 
 const char *G_OP_TYPE_QUANTIZE = "quantize";
 const char *G_OP_TYPE_DEQUANTIZE = "dequantize";
@@ -189,5 +191,7 @@ std::unordered_map<
         {G_OP_TYPE_LOGICAL_AND, {{"X", "Y"}, {"Out"}}},
         {G_OP_TYPE_LOGICAL_OR, {{"X", "Y"}, {"Out"}}},
         {G_OP_TYPE_LOGICAL_XOR, {{"X", "Y"}, {"Out"}}},
-        {G_OP_TYPE_LOGICAL_NOT, {{"X"}, {"Out"}}}};
+        {G_OP_TYPE_LOGICAL_NOT, {{"X"}, {"Out"}}},
+        {G_OP_TYPE_WRITE_TO_ARRAY, {{"X", "I"}, {"Out"}}},
+        {G_OP_TYPE_READ_FROM_ARRAY, {{"X", "I"}, {"Out"}}}};
 }  // namespace paddle_mobile

src/common/types.h

@@ -170,6 +170,8 @@ extern const char *G_OP_TYPE_LOGICAL_AND;
 extern const char *G_OP_TYPE_LOGICAL_OR;
 extern const char *G_OP_TYPE_LOGICAL_NOT;
 extern const char *G_OP_TYPE_LOGICAL_XOR;
+extern const char *G_OP_TYPE_WRITE_TO_ARRAY;
+extern const char *G_OP_TYPE_READ_FROM_ARRAY;
 
 extern const char *G_OP_TYPE_QUANTIZE;
 extern const char *G_OP_TYPE_DEQUANTIZE;

src/framework/attribute.h

@@ -90,6 +90,10 @@ class Attribute {
         attr.Set<int64_t>(attr_desc->l);
         break;
       }
+      case PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__BLOCK: {
+        attr.Set<int>(attr_desc->block_idx);
+        break;
+      }
       default:
         PADDLE_MOBILE_THROW_EXCEPTION("attr type not support");
     }

src/framework/executor.cpp

@@ -65,6 +65,7 @@ Executor<Device, T>::Executor(const Program<Device> &program,
     for (int j = 0; j < ops.size(); ++j) {
       std::shared_ptr<OpDesc> op_desc = ops[j];
       DLOG << "create op: " << op_desc->Type();
+
       auto op_handler = OpRegistry<Device>::CreateOp(
           op_desc->Type(), op_desc->GetInputs(), op_desc->GetOutputs(),
           op_desc->GetAttrMap(), program_.scope);

src/framework/load_ops.h

@@ -297,3 +297,12 @@ LOAD_OP1(logical_not, CPU);
 #ifdef LOGICAL_XOR_OP
 LOAD_OP1(logical_xor, CPU);
 #endif
+#ifdef WHILE_OP
+LOAD_OP1(while, CPU);
+#endif
+#ifdef WRITE_TO_ARRAY_OP
+LOAD_OP1(write_to_array, CPU);
+#endif
+#ifdef READ_FROM_ARRAY_OP
+LOAD_OP1(read_from_array, CPU);
+#endif

src/framework/lod_tensor.h

@@ -176,6 +176,8 @@ LoDTensor LodExpand(const LoDTensor &source, const LoD &lod, size_t level) {
   return tensor;
 }
 
+using LoDTensorArray = std::vector<LoDTensor>;
+
 // Get the absolute offset of a lod[start_level][start_idx:end_idx] and
 // relative length of details for every levels(i.e., [start_level: ]).
 //

src/framework/program/op_desc.cpp

@@ -41,9 +41,7 @@ OpDesc::OpDesc(PaddleMobile__Framework__Proto__OpDesc *desc) {
   for (int k = 0; k < desc->n_attrs; ++k) {
     PaddleMobile__Framework__Proto__OpDesc__Attr *attr = desc->attrs[k];
     std::string attr_name(attr->name);
-    if (attr->type != PADDLE_MOBILE__FRAMEWORK__PROTO__ATTR_TYPE__BLOCK) {
-      attrs_[attr_name] = Attribute::GetAttrValue(attr);
-    }
+    attrs_[attr_name] = Attribute::GetAttrValue(attr);
   }
 }
 

src/io/jni/paddle_mobile_jni.cpp

@@ -90,7 +90,8 @@ JNIEXPORT jboolean JNICALL Java_com_baidu_paddle_PML_loadQualified(
 #ifdef ENABLE_EXCEPTION
   try {
     isLoadOk = getPaddleMobileInstance()->Load(
-        jstring2cppstring(env, modelPath), optimize, qualified);
+        jstring2cppstring(env, modelPath), optimize, qualified, 1,
+        static_cast<bool>(lodMode));
   } catch (paddle_mobile::PaddleMobileException &e) {
     ANDROIDLOGE("jni got an PaddleMobileException! ", e.what());
     isLoadOk = false;
@@ -116,7 +117,7 @@ JNIEXPORT jboolean JNICALL Java_com_baidu_paddle_PML_loadCombined(
   try {
     isLoadOk = getPaddleMobileInstance()->Load(
         jstring2cppstring(env, modelPath), jstring2cppstring(env, paramPath),
-        optimize);
+        optimize, false, 1, static_cast<bool>(lodMode));
   } catch (paddle_mobile::PaddleMobileException &e) {
     ANDROIDLOGE("jni got an PaddleMobileException! ", e.what());
     isLoadOk = false;
@@ -142,7 +143,7 @@ JNIEXPORT jboolean JNICALL Java_com_baidu_paddle_PML_loadCombinedQualified(
   try {
     isLoadOk = getPaddleMobileInstance()->Load(
         jstring2cppstring(env, modelPath), jstring2cppstring(env, paramPath),
-        optimize, qualified);
+        optimize, qualified, 1, static_cast<bool>(lodMode));
   } catch (paddle_mobile::PaddleMobileException &e) {
     ANDROIDLOGE("jni got an PaddleMobileException! ", e.what());
     isLoadOk = false;

src/operators/controlflow/tensor_array_read_write_op.cpp

+/* 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. */
+
+#include "operators/controlflow/tensor_array_read_write_op.h"
+
+namespace paddle_mobile {
+namespace operators {
+
+#ifdef WRITE_TO_ARRAY_OP
+template <typename Dtype, typename T>
+void WriteToArrayOp<Dtype, T>::InferShape() const {}
+#endif  // WRITE_TO_ARRAY_OP
+
+#ifdef READ_FROM_ARRAY_OP
+template <typename Dtype, typename T>
+void ReadFromArrayOp<Dtype, T>::InferShape() const {}
+#endif  // READ_FROM_ARRAY_OP
+
+}  // namespace operators
+}  // namespace paddle_mobile
+
+namespace ops = paddle_mobile::operators;
+
+#ifdef PADDLE_MOBILE_CPU
+#ifdef WRITE_TO_ARRAY_OP
+REGISTER_OPERATOR_CPU(write_to_array, ops::WriteToArrayOp);
+#endif  // WRITE_TO_ARRAY_OP
+
+#ifdef READ_FROM_ARRAY_OP
+REGISTER_OPERATOR_CPU(read_from_array, ops::ReadFromArrayOp);
+#endif  // READ_FROM_ARRAY_OP
+#endif

src/operators/controlflow/tensor_array_read_write_op.h

+/* 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. */
+
+#pragma once
+
+#include <string>
+#include "framework/operator.h"
+#include "operators/kernel/tensor_array_read_write_kernel.h"
+#include "operators/op_param.h"
+
+namespace paddle_mobile {
+namespace operators {
+
+#ifdef WRITE_TO_ARRAY_OP
+DECLARE_OPERATOR(WriteToArray, WriteToArrayParam, WriteToArrayKernel);
+#endif  // WRITE_TO_ARRAY_OP
+
+#ifdef READ_FROM_ARRAY_OP
+DECLARE_OPERATOR(ReadFromArray, ReadFromArrayParam, ReadFromArrayKernel);
+#endif  // WRITE_TO_ARRAY_OP
+
+}  // namespace operators
+}  // namespace paddle_mobile

src/operators/controlflow/while_op.cpp

+/* 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. */
+
+#include "operators/controlflow/while_op.h"
+
+namespace paddle_mobile {
+namespace operators {
+
+#ifdef WHILE_OP
+template <typename Dtype, typename T>
+void WhileOp<Dtype, T>::InferShape() const {
+  // TODO(hjchen2)
+}
+#endif  // WHILE_OP
+
+}  // namespace operators
+}  // namespace paddle_mobile
+
+namespace ops = paddle_mobile::operators;
+
+#ifdef PADDLE_MOBILE_CPU
+#ifdef WHILE_OP
+REGISTER_OPERATOR_CPU(while, ops::WhileOp);
+#endif  // WHILE_OP
+#endif

src/operators/controlflow/while_op.h

+/* 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. */
+
+#pragma once
+
+#include <string>
+#include "framework/operator.h"
+#include "operators/kernel/while_kernel.h"
+#include "operators/op_param.h"
+
+namespace paddle_mobile {
+namespace operators {
+
+#ifdef WHILE_OP
+DECLARE_OPERATOR(While, WhileParam, WhileKernel);
+#endif  // WHILE_OP
+
+}  // namespace operators
+}  // namespace paddle_mobile

src/operators/kernel/arm/tensor_array_read_write_kernel.cpp

+/* 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. */
+
+#include "operators/kernel/tensor_array_read_write_kernel.h"
+
+namespace paddle_mobile {
+namespace operators {
+
+#ifdef WRITE_TO_ARRAY_OP
+template <>
+bool WriteToArrayKernel<CPU, float>::Init(WriteToArrayParam<CPU> *param) {
+  return true;
+}
+
+template <>
+void WriteToArrayKernel<CPU, float>::Compute(
+    const WriteToArrayParam<CPU> &param) {
+  int64_t offset = param.index_->data<int64_t>()[0];
+  if (offset >= param.output_->size()) {
+    param.output_->resize(offset);
+  }
+  framework::LoDTensor *out_tensor = &(param.output_->at(offset));
+  out_tensor->set_lod(param.input_->lod());
+  if (param.input_->memory_size() > 0) {
+    TensorCopy(*(param.input_), out_tensor);
+  }
+}
+#endif  // WRITE_TO_ARRAY_OP
+
+#ifdef READ_FROM_ARRAY_OP
+template <>
+bool ReadFromArrayKernel<CPU, float>::Init(ReadFromArrayParam<CPU> *param) {
+  return true;
+}
+
+template <>
+void ReadFromArrayKernel<CPU, float>::Compute(
+    const ReadFromArrayParam<CPU> &param) {
+  int64_t offset = param.index_->data<int64_t>()[0];
+  if (offset < param.input_->size()) {
+    TensorCopy(param.input_->at(offset), param.output_);
+  }
+}
+#endif  // READ_FROM_ARRAY_OP
+
+}  // namespace operators
+}  // namespace paddle_mobile

src/operators/kernel/arm/while_kernel.cpp

+/* 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. */
+
+#include "operators/kernel/while_kernel.h"
+
+namespace paddle_mobile {
+namespace operators {
+
+#ifdef WHILE_OP
+template <>
+bool WhileKernel<CPU, float>::Init(WhileParam<CPU> *param) {
+  return true;
+}
+
+template <>
+void WhileKernel<CPU, float>::Compute(const WhileParam<CPU> &param) {
+  // TODO(hjchen2)
+}
+#endif  // WHILE_OP
+
+}  // namespace operators
+}  // namespace paddle_mobile

src/operators/kernel/tensor_array_read_write_kernel.h

+/* 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. */
+
+#pragma once
+
+#include "framework/operator.h"
+#include "operators/op_param.h"
+
+namespace paddle_mobile {
+namespace operators {
+
+#ifdef WRITE_TO_ARRAY_OP
+DECLARE_KERNEL(WriteToArray, WriteToArrayParam);
+#endif  // WRITE_TO_ARRAY_OP
+
+#ifdef READ_FROM_ARRAY_OP
+DECLARE_KERNEL(ReadFromArray, ReadFromArrayParam);
+#endif  // READ_FROM_ARRAY_OP
+
+}  // namespace operators
+}  // namespace paddle_mobile

src/operators/kernel/while_kernel.h

+/* 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. */
+
+#pragma once
+
+#include "framework/operator.h"
+#include "operators/op_param.h"
+
+namespace paddle_mobile {
+namespace operators {
+
+#ifdef WHILE_OP
+template <typename Dtype>
+class WhileParam : public OpParam {
+ public:
+  WhileParam(const VariableNameMap &inputs, const VariableNameMap &outputs,
+             const AttributeMap &attrs, const Scope &scope)
+      : inputs_(inputs), outputs_(outputs), scope_(scope) {
+    cond_ =
+        OpParam::GetVarValue<framework::LoDTensor>("Condition", inputs, scope);
+    sub_block_ = OpParam::GetAttr<int>("sub_block", attrs);
+  }
+
+ public:
+  framework::LoDTensor *cond_;
+  int sub_block_;
+  const VariableNameMap inputs_;
+  const VariableNameMap outputs_;
+  const Scope scope_;
+};
+
+DECLARE_KERNEL(While, WhileParam);
+#endif  // WHILE_OP
+
+}  // namespace operators
+}  // namespace paddle_mobile

src/operators/math/gemm.h

@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #pragma once
+#include <cstring>
 #include <string>
 #include "common/log.h"
 #include "memory/t_malloc.h"

src/operators/op_param.h

@@ -2991,5 +2991,63 @@ class LogicalUnaryParam : public OpParam {
 };
 #endif  // LOGICAL_NOT_OP
 
+// #ifdef WHILE_OP
+// template <typename Dtype>
+// class WhileParam : public OpParam {
+//  public:
+//   WhileParam(const VariableNameMap &inputs,
+//              const VariableNameMap &outputs, const AttributeMap &attrs,
+//              const Scope &scope) {
+//     cond_ = OpParam::GetVarValue<framework::LoDTensor>("Condition", inputs,
+//     scope); block_desc_ = OpParam::GetAttr<framework::BlockDesc
+//     *>("sub_block", attrs);
+//   }
+//
+//  public:
+//   framework::LoDTensor *cond_;
+//   const framework::BlockDesc *block_desc_;
+// };
+// #endif  // WHILE_OP
+
+#ifdef WRITE_TO_ARRAY_OP
+template <typename Dtype>
+class WriteToArrayParam : public OpParam {
+ public:
+  WriteToArrayParam(const VariableNameMap &inputs,
+                    const VariableNameMap &outputs, const AttributeMap &attrs,
+                    const Scope &scope) {
+    input_ = OpParam::GetVarValue<framework::LoDTensor>("X", inputs, scope);
+    index_ = OpParam::GetVarValue<framework::LoDTensor>("I", inputs, scope);
+    output_ =
+        OpParam::GetVarValue<framework::LoDTensorArray>("Out", outputs, scope);
+  }
+
+ public:
+  framework::LoDTensor *input_;
+  framework::LoDTensor *index_;
+  framework::LoDTensorArray *output_;
+};
+#endif
+
+#ifdef READ_FROM_ARRAY_OP
+template <typename Dtype>
+class ReadFromArrayParam : public OpParam {
+ public:
+  ReadFromArrayParam(const VariableNameMap &inputs,
+                     const VariableNameMap &outputs, const AttributeMap &attrs,
+                     const Scope &scope) {
+    input_ =
+        OpParam::GetVarValue<framework::LoDTensorArray>("X", inputs, scope);
+    index_ = OpParam::GetVarValue<framework::LoDTensor>("I", inputs, scope);
+    output_ = OpParam::GetVarValue<framework::LoDTensor>("Out", outputs, scope);
+  }
+
+ public:
+  framework::LoDTensorArray *input_;
+  framework::LoDTensor *index_;
+  framework::LoDTensor *output_;
+};
+#endif
+
 }  // namespace operators
 }  // namespace paddle_mobile

test/CMakeLists.txt

@@ -337,8 +337,8 @@ if (NOT FOUND_MATCH)
     target_link_libraries(test-genet paddle-mobile)
 
     # gen test
-    ADD_EXECUTABLE(test-sigmoid operators/test_sigmoid_op.cpp test_include.h)
-    target_link_libraries(test-sigmoid paddle-mobile)
+    ADD_EXECUTABLE(test-sigmoid-op operators/test_sigmoid_op.cpp test_include.h)
+    target_link_libraries(test-sigmoid-op paddle-mobile)
 
     # gen test
     ADD_EXECUTABLE(test-depthwise-conv-op operators/test_depthwise_conv_op.cpp test_helper.h test_include.h executor_for_test.h)
@@ -408,14 +408,14 @@ if (NOT FOUND_MATCH)
     ADD_EXECUTABLE(test-ocr net/test_ocr.cpp test_helper.h test_include.h)
     target_link_libraries(test-ocr paddle-mobile)
 
-    ADD_EXECUTABLE(test-sequence-expand operators/test_sequence_expand_op.cpp test_helper.h test_include.h)
-    target_link_libraries(test-sequence-expand paddle-mobile)
+    ADD_EXECUTABLE(test-sequence-expand-op operators/test_sequence_expand_op.cpp test_helper.h test_include.h)
+    target_link_libraries(test-sequence-expand-op paddle-mobile)
 
-    ADD_EXECUTABLE(test-sequence-pool operators/test_sequence_pool_op.cpp test_helper.h test_include.h)
-    target_link_libraries(test-sequence-pool paddle-mobile)
+    ADD_EXECUTABLE(test-sequence-pool-op operators/test_sequence_pool_op.cpp test_helper.h test_include.h)
+    target_link_libraries(test-sequence-pool-op paddle-mobile)
 
-    ADD_EXECUTABLE(test-sequence-softmax operators/test_sequence_softmax_op.cpp test_helper.h test_include.h)
-    target_link_libraries(test-sequence-softmax paddle-mobile)
+    ADD_EXECUTABLE(test-sequence-softmax-op operators/test_sequence_softmax_op.cpp test_helper.h test_include.h)
+    target_link_libraries(test-sequence-softmax-op paddle-mobile)
 
     # gen test
     ADD_EXECUTABLE(test-vgg16ssd net/test_vgg16ssd.cpp test_helper.h test_include.h)

test/operators/test_conv_op.cpp

@@ -222,27 +222,8 @@ int TestConvOp(int in_channels, int in_height, int in_width, int out_channels,
 
 }  // namespace paddle_mobile
 
-int main(int argc, char *argv[]) {
-  if (argc < 5) {
-    LOG(paddle_mobile::kLOG_INFO)
-        << "Usage:\n"
-        << "  ./test-int8-conv-op in_channels in_height in_width out_channels "
-           "[groups]\n"
-        << "  params:\n"
-        << "   -in_channels: int, input image's channels\n"
-        << "   -in_height: int, input image's height\n"
-        << "   -in_width: int, input image's width\n"
-        << "   -out_channels: int, conv output channels\n";
-    return 1;
-  }
-  int in_channels = atoi(argv[1]);
-  int in_height = atoi(argv[2]);
-  int in_width = atoi(argv[3]);
-  int out_channels = atoi(argv[4]);
-  int groups = 1;
-  if (argc == 6) {
-    groups = atoi(argv[5]);
-  }
+int TestAll(const int in_channels, const int in_height, const int in_width,
+            const int out_channels, const int groups) {
   // kernel = 3, pad = 0, stride = 1
   LOG(paddle_mobile::kLOG_INFO) << "float, kernel=3, pad=0, stride=1";
   paddle_mobile::TestConvOp<int8_t, int32_t, 3, 0, 1>(
@@ -313,3 +294,18 @@ int main(int argc, char *argv[]) {
 
   return 0;
 }
+
+int main() {
+  TestAll(1, 5, 5, 1, 1);
+  TestAll(1, 5, 5, 10, 1);
+  TestAll(10, 5, 5, 10, 10);
+
+  TestAll(5, 33, 33, 5, 1);
+  TestAll(5, 33, 33, 13, 1);
+  TestAll(13, 33, 33, 13, 13);
+
+  TestAll(5, 33, 13, 5, 1);
+  TestAll(5, 33, 13, 13, 1);
+  TestAll(13, 33, 13, 13, 13);
+  return 0;
+}

test/operators/test_log_op.cpp

@@ -76,6 +76,5 @@ int main() {
   paddle_mobile::TestLogOp({1, 1, 2, 3});
   paddle_mobile::TestLogOp({1, 3, 11, 22});
   paddle_mobile::TestLogOp({1, 32, 112, 112});
-  std::cout << "test log op pass." << std::endl;
   return 0;
 }

test/operators/test_quantize_op.cpp

@@ -92,18 +92,10 @@ static float find_abs_max(const Tensor *input) {
   return max_abs;
 }
 
-int TestQuqntizeOp(int argc, char *argv[]) {
-  if (argc < 5) {
-    std::cout << "Usage: ./test-quantize-op batch_size channel height width"
-              << std::endl;
-    return 1;
-  }
-  int batch_size = atoi(argv[1]);
-  int channel = atoi(argv[2]);
-  int height = atoi(argv[3]);
-  int width = atoi(argv[4]);
-  std::cout << "batch_size: " << batch_size << ", channel: " << channel
-            << ", height: " << height << ", width: " << width << std::endl;
+int TestQuqntizeOp(const int batch_size, const int channel, const int height,
+                   const int width) {
+  DLOG << "batch_size: " << batch_size << ", channel: " << channel
+       << ", height: " << height << ", width: " << width;
   framework::DDim dim =
       framework::make_ddim({batch_size, channel, height, width});
 
@@ -140,9 +132,7 @@ int TestQuqntizeOp(int argc, char *argv[]) {
   framework::Tensor output_cmp;
   output_cmp.Resize(output->dims());
   float scale = 127 / output_scale_cmp;
-  // quantize<round::RoundToEven>(input, scale, &output_cmp);
-  // quantize<round::RoundAwayZero>(input, scale, &output_cmp);
-  quantize<round::RoundTowardsZero>(input, scale, &output_cmp);
+  quantize<round::RoundAwayZero>(input, scale, &output_cmp);
   int8_t *output_cmp_data = output_cmp.data<int8_t>();
   for (int i = 0; i < output->numel(); ++i) {
     PADDLE_MOBILE_ENFORCE(output_data[i] == output_cmp_data[i],
@@ -157,5 +147,7 @@ int TestQuqntizeOp(int argc, char *argv[]) {
 }  // namespace paddle_mobile
 
 int main(int argc, char *argv[]) {
-  return paddle_mobile::TestQuqntizeOp(argc, argv);
+  TestQuqntizeOp(1, 10, 10, 5);
+  TestQuqntizeOp(1, 111, 111, 5);
+  TestQuqntizeOp(5, 111, 111, 5);
 }

test/operators/test_sequence_pool_op.cpp

@@ -59,7 +59,7 @@ int TestSequencePoolOp(const framework::LoDTensor &input_x,
 int main(int argc, char *argv[]) {
   framework::LoDTensor input_x, output;
   // case 1
-  std::cerr << "running max case 1" << std::endl;
+  DLOG << "running max case 1";
   {
     std::vector<float> data{1, 2, 3, 4};
     input_x.Resize(framework::make_ddim({4, 1}));
@@ -71,14 +71,14 @@ int main(int argc, char *argv[]) {
     std::vector<float> expect_data{2, 4};
     for (int i = 0; i < 2; ++i) {
       if (output.data<float>()[i] != expect_data[i]) {
-        std::cerr << "output[" << i << "]: " << output.data<float>()[i]
-                  << " != expect[" << i << "]: " << expect_data[i] << std::endl;
+        DLOG << "output[" << i << "]: " << output.data<float>()[i]
+             << " != expect[" << i << "]: " << expect_data[i];
         return 1;
       }
     }
   }
   // case 2
-  std::cerr << "running max case 2" << std::endl;
+  DLOG << "running max case 2";
   {
     std::vector<float> data{1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
     input_x.Resize(framework::make_ddim({data.size(), 1}));
@@ -90,13 +90,13 @@ int main(int argc, char *argv[]) {
     std::vector<float> expect_data{3, 10};
     for (int i = 0; i < 2; ++i) {
       if (output.data<float>()[i] != expect_data[i]) {
-        std::cerr << "output[" << i << "]: " << output.data<float>()[i]
-                  << " != expect[" << i << "]: " << expect_data[i] << std::endl;
+        DLOG << "output[" << i << "]: " << output.data<float>()[i]
+             << " != expect[" << i << "]: " << expect_data[i];
         return 1;
       }
     }
   }
-  std::cerr << "running max case 3" << std::endl;
+  DLOG << "running max case 3";
   // case 3
   {
     std::vector<float> data{1, 2, 3, 4, 5, 6, 7, 8};
@@ -109,14 +109,14 @@ int main(int argc, char *argv[]) {
     std::vector<float> expect_data{3, 4, 7, 8};
     for (int i = 0; i < 4; ++i) {
       if (output.data<float>()[i] != expect_data[i]) {
-        std::cerr << "output[" << i << "]: " << output.data<float>()[i]
-                  << " != expect[" << i << "]: " << expect_data[i] << std::endl;
+        DLOG << "output[" << i << "]: " << output.data<float>()[i]
+             << " != expect[" << i << "]: " << expect_data[i];
         return 1;
       }
     }
   }
   // case 4
-  std::cerr << "running max case 4" << std::endl;
+  DLOG << "running max case 4";
   {
     std::vector<float> data{1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
                             11, 12, 13, 14, 15, 16, 17, 18, 19, 20};
@@ -129,14 +129,14 @@ int main(int argc, char *argv[]) {
     std::vector<float> expect_data{6, 7, 8, 9, 10, 16, 17, 18, 19, 20};
     for (int i = 0; i < 10; ++i) {
       if (output.data<float>()[i] != expect_data[i]) {
-        std::cerr << "output[" << i << "]: " << output.data<float>()[i]
-                  << " != expect[" << i << "]: " << expect_data[i] << std::endl;
+        DLOG << "output[" << i << "]: " << output.data<float>()[i]
+             << " != expect[" << i << "]: " << expect_data[i];
         return 1;
       }
     }
   }
   // case 1
-  std::cerr << "running sum case 1" << std::endl;
+  DLOG << "running sum case 1";
   {
     std::vector<float> data{1, 2, 3, 4};
     input_x.Resize(framework::make_ddim({4, 1}));
@@ -148,14 +148,14 @@ int main(int argc, char *argv[]) {
     std::vector<float> expect_data{3, 7};
     for (int i = 0; i < 2; ++i) {
       if (output.data<float>()[i] != expect_data[i]) {
-        std::cerr << "output[" << i << "]: " << output.data<float>()[i]
-                  << " != expect[" << i << "]: " << expect_data[i] << std::endl;
+        DLOG << "output[" << i << "]: " << output.data<float>()[i]
+             << " != expect[" << i << "]: " << expect_data[i];
         return 1;
       }
     }
   }
   // case 2
-  std::cerr << "running sum case 2" << std::endl;
+  DLOG << "running sum case 2";
   {
     std::vector<float> data{1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
     input_x.Resize(framework::make_ddim({data.size(), 1}));
@@ -167,14 +167,14 @@ int main(int argc, char *argv[]) {
     std::vector<float> expect_data{6, 49};
     for (int i = 0; i < 2; ++i) {
       if (output.data<float>()[i] != expect_data[i]) {
-        std::cerr << "output[" << i << "]: " << output.data<float>()[i]
-                  << " != expect[" << i << "]: " << expect_data[i] << std::endl;
+        DLOG << "output[" << i << "]: " << output.data<float>()[i]
+             << " != expect[" << i << "]: " << expect_data[i];
         return 1;
       }
     }
   }
   // case 3
-  std::cerr << "running sum case 3" << std::endl;
+  DLOG << "running sum case 3";
   {
     std::vector<float> data{1, 2, 3, 4, 5, 6, 7, 8};
     input_x.Resize(framework::make_ddim({4, 2}));
@@ -186,14 +186,14 @@ int main(int argc, char *argv[]) {
     std::vector<float> expect_data{4, 6, 12, 14};
     for (int i = 0; i < 4; ++i) {
       if (output.data<float>()[i] != expect_data[i]) {
-        std::cerr << "output[" << i << "]: " << output.data<float>()[i]
-                  << " != expect[" << i << "]: " << expect_data[i] << std::endl;
+        DLOG << "output[" << i << "]: " << output.data<float>()[i]
+             << " != expect[" << i << "]: " << expect_data[i];
         return 1;
       }
     }
   }
   // case 4
-  std::cerr << "running sum case 4" << std::endl;
+  DLOG << "running sum case 4";
   {
     std::vector<float> data{1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
                             11, 12, 13, 14, 15, 16, 17, 18, 19, 20};
@@ -206,14 +206,14 @@ int main(int argc, char *argv[]) {
     std::vector<float> expect_data{7, 9, 11, 13, 15, 27, 29, 31, 33, 35};
     for (int i = 0; i < 10; ++i) {
       if (output.data<float>()[i] != expect_data[i]) {
-        std::cerr << "output[" << i << "]: " << output.data<float>()[i]
-                  << " != expect[" << i << "]: " << expect_data[i] << std::endl;
+        DLOG << "output[" << i << "]: " << output.data<float>()[i]
+             << " != expect[" << i << "]: " << expect_data[i];
         return 1;
       }
     }
   }
   // case 1
-  std::cerr << "running first case 1" << std::endl;
+  DLOG << "running first case 1";
   {
     std::vector<float> data{1, 2, 3, 4};
     input_x.Resize(framework::make_ddim({4, 1}));
@@ -225,14 +225,14 @@ int main(int argc, char *argv[]) {
     std::vector<float> expect_data{1, 3};
     for (int i = 0; i < 2; ++i) {
       if (output.data<float>()[i] != expect_data[i]) {
-        std::cerr << "output[" << i << "]: " << output.data<float>()[i]
-                  << " != expect[" << i << "]: " << expect_data[i] << std::endl;
+        DLOG << "output[" << i << "]: " << output.data<float>()[i]
+             << " != expect[" << i << "]: " << expect_data[i];
         return 1;
       }
     }
   }
   // case 2
-  std::cerr << "running first case 2" << std::endl;
+  DLOG << "running first case 2";
   {
     std::vector<float> data{1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
     input_x.Resize(framework::make_ddim({data.size(), 1}));
@@ -244,14 +244,14 @@ int main(int argc, char *argv[]) {
     std::vector<float> expect_data{1, 4};
     for (int i = 0; i < 2; ++i) {
       if (output.data<float>()[i] != expect_data[i]) {
-        std::cerr << "output[" << i << "]: " << output.data<float>()[i]
-                  << " != expect[" << i << "]: " << expect_data[i] << std::endl;
+        DLOG << "output[" << i << "]: " << output.data<float>()[i]
+             << " != expect[" << i << "]: " << expect_data[i];
         return 1;
       }
     }
   }
   // case 3
-  std::cerr << "running first case 3" << std::endl;
+  DLOG << "running first case 3";
   {
     std::vector<float> data{1, 2, 3, 4, 5, 6, 7, 8};
     input_x.Resize(framework::make_ddim({4, 2}));
@@ -263,14 +263,14 @@ int main(int argc, char *argv[]) {
     std::vector<float> expect_data{1, 2, 5, 6};
     for (int i = 0; i < 4; ++i) {
       if (output.data<float>()[i] != expect_data[i]) {
-        std::cerr << "output[" << i << "]: " << output.data<float>()[i]
-                  << " != expect[" << i << "]: " << expect_data[i] << std::endl;
+        DLOG << "output[" << i << "]: " << output.data<float>()[i]
+             << " != expect[" << i << "]: " << expect_data[i];
         return 1;
       }
     }
   }
   // case 4
-  std::cerr << "running first case 4" << std::endl;
+  DLOG << "running first case 4";
   {
     std::vector<float> data{1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
                             11, 12, 13, 14, 15, 16, 17, 18, 19, 20};
@@ -283,8 +283,8 @@ int main(int argc, char *argv[]) {
     std::vector<float> expect_data{1, 2, 3, 4, 5, 11, 12, 13, 14, 15};
     for (int i = 0; i < 10; ++i) {
       if (output.data<float>()[i] != expect_data[i]) {
-        std::cerr << "output[" << i << "]: " << output.data<float>()[i]
-                  << " != expect[" << i << "]: " << expect_data[i] << std::endl;
+        DLOG << "output[" << i << "]: " << output.data<float>()[i]
+             << " != expect[" << i << "]: " << expect_data[i];
         return 1;
       }
     }

test/operators/test_sigmoid_op.cpp

@@ -76,6 +76,5 @@ int main() {
   paddle_mobile::TestSigmoidOp({1, 1, 2, 3});
   paddle_mobile::TestSigmoidOp({1, 3, 11, 22});
   paddle_mobile::TestSigmoidOp({1, 32, 112, 112});
-  std::cout << "test sigmoid op pass." << std::endl;
   return 0;
 }

test/operators/test_tanh_op.cpp

@@ -58,7 +58,7 @@ int TestTanhOp(const std::vector<int> input_shape) {
   const float *output_data = output->data<float>();
   for (int i = 0; i < output->numel(); ++i) {
     float gap = output_data[i] - output_cmp_data[i];
-    if (std::abs(gap / (output_data[i] + 1e-5)) > 1e-3) {
+    if (gap > 1e-5 && std::abs(gap / (output_data[i] + 1e-5)) > 1e-3) {
       LOG(kLOG_INFO) << "output_data[" << i << "] = " << output_data[i]
                      << ", output_cmp_data[" << i
                      << "] = " << output_cmp_data[i];

tools/ci_build.sh

@@ -15,6 +15,7 @@
 # limitations under the License.
 
 set -e
+source ./ci_run_test.sh
 
 function print_usage() {
   echo "\n${RED}Usage${NONE}:
@@ -63,7 +64,7 @@ function check_ndk() {
 }
 
 function build_android_armv7_cpu_only() {
-  rm -rf ../build/armeabi-v7a
+#  rm -rf ../build/armeabi-v7a
   cmake .. \
     -B"../build/armeabi-v7a" \
     -DANDROID_ABI="armeabi-v7a with NEON" \
@@ -82,7 +83,7 @@ function build_android_armv7_cpu_only() {
 }
 
 function build_android_armv7_gpu() {
-  rm -rf ../build/armeabi-v7a
+#  rm -rf ../build/armeabi-v7a
   cmake .. \
     -B"../build/armeabi-v7a" \
     -DANDROID_ABI="armeabi-v7a with NEON" \
@@ -231,6 +232,11 @@ function build_linux_fpga() {
     docker build -t paddle-mobile:dev - < Dockerfile
   fi
   docker run --rm -v `pwd`:/workspace paddle-mobile:dev bash /workspace/tools/docker_build_fpga.sh
+  cd -
+}
+
+function run_android_test() {
+  ExecuteAndroidTest $1
 }
 
 function main() {
@@ -239,9 +245,11 @@ function main() {
   case $CMD in
     android_armv7)
       build_android_armv7
+      run_android_test armeabi-v7a 
       ;;
     android_armv8)
       build_android_armv8
+      run_android_test arm64-v8a
       ;;
     ios)
       build_ios

tools/ci_run_test.sh

+#!/usr/bin/env bash
+
+operators=
+
+function AddTest() {
+  operators="${operators} $1"
+}
+
+function ExecuteAndroidTest() {
+  platform=$1
+  adb shell rm -rf /data/local/tmp/*
+  adb push ../build/${platform}/build/libpaddle-mobile.so /data/local/tmp/
+  for op in ${operators}
+  do
+    adb push ../test/build/test-${op}-op /data/local/tmp/
+    adb shell "cd /data/local/tmp/; LD_LIBRARY_PATH=. ./test-${op}-op"
+    echo "${BLUE}run test ${op} pass${NONE}"
+  done
+}
+
+AddTest batchnorm
+AddTest cast
+AddTest conv
+AddTest dequantize
+#AddTest elementwiseadd
+AddTest log
+AddTest logical-and
+AddTest logical-not
+AddTest logical-or
+AddTest logical-xor
+AddTest pool
+AddTest quantize
+AddTest relu
+AddTest relu6
+AddTest sequence-expand
+AddTest sequence-pool
+AddTest sequence-softmax
+AddTest sigmoid
+AddTest softmax
+AddTest tanh
+AddTest topk

tools/docker_build_fpga.sh

+#!/usr/bin/env bash
+
 apt-get update
 apt-get install -y gcc g++ cmake
 

tools/op.cmake

@@ -285,6 +285,9 @@ if(NOT FOUND_MATCH)
   set(LOGICAL_OR_OP ON)
   set(LOGICAL_NOT_OP ON)
   set(LOGICAL_XOR_OP ON)
+  set(WHILE_OP ON)
+  set(WRITE_TO_ARRAY_OP ON)
+  set(READ_FROM_ARRAY_OP ON)
 endif()
 
   # option(BATCHNORM_OP "" ON)
@@ -559,3 +562,13 @@ endif()
 if (FUSION_DECONVADDRELU_OP)
   add_definitions(-DFUSION_DECONVADDRELU_OP)
 endif()
+
+if (WHILE_OP)
+  add_definitions(-DWHILE_OP)
+endif()
+if (WRITE_TO_ARRAY_OP)
+  add_definitions(-DWRITE_TO_ARRAY_OP)
+endif()
+if (READ_FROM_ARRAY_OP)
+  add_definitions(-DREAD_FROM_ARRAY_OP)
+endif()