!7943 fix sync code bug to support fm

Merge pull request !7943 from yangjie159/sync_code

mindspore/lite/nnacl/fp32_grad/binary_cross_entropy.c

@@ -0,0 +1,60 @@
+/*
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * 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 <math.h>
+#include "nnacl/fp32_grad/binary_cross_entropy.h"
+
+static void BinaryCrossEntropyLossKernel(const int input_size, const int reduction, const float *input_x,
+                                         const float *input_y, const float *weight, float *loss, float *tmp_loss) {
+  float epsilon = 1e-12;
+  if (reduction == 0) {
+    for (int i = 0; i < input_size; i++) {
+      float value =
+        -weight[i] * (input_y[i] * logf(input_x[i] + epsilon) + (1 - input_y[i]) * logf(1 - input_x[i] + epsilon));
+      loss[i] = value;
+    }
+  } else {
+    for (int i = 0; i < input_size; i++) {
+      float value =
+        -weight[i] * (input_y[i] * logf(input_x[i] + epsilon) + (1 - input_y[i]) * logf(1 - input_x[i] + epsilon));
+      tmp_loss[i] = value;
+    }
+  }
+}
+
+void BinaryCrossEntropy(const int input_size, const int reduction, const float *input_x, const float *input_y,
+                        const float *weight, float *loss, float *tmp_loss) {
+  loss[0] = 0.0f;
+  BinaryCrossEntropyLossKernel(input_size, reduction, input_x, input_y, weight, loss, tmp_loss);
+  if (reduction != 0) {
+    if (input_size % 2 == 1) {
+      tmp_loss[0] += tmp_loss[input_size - 1];
+    }
+    for (int stride = input_size / 2; stride > 0; stride >>= 1) {
+      for (int i = 0; i < stride; i++) {
+        tmp_loss[i] += tmp_loss[i + stride];
+      }
+
+      if (stride > 2 && stride % 2 == 1) {
+        tmp_loss[0] += tmp_loss[stride - 1];
+      }
+    }
+    loss[0] += tmp_loss[0];
+    if (reduction == 1) {
+      loss[0] /= input_size;
+    }
+  }
+}

mindspore/lite/nnacl/fp32_grad/binary_cross_entropy.h

@@ -0,0 +1,36 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * 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.
+ */
+#ifndef MINDSPORE_LITE_NNACL_BINARY_CROSS_ENTROPY_H_
+#define MINDSPORE_LITE_NNACL_BINARY_CROSS_ENTROPY_H_
+
+#include "nnacl/op_base.h"
+
+typedef struct BinaryCrossEntropyParameter {
+  OpParameter op_parameter_;
+  int reduction;
+} BinaryCrossEntropyParameter;
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+void BinaryCrossEntropy(const int input_size, const int reduction, const float *input_x, const float *input_y,
+                        const float *weight, float *loss, float *tmp_loss);
+
+#ifdef __cplusplus
+}
+#endif
+#endif  // MINDSPORE_LITE_NNACL_BINARY_CROSS_ENTROPY_H_

mindspore/lite/nnacl/fp32_grad/binary_cross_entropy_grad.c

@@ -0,0 +1,42 @@
+/*
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * 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 "nnacl/fp32_grad/binary_cross_entropy_grad.h"
+
+#define MAX(a, b) ((a) > (b) ? (a) : (b))
+
+int BinaryCrossEntropyGrad(const int input_size, const int reduction, const float *input_x, const float *input_y,
+                           const float *weight, const float *dloss, float *dx) {
+  float epsilon = 1e-12;
+  if (reduction == 0) {
+    for (int i = 0; i < input_size; i++) {
+      float denominator = MAX(input_x[i] * (1 - input_x[i]), epsilon);
+      float value = weight[i] * (input_x[i] - input_y[i]) / denominator;
+      dx[i] = value * dloss[i];
+    }
+  } else {
+    float dloss1 = dloss[0];
+    if (reduction == 1) {
+      dloss1 = dloss[0] / input_size;
+    }
+    for (int i = 0; i < input_size; i++) {
+      float denominator = MAX(input_x[i] * (1 - input_x[i]), epsilon);
+      float value = weight[i] * (input_x[i] - input_y[i]) / denominator;
+      dx[i] = value * dloss1;
+    }
+  }
+  return 0;
+}

mindspore/lite/nnacl/fp32_grad/binary_cross_entropy_grad.h

@@ -0,0 +1,36 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * 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.
+ */
+#ifndef MINDSPORE_LITE_NNACL_BINARY_CROSS_ENTROPY_GRAD_H_
+#define MINDSPORE_LITE_NNACL_BINARY_CROSS_ENTROPY_GRAD_H_
+
+#include "nnacl/op_base.h"
+
+typedef struct BinaryCrossEntropyGradParameter {
+  OpParameter op_parameter_;
+  int reduction;
+} BinaryCrossEntropyGradParameter;
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+int BinaryCrossEntropyGrad(const int input_size, const int reduction, const float *input_x, const float *input_y,
+                           const float *weight, const float *dloss, float *dx);
+
+#ifdef __cplusplus
+}
+#endif
+#endif  // MINDSPORE_LITE_NNACL_BINARY_CROSS_ENTROPY_GRAD_H_

mindspore/lite/src/ops/assign_add.cc

@@ -15,6 +15,11 @@
  */
 
 #include "src/ops/assign_add.h"
+
+#ifndef PRIMITIVE_WRITEABLE
+#include "src/ops/ops_register.h"
+#endif
+
 namespace mindspore {
 namespace lite {
 #ifdef PRIMITIVE_WRITEABLE
@@ -58,7 +63,13 @@ int AssignAdd::UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffe
   fbb->Finish(prim_offset);
   return RET_OK;
 }
+
+PrimitiveC *AssignAddCreator(const schema::Primitive *primitive) {
+  return PrimitiveC::NewPrimitiveC<AssignAdd>(primitive);
+}
+Registry AssignAddRegistry(schema::PrimitiveType_AssignAdd, AssignAddCreator);
 #endif
+
 int AssignAdd::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
   Tensor *x = inputs_[0];
   Tensor *y = inputs_[1];

mindspore/lite/src/ops/binary_cross_entropy.cc

@@ -17,6 +17,10 @@
 #include <string>
 #include "src/ops/binary_cross_entropy.h"
 
+#ifndef PRIMITIVE_WRITEABLE
+#include "src/ops/ops_register.h"
+#endif
+
 namespace mindspore {
 namespace lite {
 #ifdef PRIMITIVE_WRITEABLE
@@ -85,6 +89,11 @@ int BinaryCrossEntropy::UnPackToFlatBuilder(const schema::Primitive *primitive,
 }
 
 int BinaryCrossEntropy::GetReduction() const { return this->primitive_->value_as_BinaryCrossEntropy()->reduction(); }
+
+PrimitiveC *BinaryCrossEntropyCreator(const schema::Primitive *primitive) {
+  return PrimitiveC::NewPrimitiveC<BinaryCrossEntropy>(primitive);
+}
+Registry BinaryCrossEntropyRegistry(schema::PrimitiveType_BinaryCrossEntropy, BinaryCrossEntropyCreator);
 #endif
 int BinaryCrossEntropy::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
   Tensor *x = inputs_[0];

mindspore/lite/src/ops/binary_cross_entropy_grad.cc

@@ -17,6 +17,10 @@
 #include <string>
 #include "src/ops/binary_cross_entropy_grad.h"
 
+#ifndef PRIMITIVE_WRITEABLE
+#include "src/ops/ops_register.h"
+#endif
+
 namespace mindspore {
 namespace lite {
 #ifdef PRIMITIVE_WRITEABLE
@@ -92,6 +96,11 @@ int BinaryCrossEntropyGrad::UnPackToFlatBuilder(const schema::Primitive *primiti
 int BinaryCrossEntropyGrad::GetReduction() const {
   return this->primitive_->value_as_BinaryCrossEntropyGrad()->reduction();
 }
+
+PrimitiveC *BinaryCrossEntropyGradCreator(const schema::Primitive *primitive) {
+  return PrimitiveC::NewPrimitiveC<BinaryCrossEntropyGrad>(primitive);
+}
+Registry BinaryCrossEntropyGradRegistry(schema::PrimitiveType_BinaryCrossEntropyGrad, BinaryCrossEntropyGradCreator);
 #endif
 int BinaryCrossEntropyGrad::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
   Tensor *x = inputs_[0];

mindspore/lite/src/ops/cast.cc

@@ -89,7 +89,7 @@ int Cast::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> output
   MS_ASSERT(input != nullptr);
   auto output = outputs_.front();
   MS_ASSERT(output != nullptr);
-  if (inputs_.size() != kSingleNum || outputs_.size() != kSingleNum) {
+  if (outputs_.size() != kSingleNum) {
     MS_LOG(ERROR) << "tensor number is error.";
     return RET_INPUT_TENSOR_ERROR;
   }

mindspore/lite/src/ops/gather.cc

@@ -54,8 +54,15 @@ int Gather::UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inp
       delete gather_attr;
       return RET_ERROR;
     }
-    gather_attr->axis = GetValue<int>(prim.GetAttr("axis"));
+    if (inputs[2]->isa<ValueNode>()) {
-    gather_attr->batchDims = GetValue<int>(prim.GetAttr("batchDims"));
+      ValueNodePtr axis_tensor = inputs[2]->cast<ValueNodePtr>();
+      int axis = GetValue<int>(axis_tensor->value());
+      gather_attr->axis = axis;
+    } else {
+      MS_LOG(ERROR) << "input axis is not value node.";
+      return RET_ERROR;
+    }
+    gather_attr->batchDims = 0;
     this->primitive_->value.value = gather_attr;
   }
   return RET_OK;
@@ -85,8 +92,7 @@ Registry GatherRegistry(schema::PrimitiveType_Gather, GatherCreator);
 int Gather::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
   MS_ASSERT(this->primitive_ != nullptr);
   if (inputs_.size() != kDoubleNum) {
-    MS_LOG(ERROR) << "Gather should have two inputs";
+    MS_LOG(DEBUG) << "Gather should have two inputs";
-    return RET_INPUT_TENSOR_ERROR;
   }
   if (outputs_.size() != kSingleNum) {
     MS_LOG(ERROR) << "Gather should have one outputs";

mindspore/lite/src/ops/oneslike.cc

@@ -16,6 +16,10 @@
 
 #include "src/ops/oneslike.h"
 
+#ifndef PRIMITIVE_WRITEABLE
+#include "src/ops/ops_register.h"
+#endif
+
 namespace mindspore {
 namespace lite {
 #ifdef PRIMITIVE_WRITEABLE
@@ -59,6 +63,11 @@ int OnesLike::UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffer
   fbb->Finish(prim_offset);
   return RET_OK;
 }
+
+PrimitiveC *OnesLikeCreator(const schema::Primitive *primitive) {
+  return PrimitiveC::NewPrimitiveC<OnesLike>(primitive);
+}
+Registry OnesLikeRegistry(schema::PrimitiveType_OnesLike, OnesLikeCreator);
 #endif
 int OnesLike::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
   Tensor *x = inputs_[0];

mindspore/lite/src/ops/populate/activation_grad_populate.cc

@@ -0,0 +1,41 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * 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 "src/ops/activation_grad.h"
+#include "src/ops/primitive_c.h"
+#include "src/ops/populate/populate_register.h"
+#include "nnacl/fp32_grad/activation_grad.h"
+
+namespace mindspore {
+namespace lite {
+OpParameter *PopulateActivationGradParameter(const mindspore::lite::PrimitiveC *primitive) {
+  ActivationGradParameter *act_param =
+    reinterpret_cast<ActivationGradParameter *>(malloc(sizeof(ActivationGradParameter)));
+  if (act_param == nullptr) {
+    MS_LOG(ERROR) << "malloc ActivationParameter failed.";
+    return nullptr;
+  }
+  memset(act_param, 0, sizeof(ActivationGradParameter));
+  act_param->op_parameter.type_ = primitive->Type();
+  auto activation =
+    reinterpret_cast<mindspore::lite::ActivationGrad *>(const_cast<mindspore::lite::PrimitiveC *>(primitive));
+  act_param->type_ = static_cast<int>(activation->GetType());
+  act_param->alpha_ = activation->GetAlpha();
+  return reinterpret_cast<OpParameter *>(act_param);
+}
+Registry ActivationGradParameterRegistry(schema::PrimitiveType_ActivationGrad, PopulateActivationGradParameter);
+}  // namespace lite
+}  // namespace mindspore

mindspore/lite/src/ops/populate/adam_populate.cc

@@ -0,0 +1,36 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * 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 "src/ops/adam.h"
+#include "src/ops/primitive_c.h"
+#include "src/ops/populate/populate_register.h"
+
+namespace mindspore {
+namespace lite {
+OpParameter *PopulateAdamParameter(const mindspore::lite::PrimitiveC *primitive) {
+  OpParameter *param = reinterpret_cast<OpParameter *>(malloc(sizeof(OpParameter)));
+  if (param == nullptr) {
+    MS_LOG(ERROR) << "malloc Adam Parameter failed.";
+    return nullptr;
+  }
+  memset(param, 0, sizeof(OpParameter));
+  param->type_ = primitive->Type();
+  return param;
+}
+
+Registry AdamParameterRegistry(schema::PrimitiveType_Adam, PopulateAdamParameter);
+}  // namespace lite
+}  // namespace mindspore

mindspore/lite/src/ops/populate/assign_add_populate.cc

@@ -0,0 +1,36 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * 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 "src/ops/assign_add.h"
+#include "src/ops/primitive_c.h"
+#include "src/ops/populate/populate_register.h"
+
+namespace mindspore {
+namespace lite {
+OpParameter *PopulateAssignAddParameter(const mindspore::lite::PrimitiveC *primitive) {
+  OpParameter *param = reinterpret_cast<OpParameter *>(malloc(sizeof(OpParameter)));
+  if (param == nullptr) {
+    MS_LOG(ERROR) << "malloc AssignAdd Parameter failed.";
+    return nullptr;
+  }
+  memset(param, 0, sizeof(OpParameter));
+  param->type_ = primitive->Type();
+  return param;
+}
+
+Registry AssignAddParameterRegistry(schema::PrimitiveType_AssignAdd, PopulateAssignAddParameter);
+}  // namespace lite
+}  // namespace mindspore

mindspore/lite/src/ops/populate/assign_populate.cc

@@ -0,0 +1,36 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * 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 "src/ops/assign.h"
+#include "src/ops/primitive_c.h"
+#include "src/ops/populate/populate_register.h"
+
+namespace mindspore {
+namespace lite {
+OpParameter *PopulateAssignParameter(const mindspore::lite::PrimitiveC *primitive) {
+  OpParameter *param = reinterpret_cast<OpParameter *>(malloc(sizeof(OpParameter)));
+  if (param == nullptr) {
+    MS_LOG(ERROR) << "malloc Assign Parameter failed.";
+    return nullptr;
+  }
+  memset(param, 0, sizeof(OpParameter));
+  param->type_ = primitive->Type();
+  return param;
+}
+
+Registry AssignParameterRegistry(schema::PrimitiveType_Assign, PopulateAssignParameter);
+}  // namespace lite
+}  // namespace mindspore

mindspore/lite/src/ops/populate/bias_grad_populate.cc

@@ -0,0 +1,37 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * 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 "src/ops/primitive_c.h"
+#include "src/ops/populate/populate_register.h"
+#include "nnacl/arithmetic_common.h"
+
+namespace mindspore {
+namespace lite {
+OpParameter *PopulateBiasGradParameter(const mindspore::lite::PrimitiveC *primitive) {
+  ArithmeticParameter *arithmetic_param = reinterpret_cast<ArithmeticParameter *>(malloc(sizeof(ArithmeticParameter)));
+  if (arithmetic_param == nullptr) {
+    MS_LOG(ERROR) << "malloc ArithmeticParameter failed.";
+    return nullptr;
+  }
+  memset(arithmetic_param, 0, sizeof(ArithmeticParameter));
+  arithmetic_param->op_parameter_.type_ = primitive->Type();
+
+  return reinterpret_cast<OpParameter *>(arithmetic_param);
+}
+Registry PopulateBiasGradParameterParameterRegistry(schema::PrimitiveType_BiasGrad, PopulateBiasGradParameter);
+
+}  // namespace lite
+}  // namespace mindspore

mindspore/lite/src/ops/populate/binary_cross_entropy_grad_populate.cc

@@ -0,0 +1,42 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * 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 "src/ops/binary_cross_entropy_grad.h"
+#include "src/ops/primitive_c.h"
+#include "src/ops/populate/populate_register.h"
+#include "nnacl/fp32_grad/binary_cross_entropy_grad.h"
+
+namespace mindspore {
+namespace lite {
+OpParameter *PopulateBinaryCrossEntropyGradParameter(const mindspore::lite::PrimitiveC *primitive) {
+  BinaryCrossEntropyGradParameter *bce_param =
+    reinterpret_cast<BinaryCrossEntropyGradParameter *>(malloc(sizeof(BinaryCrossEntropyGradParameter)));
+  if (bce_param == nullptr) {
+    MS_LOG(ERROR) << "malloc BinaryCrossEntropyGrad Parameter failed.";
+    return nullptr;
+  }
+  memset(bce_param, 0, sizeof(BinaryCrossEntropyGradParameter));
+  bce_param->op_parameter_.type_ = primitive->Type();
+  auto param =
+    reinterpret_cast<mindspore::lite::BinaryCrossEntropyGrad *>(const_cast<mindspore::lite::PrimitiveC *>(primitive));
+  bce_param->reduction = param->GetReduction();
+  return reinterpret_cast<OpParameter *>(bce_param);
+}
+
+Registry BinaryCrossEntropyGradParameterRegistry(schema::PrimitiveType_BinaryCrossEntropyGrad,
+                                                 PopulateBinaryCrossEntropyGradParameter);
+}  // namespace lite
+}  // namespace mindspore

mindspore/lite/src/ops/populate/binary_cross_entropy_populate.cc

@@ -0,0 +1,42 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * 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 "src/ops/binary_cross_entropy.h"
+#include "src/ops/primitive_c.h"
+#include "src/ops/populate/populate_register.h"
+#include "nnacl/fp32_grad/binary_cross_entropy.h"
+
+namespace mindspore {
+namespace lite {
+OpParameter *PopulateBinaryCrossEntropyParameter(const mindspore::lite::PrimitiveC *primitive) {
+  BinaryCrossEntropyParameter *bce_param =
+    reinterpret_cast<BinaryCrossEntropyParameter *>(malloc(sizeof(BinaryCrossEntropyParameter)));
+  if (bce_param == nullptr) {
+    MS_LOG(ERROR) << "malloc BinaryCrossEntropy Parameter failed.";
+    return nullptr;
+  }
+  memset(bce_param, 0, sizeof(BinaryCrossEntropyParameter));
+  bce_param->op_parameter_.type_ = primitive->Type();
+  auto param =
+    reinterpret_cast<mindspore::lite::BinaryCrossEntropy *>(const_cast<mindspore::lite::PrimitiveC *>(primitive));
+  bce_param->reduction = param->GetReduction();
+  return reinterpret_cast<OpParameter *>(bce_param);
+}
+
+Registry BinaryCrossEntropyParameterRegistry(schema::PrimitiveType_BinaryCrossEntropy,
+                                             PopulateBinaryCrossEntropyParameter);
+}  // namespace lite
+}  // namespace mindspore

mindspore/lite/src/ops/populate/oneslike_populate.cc

@@ -0,0 +1,36 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * 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 "src/ops/oneslike.h"
+#include "src/ops/primitive_c.h"
+#include "src/ops/populate/populate_register.h"
+
+namespace mindspore {
+namespace lite {
+OpParameter *PopulateOnesLikeParameter(const mindspore::lite::PrimitiveC *primitive) {
+  OpParameter *param = reinterpret_cast<OpParameter *>(malloc(sizeof(OpParameter)));
+  if (param == nullptr) {
+    MS_LOG(ERROR) << "malloc OnesLike Parameter failed.";
+    return nullptr;
+  }
+  memset(param, 0, sizeof(OpParameter));
+  param->type_ = primitive->Type();
+  return param;
+}
+
+Registry OnesLikeParameterRegistry(schema::PrimitiveType_OnesLike, PopulateOnesLikeParameter);
+}  // namespace lite
+}  // namespace mindspore

mindspore/lite/src/ops/populate/unsorted_segment_sum_populate.cc

@@ -0,0 +1,37 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * 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 "src/ops/unsorted_segment_sum.h"
+#include "src/ops/primitive_c.h"
+#include "src/ops/populate/populate_register.h"
+
+namespace mindspore {
+namespace lite {
+OpParameter *PopulateUnsortedSegmentSumParameter(const mindspore::lite::PrimitiveC *primitive) {
+  OpParameter *param = reinterpret_cast<OpParameter *>(malloc(sizeof(OpParameter)));
+  if (param == nullptr) {
+    MS_LOG(ERROR) << "malloc UnsortedSegmentSum Parameter failed.";
+    return nullptr;
+  }
+  memset(param, 0, sizeof(OpParameter));
+  param->type_ = primitive->Type();
+  return param;
+}
+
+Registry UnsortedSegmentSumParameterRegistry(schema::PrimitiveType_UnsortedSegmentSum,
+                                             PopulateUnsortedSegmentSumParameter);
+}  // namespace lite
+}  // namespace mindspore

mindspore/lite/src/ops/slice.cc

@@ -94,6 +94,12 @@ int Slice::UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inpu
           }
         }
       }
+      std::vector<int> axes;
+      axes.clear();
+      for (size_t i = 0; i < attr->begin.size(); i++) {
+        axes.push_back(i);
+      }
+      attr->axes = axes;
     }
     this->primitive_->value.value = attr;
   }

mindspore/lite/src/ops/unsorted_segment_sum.cc

@@ -17,6 +17,10 @@
 #include <memory>
 #include "src/ops/unsorted_segment_sum.h"
 
+#ifndef PRIMITIVE_WRITEABLE
+#include "src/ops/ops_register.h"
+#endif
+
 namespace mindspore {
 namespace lite {
 #ifdef PRIMITIVE_WRITEABLE
@@ -69,6 +73,11 @@ int UnsortedSegmentSum::GetNumSegments() const {
   int ret = this->primitive_->value_as_UnsortedSegmentSum()->numSegments();
   return ret;
 }
+
+PrimitiveC *UnsortedSegmentSumCreator(const schema::Primitive *primitive) {
+  return PrimitiveC::NewPrimitiveC<UnsortedSegmentSum>(primitive);
+}
+Registry UnsortedSegmentSumRegistry(schema::PrimitiveType_UnsortedSegmentSum, UnsortedSegmentSumCreator);
 #endif
 int UnsortedSegmentSum::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
   // check inputs and outputs