!5703 quantize parser and l2_norm op

Merge pull request !5703 from zhaodezan/master

mindspore/lite/nnacl/l2_norm.c

+/**
+ * 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/l2_norm.h"
+#include <math.h>
+
+int L2NormFp32(const float *input_ptr, float *output_ptr,
+               L2NormParameter *param) {
+  int *axis = param->axis_;
+  size_t axis_num = param->axis_num_;
+  float epsilon = param->epsilon_;
+  int shape_num = param->shape_num_;
+
+  // default case, axis is set default
+  if (shape_num == axis_num) {
+    bool default_case_flag = true;
+    for (int i = 0; i < axis_num; i++) {
+      if (axis[i] != i) {
+        default_case_flag = false;
+      }
+    }
+    if (default_case_flag) {
+      int data_num = param->data_num_;
+      float sum = 0;
+      for (int i = 0; i < data_num; i++) {
+        sum = sum + input_ptr[i] * input_ptr[i];
+      }
+      float res = sqrt(sum > epsilon ? sum : epsilon);
+      for (int i = 0; i < data_num; i++) {
+        output_ptr[i] = input_ptr[i] / res;
+      }
+      return 0;
+    }
+  } else {
+    return -1;
+  }
+  return 0;
+}

mindspore/lite/nnacl/l2_norm.h

+/**
+ * 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_L2NORM_H_
+#define MINDSPORE_LITE_NNACL_L2NORM_H_
+#include "nnacl/l2_norm_parameter.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+int L2NormFp32(const float *input_ptr, float *output_ptr,
+               L2NormParameter *param);
+#ifdef __cplusplus
+}
+#endif
+
+#endif  // MINDSPORE_LITE_NNACL_L2NORM_H_

mindspore/lite/nnacl/l2_norm_parameter.h

+/**
+ * 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_L2NORM_PARAMETER_H_
+#define MINDSPORE_LITE_NNACL_L2NORM_PARAMETER_H_
+
+#include "nnacl/op_base.h"
+
+typedef struct L2NormParameter {
+  OpParameter op_parameter_;
+  int *axis_;
+  size_t axis_num_;
+  float epsilon_;
+  float data_num_;
+  int *shape_;
+  int shape_num_;
+} L2NormParameter;
+
+#endif  // MINDSPORE_LITE_NNACL_L2NORM_PARAMETER_H_

mindspore/lite/src/populate_parameter.cc

@@ -112,6 +112,7 @@
 #include "src/ops/ceil.h"
 #include "src/ops/round.h"
 #include "src/ops/sparse_to_dense.h"
+#include "src/ops/l2_norm.h"
 #include "nnacl/op_base.h"
 #include "nnacl/fp32/arg_min_max.h"
 #include "nnacl/fp32/cast.h"
@@ -169,6 +170,7 @@
 #include "nnacl/fp32/elu.h"
 #include "nnacl/leaky_relu_parameter.h"
 #include "nnacl/sparse_to_dense.h"
+#include "nnacl/l2_norm_parameter.h"
 
 namespace mindspore::kernel {
 
@@ -1513,6 +1515,33 @@ OpParameter *PopulateEluParameter(const mindspore::lite::PrimitiveC *primitive)
   return reinterpret_cast<OpParameter *>(elu_parameter);
 }
 
+OpParameter *PopulateL2NormParameter(
+    const mindspore::lite::PrimitiveC *primitive) {
+  L2NormParameter *l2_norm_parameter =
+      reinterpret_cast<L2NormParameter *>(malloc(sizeof(L2NormParameter)));
+  if (l2_norm_parameter == nullptr) {
+    MS_LOG(ERROR) << "malloc L2NormParameter failed.";
+    return nullptr;
+  }
+  memset(l2_norm_parameter, 0, sizeof(L2NormParameter));
+  l2_norm_parameter->op_parameter_.type_ = primitive->Type();
+  auto param = reinterpret_cast<mindspore::lite::L2Norm *>(
+      const_cast<mindspore::lite::PrimitiveC *>(primitive));
+  auto axis_vec = param->GetAxis();
+  l2_norm_parameter->axis_num_ = axis_vec.size();
+  l2_norm_parameter->axis_ =
+      reinterpret_cast<int *>(malloc(axis_vec.size() * sizeof(int)));
+  for (size_t i = 0; i < axis_vec.size(); i++) {
+    l2_norm_parameter->axis_[i] = axis_vec[i];
+  }
+  if (param->GetEpsilon() < 1e-12) {
+    l2_norm_parameter->epsilon_ = 1e-12;
+  } else {
+    l2_norm_parameter->epsilon_ = param->GetEpsilon();
+  }
+  return reinterpret_cast<OpParameter *>(l2_norm_parameter);
+}
+
 PopulateParameterRegistry::PopulateParameterRegistry() {
   populate_parameter_funcs_[schema::PrimitiveType_SparseToDense] = PopulateSparseToDenseParameter;
   populate_parameter_funcs_[schema::PrimitiveType_SoftMax] = PopulateSoftmaxParameter;
@@ -1610,6 +1639,7 @@ PopulateParameterRegistry::PopulateParameterRegistry() {
   populate_parameter_funcs_[schema::PrimitiveType_Lstm] = PopulateLstmParameter;
   populate_parameter_funcs_[schema::PrimitiveType_EmbeddingLookup] = PopulateEmbeddingLookupParameter;
   populate_parameter_funcs_[schema::PrimitiveType_Elu] = PopulateEluParameter;
+  populate_parameter_funcs_[schema::PrimitiveType_L2Norm] = PopulateL2NormParameter;
 }
 
 PopulateParameterRegistry *PopulateParameterRegistry::GetInstance() {

mindspore/lite/src/runtime/kernel/arm/fp32/l2_norm.cc

+/**
+ * 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 <vector>
+#include "src/runtime/kernel/arm/fp32/l2_norm.h"
+#include "include/errorcode.h"
+#include "nnacl/l2_norm.h"
+
+
+using mindspore::kernel::KERNEL_ARCH::kCPU;
+using mindspore::lite::KernelRegistrar;
+using mindspore::lite::RET_ERROR;
+using mindspore::lite::RET_OK;
+using mindspore::schema::PrimitiveType_L2Norm;
+
+namespace mindspore::kernel {
+int L2NormCPUKernel::Init() {
+  l2_norm_param_->data_num_ = in_tensors_.at(kInputIndex)->DataSize();
+  auto shape = in_tensors_.at(kInputIndex)->shape();
+  l2_norm_param_->shape_ = reinterpret_cast<int *>(malloc(shape.size() * sizeof(int)));
+  l2_norm_param_->shape_num_ = shape.size();
+  for (size_t i = 0; i < shape.size(); i++) {
+    l2_norm_param_->shape_[i] = shape[i];
+  }
+  return RET_OK;
+}
+
+kernel::LiteKernel *
+CpuL2NormFp32KernelCreator(const std::vector<lite::tensor::Tensor *> &inputs,
+                           const std::vector<lite::tensor::Tensor *> &outputs,
+                           OpParameter *param, const lite::Context *ctx,
+                           const kernel::KernelKey &desc,
+                           const mindspore::lite::PrimitiveC *primitive) {
+  if (param == nullptr) {
+    MS_LOG(ERROR) << "input param is nullptr!";
+    return nullptr;
+  }
+  MS_ASSERT(desc.type == schema::PrimitiveType_L2Norm);
+  auto *kernel = new (std::nothrow)
+      L2NormCPUKernel(param, inputs, outputs, ctx, primitive);
+  if (kernel == nullptr) {
+    MS_LOG(ERROR) << "new L2NormCPUKernel fail!";
+    return nullptr;
+  }
+  auto ret = kernel->Init();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init kernel failed, name: " << param->name_ << ", type: "
+                  << schema::EnumNamePrimitiveType(
+                         static_cast<schema::PrimitiveType>(param->type_));
+    delete kernel;
+    return nullptr;
+  }
+  return kernel;
+}
+
+int L2NormCPUKernel::Run() {
+  auto ret = Prepare();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Prepare fail!ret: " << ret;
+    return ret;
+  }
+  auto input_ptr =
+      reinterpret_cast<float *>(in_tensors_.at(kInputIndex)->Data());
+  auto output_ptr =
+      reinterpret_cast<float *>(out_tensors_.at(kOutputIndex)->Data());
+  ret = L2NormFp32(input_ptr, output_ptr, l2_norm_param_);
+  if (ret != 0) {
+    MS_LOG_ERROR << "unsupported axis setting, more work will be done";
+    return ret;
+  }
+  return RET_OK;
+}
+
+L2NormCPUKernel::~L2NormCPUKernel() {
+  if (l2_norm_param_->shape_ != nullptr) {
+    free(l2_norm_param_->shape_);
+  }
+  if (l2_norm_param_->axis_ != nullptr) {
+    free(l2_norm_param_->axis_);
+  }
+}
+
+REG_KERNEL(kCPU, kNumberTypeFloat32, PrimitiveType_L2Norm,
+           CpuL2NormFp32KernelCreator)
+}  // namespace mindspore::kernel

mindspore/lite/src/runtime/kernel/arm/fp32/l2_norm.h

+/**
+ * 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_SRC_RUNTIME_KERNEL_ARM_FP32_RESHAPE_H_
+#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_FP32_RESHAPE_H_
+
+#include <vector>
+#include "include/context.h"
+#include "src/lite_kernel.h"
+#include "nnacl/l2_norm_parameter.h"
+#include "schema/model_generated.h"
+#include "src/kernel_registry.h"
+
+using mindspore::lite::Context;
+
+namespace mindspore::kernel {
+class L2NormCPUKernel : public LiteKernel {
+ public:
+  L2NormCPUKernel(OpParameter *parameter,
+                  const std::vector<lite::tensor::Tensor *> &inputs,
+                  const std::vector<lite::tensor::Tensor *> &outputs,
+                  const Context *ctx,
+                  const mindspore::lite::PrimitiveC *primitive)
+      : LiteKernel(parameter, inputs, outputs, ctx, primitive) {
+    l2_norm_param_ = reinterpret_cast<L2NormParameter *>(op_parameter_);
+  }
+  ~L2NormCPUKernel();
+
+  int Init() override;
+  int ReSize() override { return 0; }
+  int Run() override;
+
+ private:
+  L2NormParameter * l2_norm_param_;
+};
+}  // namespace mindspore::kernel
+
+#endif  // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_FP32_RESHAPE_H_

mindspore/lite/test/models_tflite.cfg

@@ -103,3 +103,5 @@ mnasnet_1.0_160_1_metadata_1.tflite
 mnasnet_1.0_192_1_metadata_1.tflite
 mnasnet_1.0_224_1_metadata_1.tflite
 mnasnet_1.0_96_1_metadata_1.tflite
+lite-model_on_device_vision_classifier_popular_us_products_V1_1.tflite
+lite-model_on_device_vision_classifier_popular_wine_V1_1.tflite

mindspore/lite/tools/converter/parser/tflite/tflite_quantize_parser.cc

+/**
+ * Copyright 2019 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 "tools/converter/parser/tflite/tflite_quantize_parser.h"
+#include <vector>
+#include <memory>
+#include <map>
+
+namespace mindspore {
+namespace lite {
+STATUS TfliteQuantizeParser::Parse(const std::unique_ptr<tflite::OperatorT> &tflite_op,
+                                     const std::vector<std::unique_ptr<tflite::TensorT>> &tflite_tensors,
+                                     const std::vector<std::unique_ptr<tflite::BufferT>> &tflite_model_buffer,
+                                     schema::CNodeT *op,
+                                     std::vector<int32_t> *tensors_id,
+                                     std::vector<schema::Format> *tensors_format,
+                                     std::map<int, int>  *tensors_id_map) {
+  MS_LOG(DEBUG) << "parse TfliteQuantizeNParser";
+  if (op == nullptr) {
+    MS_LOG(ERROR) << "op is null";
+    return RET_NULL_PTR;
+  }
+  op->primitive = std::make_unique<schema::PrimitiveT>();
+  if (op->primitive == nullptr) {
+    MS_LOG(ERROR) << "op->primitive is null";
+    return RET_NULL_PTR;
+  }
+
+  std::unique_ptr<schema::QuantDTypeCastT> attr = std::make_unique<schema::QuantDTypeCastT>();
+  if (attr == nullptr) {
+    MS_LOG(ERROR) << "new op failed";
+    return RET_NULL_PTR;
+  }
+
+  const auto &in_tensor = tflite_tensors[tflite_op->inputs[0]];
+  if (in_tensor == nullptr) {
+    MS_LOG(ERROR) << "input tensor is null";
+    return RET_NULL_PTR;
+  }
+  attr->srcT = GetTfliteDataType(in_tensor->type);
+  const auto &out_tensor = tflite_tensors[tflite_op->outputs[0]];
+  if (out_tensor == nullptr) {
+    MS_LOG(ERROR) << "output tensor is null";
+    return RET_NULL_PTR;
+  }
+  attr->dstT = GetTfliteDataType(out_tensor->type);
+
+  op->primitive->value.type = schema::PrimitiveType_QuantDTypeCast;
+  op->primitive->value.value = attr.release();
+
+  AddOpInput(op, tensors_id, tensors_format, tensors_id_map,
+             tflite_op->inputs[0], tensors_id->size(), tflite_tensors.size(), schema::Format_NHWC);
+  AddOpOutput(op, tensors_id, tensors_format, tensors_id_map,
+              tflite_op->outputs[0], tensors_id->size(), tflite_tensors.size(), schema::Format_NHWC);
+  return RET_OK;
+}
+
+TfliteNodeRegister g_tfliteQuantizeParser("QUANTIZE", new TfliteQuantizeParser());
+}  // namespace lite
+}  // namespace mindspore

mindspore/lite/tools/converter/parser/tflite/tflite_quantize_parser.h

+/**
+ * Copyright 2019 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_TOOLS_CONVERTER_PARSER_TFLITE_QUANTIZE_PARSER_H
+#define MINDSPORE_LITE_TOOLS_CONVERTER_PARSER_TFLITE_QUANTIZE_PARSER_H
+
+#include <vector>
+#include <memory>
+#include <map>
+#include "tools/converter/parser/tflite/tflite_node_parser.h"
+#include "tools/converter/parser/tflite/tflite_node_parser_registry.h"
+
+namespace mindspore {
+namespace lite {
+class TfliteQuantizeParser : public TfliteNodeParser {
+ public:
+  TfliteQuantizeParser() : TfliteNodeParser("Quantize") {}
+
+  STATUS Parse(const std::unique_ptr<tflite::OperatorT> &tflite_op,
+               const std::vector<std::unique_ptr<tflite::TensorT>> &tflite_tensors,
+               const std::vector<std::unique_ptr<tflite::BufferT>> &tflite_model_buffer,
+               schema::CNodeT *op,
+               std::vector<int32_t> *tensors_id,
+               std::vector<schema::Format> *tensors_format,
+               std::map<int, int>  *tensors_id_map) override;
+};
+}  // namespace lite
+}  // namespace mindspore
+
+#endif  // MINDSPORE_LITE_TOOLS_CONVERTER_PARSER_TFLITE_QUANTIZE_PARSER_H