forked from mindspore-Ecosystem/mindspore
fix static check problem
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577beb21ec
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2f1d04dd10
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@ -227,7 +227,7 @@ extern "C" JNIEXPORT jboolean JNICALL Java_com_mindspore_lite_MSTensor_setByteBu
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jobject buffer) {
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jbyte *p_data = reinterpret_cast<jbyte *>(env->GetDirectBufferAddress(buffer)); // get buffer poiter
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jlong data_len = env->GetDirectBufferCapacity(buffer); // get buffer capacity
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if (!p_data) {
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if (p_data == nullptr) {
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MS_LOGE("GetDirectBufferAddress return null");
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return NULL;
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}
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@ -126,14 +126,10 @@ std::map<tflite::ActivationFunctionType, schema::ActivationType> tfMsActivationF
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};
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std::map<int, TypeId> type_map = {
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{tflite::TensorType_FLOAT64, TypeId::kNumberTypeFloat64},
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{tflite::TensorType_FLOAT32, TypeId::kNumberTypeFloat32},
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{tflite::TensorType_FLOAT16, TypeId::kNumberTypeFloat16},
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{tflite::TensorType_INT32, TypeId::kNumberTypeInt32},
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{tflite::TensorType_INT16, TypeId::kNumberTypeInt16},
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{tflite::TensorType_INT8, TypeId::kNumberTypeInt8},
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{tflite::TensorType_INT64, TypeId::kNumberTypeInt64},
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{tflite::TensorType_UINT8, TypeId::kNumberTypeUInt8},
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{tflite::TensorType_FLOAT64, TypeId::kNumberTypeFloat64}, {tflite::TensorType_FLOAT32, TypeId::kNumberTypeFloat32},
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{tflite::TensorType_FLOAT16, TypeId::kNumberTypeFloat16}, {tflite::TensorType_INT32, TypeId::kNumberTypeInt32},
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{tflite::TensorType_INT16, TypeId::kNumberTypeInt16}, {tflite::TensorType_INT8, TypeId::kNumberTypeInt8},
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{tflite::TensorType_INT64, TypeId::kNumberTypeInt64}, {tflite::TensorType_UINT8, TypeId::kNumberTypeUInt8},
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{tflite::TensorType_BOOL, TypeId::kNumberTypeBool},
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};
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@ -190,11 +186,8 @@ size_t GetDataTypeSize(const TypeId &data_type) {
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}
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}
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STATUS getPaddingParam(const std::unique_ptr<tflite::TensorT> &tensor,
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schema::PadMode pad_mode,
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int strideH, int strideW,
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int windowH, int windowW,
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std::vector<int> *params) {
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STATUS getPaddingParam(const std::unique_ptr<tflite::TensorT> &tensor, schema::PadMode pad_mode, int strideH,
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int strideW, int windowH, int windowW, std::vector<int> *params) {
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if (tensor == nullptr) {
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MS_LOG(ERROR) << "the input tensor is null";
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return RET_ERROR;
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@ -208,12 +201,18 @@ STATUS getPaddingParam(const std::unique_ptr<tflite::TensorT> &tensor,
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auto shape = tensor->shape;
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int H_input = shape.at(1);
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int W_input = shape.at(2);
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if (strideH == 0) {
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MS_LOG(ERROR) << "strideH is zero";
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return RET_ERROR;
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}
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int H_output = ceil(H_input * 1.0 / strideH);
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int pad_needed_H = (H_output - 1) * strideH + windowH - H_input;
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padUp = floor(pad_needed_H / 2.0);
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padDown = pad_needed_H - padUp;
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if (strideW == 0) {
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MS_LOG(ERROR) << "strideW is zero";
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return RET_ERROR;
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}
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int W_output = ceil(W_input * 1.0 / strideW);
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int pad_needed_W = (W_output - 1) * strideW + windowW - W_input;
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padLeft = floor(pad_needed_W / 2.0);
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@ -227,9 +226,7 @@ STATUS getPaddingParam(const std::unique_ptr<tflite::TensorT> &tensor,
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return RET_OK;
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}
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void Split(const std::string &src_str,
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std::vector<std::string> *dst_str,
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const std::string &chr) {
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void Split(const std::string &src_str, std::vector<std::string> *dst_str, const std::string &chr) {
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std::string ::size_type p1 = 0, p2 = src_str.find(chr);
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while (std::string::npos != p2) {
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dst_str->push_back(src_str.substr(p1, p2 - p1));
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