!14350 [MS_LITE] fix issue to r1.2

From: @YeFeng_24
Reviewed-by: @hangangqiang,@zhanghaibo5
Signed-off-by: @hangangqiang

mindspore/lite/nnacl/fp32/arithmetic_fp32.c

@@ -145,6 +145,14 @@ int ElementLogicalOr(const float *in0, const float *in1, float *out, int size) {
   return NNACL_OK;
 }
 
+int ElementLogicalOrBool(const bool *in0, const bool *in1, bool *out, int size) {
+  int index = 0;
+  for (; index < size; index++) {
+    out[index] = (in0[index]) | (in1[index]);
+  }
+  return NNACL_OK;
+}
+
 int ElementMaximum(const float *in0, const float *in1, float *out, int size) {
   int index = 0;
 #ifdef ENABLE_NEON

mindspore/lite/nnacl/fp32/arithmetic_fp32.h

@@ -42,6 +42,7 @@ int ElementLogicalAndBool(const bool *in0, const bool *in1, bool *out, int size)
 
 /* logical or */
 int ElementLogicalOr(const float *in0, const float *in1, float *out, int size);
+int ElementLogicalOrBool(const bool *in0, const bool *in1, bool *out, int size);
 
 /* max min */
 int ElementMaximum(const float *in0, const float *in1, float *out, int size);

mindspore/lite/nnacl/infer/transpose_infer.c

@@ -49,6 +49,9 @@ int TransposeInferShape(const TensorC *const *inputs, size_t inputs_size, Tensor
   if (perm_tensor->shape_size_ == 0) {
     return NNACL_INFER_INVALID;
   }
+  if (perms_num != 0 && perm_data == NULL) {
+    return NNACL_INFER_INVALID;
+  }
   int perm[MAX_SHAPE_SIZE];
   size_t perm_size = 0;
   for (size_t i = 0; i < perms_num; i++) {

mindspore/lite/src/runtime/kernel/arm/fp32/arithmetic_fp32.cc

@@ -213,8 +213,8 @@ void ArithmeticCPUKernel::InitRunFunction(int primitive_type) {
      ElementOptDivInt},
     {PrimitiveType_LogicalAnd, schema::ActivationType_NO_ACTIVATION, ElementLogicalAnd, ElementLogicalAndInt,
      ElementLogicalAndBool, nullptr, nullptr},
-    {PrimitiveType_LogicalOr, schema::ActivationType_NO_ACTIVATION, ElementLogicalOr, nullptr, nullptr, nullptr,
-     nullptr},
+    {PrimitiveType_LogicalOr, schema::ActivationType_NO_ACTIVATION, ElementLogicalOr, nullptr, ElementLogicalOrBool,
+     nullptr, nullptr},
     {PrimitiveType_Maximum, schema::ActivationType_NO_ACTIVATION, ElementMaximum, ElementMaximumInt, nullptr, nullptr,
      nullptr},
     {PrimitiveType_Minimum, schema::ActivationType_NO_ACTIVATION, ElementMinimum, ElementMinimumInt, nullptr, nullptr,
@@ -435,6 +435,7 @@ REG_KERNEL(kCPU, kNumberTypeFloat32, PrimitiveType_LogicalAnd, LiteKernelCreator
 REG_KERNEL(kCPU, kNumberTypeBool, PrimitiveType_LogicalAnd, LiteKernelCreator<ArithmeticCPUKernel>)
 REG_KERNEL(kCPU, kNumberTypeInt32, PrimitiveType_LogicalAnd, LiteKernelCreator<ArithmeticCPUKernel>)
 REG_KERNEL(kCPU, kNumberTypeFloat32, PrimitiveType_LogicalOr, LiteKernelCreator<ArithmeticCPUKernel>)
+REG_KERNEL(kCPU, kNumberTypeBool, PrimitiveType_LogicalOr, LiteKernelCreator<ArithmeticCPUKernel>)
 REG_KERNEL(kCPU, kNumberTypeFloat32, PrimitiveType_Maximum, LiteKernelCreator<ArithmeticCPUKernel>)
 REG_KERNEL(kCPU, kNumberTypeFloat32, PrimitiveType_Minimum, LiteKernelCreator<ArithmeticCPUKernel>)
 REG_KERNEL(kCPU, kNumberTypeInt32, PrimitiveType_Maximum, LiteKernelCreator<ArithmeticCPUKernel>)

mindspore/lite/tools/converter/parser/tf/tf_activation_parser.cc

@@ -41,6 +41,14 @@ ops::PrimitiveC *TFActivationParser::Parse(const tensorflow::NodeDef &tf_op,
     prim->set_activation_type(mindspore::ActivationType::SELU);
   } else if (tf_op.op() == "Softplus") {
     prim->set_activation_type(mindspore::ActivationType::SOFTPLUS);
+  } else if (tf_op.op() == "LeakyRelu") {
+    prim->set_activation_type(mindspore::ActivationType::LEAKY_RELU);
+    tensorflow::AttrValue attr_value;
+    if (!TensorFlowUtils::FindAttrValue(tf_op, "alpha", &attr_value)) {
+      MS_LOG(ERROR) << "The attribute alpha should be specified.";
+      return nullptr;
+    }
+    prim->set_alpha(attr_value.f());
   } else {
     MS_LOG(ERROR) << "unsupported activation type:" << tf_op.op();
     return nullptr;
@@ -55,33 +63,12 @@ ops::PrimitiveC *TFActivationParser::Parse(const tensorflow::NodeDef &tf_op,
   return prim.release();
 }
 
-ops::PrimitiveC *TFLeakyReluParser::Parse(const tensorflow::NodeDef &tf_op,
-                                          const std::map<string, const tensorflow::NodeDef *> &tf_node_map,
-                                          std::vector<std::string> *inputs, int *output_size) {
-  auto prim = std::make_unique<ops::LeakyRelu>();
-
-  tensorflow::AttrValue attr_value;
-  if (!TensorFlowUtils::FindAttrValue(tf_op, "alpha", &attr_value)) {
-    MS_LOG(ERROR) << "The attribute alpha should be specified.";
-    return nullptr;
-  }
-  prim->set_negative_slope(attr_value.f());
-
-  *output_size = 1;
-  if (AddOpInput(tf_op, 0, inputs) != RET_OK) {
-    MS_LOG(ERROR) << "add op input failed";
-    return nullptr;
-  }
-
-  return prim.release();
-}
-
 TFNodeRegistrar g_tfReluParser("Relu", new TFActivationParser());
 TFNodeRegistrar g_tfRelu6Parser("Relu6", new TFActivationParser());
 TFNodeRegistrar g_tfSigmoidParser("Sigmoid", new TFActivationParser());
 TFNodeRegistrar g_tfTanhParser("Tanh", new TFActivationParser());
 TFNodeRegistrar g_tfSeLUParser("Selu", new TFActivationParser());
-TFNodeRegistrar g_tfLeakyReluParser("LeakyRelu", new TFLeakyReluParser());
+TFNodeRegistrar g_tfLeakyReluParser("LeakyRelu", new TFActivationParser());
 TFNodeRegistrar g_tfSoftplusParser("Softplus", new TFActivationParser());
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/tools/converter/parser/tf/tf_activation_parser.h

@@ -33,16 +33,6 @@ class TFActivationParser : public TFNodeParser {
                          const std::map<string, const tensorflow::NodeDef *> &tf_node_map,
                          std::vector<std::string> *inputs, int *output_size) override;
 };
-
-class TFLeakyReluParser : public TFNodeParser {
- public:
-  TFLeakyReluParser() = default;
-  ~TFLeakyReluParser() override = default;
-
-  ops::PrimitiveC *Parse(const tensorflow::NodeDef &tf_op,
-                         const std::map<string, const tensorflow::NodeDef *> &tf_node_map,
-                         std::vector<std::string> *inputs, int *output_size) override;
-};
 }  // namespace lite
 }  // namespace mindspore