!9220 [MS][LITE]add reduce_all mode

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

mindspore/lite/nnacl/fp32/reduce_fp32.c

@@ -144,6 +144,29 @@ int IntReduceMin(int outer_size, int inner_size, int axis_size, const int *src_d
   }
   return NNACL_OK;
 }
+
+int ReduceAll(int outer_size, int inner_size, int axis_size, const bool *src_data, bool *dst_data, int tid,
+              int thread_num) {
+  if (src_data == NULL || dst_data == NULL) {
+    return NNACL_NULL_PTR;
+  }
+  int i, j, k;
+  for (j = tid; j < outer_size; j += thread_num) {
+    const bool *outer_src = src_data + j * axis_size * inner_size;
+    bool *outer_dst = dst_data + j * inner_size;
+    for (k = 0; k < inner_size; k++) {
+      const bool *inner_src = outer_src + k;
+      bool *inner_dst = outer_dst + k;
+      bool tmp = true;
+      for (i = 0; i < axis_size; i++) {
+        tmp = tmp && inner_src[i * inner_size];
+      }
+      *inner_dst = tmp;
+    }
+  }
+  return NNACL_OK;
+}
+
 int ReduceProd(int outer_size, int inner_size, int axis_size, const float *src_data, float *dst_data, int tid,
                int thread_num) {
   if (src_data == NULL || dst_data == NULL) {

mindspore/lite/nnacl/fp32/reduce_fp32.h

@@ -38,6 +38,8 @@ int IntReduceProd(int outer_size, int inner_size, int axis_size, const int *src_
                   int thread_num);
 int ReduceSumSquare(int outer_size, int inner_size, int axis_size, const float *src_data, float *dst_data, int tid,
                     int thread_num);
+int ReduceAll(int outer_size, int inner_size, int axis_size, const bool *src_data, bool *dst_data, int tid,
+              int thread_num);
 
 #ifdef ENABLE_NNACL_INFER_SHAPE
 int ReduceInferShape(int **in_shape, size_t *dim_size, int *out_shape, int *in_format, int *out_format,

mindspore/lite/nnacl/op_base.h

@@ -63,6 +63,7 @@ typedef enum LiteDataType {
   kDataTypeFloat,
   kDataTypeInt,
   kDataTypeInt8,
+  KDataTypeBool,
 } LiteDataType;
 
 typedef enum DataOrder {

mindspore/lite/schema/ops.fbs

@@ -765,7 +765,8 @@ enum ReduceMode : byte {
     ReduceProd = 3,
     ReduceSum = 4,
     ReduceSumSquare = 5,
-    ReduceASum = 6
+    ReduceASum = 6,
+    ReduceAll = 7
 }
 
 table Reduce {

mindspore/lite/src/ops/reduce.cc

@@ -67,6 +67,11 @@ int Reduce::UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inp
       attr->mode = schema::ReduceMode_ReduceProd;
     } else if (prim.name() == "ReduceSumSquare") {
       attr->mode = schema::ReduceMode_ReduceSumSquare;
+    } else if (prim.name() == "ReduceAll") {
+      attr->mode = schema::ReduceMode_ReduceAll;
+    } else {
+      MS_LOG(ERROR) << "Not supported reduce mode: " << prim.name();
+      return RET_ERROR;
     }
 
     attr->keepDims = GetValue<bool>(prim.GetAttr("keep_dims"));

mindspore/lite/src/runtime/kernel/arm/fp32/reduce_fp32.cc

@@ -31,6 +31,7 @@ using mindspore::lite::RET_OK;
 using mindspore::schema::PrimitiveType_Mean;
 using mindspore::schema::PrimitiveType_Reduce;
 using mindspore::schema::ReduceMode;
+using mindspore::schema::ReduceMode_ReduceAll;
 using mindspore::schema::ReduceMode_ReduceASum;
 using mindspore::schema::ReduceMode_ReduceMax;
 using mindspore::schema::ReduceMode_ReduceMean;
@@ -78,6 +79,10 @@ int ReduceCPUKernel::Init() {
       reducer_ = ReduceSum;
       break;
     }
+    case static_cast<int>(ReduceMode_ReduceAll): {
+      bool_reducer_ = ReduceAll;
+      break;
+    }
     default:
       MS_LOG(ERROR) << "Reduce unsupported reduce mode: " << mode_;
       return RET_ERROR;
@@ -96,6 +101,9 @@ int ReduceCPUKernel::CallReduceUnit(int task_id) {
   if (data_type_ == kDataTypeFloat) {
     ret = reducer_(outer_size_, inner_size_, axis_size_, static_cast<const float *>(src_data_),
                    static_cast<float *>(dst_data_), task_id, context_->thread_num_);
+  } else if (data_type_ == KDataTypeBool) {
+    ret = bool_reducer_(outer_size_, inner_size_, axis_size_, static_cast<const bool *>(src_data_),
+                        static_cast<bool *>(dst_data_), task_id, context_->thread_num_);
   } else {
     ret = int_reducer_(outer_size_, inner_size_, axis_size_, static_cast<const int *>(src_data_),
                        static_cast<int *>(dst_data_), task_id, context_->thread_num_);
@@ -117,6 +125,8 @@ int ReduceImpl(void *cdata, int task_id) {
 int ReduceCPUKernel::Run() {
   if (in_tensors().at(0)->data_type() == kNumberTypeFloat32) {
     data_type_ = kDataTypeFloat;
+  } else if (in_tensors().at(0)->data_type() == kNumberTypeBool) {
+    data_type_ = KDataTypeBool;
   } else {
     data_type_ = kDataTypeInt;
   }
@@ -202,6 +212,8 @@ int ReduceCPUKernel::MallocTmpBuffer() {
     void *buffer = nullptr;
     if (data_type_ == kDataTypeFloat) {
       buffer = context_->allocator->Malloc(size * sizeof(float));
+    } else if (data_type_ == KDataTypeBool) {
+      buffer = context_->allocator->Malloc(size * sizeof(bool));
     } else {
       buffer = context_->allocator->Malloc(size * sizeof(int));
     }

mindspore/lite/src/runtime/kernel/arm/fp32/reduce_fp32.h

@@ -31,6 +31,8 @@ class ReduceCPUKernel : public ReduceBaseCPUKernel {
                          float *dst_data, const int tid, const int thread_num);
   typedef int (*IntReducer)(const int outer_size, const int inner_size, const int axis_size, const int *src_data,
                             int *dst_data, const int tid, const int thread_num);
+  typedef int (*BoolReducer)(const int outer_size, const int inner_size, const int axis_size, const bool *src_data,
+                             bool *dst_data, const int tid, const int thread_num);
 
  public:
   ReduceCPUKernel(OpParameter *param, const std::vector<lite::Tensor *> &inputs,
@@ -54,6 +56,7 @@ class ReduceCPUKernel : public ReduceBaseCPUKernel {
  private:
   ReduceParameter *reduce_param_;
   Reducer reducer_ = nullptr;
+  BoolReducer bool_reducer_ = nullptr;
   IntReducer int_reducer_ = nullptr;
   std::vector<void *> data_buffers_;
   LiteDataType data_type_;

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

@@ -52,6 +52,8 @@ STATUS TFReduceParser::Parse(const tensorflow::NodeDef &tf_op,
     attr->mode = schema::ReduceMode_ReduceMean;
   } else if (tf_op.op() == "Prod") {
     attr->mode = schema::ReduceMode_ReduceProd;
+  } else if (tf_op.op() == "All") {
+    attr->mode = schema::ReduceMode_ReduceAll;
   } else {
     MS_LOG(ERROR) << "unsupported reduce mode: " << tf_op.op();
     return RET_ERROR;
@@ -106,5 +108,6 @@ TFNodeRegistrar g_tfMaxParser("Max", new TFReduceParser());
 TFNodeRegistrar g_tfMinParser("Min", new TFReduceParser());
 TFNodeRegistrar g_tfMeanParser("Mean", new TFReduceParser());
 TFNodeRegistrar g_tfProdParser("Prod", new TFReduceParser());
+TFNodeRegistrar g_tfAllParser("All", new TFReduceParser());
 }  // namespace lite
 }  // namespace mindspore