!4936 Fix sigmoid activation bug

Merge pull request !4936 from wangminggui/master

mindspore/lite/nnacl/fp32/activation.c

@@ -43,8 +43,19 @@ int LRelu(const float *src, int length, float *dst, float alpha) {
 }
 
 int Sigmoid(const float *src, int length, float *dst) {
+  const float upper_bound = 16.619047164916992188f;
+  const float lower_bound = -9.0f;
   for (int i = 0; i < length; ++i) {
-    dst[i] = 1.0f / (1.0f + exp(-src[i]));
+    float input_val = src[i];
+    float result;
+    if (input_val > upper_bound) {
+      result = 1.0f;
+    } else if (input_val < lower_bound) {
+      result = exp(input_val);
+    } else {
+      result = 1.0f / (1.0f + exp(-input_val));
+    }
+    dst[i] = result;
   }
   return NNACL_OK;
 }

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

@@ -31,8 +31,6 @@ using mindspore::schema::PrimitiveType_Gather;
 namespace mindspore::kernel {
 
 int GatherCPUKernel::Init() {
-  axis_ = (reinterpret_cast<GatherParameter *>(op_parameter_))->axis_;
-  batchDims_ = (reinterpret_cast<GatherParameter *>(op_parameter_))->batchDims_;
   if (!InferShapeDone()) {
     return RET_OK;
   }
@@ -47,7 +45,7 @@ int GatherCPUKernel::DoGather(int task_id) {
   auto out_tensor = out_tensors_.at(0);
 
   auto input_ptr = reinterpret_cast<float *>(input_tensor->Data());
-  auto indices_ptr = reinterpret_cast<int *>(indices_tensor->Data());
+  auto indices_ptr = reinterpret_cast<float *>(indices_tensor->Data());
   auto output_ptr = reinterpret_cast<float *>(out_tensor->Data());
 
   auto input_int32 = reinterpret_cast<int32_t *>(input_tensor->Data());
@@ -56,26 +54,25 @@ int GatherCPUKernel::DoGather(int task_id) {
   auto in_shape = input_tensor->shape();
   int in_rank = in_shape.size();
   int indices_element_size = indices_tensor->ElementsNum();
+  auto axis = (reinterpret_cast<GatherParameter *>(op_parameter_))->axis_;
 
-  const int limit = in_shape[axis_];
+  const int limit = in_shape[axis];
   for (int i = 0; i < indices_element_size; ++i) {
-    if (indices_ptr[i] >= limit) {
-      MS_LOG(ERROR) << " indice data: " << indices_ptr[i] << " is not in [ 0, " << limit - 1 << " ]";
+    indices_data_[i] = static_cast<int>(indices_ptr[i]);
+    if (indices_data_[i] >= limit) {
+      MS_LOG(ERROR) << " indice data: " << indices_data_[i] << " is not in [ 0, " << limit - 1 << " ]";
       return RET_ERROR;
     }
   }
 
-  int outer_size = 1;
-  for (int i = 0; i < axis_; ++i) {
+  int outer_size = 1, inner_size = 1;
+  for (int i = 0; i < axis; ++i) {
     outer_size *= in_shape[i];
   }
-
-  int inner_size = 1;
-  for (int i = axis_ + 1; i < in_rank; ++i) {
+  for (int i = axis + 1; i < in_rank; ++i) {
     inner_size *= in_shape[i];
   }
-
-  int stride = UP_DIV(outer_size, thread_count_);
+  int stride = UP_DIV(outer_size, op_parameter_->thread_num_);
   int count = MSMIN(stride, outer_size - stride * task_id);
   auto thread_stride = stride * task_id;
 
@@ -83,17 +80,13 @@ int GatherCPUKernel::DoGather(int task_id) {
   if (input_tensor->data_type() == kNumberTypeInt32) {
     input_int32 += thread_stride * limit;
     output_int32 += thread_stride * indices_element_size;
-    error_code = GatherInt32(input_int32, count, inner_size, limit, indices_ptr, indices_element_size, output_int32);
+    error_code = GatherInt32(input_int32, count, inner_size, limit, indices_data_, indices_element_size, output_int32);
   } else {
     input_ptr += thread_stride * limit;
     output_ptr += thread_stride * indices_element_size;
-    error_code = Gather(input_ptr, count, inner_size, limit, indices_ptr, indices_element_size, output_ptr);
-  }
-
-  if (error_code != RET_OK) {
-    return RET_ERROR;
+    error_code = Gather(input_ptr, count, inner_size, limit, indices_data_, indices_element_size, output_ptr);
   }
-  return RET_OK;
+  return error_code;
 }
 
 int GatherRun(int task_id, LiteParallelGroupEnv *penv, void *cdata) {
@@ -101,9 +94,8 @@ int GatherRun(int task_id, LiteParallelGroupEnv *penv, void *cdata) {
   auto error_code = gather_kernel->DoGather(task_id);
   if (error_code != RET_OK) {
     MS_LOG(ERROR) << "GatherRun error task_id[" << task_id << "] error_code[" << error_code << "]";
-    return RET_ERROR;
   }
-  return RET_OK;
+  return error_code;
 }
 
 int GatherCPUKernel::Run() {
@@ -112,12 +104,19 @@ int GatherCPUKernel::Run() {
     MS_LOG(ERROR) << "Prepare fail!ret: " << prepare_ret;
     return prepare_ret;
   }
-  int error_code = LiteBackendParallelLaunch(GatherRun, this, thread_count_);
+
+  auto indices_tensor = in_tensors_.at(1);
+  indices_data_ = reinterpret_cast<int *>(context_->allocator->Malloc(indices_tensor->ElementsNum() * sizeof(int)));
+  if (indices_data_ == nullptr) {
+    MS_LOG(ERROR) << "Memory allocation failed";
+    context_->allocator->Free(indices_data_);
+    return RET_ERROR;
+  }
+  int error_code = LiteBackendParallelLaunch(GatherRun, this, op_parameter_->thread_num_);
   if (error_code != RET_OK) {
     MS_LOG(ERROR) << "Gather function error error_code[" << error_code << "]";
-    return RET_ERROR;
   }
-  return RET_OK;
+  return error_code;
 }
 
 kernel::LiteKernel *CpuGatherFp32KernelCreator(const std::vector<lite::tensor::Tensor *> &inputs,

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

@@ -27,7 +27,7 @@ class GatherCPUKernel : public LiteKernel {
   GatherCPUKernel(OpParameter *parameter, const std::vector<lite::tensor::Tensor *> &inputs,
                   const std::vector<lite::tensor::Tensor *> &outputs, const lite::Context *ctx,
                   const mindspore::lite::PrimitiveC *primitive)
-      : LiteKernel(parameter, inputs, outputs, ctx, primitive), thread_count_(ctx->thread_num_) {}
+      : LiteKernel(parameter, inputs, outputs, ctx, primitive) {}
   ~GatherCPUKernel() override = default;
 
   int Init() override;
@@ -36,9 +36,7 @@ class GatherCPUKernel : public LiteKernel {
   int DoGather(int task_id);
 
  private:
-  int thread_count_;
-  int batchDims_;
-  int axis_;
+  int *indices_data_;
 };
 }  // namespace mindspore::kernel