!7465 [MSLITE][Develop] fix smart reply kernel

Merge pull request !7465 from sunsuodong/fix_lite_kernel

mindspore/lite/src/common/string_util.cc

@@ -116,13 +116,13 @@ static uint64_t k2 = 0x9ae16a3b2f90404fULL;
 uint64_t Fetch64Bit(const char *p) {
   uint64_t result;
   memcpy(&result, p, sizeof(uint64_t));
-  return __builtin_bswap64(result);
+  return result;
 }
 
 uint32_t Fetch32Bit(const char *p) {
   uint32_t result;
   memcpy(&result, p, sizeof(uint32_t));
-  return __builtin_bswap32(result);
+  return result;
 }
 
 uint64_t Rotate64(uint64_t value, int shift) {

mindspore/lite/src/ops/custom_extract_features.cc

@@ -14,6 +14,7 @@
  * limitations under the License.
  */
 #include "src/ops/custom_extract_features.h"
+
 #include "src/common/string_util.h"
 
 namespace mindspore {
@@ -40,9 +41,9 @@ int CustomExtractFeatures::InferShape(std::vector<Tensor *> inputs_, std::vector
   MS_ASSERT(output0 != nullptr);
   MS_ASSERT(output1 != nullptr);
 
-  output0->set_data_type(input->data_type());
+  output0->set_data_type(kNumberTypeInt32);
   output0->SetFormat(input->GetFormat());
-  output1->set_data_type(input->data_type());
+  output1->set_data_type(kNumberTypeFloat32);
   output1->SetFormat(input->GetFormat());
 
   if (input->data_c() == nullptr) {

mindspore/lite/src/ops/custom_normalize.cc

@@ -14,6 +14,7 @@
  * limitations under the License.
  */
 #include "src/ops/custom_normalize.h"
+
 #include "src/common/string_util.h"
 
 namespace mindspore {
@@ -32,21 +33,22 @@ int CustomNormalize::UnPackToFlatBuilder(const schema::Primitive *primitive, fla
 #endif
 int CustomNormalize::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
   auto input = inputs_.at(0);
+  auto output = outputs_.at(0);
   MS_ASSERT(input != nullptr);
+  MS_ASSERT(output != nullptr);
+
+  output->set_data_type(input->data_type());
+  output->SetFormat(input->GetFormat());
+
   if (input->data_c() == nullptr) {
     MS_LOG(INFO) << "Do infer shape in runtime.";
     return RET_INFER_INVALID;
   }
-  int string_num = lite::GetStringCount(input);
-  auto output = outputs_.at(0);
-  MS_ASSERT(output != nullptr);
-
   std::vector<int> shape;
+  int string_num = lite::GetStringCount(input);
   shape.push_back(string_num == 0 ? 1 : string_num);
 
   output->set_shape(shape);
-  output->set_data_type(input->data_type());
-  output->SetFormat(input->GetFormat());
   return RET_OK;
 }
 

mindspore/lite/src/ops/custom_predict.cc

@@ -35,7 +35,12 @@ float CustomPredict::GetWeightThreshold() const {
 int CustomPredict::UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) {
   MS_ASSERT(nullptr != primitive);
   MS_ASSERT(nullptr != fbb);
-  auto val_offset = schema::CreateCustomPredict(*fbb);
+  auto attr = primitive->value_as_CustomPredict();
+  if (attr == nullptr) {
+    MS_LOG(ERROR) << "CustomPredict attr is nullptr";
+    return RET_ERROR;
+  }
+  auto val_offset = schema::CreateCustomPredict(*fbb, attr->outputNum(), attr->weightThreshold());
   auto prim_offset = schema::CreatePrimitive(*fbb, schema::PrimitiveType_CustomPredict, val_offset.o);
   fbb->Finish(prim_offset);
   return RET_OK;

mindspore/lite/src/ops/hashtable_lookup.cc

@@ -14,6 +14,7 @@
  * limitations under the License.
  */
 #include "src/ops/hashtable_lookup.h"
+
 #include "src/common/string_util.h"
 
 namespace mindspore {
@@ -54,10 +55,6 @@ int HashtableLookup::InferShape(std::vector<Tensor *> inputs_, std::vector<Tenso
     MS_LOG(INFO) << "Do infer shape in runtime.";
     return RET_INFER_INVALID;
   }
-  int string_num = lite::GetStringCount(input);
-  std::vector<int> output_shape;
-  output_shape.push_back(string_num == 0 ? 1 : string_num);
-  output->set_shape(output_shape);
   return RET_OK;
 }
 }  // namespace lite

mindspore/lite/src/ops/lsh_projection.cc

@@ -14,6 +14,7 @@
  * limitations under the License.
  */
 #include "src/ops/lsh_projection.h"
+
 #include "nnacl/lsh_projection_parameter.h"
 
 namespace mindspore {
@@ -27,16 +28,17 @@ int LshProjection::GetLshType() const { return this->primitive_->value_as_LshPro
 int LshProjection::UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) {
   MS_ASSERT(nullptr != primitive);
   MS_ASSERT(nullptr != fbb);
-  auto val_offset = schema::CreateLshProjection(*fbb);
+  auto attr = primitive->value_as_LshProjection();
+  if (attr == nullptr) {
+    MS_LOG(ERROR) << "LshProjection attr is nullptr";
+    return RET_ERROR;
+  }
+  auto val_offset = schema::CreateLshProjection(*fbb, attr->type());
   auto prim_offset = schema::CreatePrimitive(*fbb, schema::PrimitiveType_LshProjection, val_offset.o);
   fbb->Finish(prim_offset);
   return RET_OK;
 }
 #endif
-namespace {
-constexpr int kSparseType = 1;
-constexpr int kDenseType = 2;
-}  // namespace
 int LshProjection::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
   if (inputs_.size() != kDoubleNum && inputs_.size() != kMultiNum) {
     MS_LOG(ERROR) << "inputs to LshProjection operator should be 2 or 3, but " << inputs_.size() << " is given.";
@@ -47,29 +49,26 @@ int LshProjection::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor
     return RET_ERROR;
   }
 
-  auto in_hash = inputs_.at(kSingleNum);
+  auto in_hash = inputs_.at(0);
   MS_ASSERT(in_hash->shape().size() == 2);
   MS_ASSERT(in_hash->DimensionSize(1) <= 32);
-  MS_ASSERT(inputs_.at(kDoubleNum)->shape().size() >= 1);
+  MS_ASSERT(inputs_.at(1)->shape().size() >= 1);
 
   if (inputs_.size() == kMultiNum) {
-    MS_ASSERT(inputs_.at(kMultiNum)->shape().size() == 1);
-    MS_ASSERT(inputs_.at(kMultiNum)->DimensionSize(0) == in_value->DimensionSize(0));
+    MS_ASSERT(inputs_.at(2)->shape().size() == 1);
+    MS_ASSERT(inputs_.at(2)->DimensionSize(0) == in_value->DimensionSize(0));
   }
 
   auto out_tensor = outputs_.front();
   out_tensor->set_data_type(kNumberTypeInt32);
   out_tensor->SetFormat(schema::Format::Format_NHWC);
-  if (!GetInferFlag()) {
-    return RET_OK;
-  }
 
   std::vector<int> out_shape;
   switch (GetLshType()) {
-    case kSparseType:
+    case schema::LshProjectionType_SPARSE:
       out_shape.push_back(in_hash->DimensionSize(0));
       break;
-    case kDenseType:
+    case schema::LshProjectionType_DENSE:
       out_shape.push_back(in_hash->DimensionSize(0) * in_hash->DimensionSize(1));
       break;
     default:

mindspore/lite/src/ops/skip_gram.cc

@@ -68,7 +68,11 @@ int SkipGram::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> ou
   output->SetFormat(input->GetFormat());
   output->set_data_type(input->data_type());
 
-  return RET_INFER_INVALID;
+  if (input->data_c() == nullptr) {
+    MS_LOG(INFO) << "Do infer shape in runtime.";
+    return RET_INFER_INVALID;
+  }
+  return RET_OK;
 }
 }  // namespace lite
 }  // namespace mindspore

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

@@ -13,12 +13,12 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
-
 #include "src/runtime/kernel/arm/fp32/lsh_projection.h"
+
 #include "include/errorcode.h"
+#include "src/common/string_util.h"
 #include "src/kernel_registry.h"
 #include "src/runtime/runtime_api.h"
-#include "src/common/string_util.h"
 
 using mindspore::kernel::KERNEL_ARCH::kCPU;
 using mindspore::lite::KernelRegistrar;
@@ -28,12 +28,6 @@ using mindspore::lite::RET_OK;
 using mindspore::schema::PrimitiveType_LshProjection;
 
 namespace mindspore::kernel {
-
-namespace {
-constexpr int kSparseType = 1;
-constexpr int kDenseType = 2;
-}  // namespace
-
 int LshProjectionCPUKernel::Init() {
   if (!InferShapeDone()) {
     return RET_OK;
@@ -91,10 +85,10 @@ int LshProjectionCPUKernel::DoExecute(int task_id) {
   }
 
   switch (lsh_param_->lsh_type_) {
-    case kSparseType:
+    case schema::LshProjectionType_SPARSE:
       LshProjectionSparse(hash, in_data, weight, output, lsh_param_);
       break;
-    case kDenseType:
+    case schema::LshProjectionType_DENSE:
       LshProjectionDense(hash, in_data, weight, output, lsh_param_);
       break;
     default:
@@ -106,7 +100,7 @@ int LshProjectionCPUKernel::DoExecute(int task_id) {
 int LshProjectionCPUKernel::GetSignBit(char *in_data, float *weight, float seed, LshProjectionParameter *para) {
   double score = 0.0;
   for (int i = 0; i < para->in_item_num_; i++) {
-    char *key = static_cast<char *>(ctx_->allocator->Malloc(lsh_param_->key_size_));
+    char *key = static_cast<char *>(context_->allocator->Malloc(lsh_param_->key_size_));
     if (key == nullptr) {
       MS_LOG(ERROR) << "malloc key failed.";
       return RET_ERROR;
@@ -114,13 +108,14 @@ int LshProjectionCPUKernel::GetSignBit(char *in_data, float *weight, float seed,
     memcpy(key, &seed, para->seed_size_);
     memcpy(key + para->seed_size_, in_data, para->in_item_size_);
     in_data += para->in_item_size_;
-    double hash_sign = static_cast<double>(mindspore::lite::StringHash64(key, para->key_size_));
+    int64_t hash_i = static_cast<int64_t>(mindspore::lite::StringHash64(key, para->key_size_));
+    double hash_d = static_cast<double>(hash_i);
     if (weight == nullptr) {
-      score += hash_sign;
+      score += hash_d;
     } else {
-      score += weight[i] * hash_sign;
+      score += weight[i] * hash_d;
     }
-    ctx_->allocator->Free(key);
+    context_->allocator->Free(key);
   }
   return (score > 0) ? 1 : 0;
 }

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

@@ -21,7 +21,6 @@
 
 #include "nnacl/lsh_projection_parameter.h"
 #include "src/lite_kernel.h"
-#include "schema/model_generated.h"
 
 namespace mindspore::kernel {
 class LshProjectionCPUKernel : public LiteKernel {
@@ -44,7 +43,6 @@ class LshProjectionCPUKernel : public LiteKernel {
 
  private:
   LshProjectionParameter *lsh_param_ = nullptr;
-  const lite::InnerContext *ctx_;
   int thread_num_;
   int64_t elements_num_;
   int64_t count_unit_;

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

@@ -15,6 +15,7 @@
  */
 
 #include "src/runtime/kernel/arm/fp32/skip_gram.h"
+
 #include "include/errorcode.h"
 #include "src/kernel_registry.h"
 #include "src/runtime/runtime_api.h"
@@ -59,6 +60,11 @@ void ParseSentenceToWords(const StringPack &sentence, std::vector<StringPack> *w
 }
 
 int SkipGramCPUKernel::Run() {
+  auto ret = Prepare();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Prepare fail!ret: " << ret;
+    return ret;
+  }
   skip_gram_parameter_ = reinterpret_cast<SkipGramParameter *>(op_parameter_);
   if (skip_gram_parameter_->ngram_size < 1) {
     MS_LOG(ERROR) << "Skip Gram Parameter Error, NgramSize should be at least 1, get "
@@ -99,8 +105,7 @@ int SkipGramCPUKernel::Run() {
       index--;
     }
   }
-
-  int ret = mindspore::lite::WriteSeperatedStringsToTensor(out_tensors_[0], result);
+  ret = mindspore::lite::WriteSeperatedStringsToTensor(out_tensors_[0], result);
   return ret;
 }