fix arithmetic compare, matmul, logicalnot, constant_folding_fusion

mindspore/lite/src/ops/arithmetic_compare.cc

@@ -0,0 +1,33 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "src/ops/arithmetic_compare.h"
+
+namespace mindspore {
+namespace lite {
+
+int ArithmeticCompare::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
+  auto res = Arithmetic::InferShape(inputs_, outputs_);
+  if (res == RET_OK) {
+    auto output = outputs_.front();
+    output->set_data_type(TypeId::kNumberTypeBool);
+    return RET_OK;
+  } else {
+    return res;
+  }
+}
+}  // namespace lite
+}  // namespace mindspore

mindspore/lite/src/ops/arithmetic_compare.h

@@ -0,0 +1,41 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef LITE_MINDSPORE_LITE_C_OPS_ARITHMETIC_COMPARE_H_
+#define LITE_MINDSPORE_LITE_C_OPS_ARITHMETIC_COMPARE_H_
+
+#include <vector>
+#include <set>
+#include <cmath>
+
+#include "src/ops/arithmetic.h"
+
+namespace mindspore {
+namespace lite {
+class ArithmeticCompare : public Arithmetic {
+ public:
+  ArithmeticCompare() = default;
+  ~ArithmeticCompare() = default;
+#ifdef PRIMITIVE_WRITEABLE
+  MS_DECLARE_PARENT(ArithmeticCompare, Arithmetic);
+  explicit ArithmeticCompare(schema::PrimitiveT *primitive) : Arithmetic(primitive) {}
+#endif
+  int InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite::Tensor *> outputs_) override;
+};
+}  // namespace lite
+}  // namespace mindspore
+
+#endif  // LITE_MINDSPORE_LITE_C_OPS_ARITHMETIC_COMPARE_H_

mindspore/lite/src/ops/equal.cc

@@ -35,16 +35,6 @@ int Equal::UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::
 PrimitiveC *EqualCreator(const schema::Primitive *primitive) { return PrimitiveC::NewPrimitiveC<Equal>(primitive); }
 Registry EqualRegistry(schema::PrimitiveType_Equal, EqualCreator);
 #endif
-int Equal::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
-  auto input = inputs_.front();
-  MS_ASSERT(input != nullptr);
-  auto output = outputs_.front();
-  MS_ASSERT(output != nullptr);
-  output->set_shape(input->shape());
-  output->set_data_type(TypeId::kNumberTypeBool);
-  output->set_format(input->format());
-  return RET_OK;
-}
 
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/src/ops/equal.h

@@ -20,21 +20,20 @@
 #include <vector>
 #include <set>
 #include <cmath>
-#include "src/ops/arithmetic.h"
+#include "src/ops/arithmetic_compare.h"
 
 namespace mindspore {
 namespace lite {
-class Equal : public Arithmetic {
+class Equal : public ArithmeticCompare {
  public:
   Equal() = default;
   ~Equal() = default;
 #ifdef PRIMITIVE_WRITEABLE
-  MS_DECLARE_PARENT(Equal, PrimitiveC);
+  MS_DECLARE_PARENT(Equal, ArithmeticCompare);
-  explicit Equal(schema::PrimitiveT *primitive) : Arithmetic(primitive) {}
+  explicit Equal(schema::PrimitiveT *primitive) : ArithmeticCompare(primitive) {}
 #else
   int UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) override;
 #endif
-  int InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite::Tensor *> outputs_) override;
 };
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/src/ops/greater.cc

@@ -36,16 +36,6 @@ int Greater::UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers
 PrimitiveC *GreaterCreator(const schema::Primitive *primitive) { return PrimitiveC::NewPrimitiveC<Greater>(primitive); }
 Registry GreaterRegistry(schema::PrimitiveType_Greater, GreaterCreator);
 #endif
-int Greater::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
-  auto input = inputs_.front();
-  MS_ASSERT(input != nullptr);
-  auto output = outputs_.front();
-  MS_ASSERT(output != nullptr);
-  output->set_shape(input->shape());
-  output->set_data_type(TypeId::kNumberTypeBool);
-  output->set_format(input->format());
-  return RET_OK;
-}
 
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/src/ops/greater.h

@@ -20,21 +20,20 @@
 #include <set>
 #include <cmath>
 
-#include "src/ops/arithmetic.h"
+#include "src/ops/arithmetic_compare.h"
 
 namespace mindspore {
 namespace lite {
-class Greater : public Arithmetic {
+class Greater : public ArithmeticCompare {
  public:
   Greater() = default;
   ~Greater() = default;
 #ifdef PRIMITIVE_WRITEABLE
-  MS_DECLARE_PARENT(Greater, Arithmetic);
+  MS_DECLARE_PARENT(Greater, ArithmeticCompare);
-  explicit Greater(schema::PrimitiveT *primitive) : Arithmetic(primitive) {}
+  explicit Greater(schema::PrimitiveT *primitive) : ArithmeticCompare(primitive) {}
 #else
   int UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) override;
 #endif
-  int InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite::Tensor *> outputs_) override;
 };
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/src/ops/greater_equal.cc

@@ -38,16 +38,6 @@ PrimitiveC *GreaterEqualCreator(const schema::Primitive *primitive) {
 Registry GreaterEqualRegistry(schema::PrimitiveType_GreaterEqual, GreaterEqualCreator);
 
 #endif
-int GreaterEqual::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
-  auto input = inputs_.front();
-  MS_ASSERT(input != nullptr);
-  auto output = outputs_.front();
-  MS_ASSERT(output != nullptr);
-  output->set_shape(input->shape());
-  output->set_data_type(TypeId::kNumberTypeBool);
-  output->set_format(input->format());
-  return RET_OK;
-}
 
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/src/ops/greater_equal.h

@@ -21,21 +21,20 @@
 #include <set>
 #include <cmath>
 
-#include "src/ops/arithmetic.h"
+#include "src/ops/arithmetic_compare.h"
 
 namespace mindspore {
 namespace lite {
-class GreaterEqual : public Arithmetic {
+class GreaterEqual : public ArithmeticCompare {
  public:
   GreaterEqual() = default;
   ~GreaterEqual() = default;
 #ifdef PRIMITIVE_WRITEABLE
-  MS_DECLARE_PARENT(GreaterEqual, Arithmetic);
+  MS_DECLARE_PARENT(GreaterEqual, ArithmeticCompare);
-  explicit GreaterEqual(schema::PrimitiveT *primitive) : Arithmetic(primitive) {}
+  explicit GreaterEqual(schema::PrimitiveT *primitive) : ArithmeticCompare(primitive) {}
 #else
   int UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) override;
 #endif
-  int InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite::Tensor *> outputs_) override;
 };
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/src/ops/less.cc

@@ -38,16 +38,6 @@ PrimitiveC *LessCreator(const schema::Primitive *primitive) { return PrimitiveC:
 Registry LessRegistry(schema::PrimitiveType_Less, LessCreator);
 
 #endif
-int Less::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
-  auto input = inputs_.front();
-  MS_ASSERT(input != nullptr);
-  auto output = outputs_.front();
-  MS_ASSERT(output != nullptr);
-  output->set_shape(input->shape());
-  output->set_data_type(TypeId::kNumberTypeBool);
-  output->set_format(input->format());
-  return RET_OK;
-}
 
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/src/ops/less.h

@@ -21,21 +21,20 @@
 #include <set>
 #include <cmath>
 
-#include "src/ops/arithmetic.h"
+#include "src/ops/arithmetic_compare.h"
 
 namespace mindspore {
 namespace lite {
-class Less : public Arithmetic {
+class Less : public ArithmeticCompare {
  public:
   Less() = default;
   ~Less() = default;
 #ifdef PRIMITIVE_WRITEABLE
-  MS_DECLARE_PARENT(Less, Arithmetic);
+  MS_DECLARE_PARENT(Less, ArithmeticCompare);
-  explicit Less(schema::PrimitiveT *primitive) : Arithmetic(primitive) {}
+  explicit Less(schema::PrimitiveT *primitive) : ArithmeticCompare(primitive) {}
 #else
   int UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) override;
 #endif
-  int InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite::Tensor *> outputs_) override;
 };
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/src/ops/less_equal.cc

@@ -37,16 +37,6 @@ PrimitiveC *LessEqualCreator(const schema::Primitive *primitive) {
 }
 Registry LessEqualRegistry(schema::PrimitiveType_LessEqual, LessEqualCreator);
 #endif
-int LessEqual::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
-  auto input = inputs_.front();
-  MS_ASSERT(input != nullptr);
-  auto output = outputs_.front();
-  MS_ASSERT(output != nullptr);
-  output->set_shape(input->shape());
-  output->set_data_type(TypeId::kNumberTypeBool);
-  output->set_format(input->format());
-  return RET_OK;
-}
 
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/src/ops/less_equal.h

@@ -21,21 +21,20 @@
 #include <set>
 #include <cmath>
 
-#include "src/ops/arithmetic.h"
+#include "src/ops/arithmetic_compare.h"
 
 namespace mindspore {
 namespace lite {
-class LessEqual : public Arithmetic {
+class LessEqual : public ArithmeticCompare {
  public:
   LessEqual() = default;
   ~LessEqual() = default;
 #ifdef PRIMITIVE_WRITEABLE
-  MS_DECLARE_PARENT(LessEqual, Arithmetic);
+  MS_DECLARE_PARENT(LessEqual, ArithmeticCompare);
-  explicit LessEqual(schema::PrimitiveT *primitive) : Arithmetic(primitive) {}
+  explicit LessEqual(schema::PrimitiveT *primitive) : ArithmeticCompare(primitive) {}
 #else
   int UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) override;
 #endif
-  int InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite::Tensor *> outputs_) override;
 };
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/src/ops/matmul.cc

@@ -112,9 +112,17 @@ int MatMul::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outp
     input0->set_shape(a_shape);
   }
 
-  if (a_shape.size() < 2 || b_shape.size() < 2) {
+  bool del_start = false;
-    MS_LOG(ERROR) << "inputs shape is invalid";
+  bool del_end = false;
-    return RET_INPUT_TENSOR_ERROR;
+  if (a_shape.size() == 1) {
+    a_shape.insert(a_shape.begin(), 1);
+    input0->set_shape(a_shape);
+    del_start = true;
+  }
+  if (b_shape.size() == 1) {
+    b_shape.push_back(1);
+    input1->set_shape(b_shape);
+    del_end = true;
   }
   for (size_t i = 0; i < (a_shape.size() - 2) && i < (b_shape.size() - 2); ++i) {
     if (a_shape[a_shape.size() - 3 - i] != b_shape[b_shape.size() - 3 - i]) {
@@ -131,6 +139,12 @@ int MatMul::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outp
   }
   std::vector<int> c_shape(a_shape);
   c_shape[c_shape.size() - 1] = b_shape[b_shape.size() - 1];
+  if (del_start) {
+    c_shape.erase(c_shape.begin());
+  }
+  if (del_end) {
+    c_shape.pop_back();
+  }
   output->set_shape(c_shape);
   return RET_OK;
 }

mindspore/lite/src/ops/not_equal.cc

@@ -38,16 +38,6 @@ PrimitiveC *NotEqualCreator(const schema::Primitive *primitive) {
 Registry NotEqualRegistry(schema::PrimitiveType_NotEqual, NotEqualCreator);
 
 #endif
-int NotEqual::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
-  auto input = inputs_.front();
-  MS_ASSERT(input != nullptr);
-  auto output = outputs_.front();
-  MS_ASSERT(output != nullptr);
-  output->set_shape(input->shape());
-  output->set_data_type(TypeId::kNumberTypeBool);
-  output->set_format(input->format());
-  return RET_OK;
-}
 
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/src/ops/not_equal.h

@@ -21,21 +21,20 @@
 #include <set>
 #include <cmath>
 
-#include "src/ops/arithmetic.h"
+#include "src/ops/arithmetic_compare.h"
 
 namespace mindspore {
 namespace lite {
-class NotEqual : public Arithmetic {
+class NotEqual : public ArithmeticCompare {
  public:
   NotEqual() = default;
   ~NotEqual() = default;
 #ifdef PRIMITIVE_WRITEABLE
-  MS_DECLARE_PARENT(NotEqual, Arithmetic);
+  MS_DECLARE_PARENT(NotEqual, ArithmeticCompare);
-  explicit NotEqual(schema::PrimitiveT *primitive) : Arithmetic(primitive) {}
+  explicit NotEqual(schema::PrimitiveT *primitive) : ArithmeticCompare(primitive) {}
 #else
   int UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) override;
 #endif
-  int InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite::Tensor *> outputs_) override;
 };
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/src/ops/populate/arithmetic_populate.cc

@@ -58,11 +58,11 @@ Registry RealDivParameterRegistry(schema::PrimitiveType_RealDiv, PopulateArithme
 Registry LogicalAndParameterRegistry(schema::PrimitiveType_LogicalAnd, PopulateArithmetic);
 Registry ParameterRegistry(schema::PrimitiveType_LogicalOr, PopulateArithmetic);
 Registry EqualParameterRegistry(schema::PrimitiveType_Equal, PopulateArithmetic);
+Registry NotEqualParameterRegistry(schema::PrimitiveType_NotEqual, PopulateArithmetic);
 Registry LessParameterRegistry(schema::PrimitiveType_Less, PopulateArithmetic);
+Registry LessEqualParameterRegistry(schema::PrimitiveType_LessEqual, PopulateArithmetic);
 Registry GreaterParameterRegistry(schema::PrimitiveType_Greater, PopulateArithmetic);
 Registry GreaterEqualParameterRegistry(schema::PrimitiveType_GreaterEqual, PopulateArithmetic);
-Registry NotEqualParameterRegistry(schema::PrimitiveType_NotEqual, PopulateArithmetic);
-Registry LessEqualParameterRegistry(schema::PrimitiveType_LessEqual, PopulateArithmetic);
 Registry MaximumParameterRegistry(schema::PrimitiveType_Maximum, PopulateArithmetic);
 Registry MinimumParameterRegistry(schema::PrimitiveType_Minimum, PopulateArithmetic);
 Registry FloorDivParameterRegistry(schema::PrimitiveType_FloorDiv, PopulateArithmetic);

mindspore/lite/src/runtime/kernel/arm/fp32/arithmetic_compare_fp32.cc

@@ -28,77 +28,82 @@ using mindspore::schema::PrimitiveType_LessEqual;
 using mindspore::schema::PrimitiveType_NotEqual;
 
 namespace mindspore::kernel {
-namespace {
-typedef struct {
-  int primitive_type_;
-  ArithmeticCompareFp32Func func_;
-} TYPE_FUNC_INFO;
-}  // namespace
 
-ArithmeticCompareFp32Func ArithmeticCompareCPUKernel::GetArithmeticCompareFun(int primitive_type) {
+int ArithmeticCompareCPUKernel::BroadcastRun(void *input0, void *input1, void *output, int dim, int out_count,
-  TYPE_FUNC_INFO type_func_table[] = {
+                                             int out_thread_stride) {
-    {PrimitiveType_Equal, ElementEqualFp32},     {PrimitiveType_NotEqual, ElementNotEqualFp32},
+  if (dim > break_pos_) {
-    {PrimitiveType_Less, ElementLessFp32},       {PrimitiveType_LessEqual, ElementLessEqualFp32},
+    if (data_type_ == kDataTypeInt) {
-    {PrimitiveType_Greater, ElementGreaterFp32}, {PrimitiveType_GreaterEqual, ElementGreaterEqualFp32}};
+      return func_int32_(reinterpret_cast<int *>(input0) + out_thread_stride,
-  for (size_t i = 0; i < sizeof(type_func_table); i++) {
+                         reinterpret_cast<int *>(input1) + out_thread_stride,
-    if (type_func_table[i].primitive_type_ == primitive_type) {
+                         reinterpret_cast<uint8_t *>(output) + out_thread_stride, out_count);
-      return type_func_table[i].func_;
     }
+    return func_fp32_(reinterpret_cast<float *>(input0) + out_thread_stride,
+                      reinterpret_cast<float *>(input1) + out_thread_stride,
+                      reinterpret_cast<uint8_t *>(output) + out_thread_stride, out_count);
   }
-  return nullptr;
+  for (int i = 0; i < arithmeticParameter_->out_shape_[dim]; ++i) {
-}
+    int pos0_ = arithmeticParameter_->in_shape0_[dim] == 1 ? 0 : i;
-
+    int pos1_ = arithmeticParameter_->in_shape1_[dim] == 1 ? 0 : i;
-int ArithmeticCompareCPUKernel::Init() {
+    int error_code;
-  if (!InferShapeDone()) {
+    if (data_type_ == kDataTypeInt) {
-    return RET_OK;
+      error_code = BroadcastRun(reinterpret_cast<int *>(input0) + pos0_ * arithmeticParameter_->in_strides0_[dim],
+                                reinterpret_cast<int *>(input1) + pos1_ * arithmeticParameter_->in_strides1_[dim],
+                                reinterpret_cast<uint8_t *>(output) + i * arithmeticParameter_->out_strides_[dim],
+                                dim + 1, out_count, out_thread_stride);
+    } else {
+      error_code = BroadcastRun(reinterpret_cast<float *>(input0) + pos0_ * arithmeticParameter_->in_strides0_[dim],
+                                reinterpret_cast<float *>(input1) + pos1_ * arithmeticParameter_->in_strides1_[dim],
+                                reinterpret_cast<uint8_t *>(output) + i * arithmeticParameter_->out_strides_[dim],
+                                dim + 1, out_count, out_thread_stride);
+    }
+    if (error_code != RET_OK) {
+      return error_code;
+    }
   }
-  return ReSize();
+  return RET_OK;
 }
 
-int ArithmeticCompareCPUKernel::ReSize() { return RET_OK; }
+int ArithmeticCompareCPUKernel::DoArithmetic(int task_id) {
+  auto element_num = out_tensors_[0]->ElementsNum();
 
-int ArithmeticCompareCPUKernel::DoExecute(int task_id) {
+  MS_ASSERT(thread_count_ != 0);
-  if (in_tensors_.at(0)->shape() != in_tensors_.at(1)->shape()) {
+  int stride = UP_DIV(element_num, thread_count_);
-    MS_LOG(ERROR) << "Compare op must inputs have the same shape, support broadcast later! ";
+  int count = MSMIN(stride, element_num - stride * task_id);
-    return RET_ERROR;
+
-  }
+  if (func_fp32_ == nullptr) {
-  int elements_num = in_tensors_.at(0)->ElementsNum();
+    MS_LOG(ERROR) << "func_fp32_ function is nullptr!";
-  int stride = UP_DIV(elements_num, op_parameter_->thread_num_);
-  int offset = task_id * stride;
-  int count = MSMIN(stride, elements_num - offset);
-  if (count <= 0) {
-    return RET_OK;
-  }
-  if (func_ == nullptr) {
-    MS_LOG(ERROR) << "Run function is null! ";
     return RET_ERROR;
   }
-  // two inputs have the same shape, support broadcast later
-  auto *input0_ptr = reinterpret_cast<float *>(in_tensors_.at(0)->MutableData());
-  auto *input1_ptr = reinterpret_cast<float *>(in_tensors_.at(1)->MutableData());
-  auto *output_ptr = reinterpret_cast<uint8_t *>(out_tensors_.at(0)->MutableData());
-  auto ret = func_(input0_ptr + offset, input1_ptr + offset, output_ptr + offset, count);
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Run failed, illegal input! ";
-  }
-  return ret;
-}
 
-int ArithmeticCompareRun(void *cdata, int task_id) {
+  int error_code;
-  auto kernel = reinterpret_cast<ArithmeticCompareCPUKernel *>(cdata);
+  if (arithmeticParameter_->broadcasting_) {  // need broadcast
-  auto ret = kernel->DoExecute(task_id);
+    stride = UP_DIV(outside_, thread_count_);
-  if (ret != RET_OK) {
+    int out_count = MSMIN(stride, outside_ - stride * task_id);
-    MS_LOG(ERROR) << "ArithmeticSelfRuns error task_id[" << task_id << "] error_code[" << ret << "]";
+    int out_thread_stride = stride * task_id;
+    if (data_type_ == kDataTypeFloat) {
+      error_code = BroadcastRun(
+        reinterpret_cast<float *>(in_tensors_[0]->data_c()), reinterpret_cast<float *>(in_tensors_[1]->data_c()),
+        reinterpret_cast<uint8_t *>(out_tensors_[0]->data_c()), 0, out_count, out_thread_stride);
+    } else {
+      error_code = BroadcastRun(
+        reinterpret_cast<int *>(in_tensors_[0]->data_c()), reinterpret_cast<int *>(in_tensors_[1]->data_c()),
+        reinterpret_cast<uint8_t *>(out_tensors_[0]->data_c()), 0, out_count, out_thread_stride);
+    }
+  } else {  // no broadcast, neither is scalar, two same shape
+    if (data_type_ == kDataTypeFloat) {
+      error_code = func_fp32_(reinterpret_cast<float *>(in_tensors_[0]->data_c()) + stride * task_id,
+                              reinterpret_cast<float *>(in_tensors_[1]->data_c()) + stride * task_id,
+                              reinterpret_cast<uint8_t *>(out_tensors_[0]->data_c()) + stride * task_id, count);
+    } else {
+      error_code = func_int32_(reinterpret_cast<int *>(in_tensors_[0]->data_c()) + stride * task_id,
+                               reinterpret_cast<int *>(in_tensors_[1]->data_c()) + stride * task_id,
+                               reinterpret_cast<uint8_t *>(out_tensors_[0]->data_c()) + stride * task_id, count);
+    }
   }
-  return ret;
+  if (error_code != RET_OK) {
-}
+    return RET_ERROR;
-
-int ArithmeticCompareCPUKernel::Run() {
-  auto ret = ParallelLaunch(this->context_->thread_pool_, ArithmeticCompareRun, this, op_parameter_->thread_num_);
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "ArithmeticSelfRun error error_code[" << ret << "]";
   }
-  return ret;
+  return RET_OK;
 }
 
 kernel::LiteKernel *CpuArithmeticCompareFp32KernelCreator(const std::vector<lite::Tensor *> &inputs,

mindspore/lite/src/runtime/kernel/arm/fp32/arithmetic_compare_fp32.h

@@ -18,27 +18,57 @@
 
 #include <vector>
 #include "src/runtime/kernel/arm/fp32/arithmetic_fp32.h"
+#include "nnacl/fp32/arithmetic_compare_fp32.h"
 
 namespace mindspore::kernel {
 typedef int (*ArithmeticCompareFp32Func)(const float *input0, const float *input1, uint8_t *output, int element_size);
+typedef int (*ArithmeticCompareIntFunc)(const int *input0, const int *input1, uint8_t *output, int element_size);
 class ArithmeticCompareCPUKernel : public ArithmeticCPUKernel {
  public:
   explicit ArithmeticCompareCPUKernel(OpParameter *parameter, const std::vector<lite::Tensor *> &inputs,
                                       const std::vector<lite::Tensor *> &outputs, const lite::InnerContext *ctx,
                                       const mindspore::lite::PrimitiveC *primitive)
       : ArithmeticCPUKernel(parameter, inputs, outputs, ctx, primitive) {
-    func_ = GetArithmeticCompareFun(parameter->type_);
+    switch (parameter->type_) {
+      case PrimitiveType_Equal:
+        func_fp32_ = ElementEqualFp32;
+        func_int32_ = ElementEqualInt32;
+        break;
+      case PrimitiveType_NotEqual:
+        func_fp32_ = ElementNotEqualFp32;
+        func_int32_ = ElementNotEqualInt32;
+        break;
+      case PrimitiveType_Less:
+        func_fp32_ = ElementLessFp32;
+        func_int32_ = ElementLessInt32;
+        break;
+      case PrimitiveType_LessEqual:
+        func_fp32_ = ElementLessEqualFp32;
+        func_int32_ = ElementLessEqualInt32;
+        break;
+      case PrimitiveType_Greater:
+        func_fp32_ = ElementGreaterFp32;
+        func_int32_ = ElementGreaterInt32;
+        break;
+      case PrimitiveType_GreaterEqual:
+        func_fp32_ = ElementGreaterEqualFp32;
+        func_int32_ = ElementGreaterEqualInt32;
+        break;
+      default:
+        MS_LOG(ERROR) << "Error Operator type " << parameter->type_;
+        func_fp32_ = nullptr;
+        func_int32_ = nullptr;
+        break;
+    }
   }
   ~ArithmeticCompareCPUKernel() override = default;
 
-  int Init() override;
+  int DoArithmetic(int task_id) override;
-  int ReSize() override;
+  int BroadcastRun(void *input0, void *input1, void *output, int dim, int out_count, int out_thread_stride) override;
-  int Run() override;
-  virtual int DoExecute(int task_id);
 
  private:
-  ArithmeticCompareFp32Func GetArithmeticCompareFun(int primitive_type);
+  ArithmeticCompareFp32Func func_fp32_ = nullptr;
-  ArithmeticCompareFp32Func func_;
+  ArithmeticCompareIntFunc func_int32_ = nullptr;
 };
 int ArithmeticCompareRun(void *cdata, int task_id);
 }  // namespace mindspore::kernel

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

@@ -175,6 +175,15 @@ int ArithmeticCPUKernel::ReSize() {
             break;
         }
         break;
+      case PrimitiveType_Equal:
+      case PrimitiveType_Less:
+      case PrimitiveType_Greater:
+      case PrimitiveType_NotEqual:
+      case PrimitiveType_LessEqual:
+      case PrimitiveType_GreaterEqual:
+        arithmetic_opt_run_ = nullptr;
+        arithmetic_opt_run_int_ = nullptr;
+        break;
       default:
         break;
     }

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

@@ -167,19 +167,21 @@ class ArithmeticCPUKernel : public LiteKernel {
   int PreProcess() override;
   int ReSize() override;
   int Run() override;
-  int DoArithmetic(int task_id);
+  virtual int DoArithmetic(int task_id);
+  virtual int BroadcastRun(void *input0, void *input1, void *output, int dim, int out_count, int out_thread_stride);
 
- private:
+ protected:
-  int BroadcastRun(void *input0, void *input1, void *output, int dim, int out_count, int out_thread_stride);
   int break_pos_ = 0;
   int outside_ = 0;
   int thread_count_ = 1;
   ArithmeticParameter *arithmeticParameter_ = nullptr;
+  LiteDataType data_type_ = kDataTypeFloat;
+
+ private:
   ArithmeticRun arithmetic_run_ = nullptr;
   ArithmeticOptRun arithmetic_opt_run_ = nullptr;
   ArithmeticIntRun arithmetic_run_int_ = nullptr;
   ArithmeticOptIntRun arithmetic_opt_run_int_ = nullptr;
-  LiteDataType data_type_ = kDataTypeFloat;
 };
 }  // namespace mindspore::kernel
 #endif  // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_FP32_ARITHMETIC_H_

mindspore/lite/src/runtime/kernel/arm/int8/arithmetic_self_int8.cc

@@ -146,4 +146,5 @@ REG_KERNEL(kCPU, kNumberTypeInt8, PrimitiveType_Sqrt, CpuArithmeticSelfInt8Kerne
 REG_KERNEL(kCPU, kNumberTypeInt8, PrimitiveType_Rsqrt, CpuArithmeticSelfInt8KernelCreator)
 REG_KERNEL(kCPU, kNumberTypeInt8, PrimitiveType_Square, CpuArithmeticSelfInt8KernelCreator)
 REG_KERNEL(kCPU, kNumberTypeInt8, PrimitiveType_LogicalNot, CpuArithmeticSelfInt8KernelCreator)
+REG_KERNEL(kCPU, kNumberTypeBool, PrimitiveType_LogicalNot, CpuArithmeticSelfInt8KernelCreator)
 }  // namespace mindspore::kernel

mindspore/lite/tools/converter/parser/onnx/onnx_conv_parser.cc

@@ -135,17 +135,17 @@ STATUS OnnxConvParser::Parse(const onnx::GraphProto &onnx_graph, const onnx::Nod
       std::find_if(onnx_graph.initializer().begin(), onnx_graph.initializer().end(),
                    [onnx_conv_weight](const onnx::TensorProto &proto) { return proto.name() == onnx_conv_weight; });
     if (nodeIter == onnx_graph.initializer().end()) {
-      MS_LOG(ERROR) << "not find node: " << onnx_conv_weight;
+      MS_LOG(WARNING) << "not find node: " << onnx_conv_weight;
-      return RET_ERROR;
+    } else {
-    }
+      std::vector<int> weight_shape;
-    std::vector<int> weight_shape;
+      auto size = (*nodeIter).dims_size();
-    auto size = (*nodeIter).dims_size();
+      weight_shape.reserve(size);
-    weight_shape.reserve(size);
+      for (int i = 0; i < size; ++i) {
-    for (int i = 0; i < size; ++i) {
+        weight_shape.emplace_back((*nodeIter).dims(i));
-      weight_shape.emplace_back((*nodeIter).dims(i));
+      }
+      attr->channelOut = weight_shape[0];
+      attr->channelIn = weight_shape[1] * attr->group;
     }
-    attr->channelOut = weight_shape[0];
-    attr->channelIn = weight_shape[1] * attr->group;
   } else {
     auto nodeIter =
       std::find_if(onnx_graph.node().begin(), onnx_graph.node().end(),

mindspore/lite/tools/optimizer/fusion/constant_folding_fusion.cc

@@ -231,15 +231,6 @@ const AnfNodePtr ConstFoldPass::Process(const FuncGraphPtr &func_graph, const An
         output_tensors[m]->AddQuantParam(quant_arg);
       }
     }
-    // here, input_tensor's format need to be transposed nhwc according to fmkType,
-    // but for the time being, we only transpose the tensor with 0/1/2/3D.
-    // Others should be added in future.
-    for (auto &input_tensor : input_tensors) {
-      input_tensor->set_format(schema::Format::Format_NHWC);
-      if (input_tensor->shape().size() == 4) {
-        MS_LOG(INFO) << "init input_tensor format to nhwc";
-      }
-    }
     lite_primitive->InferShape(input_tensors, output_tensors);
     auto primitive = lite_primitive.get();
     MS_ASSERT(primitive != nullptr);