!14496 enhance_update on net

From: @zhaozhenlong
Reviewed-by: @zhang_xue_tong,@zhanghaibo5
Signed-off-by: @zhang_xue_tong

mindspore/lite/src/runtime/kernel/npu/argmax_npu.cc

@@ -0,0 +1,76 @@
+/**
+ * Copyright 2021 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/runtime/kernel/npu/argmax_npu.h"
+#include <memory>
+#include "include/graph/op/all_ops.h"
+#include "src/kernel_registry.h"
+#include "src/runtime/agent/npu/npu_converter_utils.h"
+
+using mindspore::kernel::KERNEL_ARCH::kNPU;
+using mindspore::lite::KernelRegistrar;
+using mindspore::schema::PrimitiveType_ArgMaxFusion;
+
+namespace mindspore::kernel {
+int ArgmaxNPUKernel::IsSupport(const std::vector<lite::Tensor *> &inputs, const std::vector<lite::Tensor *> &outputs,
+                               OpParameter *opParameter) {
+  return RET_OK;
+}
+
+int ArgmaxNPUKernel::SetNPUInputs(const std::vector<lite::Tensor *> &inputs, const std::vector<lite::Tensor *> &outputs,
+                                  const std::vector<ge::Operator *> &npu_inputs) {
+  op_ = new (std::nothrow) hiai::op::ArgMaxExt2(name_);
+  if (op_ == nullptr) {
+    MS_LOG(ERROR) << "New argmax npu operator for " << name_ << " failed.";
+    return RET_ERROR;
+  }
+  op_->set_input_x(*npu_inputs[0]);
+  auto axis_const_ = new (std::nothrow) hiai::op::Const(name_ + "_axis");
+  if (axis_const_ == nullptr) {
+    MS_LOG(ERROR) << "New weight const failed.";
+    return RET_ERROR;
+  }
+  ge::TensorDesc tensor_desc(ge::Shape({1}), ge::FORMAT_NCHW, ge::DT_INT32);
+  std::shared_ptr<ge::Tensor> ge_tensor =
+    std::make_shared<ge::Tensor>(tensor_desc, reinterpret_cast<const uint8_t *>(&(param_->axis_)), sizeof(int));
+  if (ge_tensor == nullptr) {
+    MS_LOG(ERROR) << "new ge_tensor failed.";
+    return RET_ERROR;
+  }
+  axis_const_->set_attr_value(ge_tensor);
+  op_->set_input_axis(*axis_const_);
+  op_->set_attr_keep_dims(param_->keep_dims_);
+  op_->set_attr_outmaxval(param_->out_value_);
+  op_->set_attr_topk(param_->topk_);
+
+  return RET_OK;
+}
+
+ge::Operator *mindspore::kernel::ArgmaxNPUKernel::GetNPUOp() { return op_; }
+
+ArgmaxNPUKernel::~ArgmaxNPUKernel() {
+  if (op_ != nullptr) {
+    delete op_;
+    op_ = nullptr;
+  }
+  if (axis_const_ != nullptr) {
+    delete axis_const_;
+    axis_const_ = nullptr;
+  }
+}
+
+REG_KERNEL(kNPU, kNumberTypeFloat32, PrimitiveType_ArgMaxFusion, NPUKernelCreator<ArgmaxNPUKernel>)
+}  // namespace mindspore::kernel

mindspore/lite/src/runtime/kernel/npu/argmax_npu.h

@@ -0,0 +1,48 @@
+/**
+ * Copyright 2021 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 MINDSPORE_LITE_SRC_RUNTIME_KERNEL_NPU_ARGMAX_NPU_H_
+#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_NPU_ARGMAX_NPU_H_
+
+#include <vector>
+#include "include/graph/op/all_ops.h"
+#include "include/graph/compatible/all_ops.h"
+#include "src/runtime/kernel/npu/npu_kernel.h"
+#include "nnacl/arg_min_max_parameter.h"
+
+namespace mindspore::kernel {
+class ArgmaxNPUKernel : public NPUKernel {
+ public:
+  ArgmaxNPUKernel(OpParameter *parameter, const std::vector<lite::Tensor *> &inputs,
+                  const std::vector<lite::Tensor *> &outputs, const lite::InnerContext *ctx)
+      : NPUKernel(parameter, inputs, outputs, ctx) {
+    param_ = reinterpret_cast<ArgMinMaxParameter *>(parameter);
+  }
+  ~ArgmaxNPUKernel() override;
+
+  int IsSupport(const std::vector<lite::Tensor *> &inputs, const std::vector<lite::Tensor *> &outputs,
+                OpParameter *opParameter) override;
+  int SetNPUInputs(const std::vector<lite::Tensor *> &inputs, const std::vector<lite::Tensor *> &outputs,
+                   const std::vector<ge::Operator *> &npu_inputs) override;
+  ge::Operator *GetNPUOp() override;
+
+ private:
+  hiai::op::ArgMaxExt2 *op_ = nullptr;
+  hiai::op::Const *axis_const_ = nullptr;
+  ArgMinMaxParameter *param_;
+};
+}  // namespace mindspore::kernel
+#endif  // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_NPU_ARGMAX_NPU_H_

mindspore/lite/src/runtime/kernel/npu/reshape_npu.cc

@@ -26,10 +26,17 @@ using mindspore::schema::PrimitiveType_Reshape;
 namespace mindspore::kernel {
 int ReshapeNPUKernel::IsSupport(const std::vector<lite::Tensor *> &inputs, const std::vector<lite::Tensor *> &outputs,
                                 OpParameter *opParameter) {
-  if (reshape_param_->shape_dim_ == 0) {
-    MS_LOG(ERROR) << "Npu reshape op only supports const shape.";
+  if (inputs.size() == 1 && reshape_param_->shape_dim_ == 0) {
+    MS_LOG(WARNING) << "Npu reshape op only supports const shape.";
     return RET_ERROR;
   }
+  if (inputs.size() > 1) {
+    auto shape_tensor = inputs.at(1);
+    if (!shape_tensor->IsConst()) {
+      MS_LOG(WARNING) << "Npu reshape op only supports const shape.";
+      return RET_ERROR;
+    }
+  }
   return RET_OK;
 }
 

mindspore/lite/test/models_npu.cfg

@@ -81,3 +81,4 @@ posenet_mobilenet_float_075_1_default_1.tflite 395
 nasnet_mobile.tflite 1
 ml_video_edit_art_generate.onnx 0.5
 ml_video_edit_art_transfer.onnx 3 3
+ml_video_edit_enhance_update.onnx 0.5

mindspore/lite/test/models_onnx.cfg

@@ -72,3 +72,4 @@ mtk_face_features_v2.onnx;1,256,192,3
 mtk_face_recognition_v3.onnx
 mtk_face_recognition_v2.onnx
 ml_2012_ocr_detection.onnx
+ml_video_edit_enhance_update.onnx

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

@@ -246,7 +246,7 @@ void ConvTransformFusion::CalNewWeightTensor(const CNodePtr &conv_node, const te
                                              int kernel_num, const float *trans_scale) const {
   MS_ASSERT(weight_data != nullptr);
   MS_ASSERT(trans_scale != nullptr);
-  if (weight_tensor->shape().size() != 4) {
+  if (weight_tensor->shape().size() > 4) {
     MS_LOG(ERROR) << "weight tensor shape error";
     return;
   }