diff --git a/mindspore/lite/test/models_tf.cfg b/mindspore/lite/test/models_tf.cfg
index 0da4e419c8..0c91fba2a5 100644
--- a/mindspore/lite/test/models_tf.cfg
+++ b/mindspore/lite/test/models_tf.cfg
@@ -56,3 +56,6 @@ mtk_age_gender.pb 1
 mtk_model_ckpt.pb 1
 mtk_model_face_dress.pb 1;1,128,128,3
 mtk_model_normalize_object_scene_ps_20200519.pb 1;1,224,224,3
+ml_ocr_latin.pb 1
+ml_noya_tts_melgan.pb 1;16,16,80
+ml_video_edit_oneclick_adaptis.pb 3
diff --git a/mindspore/lite/tools/converter/parser/tf/tf_deconv_parser.cc b/mindspore/lite/tools/converter/parser/tf/tf_deconv_parser.cc
index 48c5734e12..fd3f3ce800 100644
--- a/mindspore/lite/tools/converter/parser/tf/tf_deconv_parser.cc
+++ b/mindspore/lite/tools/converter/parser/tf/tf_deconv_parser.cc
@@ -26,7 +26,7 @@ namespace lite {
 STATUS TFDeconvParser::Parse(const tensorflow::NodeDef &tf_op,
                              const std::map<string, const tensorflow::NodeDef *> &tf_node_map, PrimitiveC **primitiveC,
                              std::vector<std::string> *inputs, int *output_size) {
-  MS_LOG(INFO) << "TF DeConvParser";
+  MS_LOG(DEBUG) << "TF DeConvParser";
   if (primitiveC == nullptr || output_size == nullptr) {
     MS_LOG(ERROR) << "primitiveC is nullptr";
     return RET_NULL_PTR;
@@ -71,8 +71,8 @@ STATUS TFDeconvParser::Parse(const tensorflow::NodeDef &tf_op,
     }
     attr->kernelH = kernels[0];
     attr->kernelW = kernels[1];
-    attr->channelIn = kernels[2];
-    attr->channelOut = kernels[3];
+    attr->channelOut = kernels[2];
+    attr->channelIn = kernels[3];
   } else {
     attr->kernelH = -1;
     attr->kernelW = -1;
diff --git a/mindspore/lite/tools/converter/parser/tf/tf_logical_parser.cc b/mindspore/lite/tools/converter/parser/tf/tf_logical_parser.cc
index b362bfa2a0..3202d4d50f 100644
--- a/mindspore/lite/tools/converter/parser/tf/tf_logical_parser.cc
+++ b/mindspore/lite/tools/converter/parser/tf/tf_logical_parser.cc
@@ -45,6 +45,27 @@ STATUS TFLogicalParser::Parse(const tensorflow::NodeDef &tf_op,
     primitive->value.type = schema::PrimitiveType_LogicalAnd;
     primitive->value.value = attr.release();
     *primitiveC = PrimitiveC::Create(primitive.release());
+  } else if (tf_op.op() == "LogicalOr") {
+    auto attr = std::make_unique<schema::LogicalOrT>();
+    if (attr == nullptr) {
+      MS_LOG(ERROR) << "new op failed";
+      return RET_NULL_PTR;
+    }
+    primitive->value.type = schema::PrimitiveType_LogicalOr;
+    primitive->value.value = attr.release();
+    *primitiveC = PrimitiveC::Create(primitive.release());
+  } else if (tf_op.op() == "LogicalNot") {
+    auto attr = std::make_unique<schema::LogicalNotT>();
+    if (attr == nullptr) {
+      MS_LOG(ERROR) << "new op failed";
+      return RET_NULL_PTR;
+    }
+    primitive->value.type = schema::PrimitiveType_LogicalNot;
+    primitive->value.value = attr.release();
+    *primitiveC = PrimitiveC::Create(primitive.release());
+  } else {
+    MS_LOG(ERROR) << tf_op.op() << " is not supported.";
+    return RET_ERROR;
   }
   if (*primitiveC == nullptr) {
     MS_LOG(ERROR) << "primitiveC is nullptr";
@@ -59,5 +80,7 @@ STATUS TFLogicalParser::Parse(const tensorflow::NodeDef &tf_op,
   return RET_OK;
 }
 TFNodeRegistrar g_tfLogicalAndParser("LogicalAnd", new TFLogicalParser());
+TFNodeRegistrar g_tfLogicalOrParser("LogicalOr", new TFLogicalParser());
+TFNodeRegistrar g_tfLogicalNotParser("LogicalNot", new TFLogicalParser());
 }  // namespace lite
 }  // namespace mindspore
diff --git a/mindspore/lite/tools/optimizer/fusion/conv_transform_fusion.cc b/mindspore/lite/tools/optimizer/fusion/conv_transform_fusion.cc
index 164fb702ed..dbe3452f79 100644
--- a/mindspore/lite/tools/optimizer/fusion/conv_transform_fusion.cc
+++ b/mindspore/lite/tools/optimizer/fusion/conv_transform_fusion.cc
@@ -222,8 +222,16 @@ void ConvTransformFusion::CalNewWeightTensor(const CNodePtr &conv_node, const Pa
       return;
     }
     if (this->fmk_type_ == lite::converter::FmkType_TF) {
-      for (int i = 0; i < weight_shape_size; i++) {
-        tmp_weight_data[i] = weight_data[i] * trans_scale[i % kernel_num];
+      auto group = primc->GetGroup();
+      auto cin_group = weight_tensor->tensor_shape()[3] / group;
+      int area_size = weight_tensor->tensor_shape()[0] * weight_tensor->tensor_shape()[1];
+      for (int j = 0; j < area_size; j++) {
+        for (int i = 0; i < kernel_num; ++i) {
+          for (int k = 0; k < cin_group; ++k) {
+            tmp_weight_data[k + i * cin_group + j * kernel_num * cin_group] =
+              weight_data[k + i * cin_group + j * kernel_num * cin_group] * trans_scale[i];
+          }
+        }
       }
     } else {
       auto group = primc->GetGroup();