diff --git a/docs/api/lite_api_python/mindspore_lite/mindspore_lite.Converter.rst b/docs/api/lite_api_python/mindspore_lite/mindspore_lite.Converter.rst
index f575be1597e..3a22c17c98c 100644
--- a/docs/api/lite_api_python/mindspore_lite/mindspore_lite.Converter.rst
+++ b/docs/api/lite_api_python/mindspore_lite/mindspore_lite.Converter.rst
@@ -9,8 +9,8 @@ mindspore_lite.Converter
         参数默认值是None时表示不设置。
 
     参数：
-        - **fmk_type** (FmkType) - 输入模型框架类型。选项：FmkType.TF | FmkType.CAFFE | FmkType.ONNX | FmkType.MINDIR | FmkType.TFLITE。
-        - **model_file** (str) - 输入模型文件路径。e.g. "/home/user/model.prototxt"。选项：TF: "\*.pb" | CAFFE: "\*.prototxt" | ONNX: "\*.onnx" | MINDIR: "\*.mindir" | TFLITE: "\*.tflite"。
+        - **fmk_type** (FmkType) - 输入模型框架类型。选项：FmkType.TF | FmkType.CAFFE | FmkType.ONNX | FmkType.MINDIR | FmkType.TFLITE | FmkType.PYTORCH。
+        - **model_file** (str) - 输入模型文件路径。e.g. "/home/user/model.prototxt"。选项：TF: "\*.pb" | CAFFE: "\*.prototxt" | ONNX: "\*.onnx" | MINDIR: "\*.mindir" | TFLITE: "\*.tflite" | PYTORCH: "\*.pt or \*.pth"。
         - **output_file** (str) - 输出模型文件路径。可自动生成.ms后缀。e.g. "/home/user/model.prototxt"，它将生成名为model.prototxt.ms的模型在/home/user/路径下。
         - **weight_file** (str，可选) - 输入模型权重文件。仅当输入模型框架类型为FmkType.CAFFE时必选。e.g. "/home/user/model.caffemodel"。默认值：""。
         - **config_file** (str，可选) - 作为训练后量化或离线拆分算子并行的配置文件路径，禁用算子融合功能并将插件设置为so路径。默认值：""。
diff --git a/docs/api/lite_api_python/mindspore_lite/mindspore_lite.FmkType.rst b/docs/api/lite_api_python/mindspore_lite/mindspore_lite.FmkType.rst
index a54772329a6..459f66aa54d 100644
--- a/docs/api/lite_api_python/mindspore_lite/mindspore_lite.FmkType.rst
+++ b/docs/api/lite_api_python/mindspore_lite/mindspore_lite.FmkType.rst
@@ -26,4 +26,5 @@ mindspore_lite.FmkType
       ``FmkType.ONNX``             ONNX模型的框架类型，该模型使用.onnx作为后缀
       ``FmkType.MINDIR``           MindSpore模型的框架类型，该模型使用.mindir作为后缀
       ``FmkType.TFLITE``           TensorFlow Lite模型的框架类型，该模型使用.tflite作为后缀
+      ``FmkType.PYTORCH``          PyTorch模型的框架类型，该模型使用.pt或.pth作为后缀
       ===========================  ====================================================
diff --git a/docs/api/lite_api_python_en/mindspore_lite.rst b/docs/api/lite_api_python_en/mindspore_lite.rst
index 41155261ed4..77caf213b92 100644
--- a/docs/api/lite_api_python_en/mindspore_lite.rst
+++ b/docs/api/lite_api_python_en/mindspore_lite.rst
@@ -43,7 +43,7 @@ Converter
     ``FmkType.ONNX``             ONNX model's framework type, and the model uses .onnx as suffix
     ``FmkType.MINDIR``           MindSpore model's framework type, and the model uses .mindir as suffix
     ``FmkType.TFLITE``           TensorFlow Lite model's framework type, and the model uses .tflite as suffix
-    ``FmkType.PYTORCH``          PYTORCH model's framework type, and the model uses .pt or .pth as suffix
+    ``FmkType.PYTORCH``          PyTorch model's framework type, and the model uses .pt or .pth as suffix
     ===========================  ============================================================================
 
 .. autosummary::
diff --git a/mindspore/lite/python/api/converter.py b/mindspore/lite/python/api/converter.py
index c2e494bf37f..9fbbf237a19 100644
--- a/mindspore/lite/python/api/converter.py
+++ b/mindspore/lite/python/api/converter.py
@@ -36,6 +36,7 @@ class FmkType(Enum):
     ONNX = 2
     MINDIR = 3
     TFLITE = 4
+    PYTORCH = 5
 
 
 class Converter:
@@ -47,9 +48,10 @@ class Converter:
 
     Args:
         fmk_type (FmkType): Input model framework type. Options: FmkType.TF | FmkType.CAFFE | FmkType.ONNX |
-            FmkType.MINDIR | FmkType.TFLITE.
+            FmkType.MINDIR | FmkType.TFLITE | FmkType.PYTORCH.
         model_file (str): Path of the input model. e.g. "/home/user/model.prototxt". Options:
-            TF: "\*.pb" | CAFFE: "\*.prototxt" | ONNX: "\*.onnx" | MINDIR: "\*.mindir" | TFLITE: "\*.tflite".
+            TF: "\*.pb" | CAFFE: "\*.prototxt" | ONNX: "\*.onnx" | MINDIR: "\*.mindir" | TFLITE: "\*.tflite" |
+            PYTORCH: "\*.pt or \*.pth".
         output_file (str): Path of the output model. The suffix .ms can be automatically generated.
             e.g. "/home/user/model.prototxt", it will generate the model named model.prototxt.ms in /home/user/
         weight_file (str, optional): Input model weight file. Required only when fmk_type is FmkType.CAFFE.
@@ -175,6 +177,7 @@ class Converter:
             FmkType.ONNX: _c_lite_wrapper.FmkType.kFmkTypeOnnx,
             FmkType.MINDIR: _c_lite_wrapper.FmkType.kFmkTypeMs,
             FmkType.TFLITE: _c_lite_wrapper.FmkType.kFmkTypeTflite,
+            FmkType.PYTORCH: _c_lite_wrapper.FmkType.kFmkTypePytorch,
         }
         self._converter = _c_lite_wrapper.ConverterBind(fmk_type_py_cxx_map.get(fmk_type), model_file, output_file,
                                                         weight_file)
diff --git a/mindspore/lite/python/src/converter_pybind.cc b/mindspore/lite/python/src/converter_pybind.cc
index 7898b0bcb8c..56f1b35fc3b 100644
--- a/mindspore/lite/python/src/converter_pybind.cc
+++ b/mindspore/lite/python/src/converter_pybind.cc
@@ -27,7 +27,8 @@ void ConverterPyBind(const py::module &m) {
     .value("kFmkTypeCaffe", converter::FmkType::kFmkTypeCaffe)
     .value("kFmkTypeOnnx", converter::FmkType::kFmkTypeOnnx)
     .value("kFmkTypeMs", converter::FmkType::kFmkTypeMs)
-    .value("kFmkTypeTflite", converter::FmkType::kFmkTypeTflite);
+    .value("kFmkTypeTflite", converter::FmkType::kFmkTypeTflite)
+    .value("kFmkTypePytorch", converter::FmkType::kFmkTypePytorch);
 
   py::class_<Converter, std::shared_ptr<Converter>>(m, "ConverterBind")
     .def(py::init<converter::FmkType, const std::string &, const std::string &, const std::string &>())