diff --git a/python/paddle/fluid/contrib/slim/tests/CMakeLists.txt b/python/paddle/fluid/contrib/slim/tests/CMakeLists.txt
index f401d64b73b89327afa1a4b81de78118e1f7ce3b..095489bc736e480062ac5c0e1ea9fbd1bc687507 100644
--- a/python/paddle/fluid/contrib/slim/tests/CMakeLists.txt
+++ b/python/paddle/fluid/contrib/slim/tests/CMakeLists.txt
@@ -113,6 +113,13 @@ function(save_qat_nlp_model_test target qat_model_dir fp32_model_save_path int8_
 	         --int8_model_save_path ${int8_model_save_path})
 endfunction()
 
+function(convert_model2dot_test target model_path save_graph_dir save_graph_name)
+    py_test(${target} SRCS ${CMAKE_CURRENT_SOURCE_DIR}/convert_model2dot.py
+            ARGS --model_path ${model_path}
+	         --save_graph_dir ${save_graph_dir}
+	         --save_graph_name ${save_graph_name})
+endfunction()
+
 if(WIN32)
 	list(REMOVE_ITEM TEST_OPS test_light_nas)
 	list(REMOVE_ITEM TEST_OPS test_post_training_quantization_mobilenetv1)
@@ -277,6 +284,10 @@ if(LINUX AND WITH_MKLDNN)
 	set(QAT2_FP32_ERNIE_SAVE_PATH "${QAT_INSTALL_DIR}/Ernie_qat2_fp32")
 	save_qat_nlp_model_test(save_qat2_model_ernie ${QAT2_ERNIE_MODEL_DIR}/Ernie_qat/float ${QAT2_FP32_ERNIE_SAVE_PATH} ${QAT2_INT8_ERNIE_SAVE_PATH})
 
+	# Convert QAT2 model to dot and pdf files 
+	set(QAT2_INT8_ERNIE_DOT_SAVE_PATH "${QAT_INSTALL_DIR}/Ernie_qat2_int8_dot_file")
+	convert_model2dot_test(convert_model2dot_ernie ${QAT2_ERNIE_MODEL_DIR}/Ernie_qat/float ${QAT2_INT8_ERNIE_DOT_SAVE_PATH} "Ernie_qat2_int8")
+
 endif()
 
 # Since the tests for QAT FP32 & INT8 comparison support only testing on Linux 
diff --git a/python/paddle/fluid/contrib/slim/tests/convert_model2dot.py b/python/paddle/fluid/contrib/slim/tests/convert_model2dot.py
new file mode 100644
index 0000000000000000000000000000000000000000..877897c0a0e7282546727d56b54c0af506e18bc0
--- /dev/null
+++ b/python/paddle/fluid/contrib/slim/tests/convert_model2dot.py
@@ -0,0 +1,72 @@
+#   copyright (c) 2020 paddlepaddle authors. all rights reserved.
+#
+# 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.
+
+import unittest
+import os
+import sys
+import argparse
+import paddle.fluid as fluid
+from paddle.fluid.framework import IrGraph
+from paddle.fluid import core
+
+
+def parse_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        '--model_path', type=str, default='', help='A path to a model.')
+    parser.add_argument(
+        '--save_graph_dir',
+        type=str,
+        default='',
+        help='A path to save the graph.')
+    parser.add_argument(
+        '--save_graph_name',
+        type=str,
+        default='',
+        help='A name to save the graph. Default - name from model path will be used'
+    )
+
+    test_args, args = parser.parse_known_args(namespace=unittest)
+    return test_args, sys.argv[:1] + args
+
+
+def generate_dot_for_model(model_path, save_graph_dir, save_graph_name):
+    place = fluid.CPUPlace()
+    exe = fluid.Executor(place)
+    inference_scope = fluid.executor.global_scope()
+    with fluid.scope_guard(inference_scope):
+        if os.path.exists(os.path.join(model_path, '__model__')):
+            [inference_program, feed_target_names,
+             fetch_targets] = fluid.io.load_inference_model(model_path, exe)
+        else:
+            [inference_program, feed_target_names,
+             fetch_targets] = fluid.io.load_inference_model(model_path, exe,
+                                                            'model', 'params')
+        graph = IrGraph(core.Graph(inference_program.desc), for_test=True)
+        if not os.path.exists(save_graph_dir):
+            os.makedirs(save_graph_dir)
+        model_name = os.path.basename(os.path.normpath(save_graph_dir))
+        if save_graph_name is '':
+            save_graph_name = model_name
+        graph.draw(save_graph_dir, save_graph_name, graph.all_op_nodes())
+        print(
+            "Success! Generated dot and pdf files for {0} model, that can be found at {1} named {2}.\n".
+            format(model_name, save_graph_dir, save_graph_name))
+
+
+if __name__ == '__main__':
+    global test_args
+    test_args, remaining_args = parse_args()
+    generate_dot_for_model(test_args.model_path, test_args.save_graph_dir,
+                           test_args.save_graph_name)