chore: import upstream snapshot with attribution

test/quantization/convert_model2dot.py

@@ -0,0 +1,92 @@
+#   copyright (c) 2022 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 argparse
+import os
+import sys
+import unittest
+
+import paddle
+from paddle.base.framework import IrGraph
+from paddle.framework import core
+
+paddle.enable_static()
+
+
+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 = paddle.CPUPlace()
+    exe = paddle.static.Executor(place)
+    inference_scope = paddle.static.global_scope()
+    with paddle.static.scope_guard(inference_scope):
+        if os.path.exists(os.path.join(model_path, '__model__')):
+            [
+                inference_program,
+                feed_target_names,
+                fetch_targets,
+            ] = paddle.static.io.load_inference_model(
+                model_path, exe, model_filename='__model__'
+            )
+        else:
+            [
+                inference_program,
+                feed_target_names,
+                fetch_targets,
+            ] = paddle.static.load_inference_model(
+                model_path,
+                exe,
+                model_filename='model',
+                params_filename='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 == '':
+            save_graph_name = model_name
+        graph.draw(save_graph_dir, save_graph_name, graph.all_op_nodes())
+        print(
+            f"Success! Generated dot and pdf files for {model_name} model, that can be found at {save_graph_dir} named {save_graph_name}.\n"
+        )
+
+
+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,
+    )