add save_inference_model in infer.py (#2714)

* add save_inference_model in infer.py

* format code

* add comment

* add save_inference_model doc

* refine doc

PaddleCV/PaddleDetection/docs/GETTING_STARTED.md

@@ -72,6 +72,18 @@ python tools/infer.py -c configs/faster_rcnn_r50_1x.yml --infer_dir=demo
 The visualization files are saved in `output` by default, to specify a different
 path, simply add a `--save_file=` flag.
 
+- Save inference model
+
+```bash
+export CUDA_VISIBLE_DEVICES=0
+# or run on CPU with:
+# export CPU_NUM=1
+python tools/infer.py -c configs/faster_rcnn_r50_1x.yml --infer_img=demo/000000570688.jpg \
+                      --save_inference_model
+```
+
+Save inference model by set `--save_inference_model`.
+
 
 ## FAQ
 

PaddleCV/PaddleDetection/tools/infer.py

@@ -81,6 +81,24 @@ def get_test_images(infer_dir, infer_img):
     return images
 
 
+def save_infer_model(FLAGS, exe, feed_vars, test_fetches, infer_prog):
+    cfg_name = os.path.basename(FLAGS.config).split('.')[0]
+    save_dir = os.path.join(FLAGS.output_dir, cfg_name)
+    feeded_var_names = [var.name for var in feed_vars.values()]
+    # im_id is only used for visualize, not used in inference model
+    feeded_var_names.remove('im_id')
+    target_vars = test_fetches.values()
+    logger.info("Save inference model to {}, input: {}, output: "
+                "{}...".format(save_dir, feeded_var_names,
+                            [var.name for var in target_vars]))
+    fluid.io.save_inference_model(save_dir, 
+                                  feeded_var_names=feeded_var_names,
+                                  target_vars=target_vars,
+                                  executor=exe,
+                                  main_program=infer_prog,
+                                  params_filename="__parmas__")
+
+
 def main():
     cfg = load_config(FLAGS.config)
 
@@ -119,6 +137,9 @@ def main():
     if cfg.weights:
         checkpoint.load_checkpoint(exe, infer_prog, cfg.weights)
 
+    if FLAGS.save_inference_model:
+        save_infer_model(FLAGS, exe, feed_vars, test_fetches, infer_prog)
+
     # parse infer fetches
     extra_keys = []
     if cfg['metric'] == 'COCO':
@@ -196,5 +217,10 @@ if __name__ == '__main__':
         type=float,
         default=0.5,
         help="Threshold to reserve the result for visualization.")
+    parser.add_argument(
+        "--save_inference_model",
+        action='store_true',
+        default=False,
+        help="Save inference model in output_dir if True.")
     FLAGS = parser.parse_args()
     main()