Modify save_quant_model to support different input and output filenames

python/paddle/fluid/contrib/slim/tests/save_quant_model.py

@@ -52,6 +52,30 @@ def parse_args():
         '--debug',
         action='store_true',
         help='If used, the graph of Quant model is drawn.')
+    parser.add_argument(
+        '--quant_model_filename',
+        type=str,
+        default="",
+        help='The input model`s file name. If empty, search default `__model__` and separate parameter files and use them or in case if not found, attempt loading `model` and `params` files.'
+    )
+    parser.add_argument(
+        '--quant_params_filename',
+        type=str,
+        default="",
+        help='If quant_model_filename is empty, this field is ignored. The input model`s all parameters file name. If empty load parameters from separate files.'
+    )
+    parser.add_argument(
+        '--save_model_filename',
+        type=str,
+        default="__model__",
+        help='The name of file to save the inference program itself. If is set None, a default filename __model__ will be used.'
+    )
+    parser.add_argument(
+        '--save_params_filename',
+        type=str,
+        default=None,
+        help='The name of file to save all related parameters. If it is set None, parameters will be saved in separate files'
+    )
 
     test_args, args = parser.parse_known_args(namespace=unittest)
     return test_args, sys.argv[:1] + args
@@ -61,18 +85,29 @@ def transform_and_save_int8_model(original_path,
                                   save_path,
                                   ops_to_quantize='',
                                   op_ids_to_skip='',
-                                  debug=False):
+                                  debug=False,
+                                  quant_model_filename='',
+                                  quant_params_filename='',
+                                  save_model_filename='',
+                                  save_params_filename=''):
     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(original_path, '__model__')):
-            [inference_program, feed_target_names,
-             fetch_targets] = fluid.io.load_inference_model(original_path, exe)
+        if not quant_model_filename:
+            if os.path.exists(os.path.join(original_path, '__model__')):
+                [inference_program, feed_target_names,
+                 fetch_targets] = fluid.io.load_inference_model(original_path,
+                                                                exe)
+            else:
+                [inference_program, feed_target_names,
+                 fetch_targets] = fluid.io.load_inference_model(
+                     original_path, exe, 'model', 'params')
         else:
             [inference_program, feed_target_names,
-             fetch_targets] = fluid.io.load_inference_model(original_path, exe,
-                                                            'model', 'params')
+             fetch_targets] = fluid.io.load_inference_model(
+                 original_path, exe, quant_model_filename,
+                 quant_params_filename)
 
         ops_to_quantize_set = set()
         print(ops_to_quantize)
@@ -97,8 +132,14 @@ def transform_and_save_int8_model(original_path,
         graph = transform_to_mkldnn_int8_pass.apply(graph)
         inference_program = graph.to_program()
         with fluid.scope_guard(inference_scope):
-            fluid.io.save_inference_model(save_path, feed_target_names,
-                                          fetch_targets, exe, inference_program)
+            fluid.io.save_inference_model(
+                save_path,
+                feed_target_names,
+                fetch_targets,
+                exe,
+                inference_program,
+                model_filename=save_model_filename,
+                params_filename=save_params_filename)
         print(
             "Success! INT8 model obtained from the Quant model can be found at {}\n"
             .format(save_path))
@@ -109,4 +150,6 @@ def transform_and_save_int8_model(original_path,
     test_args, remaining_args = parse_args()
     transform_and_save_int8_model(
         test_args.quant_model_path, test_args.int8_model_save_path,
-        test_args.ops_to_quantize, test_args.op_ids_to_skip, test_args.debug)
+        test_args.ops_to_quantize, test_args.op_ids_to_skip, test_args.debug,
+        test_args.save_model_filename, test_args.save_params_filename,
+        test_args.quant_model_filename, test_args.quant_params_filename)