add support for no dist (#1989)

docs/zh_CN/PULC/PULC_traffic_sign.md

@@ -131,7 +131,7 @@ cd path_to_PaddleClas
 
 ```shell
 cd dataset
-wget https://paddleclas.bj.bcebos.com/data/cls_demo/traffic_sign.tar
+wget https://paddleclas.bj.bcebos.com/data/PULC/traffic_sign.tar
 tar -xf traffic_sign.tar
 cd ../
 ```

ppcls/configs/PULC/traffic_sign/search.yaml

@@ -30,6 +30,7 @@ search_dict:
       - [0.0, 0.4, 0.4, 0.8, 0.8, 1.0]
       - [1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
 teacher:
+  algorithm: "skl-ugi"
   rm_keys:
     - Arch.lr_mult_list
   search_values:

ppcls/configs/PULC/vehicle_attr/search.yaml

@@ -25,6 +25,7 @@ search_dict:
       - [0.0, 0.4, 0.4, 0.8, 0.8, 1.0]
       - [1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
 teacher:
+  algorithm: "skl-ugi"
   rm_keys:
     - Arch.lr_mult_list
   search_values:

ppcls/data/preprocess/ops/operators.py

@@ -365,9 +365,6 @@ class RandomCropImage(object):
         j = random.randint(0, w - tw)
 
         img = img[i:i + th, j:j + tw, :]
-        if img.shape[0] != 256 or img.shape[1] != 192:
-            raise ValueError('sample: ', h, w, i, j, th, tw, img.shape)
-
         return img
 
 

tools/search_strategy.py

@@ -20,8 +20,13 @@ def get_result(log_dir):
     return res
 
 
-def search_train(search_list, base_program, base_output_dir, search_key,
+def search_train(search_list,
-                 config_replace_value, model_name, search_times=1):
+                 base_program,
+                 base_output_dir,
+                 search_key,
+                 config_replace_value,
+                 model_name,
+                 search_times=1):
     best_res = 0.
     best = search_list[0]
     all_result = {}
@@ -33,7 +38,8 @@ def search_train(search_list, base_program, base_output_dir, search_key,
                 model_name = search_i
         res_list = []
         for j in range(search_times):
-            output_dir = "{}/{}_{}_{}".format(base_output_dir, search_key, search_i, j).replace(".", "_")
+            output_dir = "{}/{}_{}_{}".format(base_output_dir, search_key,
+                                              search_i, j).replace(".", "_")
             program += ["-o", "Global.output_dir={}".format(output_dir)]
             process = subprocess.Popen(program)
             process.communicate()
@@ -50,14 +56,17 @@ def search_train(search_list, base_program, base_output_dir, search_key,
 
 def search_strategy():
     args = config.parse_args()
-    configs = config.get_config(args.config, overrides=args.override, show=False)
+    configs = config.get_config(
+        args.config, overrides=args.override, show=False)
     base_config_file = configs["base_config_file"]
     distill_config_file = configs["distill_config_file"]
     model_name = config.get_config(base_config_file)["Arch"]["name"]
     gpus = configs["gpus"]
     gpus = ",".join([str(i) for i in gpus])
-    base_program = ["python3.7", "-m", "paddle.distributed.launch", "--gpus={}".format(gpus),
+    base_program = [
-                    "tools/train.py", "-c", base_config_file]
+        "python3.7", "-m", "paddle.distributed.launch",
+        "--gpus={}".format(gpus), "tools/train.py", "-c", base_config_file
+    ]
     base_output_dir = configs["output_dir"]
     search_times = configs["search_times"]
     search_dict = configs.get("search_dict")
@@ -67,41 +76,61 @@ def search_strategy():
         search_values = search_i["search_values"]
         replace_config = search_i["replace_config"]
         res = search_train(search_values, base_program, base_output_dir,
-                           search_key, replace_config, model_name, search_times)
+                           search_key, replace_config, model_name,
+                           search_times)
         all_results[search_key] = res
         best = res.get("best")
         for v in replace_config:
             base_program += ["-o", "{}={}".format(v, best)]
 
     teacher_configs = configs.get("teacher", None)
-    if teacher_configs is not None:
+    if teacher_configs is None:
+        print(all_results, base_program)
+        return
+
+    algo = teacher_configs.get("algorithm", "skl-ugi")
+    supported_list = ["skl-ugi", "udml"]
+    assert algo in supported_list, f"algorithm must be in {supported_list} but got {algo}"
+    if algo == "skl-ugi":
         teacher_program = base_program.copy()
         # remove incompatible keys
         teacher_rm_keys = teacher_configs["rm_keys"]
         rm_indices = []
         for rm_k in teacher_rm_keys:
             for ind, ki in enumerate(base_program):
-              if rm_k in ki:
+                if rm_k in ki:
-                rm_indices.append(ind)
+                    rm_indices.append(ind)
         for rm_index in rm_indices[::-1]:
             teacher_program.pop(rm_index)
-            teacher_program.pop(rm_index-1)
+            teacher_program.pop(rm_index - 1)
         replace_config = ["Arch.name"]
         teacher_list = teacher_configs["search_values"]
-        res = search_train(teacher_list, teacher_program, base_output_dir, "teacher", replace_config, model_name)
+        res = search_train(teacher_list, teacher_program, base_output_dir,
+                           "teacher", replace_config, model_name)
         all_results["teacher"] = res
         best = res.get("best")
-        t_pretrained = "{}/{}_{}_0/{}/best_model".format(base_output_dir, "teacher", best, best)
+        t_pretrained = "{}/{}_{}_0/{}/best_model".format(base_output_dir,
-        base_program += ["-o", "Arch.models.0.Teacher.name={}".format(best),
+                                                         "teacher", best, best)
-                         "-o", "Arch.models.0.Teacher.pretrained={}".format(t_pretrained)]
+        base_program += [
+            "-o", "Arch.models.0.Teacher.name={}".format(best), "-o",
+            "Arch.models.0.Teacher.pretrained={}".format(t_pretrained)
+        ]
+    elif algo == "udml":
+        if "lr_mult_list" in all_results:
+            base_program += [
+                "-o", "Arch.models.0.Teacher.lr_mult_list={}".format(
+                    all_results["lr_mult_list"]["best"])
+            ]
+
     output_dir = "{}/search_res".format(base_output_dir)
     base_program += ["-o", "Global.output_dir={}".format(output_dir)]
     final_replace = configs.get('final_replace')
     for i in range(len(base_program)):
-      base_program[i] = base_program[i].replace(base_config_file, distill_config_file)
+        base_program[i] = base_program[i].replace(base_config_file,
-      for k in final_replace:
+                                                  distill_config_file)
-        v = final_replace[k]
+        for k in final_replace:
-        base_program[i] = base_program[i].replace(k, v)
+            v = final_replace[k]
+            base_program[i] = base_program[i].replace(k, v)
 
     process = subprocess.Popen(base_program)
     process.communicate()