fix_pir_pre-commit

.pre-commit-config.yaml

@@ -8,13 +8,13 @@ repos:
         files: \.(md|yml)$
     -   id: remove-tabs
         files: \.(md|yml)$
--   repo: https://github.com/PaddlePaddle/mirrors-yapf.git
-    rev: v0.16.2
+-   repo: https://github.com/pre-commit/mirrors-yapf.git
+    rev: v0.32.0
     hooks:
     -   id: yapf
         files: (.*\.(py|bzl)|BUILD|.*\.BUILD|WORKSPACE)$
 -   repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
+    rev: v4.6.0
     hooks:
     -   id: check-added-large-files
     -   id: check-merge-conflict

ce_tests/dygraph/quant/src/eval.py

@@ -17,9 +17,14 @@
 
 
 def eval(args):
-    model_file = os.path.join(args.model_path, args.model_filename)
-    params_file = os.path.join(args.model_path, args.params_filename)
-    config = paddle_infer.Config(model_file, params_file)
+    if '2' in paddle.__version__.split('.')[0]:
+        config = paddle.inference.Config(
+            os.path.join(args.model_path, args.model_filename),
+            os.path.join(args.model_path, args.params_filename))
+    else:
+        model_prefix = args.model_filename.split('.')[0]
+        config = paddle.inference.Config(
+            os.path.join(args.model_path, model_prefix))
     config.enable_mkldnn()
     config.switch_ir_optim(False)
 

ce_tests/dygraph/quant/src/test.py

@@ -18,9 +18,14 @@
 
 def eval(args):
     # create predictor
-    model_file = os.path.join(args.model_path, args.model_filename)
-    params_file = os.path.join(args.model_path, args.params_filename)
-    config = paddle_infer.Config(model_file, params_file)
+    if '2' in paddle.__version__.split('.')[0]:
+        config = paddle.inference.Config(
+            os.path.join(args.model_path, args.model_filename),
+            os.path.join(args.model_path, args.params_filename))
+    else:
+        model_prefix = args.model_filename.split('.')[0]
+        config = paddle.inference.Config(
+            os.path.join(args.model_path, model_prefix))
     if args.use_gpu:
         config.enable_use_gpu(1000, 0)
     if not args.ir_optim:

demo/dygraph/post_quant/eval.py

@@ -30,9 +30,15 @@
 
 def eval():
     # create predictor
-    model_file = os.path.join(FLAGS.model_path, FLAGS.model_filename)
-    params_file = os.path.join(FLAGS.model_path, FLAGS.params_filename)
-    config = paddle_infer.Config(model_file, params_file)
+    if '2' in paddle.__version__.split('.')[0]:
+        config = paddle.inference.Config(
+            os.path.join(FLAGS.model_path, FLAGS.model_filename),
+            os.path.join(FLAGS.model_path, FLAGS.params_filename))
+    else:
+        model_prefix = FLAGS.model_filename.split('.')[0]
+        config = paddle.inference.Config(
+            os.path.join(FLAGS.model_path, model_prefix))
+
     if FLAGS.use_gpu:
         config.enable_use_gpu(1000, 0)
     if not FLAGS.ir_optim:
@@ -97,8 +103,8 @@ def eval():
     acc5 = correct_5_num / total_num
     avg_time = cost_time / total_num
     print("End test: test image {}".format(total_num))
-    print("test_acc1: {:.4f}; test_acc5: {:.4f}; avg time: {:.5f} sec/img".format(
-        acc1, acc5, avg_time))
+    print("test_acc1: {:.4f}; test_acc5: {:.4f}; avg time: {:.5f} sec/img".
+          format(acc1, acc5, avg_time))
     print("\n")
 
 

example/auto_compression/detection/paddle_inference_eval.py

@@ -65,8 +65,7 @@ def argsparser():
         "--device",
         type=str,
         default="GPU",
-        help=
-        "Choose the device you want to run, it can be: CPU/GPU/XPU, default is GPU",
+        help="Choose the device you want to run, it can be: CPU/GPU/XPU, default is GPU",
     )
     parser.add_argument(
         "--use_dynamic_shape",
@@ -243,9 +242,13 @@ def load_predictor(
         raise ValueError(
             "Predict by TensorRT mode: {}, expect device=='GPU', but device == {}".
             format(precision, device))
-    config = Config(
-        os.path.join(model_dir, "model.pdmodel"),
-        os.path.join(model_dir, "model.pdiparams"))
+    # support paddle 2.x
+    if '2' in paddle.__version__.split('.')[0]:
+        config = Config(
+            os.path.join(model_dir, "model.pdmodel"),
+            os.path.join(model_dir, "model.pdiparams"))
+    else:
+        config = Config(os.path.join(model_dir, "model"))
 
     config.enable_memory_optim()
     if device == "GPU":
@@ -281,8 +284,8 @@ def load_predictor(
             dynamic_shape_file = os.path.join(FLAGS.model_path,
                                               "dynamic_shape.txt")
             if os.path.exists(dynamic_shape_file):
-                config.enable_tuned_tensorrt_dynamic_shape(
-                    dynamic_shape_file, True)
+                config.enable_tuned_tensorrt_dynamic_shape(dynamic_shape_file,
+                                                           True)
                 print("trt set dynamic shape done!")
             else:
                 config.collect_shape_range_info(dynamic_shape_file)
@@ -434,10 +437,9 @@ def main():
         reader_cfg = load_config(FLAGS.reader_config)
         dataset = reader_cfg["EvalDataset"]
         global val_loader
-        val_loader = create("EvalReader")(
-            reader_cfg["EvalDataset"],
-            reader_cfg["worker_num"],
-            return_list=True)
+        val_loader = create("EvalReader")(reader_cfg["EvalDataset"],
+                                          reader_cfg["worker_num"],
+                                          return_list=True)
         clsid2catid = {v: k for k, v in dataset.catid2clsid.items()}
         anno_file = dataset.get_anno()
         metric = COCOMetric(
@@ -463,4 +465,4 @@ def main():
     # DataLoader need run on cpu
     paddle.set_device("cpu")
 
-    main()
+    main()

example/auto_compression/image_classification/paddle_inference_eval.py

@@ -113,9 +113,15 @@ def __init__(self):
 
     def _create_paddle_predictor(self):
         inference_model_dir = args.model_path
-        model_file = os.path.join(inference_model_dir, args.model_filename)
-        params_file = os.path.join(inference_model_dir, args.params_filename)
-        config = paddle.inference.Config(model_file, params_file)
+        if '2' in paddle.__version__.split('.')[0]:
+            config = paddle.inference.Config(
+                os.path.join(inference_model_dir, args.model_filename),
+                os.path.join(inference_model_dir, args.params_filename))
+        else:
+            model_prefix = args.model_filename.split('.')[0]
+            config = paddle.inference.Config(
+                os.path.join(inference_model_dir, model_prefix))
+
         precision = paddle.inference.Config.Precision.Float32
         if args.use_int8:
             precision = paddle.inference.Config.Precision.Int8

example/auto_compression/nlp/paddle_inference_eval.py

@@ -91,8 +91,7 @@ def parse_args():
         "--max_seq_length",
         default=128,
         type=int,
-        help=
-        "The maximum total input sequence length after tokenization. Sequences longer "
+        help="The maximum total input sequence length after tokenization. Sequences longer "
         "than this will be truncated, sequences shorter will be padded.", )
     parser.add_argument(
         "--perf_warmup_steps",
@@ -108,8 +107,7 @@ def parse_args():
         type=str,
         default="fp32",
         choices=["fp32", "fp16", "int8"],
-        help=
-        "The precision of inference. It can be 'fp32', 'fp16' or 'int8'. Default is 'fp16'.",
+        help="The precision of inference. It can be 'fp32', 'fp16' or 'int8'. Default is 'fp16'.",
     )
     parser.add_argument(
         "--use_mkldnn",
@@ -158,7 +156,8 @@ def _convert_example(example,
             }
         elif "target" in example:  # wsc
             text, query, pronoun, query_idx, pronoun_idx = (
-                example["text"], example["target"]["span1_text"],
+                example["text"],
+                example["target"]["span1_text"],
                 example["target"]["span2_text"],
                 example["target"]["span1_index"],
                 example["target"]["span2_index"], )
@@ -207,9 +206,14 @@ def create_predictor(cls, args):
         create_predictor func
         """
         cls.rerun_flag = False
-        config = paddle.inference.Config(
-            os.path.join(args.model_path, args.model_filename),
-            os.path.join(args.model_path, args.params_filename))
+        if '2' in paddle.__version__.split('.')[0]:
+            config = paddle.inference.Config(
+                os.path.join(args.model_path, args.model_filename),
+                os.path.join(args.model_path, args.params_filename))
+        else:
+            model_prefix = args.model_filename.split('.')[0]
+            config = paddle.inference.Config(
+                os.path.join(args.model_path, model_prefix))
         config.switch_ir_debug(True)
         # 适用于ERNIE 3.0-Medium模型
         # config.exp_disable_tensorrt_ops(["elementwise_add"])
@@ -246,8 +250,8 @@ def create_predictor(cls, args):
             dynamic_shape_file = os.path.join(args.model_path,
                                               "dynamic_shape.txt")
             if os.path.exists(dynamic_shape_file):
-                config.enable_tuned_tensorrt_dynamic_shape(
-                    dynamic_shape_file, True)
+                config.enable_tuned_tensorrt_dynamic_shape(dynamic_shape_file,
+                                                           True)
                 print("trt set dynamic shape done!")
             else:
                 config.collect_shape_range_info(dynamic_shape_file)
@@ -372,4 +376,4 @@ def main():
 
 if __name__ == "__main__":
     paddle.set_device("cpu")
-    main()
+    main()

example/auto_compression/nlp/paddle_inference_eval_uie.py

@@ -163,9 +163,14 @@ def create_predictor(cls, args):
         create_predictor func
         """
         cls.rerun_flag = False
-        config = paddle.inference.Config(
-            os.path.join(args.model_path, args.model_filename),
-            os.path.join(args.model_path, args.params_filename))
+        if '2' in paddle.__version__.split('.')[0]:
+            config = paddle.inference.Config(
+                os.path.join(args.model_path, args.model_filename),
+                os.path.join(args.model_path, args.params_filename))
+        else:
+            model_prefix = args.model_filename.split('.')[0]
+            config = paddle.inference.Config(
+                os.path.join(args.model_path, model_prefix))
         if args.device == "gpu":
             # set GPU configs accordingly
             config.enable_use_gpu(100, 0)

example/auto_compression/pytorch_huggingface/paddle_inference_eval.py

@@ -103,8 +103,7 @@ def parse_args():
         "--max_seq_length",
         default=128,
         type=int,
-        help=
-        "The maximum total input sequence length after tokenization. Sequences longer "
+        help="The maximum total input sequence length after tokenization. Sequences longer "
         "than this will be truncated, sequences shorter will be padded.", )
     parser.add_argument(
         "--perf_warmup_steps",
@@ -120,8 +119,7 @@ def parse_args():
         type=str,
         default="fp32",
         choices=["fp32", "fp16", "int8"],
-        help=
-        "The precision of inference. It can be 'fp32', 'fp16' or 'int8'. Default is 'fp16'.",
+        help="The precision of inference. It can be 'fp32', 'fp16' or 'int8'. Default is 'fp16'.",
     )
     parser.add_argument(
         "--use_mkldnn",
@@ -188,9 +186,15 @@ def create_predictor(cls, args):
         create_predictor func
         """
         cls.rerun_flag = False
-        config = paddle.inference.Config(
-            os.path.join(args.model_path, args.model_filename),
-            os.path.join(args.model_path, args.params_filename))
+
+        if '2' in paddle.__version__.split('.')[0]:
+            config = paddle.inference.Config(
+                os.path.join(args.model_path, args.model_filename),
+                os.path.join(args.model_path, args.params_filename))
+        else:
+            model_prefix = args.model_filename.split('.')[0]
+            config = paddle.inference.Config(
+                os.path.join(args.model_path, model_prefix))
 
         if args.device == "gpu":
             # set GPU configs accordingly
@@ -223,8 +227,8 @@ def create_predictor(cls, args):
             dynamic_shape_file = os.path.join(args.model_path,
                                               "dynamic_shape.txt")
             if os.path.exists(dynamic_shape_file):
-                config.enable_tuned_tensorrt_dynamic_shape(
-                    dynamic_shape_file, True)
+                config.enable_tuned_tensorrt_dynamic_shape(dynamic_shape_file,
+                                                           True)
                 print("trt set dynamic shape done!")
             else:
                 config.collect_shape_range_info(dynamic_shape_file)

example/auto_compression/pytorch_yolo_series/paddle_inference_eval.py

@@ -253,9 +253,13 @@ def load_predictor(
         raise ValueError(
             "Predict by TensorRT mode: {}, expect device=='GPU', but device == {}".
             format(precision, device))
-    config = Config(
-        os.path.join(model_dir, "model.pdmodel"),
-        os.path.join(model_dir, "model.pdiparams"))
+    if '2' in paddle.__version__.split('.')[0]:
+        config = Config(
+            os.path.join(model_dir, "model.pdmodel"),
+            os.path.join(model_dir, "model.pdiparams"))
+    else:
+        config = Config(os.path.join(model_dir, "model"))
+
     if device == "GPU":
         # initial GPU memory(M), device ID
         config.enable_use_gpu(200, 0)

example/auto_compression/pytorch_yolo_series/paddle_trt_infer.py

@@ -244,9 +244,12 @@ def load_predictor(model_dir,
         raise ValueError(
             "Predict by TensorRT mode: {}, expect device=='GPU', but device == {}"
             .format(run_mode, device))
-    config = Config(
-        os.path.join(model_dir, 'model.pdmodel'),
-        os.path.join(model_dir, 'model.pdiparams'))
+    if '2' in paddle.__version__.split('.')[0]:
+        config = Config(
+            os.path.join(model_dir, "model.pdmodel"),
+            os.path.join(model_dir, "model.pdiparams"))
+    else:
+        config = Config(os.path.join(model_dir, "model"))
     if device == 'GPU':
         # initial GPU memory(M), device ID
         config.enable_use_gpu(200, 0)

example/auto_compression/semantic_segmentation/configs/deeplabv3/deeplabv3_qat.yaml

@@ -1,8 +1,8 @@
 Global:
   reader_config: configs/dataset/cityscapes_1024x512_scale1.0.yml
   model_dir: ./RES-paddle2-Deeplabv3-ResNet50
-  model_filename: model
-  params_filename: params
+  model_filename: model.pdmodel
+  params_filename: model.pdiparams
   batch_size: 4
 
 Distillation:

example/auto_compression/semantic_segmentation/configs/hrnet/hrnet_qat.yaml

@@ -1,9 +1,8 @@
 Global:
   reader_config: configs/dataset/cityscapes_1024x512_scale1.0.yml
   model_dir: ./RES-paddle2-HRNetW18-Seg
-  model_filename: model
-  params_filename: params
-
+  model_filename: model.pdmodel
+  params_filename: model.pdiparams
 Distillation:
   alpha: 1.0
   loss: l2

example/auto_compression/semantic_segmentation/configs/hrnet/hrnet_sparse.yaml

@@ -1,8 +1,8 @@
 Global:
   reader_config: configs/dataset/cityscapes_1024x512_scale1.0.yml
   model_dir: ./RES-paddle2-HRNetW18-Seg
-  model_filename: model
-  params_filename: params
+  model_filename: model.pdmodel
+  params_filename: model.pdiparams
 
 Distillation:
   alpha: 1.0

example/auto_compression/semantic_segmentation/configs/pp_liteseg/pp_liteseg_auto.yaml

@@ -1,8 +1,8 @@
 Global:
   reader_config: configs/dataset/cityscapes_1024x512_scale1.0.yml
   model_dir: ./RES-paddle2-PPLIteSegSTDC1
-  model_filename: model
-  params_filename: params
+  model_filename: model.pdmodel
+  params_filename: model.pdiparams
 
 TrainConfig:
  epochs: 14

example/auto_compression/semantic_segmentation/configs/pp_liteseg/pp_liteseg_qat.yaml

@@ -1,8 +1,8 @@
 Global:
   reader_config: configs/dataset/cityscapes_1024x512_scale1.0.yml
   model_dir: ./RES-paddle2-PPLIteSegSTDC1
-  model_filename: model
-  params_filename: params
+  model_filename: model.pdmodel
+  params_filename: model.pdiparams
 
 Distillation:
   alpha: 1.0

example/auto_compression/semantic_segmentation/configs/pp_liteseg/pp_liteseg_sparse.yaml

@@ -1,8 +1,8 @@
 Global:
   reader_config: configs/dataset/cityscapes_1024x512_scale1.0.yml
   model_dir: ./RES-paddle2-PPLIteSegSTDC1
-  model_filename: model
-  params_filename: params
+  model_filename: model.pdmodel
+  params_filename: model.pdiparams
 
 Distillation:
   alpha: 1.0