remove redundant seed fixing code and logger init code, and remove this behaviour to yaml

Author: HydrogenSulfate

examples/RegAE/RegAE.py

@@ -14,23 +14,15 @@
 
 from __future__ import annotations
 
-from os import path as osp
-
 import hydra
 import paddle
 from omegaconf import DictConfig
 from paddle.nn import functional as F
 
 import ppsci
-from ppsci.utils import logger
 
 
 def train(cfg: DictConfig):
-    # set random seed for reproducibility
-    ppsci.utils.misc.set_random_seed(cfg.seed)
-    # initialize logger
-    logger.init_logger("ppsci", osp.join(cfg.output_dir, "train.log"), "info")
-
     # set model
     model = ppsci.arch.AutoEncoder(**cfg.MODEL)
 
@@ -114,11 +106,6 @@ def loss_expr(output_dict, label_dict, weight_dict=None):
 
 
 def evaluate(cfg: DictConfig):
-    # set random seed for reproducibility
-    ppsci.utils.misc.set_random_seed(cfg.seed)
-    # initialize logger
-    logger.init_logger("ppsci", osp.join(cfg.output_dir, "eval.log"), "info")
-
     # set model
     model = ppsci.arch.AutoEncoder(**cfg.MODEL)
 

examples/RegAE/conf/RegAE.yaml

@@ -14,6 +14,9 @@ hydra:
           - mode
           - output_dir
           - log_freq
+  callbacks:
+    init_callback:
+      _target_: ppsci.utils.callbacks.InitCallback
   sweep:
     # output directory for multirun
     dir: ${hydra.run.dir}

examples/amgnet/amgnet_airfoil.py

@@ -14,7 +14,6 @@
 
 from __future__ import annotations
 
-from os import path as osp
 from typing import TYPE_CHECKING
 from typing import Dict
 from typing import List
@@ -53,11 +52,6 @@ def eval_rmse_func(
 
 
 def train(cfg: DictConfig):
-    # set random seed for reproducibility
-    ppsci.utils.misc.set_random_seed(cfg.seed)
-    # initialize logger
-    logger.init_logger("ppsci", osp.join(cfg.output_dir, "train.log"), "info")
-
     # set airfoil model
     model = ppsci.arch.AMGNet(**cfg.MODEL)
 
@@ -76,7 +70,6 @@ def train(cfg: DictConfig):
             "drop_last": False,
             "shuffle": True,
         },
-        "num_workers": 1,
     }
 
     # set constraint
@@ -102,11 +95,6 @@ def train(cfg: DictConfig):
             "mesh_graph_path": cfg.EVAL_MESH_GRAPH_PATH,
         },
         "batch_size": cfg.EVAL.batch_size,
-        "sampler": {
-            "name": "BatchSampler",
-            "drop_last": False,
-            "shuffle": False,
-        },
     }
     rmse_validator = ppsci.validate.SupervisedValidator(
         eval_dataloader_cfg,
@@ -152,11 +140,6 @@ def train(cfg: DictConfig):
 
 
 def evaluate(cfg: DictConfig):
-    # set random seed for reproducibility
-    ppsci.utils.misc.set_random_seed(cfg.seed)
-    # initialize logger
-    logger.init_logger("ppsci", osp.join(cfg.output_dir, "eval.log"), "info")
-
     # set airfoil model
     model = ppsci.arch.AMGNet(**cfg.MODEL)
 
@@ -170,11 +153,6 @@ def evaluate(cfg: DictConfig):
             "mesh_graph_path": cfg.EVAL_MESH_GRAPH_PATH,
         },
         "batch_size": cfg.EVAL.batch_size,
-        "sampler": {
-            "name": "BatchSampler",
-            "drop_last": False,
-            "shuffle": False,
-        },
     }
     rmse_validator = ppsci.validate.SupervisedValidator(
         eval_dataloader_cfg,

examples/amgnet/amgnet_cylinder.py

@@ -14,7 +14,6 @@
 
 from __future__ import annotations
 
-from os import path as osp
 from typing import TYPE_CHECKING
 from typing import Dict
 from typing import List
@@ -53,11 +52,6 @@ def eval_rmse_func(
 
 
 def train(cfg: DictConfig):
-    # set random seed for reproducibility
-    ppsci.utils.misc.set_random_seed(cfg.seed)
-    # initialize logger
-    logger.init_logger("ppsci", osp.join(cfg.output_dir, "train.log"), "info")
-
     # set cylinder model
     model = ppsci.arch.AMGNet(**cfg.MODEL)
 
@@ -76,7 +70,6 @@ def train(cfg: DictConfig):
             "drop_last": False,
             "shuffle": True,
         },
-        "num_workers": 1,
     }
 
     # set constraint
@@ -102,11 +95,6 @@ def train(cfg: DictConfig):
             "mesh_graph_path": cfg.EVAL_MESH_GRAPH_PATH,
         },
         "batch_size": cfg.EVAL.batch_size,
-        "sampler": {
-            "name": "BatchSampler",
-            "drop_last": False,
-            "shuffle": False,
-        },
     }
     rmse_validator = ppsci.validate.SupervisedValidator(
         eval_dataloader_cfg,
@@ -152,11 +140,6 @@ def train(cfg: DictConfig):
 
 
 def evaluate(cfg: DictConfig):
-    # set random seed for reproducibility
-    ppsci.utils.misc.set_random_seed(cfg.seed)
-    # initialize logger
-    logger.init_logger("ppsci", osp.join(cfg.output_dir, "eval.log"), "info")
-
     # set airfoil model
     model = ppsci.arch.AMGNet(**cfg.MODEL)
 
@@ -170,11 +153,6 @@ def evaluate(cfg: DictConfig):
             "mesh_graph_path": cfg.EVAL_MESH_GRAPH_PATH,
         },
         "batch_size": cfg.EVAL.batch_size,
-        "sampler": {
-            "name": "BatchSampler",
-            "drop_last": False,
-            "shuffle": False,
-        },
     }
     rmse_validator = ppsci.validate.SupervisedValidator(
         eval_dataloader_cfg,

examples/amgnet/conf/amgnet_airfoil.yaml

@@ -14,6 +14,9 @@ hydra:
           - mode
           - output_dir
           - log_freq
+  callbacks:
+    init_callback:
+      _target_: ppsci.utils.callbacks.InitCallback
   sweep:
     # output directory for multirun
     dir: ${hydra.run.dir}

examples/amgnet/conf/amgnet_cylinder.yaml

@@ -14,6 +14,9 @@ hydra:
           - mode
           - output_dir
           - log_freq
+  callbacks:
+    init_callback:
+      _target_: ppsci.utils.callbacks.InitCallback
   sweep:
     # output directory for multirun
     dir: ${hydra.run.dir}

examples/biharmonic2d/biharmonic2d.py

@@ -69,11 +69,6 @@ def plotting(figname, output_dir, data, griddata_points, griddata_xi, boundary):
 
 
 def train(cfg: DictConfig):
-    # set random seed for reproducibility
-    ppsci.utils.misc.set_random_seed(cfg.seed)
-    # initialize logger
-    logger.init_logger("ppsci", osp.join(cfg.output_dir, f"{cfg.mode}.log"), "info")
-
     # set models
     disp_net = ppsci.arch.MLP(**cfg.MODEL)
 
@@ -268,11 +263,6 @@ def train(cfg: DictConfig):
 
 
 def evaluate(cfg: DictConfig):
-    # set random seed for reproducibility
-    ppsci.utils.misc.set_random_seed(cfg.seed)
-    # initialize logger
-    logger.init_logger("ppsci", osp.join(cfg.output_dir, f"{cfg.mode}.log"), "info")
-
     # set models
     disp_net = ppsci.arch.MLP(**cfg.MODEL)
 

examples/biharmonic2d/conf/biharmonic2d.yaml

@@ -14,6 +14,9 @@ hydra:
           - mode
           - output_dir
           - log_freq
+  callbacks:
+    init_callback:
+      _target_: ppsci.utils.callbacks.InitCallback
   sweep:
     # output directory for multirun
     dir: ${hydra.run.dir}

examples/bracket/bracket.py

@@ -277,11 +277,6 @@ def train(cfg: DictConfig):
             "input": input_dict,
             "label": label_dict,
         },
-        "sampler": {
-            "name": "BatchSampler",
-            "drop_last": False,
-            "shuffle": False,
-        },
     }
     sup_validator = ppsci.validate.SupervisedValidator(
         {**eval_dataloader_cfg, "batch_size": cfg.EVAL.batch_size.sup_validator},

examples/bubble/bubble.py

@@ -32,11 +32,6 @@
 
 
 def train(cfg: DictConfig):
-    # set random seed for reproducibility
-    ppsci.utils.misc.set_random_seed(cfg.seed)
-    # initialize logger
-    logger.init_logger("ppsci", osp.join(cfg.output_dir, f"{cfg.mode}.log"), "info")
-
     # load Data
     data = scipy.io.loadmat(cfg.DATA_PATH)
     # normalize data
@@ -171,11 +166,6 @@ def transform_out(in_, out):
                 "label": test_label,
             },
             "batch_size": cfg.TRAIN.batch_size.mse_validator,
-            "sampler": {
-                "name": "BatchSampler",
-                "drop_last": False,
-                "shuffle": False,
-            },
         },
         ppsci.loss.MSELoss("mean"),
         metric={"MSE": ppsci.metric.MSE()},
@@ -249,11 +239,6 @@ def transform_out(in_, out):
 
 
 def evaluate(cfg: DictConfig):
-    # set random seed for reproducibility
-    ppsci.utils.misc.set_random_seed(cfg.seed)
-    # initialize logger
-    logger.init_logger("ppsci", osp.join(cfg.output_dir, f"{cfg.mode}.log"), "info")
-
     # load Data
     data = scipy.io.loadmat(cfg.DATA_PATH)
     # normalize data
@@ -343,11 +328,6 @@ def transform_out(in_, out):
                 "label": test_label,
             },
             "batch_size": cfg.TRAIN.batch_size.mse_validator,
-            "sampler": {
-                "name": "BatchSampler",
-                "drop_last": False,
-                "shuffle": False,
-            },
         },
         ppsci.loss.MSELoss("mean"),
         metric={"MSE": ppsci.metric.MSE()},