feat(exp): get_trainer method, add pre-commit (#1263)

.pre-commit-config.yaml

+repos:
+  - repo: https://github.com/pycqa/flake8
+    rev: 3.8.3
+    hooks:
+      - id: flake8
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v3.1.0
+    hooks:
+      - id: check-added-large-files
+      - id: check-docstring-first
+      - id: check-executables-have-shebangs
+      - id: check-json
+      - id: check-yaml
+        args: ["--unsafe"]
+      - id: debug-statements
+      - id: end-of-file-fixer
+      - id: requirements-txt-fixer
+      - id: trailing-whitespace
+  - repo: https://github.com/jorisroovers/gitlint
+    rev: v0.15.1
+    hooks:
+      - id: gitlint
+  - repo: https://github.com/pycqa/isort
+    rev: 4.3.21
+    hooks:
+      - id: isort
+
+  - repo: https://github.com/PyCQA/autoflake
+    rev: v1.4
+    hooks:
+      - id: autoflake
+        name: Remove unused variables and imports
+        entry: autoflake
+        language: python
+        args:
+          [
+            "--in-place",
+            "--remove-all-unused-imports",
+            "--remove-unused-variables",
+            "--expand-star-imports",
+            "--ignore-init-module-imports",
+          ]
+        files: \.py$

tools/train.py

@@ -10,8 +10,8 @@ from loguru import logger
 import torch
 import torch.backends.cudnn as cudnn
 
-from yolox.core import Trainer, launch
-from yolox.exp import get_exp
+from yolox.core import launch
+from yolox.exp import Exp, get_exp
 from yolox.utils import configure_module, configure_nccl, configure_omp, get_num_devices
 
 
@@ -97,7 +97,7 @@ def make_parser():
 
 
 @logger.catch
-def main(exp, args):
+def main(exp: Exp, args):
     if exp.seed is not None:
         random.seed(exp.seed)
         torch.manual_seed(exp.seed)
@@ -113,7 +113,7 @@ def main(exp, args):
     configure_omp()
     cudnn.benchmark = True
 
-    trainer = Trainer(exp, args)
+    trainer = exp.get_trainer(args)
     trainer.train()
 
 

yolox/core/trainer.py

@@ -12,6 +12,7 @@ from torch.nn.parallel import DistributedDataParallel as DDP
 from torch.utils.tensorboard import SummaryWriter
 
 from yolox.data import DataPrefetcher
+from yolox.exp import Exp
 from yolox.utils import (
     MeterBuffer,
     ModelEMA,
@@ -33,7 +34,7 @@ from yolox.utils import (
 
 
 class Trainer:
-    def __init__(self, exp, args):
+    def __init__(self, exp: Exp, args):
         # init function only defines some basic attr, other attrs like model, optimizer are built in
         # before_train methods.
         self.exp = exp

yolox/exp/yolox_base.py

@@ -127,9 +127,7 @@ class Exp(BaseExp):
         self.model.train()
         return self.model
 
-    def get_data_loader(
-        self, batch_size, is_distributed, no_aug=False, cache_img=False
-    ):
+    def get_data_loader(self, batch_size, is_distributed, no_aug=False, cache_img=False):
         from yolox.data import (
             COCODataset,
             TrainTransform,
@@ -314,5 +312,11 @@ class Exp(BaseExp):
         )
         return evaluator
 
+    def get_trainer(self, args):
+        from yolox.core import Trainer
+        trainer = Trainer(self, args)
+        # NOTE: trainer shouldn't be an attribute of exp object
+        return trainer
+
     def eval(self, model, evaluator, is_distributed, half=False):
         return evaluator.evaluate(model, is_distributed, half)