add comment

ppcls/utils/__init__.py

@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from . import environment
 from . import model_zoo
 from . import misc
 from . import logger

ppcls/utils/environment.py

-# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
-#
-#Licensed under the Apache License, Version 2.0 (the "License");
-#you may not use this file except in compliance with the License.
-#You may obtain a copy of the License at
-#
-#    http://www.apache.org/licenses/LICENSE-2.0
-#
-#Unless required by applicable law or agreed to in writing, software
-#distributed under the License is distributed on an "AS IS" BASIS,
-#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#See the License for the specific language governing permissions and
-#limitations under the License.
-
-import os
-import paddle
-import paddle.fluid as fluid
-import paddle.fluid.framework as pff
-
-trainers_num = int(os.environ.get('PADDLE_TRAINERS_NUM', 1))
-trainer_id = int(os.environ.get("PADDLE_TRAINER_ID", 0))
-
-
-def place():
-    gpu_id = int(os.environ.get('FLAGS_selected_gpus', 0))
-    return fluid.CUDAPlace(gpu_id)
-
-
-def places():
-    """
-    Returns available running places, the numbers are usually
-    indicated by 'export CUDA_VISIBLE_DEVICES= '
-    Args:
-    """
-
-    if trainers_num <= 1:
-        return pff.cuda_places()
-    else:
-        return place()

tools/eval.py

@@ -25,7 +25,6 @@ import paddle.fluid as fluid
 import program
 
 from ppcls.data import Reader
-import ppcls.utils.environment as env
 from ppcls.utils.config import get_config
 from ppcls.utils.save_load import init_model, save_model
 from ppcls.utils import logger
@@ -58,7 +57,8 @@ def main(args):
     fleet.init(role)
 
     config = get_config(args.config, overrides=args.override, show=True)
-    place = env.place()
+    gpu_id = int(os.environ.get('FLAGS_selected_gpus', 0))
+    place = fluid.CUDAPlace(gpu_id)
 
     startup_prog = fluid.Program()
     valid_prog = fluid.Program()
@@ -69,7 +69,7 @@ def main(args):
     exe = fluid.Executor(place)
     exe.run(startup_prog)
 
-    init_model(config, valid_prog, exe)
+    init_model(config, valid_prog, exe, 'ppcls')
 
     valid_reader = Reader(config, 'valid')()
     valid_dataloader.set_sample_list_generator(valid_reader, place)

tools/train.py

@@ -19,8 +19,6 @@ from __future__ import print_function
 
 import argparse
 import os
-import sys
-sys.path.append(os.getcwd())
 
 import paddle
 import paddle.fluid as fluid
@@ -28,7 +26,6 @@ import paddle.fluid as fluid
 import program
 
 from ppcls.data import Reader
-import ppcls.utils.environment as env
 from ppcls.utils.config import get_config
 from ppcls.utils.save_load import init_model, save_model
 from ppcls.utils import logger
@@ -60,8 +57,12 @@ def main(args):
     fleet.init(role)
 
     config = get_config(args.config, overrides=args.override, show=True)
-    place = env.place()
+    # assign the place
+    gpu_id = int(os.environ.get('FLAGS_selected_gpus', 0))
+    place = fluid.CUDAPlace(gpu_id)
 
+    # startup_prog is used to do some parameter init work,
+    # and train prog is used to hold the network
     startup_prog = fluid.Program()
     train_prog = fluid.Program()
 
@@ -72,11 +73,15 @@ def main(args):
         valid_prog = fluid.Program()
         valid_dataloader, valid_fetchs = program.build(
             config, valid_prog, startup_prog, is_train=False)
+        # clone to prune some content which is irrelevant in valid_prog
         valid_prog = valid_prog.clone(for_test=True)
 
-    exe = fluid.Executor(place)
+    # create the "Executor" with the statement of which place 
+    exe = fluid.Executor(place=place)
+    # only run startup_prog once to init
     exe.run(startup_prog)
 
+    # load model from checkpoint or pretrained model
     init_model(config, train_prog, exe)
 
     train_reader = Reader(config, 'train')()
@@ -89,13 +94,15 @@ def main(args):
 
     compiled_train_prog = fleet.main_program
     for epoch_id in range(config.epochs):
+        # 1. train with train dataset
         program.run(train_dataloader, exe, compiled_train_prog, train_fetchs,
                     epoch_id, 'train')
-
+        # 2. validate with validate dataset 
         if config.validate and epoch_id % config.valid_interval == 0:
             program.run(valid_dataloader, exe, compiled_valid_prog,
                         valid_fetchs, epoch_id, 'valid')
 
+        # 3. save the persistable model 
         if epoch_id % config.save_interval == 0:
             model_path = os.path.join(config.model_save_dir,
                                       config.ARCHITECTURE["name"])