Add copyright and fix profile.py (#1292)

fluid/faster_rcnn/eval_coco_map.py

+#  Copyright (c) 2018 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.
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
 import os
 import time
 import numpy as np
-import argparse
-import functools
 from eval_helper import get_nmsed_box
 from eval_helper import get_dt_res
 import paddle
 import paddle.fluid as fluid
 import reader
 from utility import print_arguments, parse_args
-# A special mAP metric for COCO dataset, which averages AP in different IoUs.
-# To use this eval_coco_map.py, [cocoapi](https://github.com/cocodataset/cocoapi) is needed.
 import models.model_builder as model_builder
 import models.resnet as resnet
 import json

fluid/faster_rcnn/eval_helper.py

+#  Copyright (c) 2018 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 numpy as np
 import paddle.fluid as fluid

fluid/faster_rcnn/learning_rate.py

+#  Copyright (c) 2018 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.
+
 from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function

fluid/faster_rcnn/models/model_builder.py

+#  Copyright (c) 2018 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 paddle.fluid as fluid
 from paddle.fluid.param_attr import ParamAttr
 from paddle.fluid.initializer import Constant

fluid/faster_rcnn/models/resnet.py

+#  Copyright (c) 2018 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 paddle.fluid as fluid
 from paddle.fluid.param_attr import ParamAttr
 from paddle.fluid.initializer import Constant

fluid/faster_rcnn/profile.py

+#  Copyright (c) 2018 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 time
 import numpy as np
 import argparse
-import functools
-import shutil
-import cPickle
-from utility import add_arguments, print_arguments
+from utility import parse_args, add_arguments, print_arguments
 
 import paddle
 import paddle.fluid as fluid
@@ -16,50 +27,12 @@ import models.model_builder as model_builder
 import models.resnet as resnet
 from learning_rate import exponential_with_warmup_decay
 
-parser = argparse.ArgumentParser(description=__doc__)
-add_arg = functools.partial(add_arguments, argparser=parser)
-# yapf: disable
-# ENV
-add_arg('parallel',         bool,   True,       "Minibatch size.")
-add_arg('use_gpu',          bool,   True,      "Whether use GPU.")
-add_arg('model_save_dir',   str,    'model',     "The path to save model.")
-add_arg('pretrained_model', str,    'imagenet_resnet50_fusebn', "The init model path.")
-add_arg('dataset',          str,    'coco2017', "coco2014, coco2017, and pascalvoc.")
-add_arg('data_dir',         str,    'data/COCO17', "data directory")
-add_arg('skip_reader',      bool,  False,            "Whether to skip data reader.")
-add_arg('use_profile',      bool,  False,            "Whether to use profiler tool.")
-add_arg('class_num',        int,   81,          "Class number.")
-add_arg('use_pyreader',     bool,  False,          "Class number.")
-# SOLVER
-add_arg('learning_rate',    float,  0.01,     "Learning rate.")
-add_arg('num_iteration',    int,   10,              "Epoch number.")
-# RPN
-add_arg('anchor_sizes',     int,    [32,64,128,256,512],  "The size of anchors.")
-add_arg('aspect_ratios',    float,  [0.5,1.0,2.0],    "The ratio of anchors.")
-add_arg('variance',         float,  [1.,1.,1.,1.],    "The variance of anchors.")
-add_arg('rpn_stride',       float,  16.,    "Stride of the feature map that RPN is attached.")
-# FAST RCNN
-# TRAIN TEST
-add_arg('batch_size',       int,    1,          "Minibatch size.")
-add_arg('max_size',         int,    1333,    "The max resized image size.")
-add_arg('scales',           int,    [800],    "The resized image height.")
-add_arg('batch_size_per_im',int,    512,    "fast rcnn head batch size")
-add_arg('mean_value',       float,  [102.9801, 115.9465, 122.7717], "pixel mean")
-add_arg('debug',            bool,   False,   "Debug mode")
-#yapf: enable
 
 def train(cfg):
     batch_size = cfg.batch_size
     learning_rate = cfg.learning_rate
     image_shape = [3, cfg.max_size, cfg.max_size]
-    num_iterations = cfg.num_iteration
-
-    if cfg.debug:
-        fluid.default_startup_program().random_seed = 1000
-        fluid.default_main_program().random_seed = 1000
-        import random
-        random.seed(0)
-        np.random.seed(0)
+    num_iterations = cfg.max_iter
 
     devices = os.getenv("CUDA_VISIBLE_DEVICES") or ""
     devices_num = len(devices.split(","))
@@ -72,21 +45,22 @@ def train(cfg):
         use_random=False)
     model.build_model(image_shape)
     loss_cls, loss_bbox, rpn_cls_loss, rpn_reg_loss = model.loss()
-    loss_cls.persistable=True
-    loss_bbox.persistable=True
-    rpn_cls_loss.persistable=True
-    rpn_reg_loss.persistable=True
+    loss_cls.persistable = True
+    loss_bbox.persistable = True
+    rpn_cls_loss.persistable = True
+    rpn_reg_loss.persistable = True
     loss = loss_cls + loss_bbox + rpn_cls_loss + rpn_reg_loss
 
     boundaries = [120000, 160000]
-    values = [learning_rate, learning_rate*0.1, learning_rate*0.01]
+    values = [learning_rate, learning_rate * 0.1, learning_rate * 0.01]
 
     optimizer = fluid.optimizer.Momentum(
-        learning_rate=exponential_with_warmup_decay(learning_rate=learning_rate,
+        learning_rate=exponential_with_warmup_decay(
+            learning_rate=learning_rate,
             boundaries=boundaries,
             values=values,
             warmup_iter=500,
-            warmup_factor=1.0/3.0),
+            warmup_factor=1.0 / 3.0),
         regularization=fluid.regularizer.L2Decay(0.0001),
         momentum=0.9)
     optimizer.minimize(loss)
@@ -98,21 +72,32 @@ def train(cfg):
     exe.run(fluid.default_startup_program())
 
     if cfg.pretrained_model:
+
         def if_exist(var):
             return os.path.exists(os.path.join(cfg.pretrained_model, var.name))
+
         fluid.io.load_vars(exe, cfg.pretrained_model, predicate=if_exist)
 
     if cfg.parallel:
         train_exe = fluid.ParallelExecutor(
             use_cuda=bool(cfg.use_gpu), loss_name=loss.name)
 
+    assert cfg.batch_size % devices_num == 0, \
+        "batch_size = %d, devices_num = %d" %(cfg.batch_size, devices_num)
 
+    batch_size_per_dev = cfg.batch_size / devices_num
     if cfg.use_pyreader:
-        train_reader = reader.train(cfg, batch_size=1, shuffle=not cfg.debug)
+        train_reader = reader.train(
+            cfg,
+            batch_size=batch_size_per_dev,
+            total_batch_size=cfg.batch_size,
+            padding_total=cfg.padding_minibatch,
+            shuffle=False)
         py_reader = model.py_reader
         py_reader.decorate_paddle_reader(train_reader)
     else:
-        train_reader = reader.train(cfg, batch_size=cfg.batch_size, shuffle=not cfg.debug)
+        train_reader = reader.train(
+            cfg, batch_size=cfg.batch_size, shuffle=False)
         feeder = fluid.DataFeeder(place=place, feed_list=model.feeds())
 
     fetch_list = [loss, loss_cls, loss_bbox, rpn_cls_loss, rpn_reg_loss]
@@ -128,18 +113,23 @@ def train(cfg):
             end_time = time.time()
             reader_time.append(end_time - start_time)
             start_time = time.time()
+            if cfg.parallel:
                 losses = train_exe.run(fetch_list=[v.name for v in fetch_list],
                                        feed=feeder.feed(data))
+            else:
+                losses = exe.run(fluid.default_main_program(),
+                                 fetch_list=[v.name for v in fetch_list],
+                                 feed=feeder.feed(data))
             end_time = time.time()
             run_time.append(end_time - start_time)
-            total_images += data[0][0].shape[0]
+            total_images += len(data)
 
-            lr = np.array(fluid.global_scope().find_var('learning_rate').get_tensor())
-            print("Batch {:d}, lr {:.6f}, loss {:.6f} ".format(
-                  batch_id, lr[0], losses[0][0]))
+            lr = np.array(fluid.global_scope().find_var('learning_rate')
+                          .get_tensor())
+            print("Batch {:d}, lr {:.6f}, loss {:.6f} ".format(batch_id, lr[0],
+                                                               losses[0][0]))
         return reader_time, run_time, total_images
 
-
     def run_pyreader(iterations):
         reader_time = [0]
         run_time = []
@@ -149,13 +139,19 @@ def train(cfg):
         try:
             for batch_id in range(iterations):
                 start_time = time.time()
-                losses = train_exe.run(fetch_list=[v.name for v in fetch_list])
+                if cfg.parallel:
+                    losses = train_exe.run(
+                        fetch_list=[v.name for v in fetch_list])
+                else:
+                    losses = exe.run(fluid.default_main_program(),
+                                     fetch_list=[v.name for v in fetch_list])
                 end_time = time.time()
                 run_time.append(end_time - start_time)
                 total_images += devices_num
-                lr = np.array(fluid.global_scope().find_var('learning_rate').get_tensor())
-                print("Batch {:d}, lr {:.6f}, loss {:.6f} ".format(
-                      batch_id, lr[0], losses[0][0]))
+                lr = np.array(fluid.global_scope().find_var('learning_rate')
+                              .get_tensor())
+                print("Batch {:d}, lr {:.6f}, loss {:.6f} ".format(batch_id, lr[
+                    0], losses[0][0]))
         except fluid.core.EOFException:
             py_reader.reset()
 
@@ -167,20 +163,23 @@ def train(cfg):
     run_func(2)
     # profiling
     start = time.time()
-    if cfg.use_profile:
+    use_profile = False
+    if use_profile:
         with profiler.profiler('GPU', 'total', '/tmp/profile_file'):
-            reader_time, run_time, total_images = run(num_iterations)
+            reader_time, run_time, total_images = run_func(num_iterations)
     else:
         reader_time, run_time, total_images = run_func(num_iterations)
 
     end = time.time()
     total_time = end - start
-    print("Total time: {0}, reader time: {1} s, run time: {2} s, images/s: {3}".format(
-        total_time, np.sum(reader_time), np.sum(run_time), total_images / total_time))
+    print("Total time: {0}, reader time: {1} s, run time: {2} s, images/s: {3}".
+          format(total_time,
+                 np.sum(reader_time),
+                 np.sum(run_time), total_images / total_time))
 
 
 if __name__ == '__main__':
-    args = parser.parse_args()
+    args = parse_args()
     print_arguments(args)
 
     data_args = reader.Settings(args)

fluid/faster_rcnn/train.py

+#  Copyright (c) 2018 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.
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
 import os
-import time
+import sys
 import numpy as np
-import argparse
-import functools
+import time
 import shutil
-import cPickle
 from utility import parse_args, print_arguments, SmoothedValue
 
 import paddle
@@ -117,7 +132,7 @@ def train(cfg):
                     iter_id, lr[0],
                     smoothed_loss.get_median_value(
                     ), start_time - prev_start_time))
-                #print('cls_loss ', losses[1][0], ' reg_loss ', losses[2][0], ' loss_cls ', losses[3][0], ' loss_bbox ', losses[4][0])
+                sys.stdout.flush()
                 if (iter_id + 1) % cfg.snapshot_stride == 0:
                     save_model("model_iter{}".format(iter_id))
         except fluid.core.EOFException:
@@ -143,7 +158,7 @@ def train(cfg):
             print("Iter {:d}, lr {:.6f}, loss {:.6f}, time {:.5f}".format(
                 iter_id, lr[0],
                 smoothed_loss.get_median_value(), start_time - prev_start_time))
-            #print('cls_loss ', losses[1][0], ' reg_loss ', losses[2][0], ' loss_cls ', losses[3][0], ' loss_bbox ', losses[4][0])
+            sys.stdout.flush()
             if (iter_id + 1) % cfg.snapshot_stride == 0:
                 save_model("model_iter{}".format(iter_id))
             if (iter_id + 1) == cfg.max_iter:

fluid/faster_rcnn/utility.py

-"""Contains common utility functions."""
 #  Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
 #
 #Licensed under the Apache License, Version 2.0 (the "License");
@@ -12,6 +11,9 @@
 #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.
+"""
+Contains common utility functions.
+"""
 
 from __future__ import absolute_import
 from __future__ import division
@@ -83,8 +85,7 @@ class SmoothedValue(object):
 
 
 def parse_args():
-    """
-	return all args
+    """return all args
     """
     parser = argparse.ArgumentParser(description=__doc__)
     add_arg = functools.partial(add_arguments, argparser=parser)