add prune dygraph, test=dygraph (#2123)

* add prune dygraph, test=dygraph

* fix slim readme and prune

dygraph/configs/slim/README.md

+# 模型压缩
+
+在PaddleDetection中, 提供了基于[PaddleSlim](https://github.com/PaddlePaddle/PaddleSlim)进行模型压缩的完整教程和benchmark。目前支持的方法：
+
+- [剪裁](prune)
+
+推荐您使用剪裁和蒸馏联合训练，或者使用剪裁和量化，进行检测模型压缩。 下面以YOLOv3为例，进行剪裁、蒸馏和量化实验。
+
+## Benchmark
+
+### 剪裁
+
+#### Pascal VOC上benchmark
+
+| 模型         |  压缩策略 |     GFLOPs     |  模型体积(MB)   | 输入尺寸 | 预测时延（SD855）|   Box AP   |                           下载                          | 模型配置文件 | 压缩算法配置文件  |
+| :----------------| :-------: | :------------: | :-------------: | :------: | :--------: | :------: | :-----------------------------------------------------: |:-------------: | :------: |
+| YOLOv3-MobileNetV1      |  baseline | 24.13          |  93          |   608    | 289.9ms | 75.1       | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/dygraph/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml)  |  -  |
+| YOLOv3-MobileNetV1      |  剪裁-l1_norm(sensity) | 15.78(-34.49%) |  66(-29%) |   608   | - | 77.6(+2.5) | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/dygraph/slim/yolov3_mobilenet_v1_voc_prune_l1_norm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml)  |  [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/slim/prune/yolov3_prune_l1_norm.yml)  |
+
+- SD855预测时延为使用PaddleLite部署，使用arm8架构并使用4线程(4 Threads)推理时延
+
+## 实验环境
+
+- Python 3.7+
+- PaddlePaddle >= 2.0.0
+- PaddleSlim >= 2.0.0
+- CUDA 9.0+
+- cuDNN >=7.5
+
+## 快速开始
+
+### 训练
+
+```shell
+python tools/train.py -c configs/{MODEL.yml} --slim_config configs/slim/{SLIM_CONFIG.yml}
+```
+
+- `-c`: 指定模型配置文件。
+- `--slim_config`: 指定压缩策略配置文件。
+
+
+### 评估
+
+```shell
+python tools/eval.py -c configs/{MODEL.yml} --slim_config configs/slim/{SLIM_CONFIG.yml} -o weights=output/{SLIM_CONFIG}/model_final
+```
+
+- `-c`: 指定模型配置文件。
+- `--slim_config`: 指定压缩策略配置文件。
+- `-o weights`: 指定压缩算法训好的模型路径。
+
+### 测试
+
+```shell
+python tools/infer.py -c configs/{MODEL.yml} --slim_config configs/slim/{SLIM_CONFIG.yml} \
+    -o weights=output/{SLIM_CONFIG}/model_final
+    --infer_img={IMAGE_PATH}
+```
+
+- `-c`: 指定模型配置文件。
+- `--slim_config`: 指定压缩策略配置文件。
+- `-o weights`: 指定压缩算法训好的模型路径。
+- `--infer_img`: 指定测试图像路径。
+
+
+### 动转静导出模型
+
+```shell
+python tools/export_model.py -c configs/{MODEL.yml} --slim_config configs/slim/{SLIM_CONFIG.yml} -o weights=output/{SLIM_CONFIG}/model_final
+```
+
+- `-c`: 指定模型配置文件。
+- `--slim_config`: 指定压缩策略配置文件。
+- `-o weights`: 指定压缩算法训好的模型路径。

dygraph/configs/slim/prune/yolov3_prune_fpgm.yml

+# Weights of yolov3_mobilenet_v1_voc
+pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/dygraph/yolov3_mobilenet_v1_270e_voc.pdparams
+load_static_weights: False
+weight_type: resume
+slim: Pruner
+
+Pruner:
+  criterion: fpgm
+  pruned_params: ['yolo_block.0.0.0.conv.weights', 'yolo_block.0.0.1.conv.weights', 'yolo_block.0.1.0.conv.weights',
+                  'yolo_block.0.1.1.conv.weights', 'yolo_block.0.2.conv.weights', 'yolo_block.0.tip.conv.weights',
+                  'yolo_block.1.0.0.conv.weights', 'yolo_block.1.0.1.conv.weights', 'yolo_block.1.1.0.conv.weights',
+                  'yolo_block.1.1.1.conv.weights', 'yolo_block.1.2.conv.weights', 'yolo_block.1.tip.conv.weights',
+                  'yolo_block.2.0.0.conv.weights', 'yolo_block.2.0.1.conv.weights', 'yolo_block.2.1.0.conv.weights',
+                  'yolo_block.2.1.1.conv.weights', 'yolo_block.2.2.conv.weights', 'yolo_block.2.tip.conv.weights']
+  pruned_ratios: [0.1,0.2,0.2,0.2,0.2,0.1,0.2,0.3,0.3,0.3,0.2,0.1,0.3,0.4,0.4,0.4,0.4,0.3]
+  print_params: False

dygraph/configs/slim/prune/yolov3_prune_l1_norm.yml

+# Weights of yolov3_mobilenet_v1_voc
+pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/dygraph/yolov3_mobilenet_v1_270e_voc.pdparams
+load_static_weights: False
+weight_type: resume
+slim: Pruner
+
+Pruner:
+  criterion: l1_norm
+  pruned_params: ['yolo_block.0.0.0.conv.weights', 'yolo_block.0.0.1.conv.weights', 'yolo_block.0.1.0.conv.weights',
+                  'yolo_block.0.1.1.conv.weights', 'yolo_block.0.2.conv.weights', 'yolo_block.0.tip.conv.weights',
+                  'yolo_block.1.0.0.conv.weights', 'yolo_block.1.0.1.conv.weights', 'yolo_block.1.1.0.conv.weights',
+                  'yolo_block.1.1.1.conv.weights', 'yolo_block.1.2.conv.weights', 'yolo_block.1.tip.conv.weights',
+                  'yolo_block.2.0.0.conv.weights', 'yolo_block.2.0.1.conv.weights', 'yolo_block.2.1.0.conv.weights',
+                  'yolo_block.2.1.1.conv.weights', 'yolo_block.2.2.conv.weights', 'yolo_block.2.tip.conv.weights']
+  pruned_ratios: [0.1,0.2,0.2,0.2,0.2,0.1,0.2,0.3,0.3,0.3,0.2,0.1,0.3,0.4,0.4,0.4,0.4,0.3]
+  print_params: False

dygraph/ppdet/__init__.py

@@ -13,4 +13,4 @@
 # limitations under the License.
 
 from . import (core, data, engine, modeling, model_zoo, optimizer, metrics,
-               py_op, utils)
+               py_op, utils, slim)

dygraph/ppdet/engine/trainer.py

@@ -48,9 +48,18 @@ class Trainer(object):
         assert mode.lower() in ['train', 'eval', 'test'], \
                 "mode should be 'train', 'eval' or 'test'"
         self.mode = mode.lower()
+        self.optimizer = None
 
         # build model
         self.model = create(cfg.architecture)
+
+        # model slim build
+        if cfg.slim:
+            if self.mode == 'train':
+                self.load_weights(cfg.pretrain_weights, cfg.weight_type)
+            slim = create(cfg.slim)
+            slim(self.model)
+
         if ParallelEnv().nranks > 1:
             self.model = paddle.DataParallel(self.model)
 
@@ -62,7 +71,6 @@ class Trainer(object):
                 self.dataset, cfg.worker_num)
 
         # build optimizer in train mode
-        self.optimizer = None
         if self.mode == 'train':
             steps_per_epoch = len(self.loader)
             self.lr = create('LearningRate')(steps_per_epoch)

dygraph/ppdet/slim/__init__.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# 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 . import prune
+
+from .prune import *

dygraph/ppdet/slim/prune.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# 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 paddle
+from paddle.utils import try_import
+
+from ppdet.core.workspace import register, serializable
+from ppdet.utils.logger import setup_logger
+logger = setup_logger(__name__)
+
+
+def print_prune_params(model):
+    model_dict = model.state_dict()
+    for key in model_dict.keys():
+        weight_name = model_dict[key].name
+        logger.info('Parameter name: {}, shape: {}'.format(
+            weight_name, model_dict[key].shape))
+
+
+@register
+@serializable
+class Pruner(object):
+    def __init__(self,
+                 criterion,
+                 pruned_params,
+                 pruned_ratios,
+                 print_params=False):
+        super(Pruner, self).__init__()
+        assert criterion in ['l1_norm', 'fpgm'], \
+            "unsupported prune criterion: {}".format(criterion)
+        self.criterion = criterion
+        self.pruned_params = pruned_params
+        self.pruned_ratios = pruned_ratios
+        self.print_params = print_params
+
+    def __call__(self, model):
+        paddleslim = try_import('paddleslim')
+        from paddleslim.analysis import dygraph_flops as flops
+        input_spec = [{
+            "image": paddle.ones(
+                shape=[1, 3, 640, 640], dtype='float32'),
+            "im_shape": paddle.full(
+                [1, 2], 640, dtype='float32'),
+            "scale_factor": paddle.ones(
+                shape=[1, 2], dtype='float32')
+        }]
+        if self.print_params:
+            print_prune_params(model)
+
+        ori_flops = flops(model, input_spec) / 1000
+        logger.info("FLOPs before pruning: {}GFLOPs".format(ori_flops))
+        if self.criterion == 'fpgm':
+            pruner = paddleslim.dygraph.FPGMFilterPruner(model, input_spec)
+        elif self.criterion == 'l1_norm':
+            pruner = paddleslim.dygraph.L1NormFilterPruner(model, input_spec)
+
+        logger.info("pruned params: {}".format(self.pruned_params))
+        pruned_ratios = [float(n) for n in self.pruned_ratios]
+        ratios = {}
+        for i, param in enumerate(self.pruned_params):
+            ratios[param] = pruned_ratios[i]
+        pruner.prune_vars(ratios, [0])
+        pruned_flops = flops(model, input_spec) / 1000
+        logger.info("FLOPs after pruning: {}GFLOPs; pruned ratio: {}".format(
+            pruned_flops, (ori_flops - pruned_flops) / ori_flops))
+
+        return model

dygraph/tools/eval.py

@@ -49,6 +49,12 @@ def parse_args():
     parser.add_argument(
         '--json_eval', action='store_true', default=False, help='')
 
+    parser.add_argument(
+        "--slim_config",
+        default=None,
+        type=str,
+        help="Configuration file of slim method.")
+
     parser.add_argument(
         '--use_gpu', action='store_true', default=False, help='')
 
@@ -72,6 +78,9 @@ def main():
 
     cfg = load_config(FLAGS.config)
     merge_config(FLAGS.opt)
+    if FLAGS.slim_config:
+        slim_cfg = load_config(FLAGS.slim_config)
+        merge_config(slim_cfg)
     check_config(cfg)
     check_gpu(cfg.use_gpu)
     check_version()

dygraph/tools/export_model.py

@@ -43,6 +43,11 @@ def parse_args():
         type=str,
         default="output_inference",
         help="Directory for storing the output model files.")
+    parser.add_argument(
+        "--slim_config",
+        default=None,
+        type=str,
+        help="Configuration file of slim method.")
     args = parser.parse_args()
     return args
 
@@ -67,6 +72,9 @@ def main():
     if 'norm_type' in cfg and cfg['norm_type'] == 'sync_bn':
         FLAGS.opt['norm_type'] = 'bn'
     merge_config(FLAGS.opt)
+    if FLAGS.slim_config:
+        slim_cfg = load_config(FLAGS.slim_config)
+        merge_config(slim_cfg)
     check_config(cfg)
     check_gpu(cfg.use_gpu)
     check_version()

dygraph/tools/infer.py

@@ -59,6 +59,11 @@ def parse_args():
         type=float,
         default=0.5,
         help="Threshold to reserve the result for visualization.")
+    parser.add_argument(
+        "--slim_config",
+        default=None,
+        type=str,
+        help="Configuration file of slim method.")
     parser.add_argument(
         "--use_vdl",
         type=bool,
@@ -126,6 +131,9 @@ def main():
 
     cfg = load_config(FLAGS.config)
     merge_config(FLAGS.opt)
+    if FLAGS.slim_config:
+        slim_cfg = load_config(FLAGS.slim_config)
+        merge_config(slim_cfg)
     check_config(cfg)
     check_gpu(cfg.use_gpu)
     check_version()

dygraph/tools/train.py

@@ -65,10 +65,10 @@ def parse_args():
         default=False,
         help="Whether to perform evaluation in train")
     parser.add_argument(
-        "--output_eval",
+        "--slim_config",
         default=None,
         type=str,
-        help="Evaluation directory, default is current directory.")
+        help="Configuration file of slim method.")
     parser.add_argument(
         "--enable_ce",
         type=bool,
@@ -92,7 +92,8 @@ def run(FLAGS, cfg):
     trainer = Trainer(cfg, mode='train')
 
     # load weights
-    trainer.load_weights(cfg.pretrain_weights, FLAGS.weight_type)
+    if not FLAGS.slim_config:
+        trainer.load_weights(cfg.pretrain_weights, FLAGS.weight_type)
 
     # training
     trainer.train()
@@ -103,6 +104,11 @@ def main():
 
     cfg = load_config(FLAGS.config)
     merge_config(FLAGS.opt)
+    if FLAGS.slim_config:
+        slim_cfg = load_config(FLAGS.slim_config)
+        merge_config(slim_cfg)
+        if 'weight_type' not in cfg:
+            cfg.weight_type = FLAGS.weight_type
     check.check_config(cfg)
     check.check_gpu(cfg.use_gpu)
     check.check_version()