From f92927ef63ea0813aba780181bd5d2d782f64669 Mon Sep 17 00:00:00 2001 From: whs Date: Thu, 13 Feb 2020 21:15:08 +0800 Subject: [PATCH] Remove unused file from pruning demo. (#225) --- slim/prune/compress.py | 262 ----------------------- slim/prune/images/MobileNetV1-YoloV3.pdf | Bin 174731 -> 0 bytes slim/prune/yolov3_mobilenet_v1_slim.yaml | 23 -- 3 files changed, 285 deletions(-) delete mode 100644 slim/prune/compress.py delete mode 100644 slim/prune/images/MobileNetV1-YoloV3.pdf delete mode 100644 slim/prune/yolov3_mobilenet_v1_slim.yaml diff --git a/slim/prune/compress.py b/slim/prune/compress.py deleted file mode 100644 index ed2426df4..000000000 --- a/slim/prune/compress.py +++ /dev/null @@ -1,262 +0,0 @@ -# Copyright (c) 2019 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 os -import time -import multiprocessing -import numpy as np -import sys -sys.path.append("../../") -from paddle.fluid.contrib.slim import Compressor - - -def set_paddle_flags(**kwargs): - for key, value in kwargs.items(): - if os.environ.get(key, None) is None: - os.environ[key] = str(value) - - -# NOTE(paddle-dev): All of these flags should be set before -# `import paddle`. Otherwise, it would not take any effect. -set_paddle_flags( - FLAGS_eager_delete_tensor_gb=0, # enable GC to save memory -) - -from paddle import fluid -from ppdet.core.workspace import load_config, merge_config, create -from ppdet.data.data_feed import create_reader -from ppdet.utils.eval_utils import parse_fetches, eval_results -from ppdet.utils.cli import ArgsParser -from ppdet.utils.check import check_gpu -import ppdet.utils.checkpoint as checkpoint -from ppdet.modeling.model_input import create_feed - -import logging -FORMAT = '%(asctime)s-%(levelname)s: %(message)s' -logging.basicConfig(level=logging.INFO, format=FORMAT) -logger = logging.getLogger(__name__) - - -def eval_run(exe, compile_program, reader, keys, values, cls, test_feed, cfg): - """ - Run evaluation program, return program outputs. - """ - iter_id = 0 - results = [] - if len(cls) != 0: - values = [] - for i in range(len(cls)): - _, accum_map = cls[i].get_map_var() - cls[i].reset(exe) - values.append(accum_map) - - images_num = 0 - start_time = time.time() - has_bbox = 'bbox' in keys - for data in reader(): - data = test_feed.feed(data) - feed_data = {'image': data['image'], 'im_size': data['im_size']} - outs = exe.run(compile_program, - feed=feed_data, - fetch_list=[values[0]], - return_numpy=False) - - if cfg.metric == 'VOC': - outs.append(data['gt_box']) - outs.append(data['gt_label']) - outs.append(data['is_difficult']) - elif cfg.metric == 'COCO': - outs.append(data['im_info']) - outs.append(data['im_id']) - outs.append(data['im_shape']) - - res = { - k: (np.array(v), v.recursive_sequence_lengths()) - for k, v in zip(keys, outs) - } - results.append(res) - if iter_id % 100 == 0: - logger.info('Test iter {}'.format(iter_id)) - iter_id += 1 - images_num += len(res['bbox'][1][0]) if has_bbox else 1 - logger.info('Test finish iter {}'.format(iter_id)) - - end_time = time.time() - fps = images_num / (end_time - start_time) - if has_bbox: - logger.info('Total number of images: {}, inference time: {} fps.'. - format(images_num, fps)) - else: - logger.info('Total iteration: {}, inference time: {} batch/s.'.format( - images_num, fps)) - - return results - - -def main(): - cfg = load_config(FLAGS.config) - if 'architecture' in cfg: - main_arch = cfg.architecture - else: - raise ValueError("'architecture' not specified in config file.") - - merge_config(FLAGS.opt) - if 'log_iter' not in cfg: - cfg.log_iter = 20 - - # check if set use_gpu=True in paddlepaddle cpu version - check_gpu(cfg.use_gpu) - - if cfg.use_gpu: - devices_num = fluid.core.get_cuda_device_count() - else: - devices_num = int( - os.environ.get('CPU_NUM', multiprocessing.cpu_count())) - - if 'train_feed' not in cfg: - train_feed = create(main_arch + 'TrainFeed') - else: - train_feed = create(cfg.train_feed) - - if 'eval_feed' not in cfg: - eval_feed = create(main_arch + 'EvalFeed') - else: - eval_feed = create(cfg.eval_feed) - - place = fluid.CUDAPlace(0) if cfg.use_gpu else fluid.CPUPlace() - exe = fluid.Executor(place) - - lr_builder = create('LearningRate') - optim_builder = create('OptimizerBuilder') - - # build program - startup_prog = fluid.Program() - train_prog = fluid.Program() - with fluid.program_guard(train_prog, startup_prog): - with fluid.unique_name.guard(): - model = create(main_arch) - _, feed_vars = create_feed(train_feed, True) - train_fetches = model.train(feed_vars) - loss = train_fetches['loss'] - lr = lr_builder() - optimizer = optim_builder(lr) - optimizer.minimize(loss) - - train_reader = create_reader(train_feed, cfg.max_iters, FLAGS.dataset_dir) - - # parse train fetches - train_keys, train_values, _ = parse_fetches(train_fetches) - train_keys.append("lr") - train_values.append(lr.name) - - train_fetch_list = [] - for k, v in zip(train_keys, train_values): - train_fetch_list.append((k, v)) - - eval_prog = fluid.Program() - with fluid.program_guard(eval_prog, startup_prog): - with fluid.unique_name.guard(): - model = create(main_arch) - _, test_feed_vars = create_feed(eval_feed, True) - fetches = model.eval(test_feed_vars) - - eval_prog = eval_prog.clone(True) - - eval_reader = create_reader(eval_feed, args_path=FLAGS.dataset_dir) - test_data_feed = fluid.DataFeeder(test_feed_vars.values(), place) - - # parse eval fetches - extra_keys = [] - if cfg.metric == 'COCO': - extra_keys = ['im_info', 'im_id', 'im_shape'] - if cfg.metric == 'VOC': - extra_keys = ['gt_box', 'gt_label', 'is_difficult'] - eval_keys, eval_values, eval_cls = parse_fetches(fetches, eval_prog, - extra_keys) - eval_fetch_list = [] - for k, v in zip(eval_keys, eval_values): - eval_fetch_list.append((k, v)) - - exe.run(startup_prog) - checkpoint.load_params(exe, train_prog, cfg.pretrain_weights) - - best_box_ap_list = [] - - def eval_func(program, scope): - - #place = fluid.CPUPlace() - #exe = fluid.Executor(place) - results = eval_run(exe, program, eval_reader, eval_keys, eval_values, - eval_cls, test_data_feed, cfg) - - resolution = None - if 'mask' in results[0]: - resolution = model.mask_head.resolution - box_ap_stats = eval_results(results, eval_feed, cfg.metric, - cfg.num_classes, resolution, False, - FLAGS.output_eval) - if len(best_box_ap_list) == 0: - best_box_ap_list.append(box_ap_stats[0]) - elif box_ap_stats[0] > best_box_ap_list[0]: - best_box_ap_list[0] = box_ap_stats[0] - logger.info("Best test box ap: {}".format(best_box_ap_list[0])) - return best_box_ap_list[0] - - test_feed = [('image', test_feed_vars['image'].name), - ('im_size', test_feed_vars['im_size'].name)] - - com = Compressor( - place, - fluid.global_scope(), - train_prog, - train_reader=train_reader, - train_feed_list=[(key, value.name) for key, value in feed_vars.items()], - train_fetch_list=train_fetch_list, - eval_program=eval_prog, - eval_reader=eval_reader, - eval_feed_list=test_feed, - eval_func={'map': eval_func}, - eval_fetch_list=[eval_fetch_list[0]], - save_eval_model=True, - prune_infer_model=[["image", "im_size"], ["multiclass_nms_0.tmp_0"]], - train_optimizer=None) - com.config(FLAGS.slim_file) - com.run() - - -if __name__ == '__main__': - parser = ArgsParser() - parser.add_argument( - "-s", - "--slim_file", - default=None, - type=str, - help="Config file of PaddleSlim.") - parser.add_argument( - "--output_eval", - default=None, - type=str, - help="Evaluation directory, default is current directory.") - parser.add_argument( - "-d", - "--dataset_dir", - default=None, - type=str, - help="Dataset path, same as DataFeed.dataset.dataset_dir") - FLAGS = parser.parse_args() - main() diff --git a/slim/prune/images/MobileNetV1-YoloV3.pdf b/slim/prune/images/MobileNetV1-YoloV3.pdf deleted file mode 100644 index f5d3a22db5030ffc6beb1e7f8c92bddd61e366e6..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 174731 zcmYhibCg`&_dJ|rkg+qiZQB{!HZrztqsO*w+qN^d&CJZ($@BTG_xo3`)wkC=x6eJd zcI~R#Byz%{Gz_#XP$Z2PRc}yC`1JTT2EU-Vx$)_wjIB)_&G4ClUnxN0^&O3cjSX##jG=gWp&T6TjrFadTr(y*HDg#fl5iezy9x2mJdT+!>gg 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