def main(): args = conf.parse_args() config = conf.get_config(args.config, overrides=args.override, show=False) assert os.path.exists( os.path.join(config["Global"]["save_inference_dir"], 'inference.pdmodel')) and os.path.exists( os.path.join(config["Global"]["save_inference_dir"], 'inference.pdiparams')) config["DataLoader"]["Eval"]["sampler"]["batch_size"] = 1 config["DataLoader"]["Eval"]["loader"]["num_workers"] = 0 init_logger() device = paddle.set_device("cpu") train_dataloader = build_dataloader(config["DataLoader"], "Eval", device, False) def sample_generator(loader): def __reader__(): for indx, data in enumerate(loader): images = np.array(data[0]) yield images return __reader__ paddle.enable_static() place = paddle.CPUPlace() exe = paddle.static.Executor(place) paddleslim.quant.quant_post_static( executor=exe, model_dir=config["Global"]["save_inference_dir"], model_filename='inference.pdmodel', params_filename='inference.pdiparams', quantize_model_path=os.path.join( config["Global"]["save_inference_dir"], "quant_post_static_model"), sample_generator=sample_generator(train_dataloader), batch_nums=10)
# 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 sys __dir__ = os.path.dirname(os.path.abspath(__file__)) sys.path.append(os.path.abspath(os.path.join(__dir__, '../'))) from ppcls.utils import config from ppcls.engine.engine import Engine if __name__ == "__main__": args = config.parse_args() config = config.get_config(args.config, overrides=args.override, show=False) engine = Engine(config, mode="infer") engine.infer()
def main(): args = parse_args() configs = parse_config(args.config) init_logger(name='gallery2fc') export_fuse_model(configs)