# Copyright (c) 2016 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 print_function import requests import hashlib import os import errno import shutil import six import sys import importlib import paddle.dataset import six.moves.cPickle as pickle import tempfile import glob import paddle __all__ = [] HOME = os.path.expanduser('~') # If the default HOME dir does not support writing, we # will create a temporary folder to store the cache files. if not os.access(HOME, os.W_OK): """ gettempdir() return the name of the directory used for temporary files. On Windows, the directories C:\TEMP, C:\TMP, \TEMP, and \TMP, in that order. On all other platforms, the directories /tmp, /var/tmp, and /usr/tmp, in that order. For more details, please refer to https://docs.python.org/3/library/tempfile.html """ HOME = tempfile.gettempdir() DATA_HOME = os.path.join(HOME, '.cache', 'paddle', 'dataset') # When running unit tests, there could be multiple processes that # trying to create DATA_HOME directory simultaneously, so we cannot # use a if condition to check for the existence of the directory; # instead, we use the filesystem as the synchronization mechanism by # catching returned errors. def must_mkdirs(path): try: os.makedirs(DATA_HOME) except OSError as exc: if exc.errno != errno.EEXIST: raise pass must_mkdirs(DATA_HOME) def md5file(fname): hash_md5 = hashlib.md5() f = open(fname, "rb") for chunk in iter(lambda: f.read(4096), b""): hash_md5.update(chunk) f.close() return hash_md5.hexdigest() def download(url, module_name, md5sum, save_name=None): dirname = os.path.join(DATA_HOME, module_name) if not os.path.exists(dirname): os.makedirs(dirname) filename = os.path.join( dirname, url.split('/')[-1] if save_name is None else save_name) if os.path.exists(filename) and md5file(filename) == md5sum: return filename retry = 0 retry_limit = 3 while not (os.path.exists(filename) and md5file(filename) == md5sum): if os.path.exists(filename): sys.stderr.write("file %s md5 %s\n" % (md5file(filename), md5sum)) if retry < retry_limit: retry += 1 else: raise RuntimeError( "Cannot download {0} within retry limit {1}".format( url, retry_limit)) sys.stderr.write("Cache file %s not found, downloading %s \n" % (filename, url)) sys.stderr.write("Begin to download\n") try: r = requests.get(url, stream=True) total_length = r.headers.get('content-length') if total_length is None: with open(filename, 'wb') as f: shutil.copyfileobj(r.raw, f) else: with open(filename, 'wb') as f: chunk_size = 4096 total_length = int(total_length) total_iter = total_length / chunk_size + 1 log_interval = total_iter // 20 if total_iter > 20 else 1 log_index = 0 bar = paddle.hapi.progressbar.ProgressBar(total_iter, name='item') for data in r.iter_content(chunk_size=chunk_size): f.write(data) log_index += 1 bar.update(log_index, {}) if log_index % log_interval == 0: bar.update(log_index) except Exception as e: # re-try continue sys.stderr.write("\nDownload finished\n") sys.stdout.flush() return filename def fetch_all(): for module_name in [ x for x in dir(paddle.dataset) if not x.startswith("__") ]: if "fetch" in dir( importlib.import_module("paddle.dataset.%s" % module_name)): getattr(importlib.import_module("paddle.dataset.%s" % module_name), "fetch")() def split(reader, line_count, suffix="%05d.pickle", dumper=pickle.dump): """ you can call the function as: split(paddle.dataset.cifar.train10(), line_count=1000, suffix="imikolov-train-%05d.pickle") the output files as: |-imikolov-train-00000.pickle |-imikolov-train-00001.pickle |- ... |-imikolov-train-00480.pickle :param reader: is a reader creator :param line_count: line count for each file :param suffix: the suffix for the output files, should contain "%d" means the id for each file. Default is "%05d.pickle" :param dumper: is a callable function that dump object to file, this function will be called as dumper(obj, f) and obj is the object will be dumped, f is a file object. Default is cPickle.dump. """ if not callable(dumper): raise TypeError("dumper should be callable.") lines = [] indx_f = 0 for i, d in enumerate(reader()): lines.append(d) if i >= line_count and i % line_count == 0: with open(suffix % indx_f, "w") as f: dumper(lines, f) lines = [] indx_f += 1 if lines: with open(suffix % indx_f, "w") as f: dumper(lines, f) def cluster_files_reader(files_pattern, trainer_count, trainer_id, loader=pickle.load): """ Create a reader that yield element from the given files, select a file set according trainer count and trainer_id :param files_pattern: the files which generating by split(...) :param trainer_count: total trainer count :param trainer_id: the trainer rank id :param loader: is a callable function that load object from file, this function will be called as loader(f) and f is a file object. Default is cPickle.load """ def reader(): if not callable(loader): raise TypeError("loader should be callable.") file_list = glob.glob(files_pattern) file_list.sort() my_file_list = [] for idx, fn in enumerate(file_list): if idx % trainer_count == trainer_id: print("append file: %s" % fn) my_file_list.append(fn) for fn in my_file_list: with open(fn, "r") as f: lines = loader(f) for line in lines: yield line return reader def _check_exists_and_download(path, url, md5, module_name, download=True): if path and os.path.exists(path): return path if download: return paddle.dataset.common.download(url, module_name, md5) else: raise ValueError( '{} not exists and auto download disabled'.format(path))