标签：常用 min users perl 简易 org images 训练 ror
基本分类（Basic classification）：https://www.tensorflow.org/tutorials/keras/basic_classification
是一种用于在TensorFlow中构建和训练模型的高阶API：https://www.tensorflow.org/api_docs/python/tf/keras/
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错误提示
Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-labels-idx1-ubyte.gz
......
Exception: URL fetch failure on https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-labels-idx1-ubyte.gz: None -- [WinError 10060] A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond
处理方法1
选择一个链接，
手工下载下面四个文件，并存放在“~/.keras/datasets”下的fashion-mnist目录。
guowli@5CG450158J MINGW64 ~/.keras/datasets $ pwd /c/Users/guowli/.keras/datasets guowli@5CG450158J MINGW64 ~/.keras/datasets $ ls -l total 0 drwxr-xr-x 1 guowli 1049089 0 Mar 27 14:44 fashion-mnist/ guowli@5CG450158J MINGW64 ~/.keras/datasets $ ls -l fashion-mnist/ total 30164 -rw-r--r-- 1 guowli 1049089 4422102 Mar 27 15:47 t10k-images-idx3-ubyte.gz -rw-r--r-- 1 guowli 1049089 5148 Mar 27 15:47 t10k-labels-idx1-ubyte.gz -rw-r--r-- 1 guowli 1049089 26421880 Mar 27 15:47 train-images-idx3-ubyte.gz -rw-r--r-- 1 guowli 1049089 29515 Mar 27 15:47 train-labels-idx1-ubyte.gz
处理方法2
手工下载文件，存放在指定目录。
改写“tensorflow\python\keras\datasets\fashion_mnist.py”定义的load_data()函数。
from tensorflow.python.keras.utils import get_file import numpy as np import pathlib import gzip def load_data(): # 改写“tensorflow\python\keras\datasets\fashion_mnist.py”定义的load_data()函数 base = "file:///" + str(pathlib.Path.cwd()) + "\\" # 当前目录 files = [ ‘train-labels-idx1-ubyte.gz‘, ‘train-images-idx3-ubyte.gz‘, ‘t10k-labels-idx1-ubyte.gz‘, ‘t10k-images-idx3-ubyte.gz‘ ] paths = [] for fname in files: paths.append(get_file(fname, origin=base + fname)) with gzip.open(paths[0], ‘rb‘) as lbpath: y_train = np.frombuffer(lbpath.read(), np.uint8, offset=8) with gzip.open(paths[1], ‘rb‘) as imgpath: x_train = np.frombuffer( imgpath.read(), np.uint8, offset=16).reshape(len(y_train), 28, 28) with gzip.open(paths[2], ‘rb‘) as lbpath: y_test = np.frombuffer(lbpath.read(), np.uint8, offset=8) with gzip.open(paths[3], ‘rb‘) as imgpath: x_test = np.frombuffer( imgpath.read(), np.uint8, offset=16).reshape(len(y_test), 28, 28) return (x_train, y_train), (x_test, y_test) (train_images, train_labels), (test_images, test_labels) = load_data()
错误提示
“OSError: Not a gzipped file (b‘\n\n‘)”
处理方法
对于损坏的、不完整的.gz文件，zip.open()将无法打开。检查.gz文件是否完整无损。
参考信息
https://github.com/tensorflow/tensorflow/issues/170
标签：常用 min users perl 简易 org images 训练 ror
原文地址：https://www.cnblogs.com/anliven/p/10612178.html
