plot.py中'basestring'没定义过
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File "C:\Users\11856\AppData\Roaming\Python\Python37\site-packages\paddle\utils\plot.py", line 75, in append
assert isinstance(title, basestring)
NameError: name 'basestring' is not defined
我看了源代码,plot.py文件中'basestring'确实只出现过一次,没有定义过,是否是源码有问题?
这个程序来自官方的使用文档中,图像分类的代码
版本:fluid1.2
import paddle
import paddle.fluid as fluid
import numpy
import sys
def vgg_bn_drop(input):
def conv_block(ipt, num_filter, groups, dropouts):
return fluid.nets.img_conv_group(
input=ipt,
pool_size=2,
pool_stride=2,
conv_num_filter=[num_filter] * groups,
conv_filter_size=3,
conv_act='relu',
conv_with_batchnorm=True,
conv_batchnorm_drop_rate=dropouts,
pool_type='max')
conv1 = conv_block(input, 64, 2, [0.3, 0])
conv2 = conv_block(conv1, 128, 2, [0.4, 0])
conv3 = conv_block(conv2, 256, 3, [0.4, 0.4, 0])
conv4 = conv_block(conv3, 512, 3, [0.4, 0.4, 0])
conv5 = conv_block(conv4, 512, 3, [0.4, 0.4, 0])
drop = fluid.layers.dropout(x=conv5, dropout_prob=0.5)
fc1 = fluid.layers.fc(input=drop, size=512, act=None)
bn = fluid.layers.batch_norm(input=fc1, act='relu')
drop2 = fluid.layers.dropout(x=bn, dropout_prob=0.5)
fc2 = fluid.layers.fc(input=drop2, size=512, act=None)
predict = fluid.layers.fc(input=fc2, size=10, act='softmax')
return predict
def inference_program():
data_shape = [3, 32, 32]
images = fluid.layers.data(name='pixel', shape=data_shape, dtype='float32')
predict = vgg_bn_drop(images) # un-comment to use vgg net
return predict
def train_program(predict = inference_program()):
label = fluid.layers.data(name='label', shape=[1], dtype='int64')
cost = fluid.layers.cross_entropy(input=predict, label=label)
avg_cost = fluid.layers.mean(cost)
accuracy = fluid.layers.accuracy(input=predict, label=label)
return [avg_cost, accuracy]
def optimizer_program():
return fluid.optimizer.Adam(learning_rate=0.001)
BATCH_SIZE = 128
train_reader = paddle.batch(
paddle.reader.shuffle(paddle.dataset.cifar.train10(), buf_size=50000),
batch_size=BATCH_SIZE)
test_reader = paddle.batch(
paddle.dataset.cifar.test10(), batch_size=BATCH_SIZE)
feed_order = ['pixel', 'label']
main_program = fluid.default_main_program()
star_program = fluid.default_startup_program()
test_program = main_program.clone(for_test=True)
predict = inference_program()
avg_cost, acc = train_program(predict)
optimizer = optimizer_program()
optimizer.minimize(avg_cost)
use_cuda = False
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
exe = fluid.Executor(place)
EPOCH_NUM = 2
def train_test(program, reader):
count = 0
feed_var_list = [
program.global_block().var(var_name) for var_name in feed_order
]
feeder_test = fluid.DataFeeder(
feed_list=feed_var_list, place=place)
test_exe = fluid.Executor(place)
accumulated = len([avg_cost, acc]) * [0]
for tid, test_data in enumerate(reader()):
avg_cost_np = test_exe.run(program=program,
feed=feeder_test.feed(test_data),
fetch_list=[avg_cost, acc])
accumulated = [x[0] + x[1][0] for x in zip(accumulated, avg_cost_np)]
count += 1
return [x / count for x in accumulated]
params_dirname = "image_classification_resnet.inference.model"
from paddle.utils.plot import Ploter
train_prompt = "Train cost"
test_prompt = "Test cost"
plot_cost = Ploter(test_prompt,train_prompt)
def train_loop():
feed_var_list_loop = [
main_program.global_block().var(var_name) for var_name in feed_order
]
feeder = fluid.DataFeeder(
feed_list=feed_var_list_loop, place=place)
exe.run(star_program)
step = 0
for pass_id in range(EPOCH_NUM):
for step_id, data_train in enumerate(train_reader()):
avg_loss_value = exe.run(main_program,
feed=feeder.feed(data_train),
fetch_list=[avg_cost, acc])
if step % 1 == 0:
plot_cost.append(train_prompt, step, avg_loss_value[0])
plot_cost.plot()
step += 1
avg_cost_test, accuracy_test = train_test(test_program,
reader=test_reader)
plot_cost.append(test_prompt, step, avg_cost_test)
if params_dirname is not None:
fluid.io.save_inference_model(params_dirname, ["pixel"],
[predict], exe)
train_loop()
1
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你好,能发一下你运行的代码吗?
发不出来= =一直告诉我审核没通过,有色情内容
https://github.com/CzhaiXy/Project/blob/master/error.py
上传到github上了,windows平台下,paddlepaddle1.2.1
在windows环境下,paddlepaddle1.2.1
谢谢反馈,这个应该是一个python3版本兼容的问题,basestring是python2的内置函数,python3下没有这个了,我们考虑在接下来修复它
谢谢反馈,这个应该是一个python3版本兼容的问题,basestring是python2的内置函数,python3下没有这个了,我们考虑在接下来修复它
我也是这个问题,1.3了,还没解决吗?
下边一行还是.has_key...............