我尝试在PHP脚本中使用import random
import time
from keras.models import Sequential
from keras.layers import Dense
from keras import backend as K
import tracemalloc
def run():
tracemalloc.start()
num_input_nodes = 12
num_hidden_nodes = 8
num_output_nodes = 1
random_numbers = random.sample(range(1000), 50)
train_x, train_y = create_training_dataset(random_numbers, num_input_nodes)
for i in range(100):
snapshot = tracemalloc.take_snapshot()
for j in range(10):
start_time = time.time()
nn = Sequential()
nn.add(Dense(num_hidden_nodes, input_dim=num_input_nodes, activation='relu'))
nn.add(Dense(num_output_nodes))
nn.compile(loss='mean_squared_error', optimizer='adam')
nn.fit(train_x, train_y, nb_epoch=300, batch_size=2, verbose=0)
K.clear_session()
print("Iteration {iter}. Current time {t}. Took {elapsed} seconds".
format(iter=i*10 + j + 1, t=time.strftime('%H:%M:%S'), elapsed=int(time.time() - start_time)))
top_stats = tracemalloc.take_snapshot().compare_to(snapshot, 'lineno')
print("[ Top 5 differences ]")
for stat in top_stats[:5]:
print(stat)
def create_training_dataset(dataset, input_nodes):
"""
Outputs a training dataset (train_x, train_y) as numpy arrays.
Each item in train_x has 'input_nodes' number of items while train_y items are of size 1
:param dataset: list of ints
:param input_nodes:
:return: (numpy array, numpy array), train_x, train_y
"""
data_x, data_y = [], []
for i in range(len(dataset) - input_nodes - 1):
a = dataset[i:(i + input_nodes)]
data_x.append(a)
data_y.append(dataset[i + input_nodes])
return numpy.array(data_x), numpy.array(data_y)
run()
创建文件夹
在mkdir()的位置，我有一个名为＆＃34的文件夹;详细信息＆＃34;。在该文件夹中，我想创建另一个文件夹。
我使用此代码：
file.php但我总是得到这个警告：
警告：mkdir（）： 40 >
\ Users \ Lenovo \ xampp \ htdocs \ public_html \ file.php 中的参数无效
我通过回复来检查mkdir("details/$id", 0777, true);
是否为空。
如何在详细信息文件夹下创建$id名称的文件夹？
答案 0 :(得分：0)
您不能在字符串中使用$ id，必须将其连接起来
mkdir("details/". $id, 0777, true);
OR
mkdir("details/{$id}", 0777, true);