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jblitzar
/
github-python-corpus

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embedding_dim = 64 # 词向量维度
seq_length = 20 # 序列长度
num_classes = 4 # 类别数
num_filters = 256 # 卷积核数目
kernel_size = 5 # 卷积核尺寸
vocab_size = 1075 # 词汇表达小
hidden_dim = 128 # 全连接层神经元
dropout_keep_prob = 0.5 # dropout保留比例
learning_rate = 1e-3 # 学习率
batch_size = 64 # 每批训练大小
num_epochs = 10 # 总迭代轮次
print_per_batch = 100 # 每多少轮输出一次结果
save_per_batch = 10 # 每多少轮存入tensorboard
class TextCNN(object):
"""文本分类，CNN模型"""
def __init__(self, config):
self.config = config
# 三个待输入的数据
self.input_x = tf.placeholder(tf.int32, [None, self.config.seq_length], name='input_x')
self.input_y = tf.placeholder(tf.float32, [None, self.config.num_classes], name='input_y')
self.keep_prob = tf.placeholder(tf.float32, name='keep_prob')
self.cnn()
def cnn(self):
"""CNN模型"""
# 词向量映射
with tf.device('/cpu:0'):
embedding = tf.get_variable('embedding', [self.config.vocab_size, self.config.embedding_dim])
embedding_inputs = tf.nn.embedding_lookup(embedding, self.input_x)
with tf.name_scope("cnn"):
# CNN layer
conv = tf.layers.conv1d(embedding_inputs, self.config.num_filters, self.config.kernel_size, name='conv')
# global max pooling layer
gmp = tf.reduce_max(conv, reduction_indices=[1], name='gmp')
with tf.name_scope("score"):
# 全连接层，后面接dropout以及relu激活
fc = tf.layers.dense(gmp, self.config.hidden_dim, name='fc1')
fc = tf.contrib.layers.dropout(fc, self.keep_prob)
fc = tf.nn.relu(fc)
# 分类器
self.logits = tf.layers.dense(fc, self.config.num_classes, name='fc2')
self.y_pred_cls = tf.argmax(tf.nn.softmax(self.logits), 1) # 预测类别
with tf.name_scope("optimize"):
# 损失函数，交叉熵
cross_entropy = tf.nn.softmax_cross_entropy_with_logits(logits=self.logits, labels=self.input_y)
self.loss = tf.reduce_mean(cross_entropy)
# 优化器
self.optim = tf.train.AdamOptimizer(learning_rate=self.config.learning_rate).minimize(self.loss)
with tf.name_scope("accuracy"):
# 准确率
correct_pred = tf.equal(tf.argmax(self.input_y, 1), self.y_pred_cls)
self.acc = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
# <FILESEP>
class MinerException(Exception):
"""
Base exception class for this application.
"""
def __init__(self, *args: object):
if args:
super().__init__(*args)
else:
super().__init__("Unknown miner error")
class ExitRequest(MinerException):
"""
Raised when the application is requested to exit from outside of the main loop.
Intended for internal use only.
"""
def __init__(self):
super().__init__("Application was requested to exit")
class ReloadRequest(MinerException):
"""
Raised when the application is requested to reload entirely, without closing the GUI.
Intended for internal use only.
"""
def __init__(self):
super().__init__("Application was requested to reload entirely")
class RequestException(MinerException):
"""