统计附件文件"news.txt"中出现的英文字母的次数,并按次数从高到低的排序打印出现次数最多的5个字母。
统一转化为小写字母进行统计。
(提交包括源代码和可执行文件)
文件news.txt是
The dominant sequence transduction models are based on complex recurrent
or convolutional neural networks in an encoder
decoder configuration.
The best performing models also connect the encoder and decoder through
an attention mechanism. We propose a new
simple network architecture,
the Transformer, based solely on attention mechanisms, dispensing with
recurrence and convolutions entirely. Experiments on two machine
translation tasks show these models to be superior in quality while
being more parallelizab
le and requiring significantly less time to train.
Our model achieves 28.4 BLEU on the WMT 2014 English
to
German
translation task, improving over the existing best results, including
ensembles by over 2 BLEU. On the WMT 2014 English
to
French translation
task, our model establishes a new single
model state
of
the
art BLEU
score of 41.8 after training for 3.5 days on eight GPUs, a small fraction
of the training costs of the best models from the literature. We show
that the Transformer generalizes well to ot
her tasks by applying it
successfully to English constituency parsing both with large and limited
training data.