src/text.py

# target_text = """\
# Obama was born in Honolulu, Hawaii.
# After graduating from Columbia University in 1983, he worked as a community organizer in Chicago.
# In 1988, he enrolled in Harvard Law School, where he was the first black president of the Harvard Law Review.
# After graduating, he became a civil rights attorney and an academic, teaching constitutional law at the University of Chicago Law School from 1992 to 2004.
# Turning to elective politics, he represented the 13th district in the Illinois Senate from 1997 until 2004, when he ran for the U.S.
# Senate.
# Obama received national attention in 2004 with his March Senate primary win, his well-received July Democratic National Convention keynote address, and his landslide November election to the Senate.
# In 2008, after a close primary campaign against Hillary Clinton, he was nominated by the Democratic Party for president and chose Joe Biden as his running mate.
# Obama was elected over Republican nominee John McCain in the presidential election and was inaugurated on January 20, 2009.
# Nine months later, he was named the 2009 Nobel Peace Prize laureate, a decision that drew a mixture of praise and criticism.
# """
# target_text = """\
# Biology
# Metapod is an insect Pokémon that resembles a green chrysalis.
# Its body is crescent-shaped with several segments making up the lower point.
# The front of Metapod's shell resembles a face with heavy-lidded eyes and a sharply pointed nose.
# The back of its shell consists of several geometrically shaped portions and projections.

# Metapod's soft body is protected by a hard outer shell as it undergoes metamorphosis.
# While this shell is said to be as hard as steel, a sudden, powerful impact could cause its liquid innards to pop out, leaving it completely exposed. Metapod generally remains motionless, rebuilding its cells for evolution.
# If an enemy discovers Metapod, it is unable to do anything other than harden its outer shell. Metapod lives in temperate forests and jungles, often in groups. Pikipek is a natural predator of Metapod.
# """
# target_text = """
# The Icelandic horse (Icelandic: íslenski hesturinn [ˈistlɛnscɪ ˈhɛstʏrɪn]) is a breed of horse developed in Iceland. Although the horses are small, at times pony-sized, most registries for the Icelandic refer to it as a horse. Icelandic horses are long-lived and hardy. In their native country they have few diseases; Icelandic law prevents horses from being imported into the country and exported animals are not allowed to return. The Icelandic displays two gaits in addition to the typical walk, trot, and canter/gallop commonly displayed by other breeds. The only breed of horse in Iceland, they are also popular internationally, and sizable populations exist in Europe and North America. The breed is still used for traditional sheepherding work in its native country, as well as for leisure, showing, and racing.

# Developed from ponies taken to Iceland by Norse settlers in the 9th and 10th centuries, the breed is mentioned in literature and historical records throughout Icelandic history; the first reference to a named horse appears in the 12th century. Horses were venerated in Norse mythology, a custom brought to Iceland by the country's earliest settlers. Selective breeding over the centuries has developed the breed into its current form. Natural selection has also played a role, as the harsh Icelandic climate eliminated many horses through exposure and malnourishment. In the 1780s, much of the breed was wiped out in the aftermath of a volcanic eruption at Laki. The first breed society for the Icelandic horse was created in Iceland in 1904, and today the breed is represented by organizations in 19 different nations, organized under a parent association, the International Federation of Icelandic Horse Associations.
# """
target_text = """
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 parallelizable 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 other tasks by applying it successfully to English constituency parsing both with large and limited training data.
"""


def get_text():
    return target_text