def __init__(self, name, layer, width):
self.name = check.check_not_empty(name)
self.layer = layer
if layer is not None:
check.check_gte(layer, 0)
self.width = check.check_gte(width, 1)
def __init__(self, stream_fn, size=None, order_of_magnitude=None):
self.stream_fn = check.check_function(stream_fn)
which = check.check_exclusive({
"size": size,
"order_of_magnitude": order_of_magnitude
})
if which == "size":
self.size = check.check_gte(size, 1)
self.order_of_magnitude = util.order_of_magnitude(size)
elif which == "order_of_magnitude":
self.size = None
self.order_of_magnitude = check.check_gte(order_of_magnitude, 0)
else:
self.size = None
self.order_of_magnitude = None
def _within(self, candidate, target, operator, tolerance):
check.check_lte(check.check_gte(tolerance, 0), 1)
for i in range(len(candidate)):
if operator[i] is None or operator[i] == "eq":
if not (abs(candidate[i] - target[i]) < tolerance):
return False
elif operator[i] == "lt":
if not (candidate[i] < (target[i] + tolerance)):
return False
elif operator[i] == "gt":
if not (candidate[i] > (target[i] - tolerance)):
return False
else:
raise ValueError("unknown operator: %s" % operator[i])
return True
def __init__(self, model_dir, step, version_key):
self.model_dir = check.check_instance(model_dir, str)
self.step = check.check_gte(check.check_instance(step, int), 0)
self.version_key = check.check_instance(version_key, str)
def __init__(self, threshold, exclude_numbers):
self.threshold = check.check_gte(threshold, 1)
self.exclude_numbers = check.check_one_of(exclude_numbers, [True, False])
self.word_counts = {}
def __init__(self, words, elides, count):
assert len(elides) == len(words) + 1
self.words = words
self.elides = elides
self.count = check.check_gte(count, 1)
def with_window_size(self, value):
return self._copy("window_size", check.check_gte(value, 1))
def with_maximum_decays(self, value):
return self._copy("maximum_decays", check.check_gte(value, 1))
def epochs(self, value=None):
if value is None:
return self._epochs
self._epochs = check.check_gte(value, 1)
return self
def with_dropout_rate(self, value=None):
return self._copy("dropout_rate", check.check_gte(value, 0))
def with_epoch_size(self, value):
return self._copy("epoch_size", check.check_gte(value, 1))
def auto_sentence_bleu(expected, actual):
check.check_gte(len(expected), 1)
ngrams = min(min(len(expected), len(actual)), 4)
weight = 1.0 / ngrams
return sentence_bleu([expected], actual, weights=tuple([weight] * ngrams))
def window(self, value=None):
if value is None:
return self._window
self._window = check.check_gte(value, 1)
return self
def absolute(self, value=None):
if value is None:
return self._absolute
self._absolute = check.check_gte(value, 0.0)
return self
def learning_rate(self, value=None):
if value is None:
return self._learning_rate
self._learning_rate = check.check_gte(value, 0)
return self
def dropout_rate(self, value=None):
if value is None:
return self._dropout_rate
self._dropout_rate = check.check_gte(value, 0)
return self
def with_learning_rate(self, value=None):
return self._copy("learning_rate", check.check_gte(value, 0))
def batch(self, value=None):
if value is None:
return self._batch
self._batch = check.check_gte(value, 1)
return self
