def test_extra():
"""Returns dict of extrapolation testing modules."""
sample_args_pure = composition.PreSampleArgs(1, 1, *_ENTROPY_EXTRAPOLATE)
add_sub_sample_args_pure = composition.PreSampleArgs(
1, 1, *_ADD_SUB_ENTROPY_EXTRAPOLATE)
train_length = arithmetic.length_range_for_entropy(_ENTROPY_TRAIN[1])[1]
def extrapolate_length():
return random.randint(
train_length + 1, train_length + _EXTRAPOLATE_EXTRA_LENGTH)
def add_sub_multiple_longer():
return add_sub_multiple(_INT, sample_args_pure, length=extrapolate_length())
def mul_div_multiple_longer():
return mul_div_multiple(_INT, sample_args_pure, length=extrapolate_length())
def mixed_longer():
return mixed(_INT, sample_args_pure, length=extrapolate_length())
return {
'add_or_sub_big': functools.partial(
add_or_sub, None, add_sub_sample_args_pure),
'mul_big': functools.partial(mul, None, sample_args_pure),
'div_big': functools.partial(div, None, sample_args_pure),
'add_sub_multiple_longer': add_sub_multiple_longer,
'mul_div_multiple_longer': mul_div_multiple_longer,
'mixed_longer': mixed_longer,
}
def _make_modules(entropy, num_modules_composed):
"""Returns modules given "difficulty" parameters."""
fns = {
'gcd': gcd,
'lcm': lcm,
'div_remainder': div_remainder,
'is_prime': is_prime,
'is_factor': is_factor,
'round_number': round_number,
'place_value': place_value,
'list_prime_factors': list_prime_factors,
}
# These modules don't have both pure and composed.
modules = {
'base_conversion': functools.partial(base_conversion, *entropy),
}
sample_args_pure = composition.PreSampleArgs(1, 1, *entropy)
sample_args_composed = composition.PreSampleArgs(num_modules_composed[0],
num_modules_composed[1],
*entropy)
for name, module in six.iteritems(fns):
modules[name] = functools.partial(module, None, sample_args_pure)
modules[name + '_composed'] = functools.partial(
module, None, sample_args_composed)
return modules
def _make_modules(entropy, add_sub_entropy):
"""Returns modules given "difficulty" parameters."""
sample_args_pure = composition.PreSampleArgs(1, 1, *entropy)
add_sub_sample_args_pure = composition.PreSampleArgs(1, 1, *add_sub_entropy)
# TODO(b/124039105): consider composed modules?
return {
# Addition and subtraction of integers (and decimals)
'add_or_sub': functools.partial(
add_or_sub, None, add_sub_sample_args_pure),
'add_sub_multiple': functools.partial(
add_sub_multiple, _INT, sample_args_pure),
'add_or_sub_in_base': functools.partial(
add_or_sub_in_base, sample_args_pure),
# Multiplication and division
'mul': functools.partial(mul, None, sample_args_pure),
'div': functools.partial(div, None, sample_args_pure),
'mul_div_multiple': functools.partial(
mul_div_multiple, _INT_OR_RATIONAL, sample_args_pure),
# All together!
'mixed': functools.partial(mixed, _INT_OR_RATIONAL, sample_args_pure),
# And some other arithmetic-related stuff.
'nearest_integer_root': functools.partial(
nearest_integer_root, sample_args_pure),
'simplify_surd': functools.partial(simplify_surd, None, sample_args_pure),
}
def _make_modules(entropy):
"""Returns modules given "difficulty" parameters."""
sample_args_pure = composition.PreSampleArgs(1, 1, *entropy)
sample_args_composed = composition.PreSampleArgs(2, 4, *entropy)
sample_args_mixed = composition.PreSampleArgs(1, 4, *entropy)
return {
'coefficient_named':
functools.partial(coefficient_named, None, sample_args_pure),
'evaluate':
functools.partial(evaluate, None, sample_args_pure),
'evaluate_composed':
functools.partial(evaluate, None, sample_args_composed),
# TODO(b/124038948): consider doing pure sample args for 'add'?
'add':
functools.partial(add, None, sample_args_mixed),
'expand':
functools.partial(expand, None, sample_args_pure),
'collect':
functools.partial(collect, None, sample_args_pure),
'compose':
functools.partial(compose, None, sample_args_mixed),
# Rearranging powers:
'simplify_power':
functools.partial(simplify_power, None, sample_args_pure),
}
def _make_modules(entropy):
"""Returns modules given "difficulty" parameters."""
sample_args_pure = composition.PreSampleArgs(1, 1, *entropy)
sample_args_composed = composition.PreSampleArgs(2, 4, *entropy)
return {
'differentiate_composed':
functools.partial(differentiate_univariate, None,
sample_args_composed),
'differentiate':
functools.partial(differentiate, None, sample_args_pure),
}
def test_extra():
"""Returns dict of extrapolation testing modules."""
sample_args_pure = composition.PreSampleArgs(1, 1, *_ENTROPY_EXTRAPOLATE)
def sort_count():
lower = _sort_count_range(_ENTROPY_TRAIN[1])[1]
return random.randint(lower + 1, lower + _EXTRAPOLATION_EXTRA_COUNT)
def closest_count():
lower = _closest_count_range(_ENTROPY_TRAIN[1])[1]
return random.randint(lower + 1, lower + _EXTRAPOLATION_EXTRA_COUNT)
def kth_biggest_more():
return kth_biggest(sample_args_pure, count=sort_count())
def sort_more():
return sort(sample_args_pure, count=sort_count())
def closest_more():
return closest(sample_args_pure, count=closest_count())
return {
'kth_biggest_more': kth_biggest_more,
'sort_more': sort_more,
'closest_more': closest_more,
}
def test_extra():
"""Returns dict of extrapolation testing modules."""
sample_args_pure = composition.PreSampleArgs(1, 1, *_ENTROPY_EXTRAPOLATE)
return {
'round_number_big': functools.partial(round_number, None,
sample_args_pure),
'place_value_big': functools.partial(place_value, None,
sample_args_pure),
}
def _make_modules(entropy):
"""Returns modules given "difficulty" parameters."""
sample_args_pure = composition.PreSampleArgs(1, 1, *entropy)
sample_args_composed = composition.PreSampleArgs(2, 4, *entropy)
return {
'pair':
functools.partial(pair, sample_args_pure),
'pair_composed':
functools.partial(pair, sample_args_composed),
'kth_biggest':
functools.partial(kth_biggest, sample_args_pure),
'kth_biggest_composed':
functools.partial(kth_biggest, sample_args_composed),
'closest':
functools.partial(closest, sample_args_pure),
'closest_composed':
functools.partial(closest, sample_args_composed),
'sort':
functools.partial(sort, sample_args_pure),
'sort_composed':
functools.partial(sort, sample_args_composed),
}