def test_field_finalize():
vocab = MockVocab()
f = Field(name="F", numericalizer=vocab)
assert not vocab.is_finalized
f.finalize()
assert vocab.is_finalized
with pytest.raises(Exception):
f.finalize()
def test_missing_symbol_index_custom_numericalize():
fld = Field(
name="test_field",
keep_raw=True,
tokenizer=None,
numericalizer=int,
allow_missing_data=True,
)
fld.finalize()
assert fld.get_default_value() == -1
def test_field_custom_numericalization_no_tokenization():
tfield = Field("bla", numericalizer=lambda x: x, tokenizer=None)
_, data1 = tfield.preprocess([1, 2, 3])[0]
_, data2 = tfield.preprocess([3, 2, 1])[0]
_, data3 = tfield.preprocess([3, 4, 5, 6])[0]
_, data4 = tfield.preprocess([2, 3, 6])[0]
tfield.finalize()
assert np.all(tfield.numericalize(data1) == np.array([1, 2, 3]))
assert np.all(tfield.numericalize(data2) == np.array([3, 2, 1]))
assert np.all(tfield.numericalize(data3) == np.array([3, 4, 5, 6]))
assert np.all(tfield.numericalize(data4) == np.array([2, 3, 6]))
def test_field_custom_numericalization_vocab_non_string():
vocab = Vocab(specials=())
tfield = Field("bla", numericalizer=vocab, tokenizer=None)
_, data1 = tfield.preprocess([1, 2, 3])[0]
_, data2 = tfield.preprocess([3, 2, 1])[0]
_, data3 = tfield.preprocess([3, 4, 5, 6])[0]
_, data4 = tfield.preprocess([2, 3, 6])[0]
tfield.finalize()
assert np.all(tfield.numericalize(data1) == vocab.numericalize([1, 2, 3]))
assert np.all(tfield.numericalize(data2) == vocab.numericalize([3, 2, 1]))
assert np.all(tfield.numericalize(data3) == vocab.numericalize([3, 4, 5, 6]))
assert np.all(tfield.numericalize(data4) == vocab.numericalize([2, 3, 6]))
def test_field_custom_numericalization_no_tokenization_2():
label_indexer = {"one": 1, "two": 2, "three": 3, "four": 4}
tfield = Field("bla", numericalizer=label_indexer.get, tokenizer=None)
_, data1 = tfield.preprocess(["one", "two", "three"])[0]
_, data2 = tfield.preprocess(["three", "two", "one"])[0]
_, data3 = tfield.preprocess(["three", "four", "four", "two"])[0]
_, data4 = tfield.preprocess(["two", "three", "one"])[0]
tfield.finalize()
assert np.all(tfield.numericalize(data1) == np.array([1, 2, 3]))
assert np.all(tfield.numericalize(data2) == np.array([3, 2, 1]))
assert np.all(tfield.numericalize(data3) == np.array([3, 4, 4, 2]))
assert np.all(tfield.numericalize(data4) == np.array([2, 3, 1]))
def test_missing_symbol_index_vocab():
vocab = Vocab()
fld = Field(
name="test_field",
tokenizer="split",
keep_raw=False,
numericalizer=vocab,
allow_missing_data=True,
)
fld.preprocess("a b c d")
((_, data),) = fld.preprocess(None)
assert data == (None, None)
fld.finalize()
assert fld.numericalize((None, None)) is None
assert fld.get_default_value() == -1
def test_missing_values_default_sequential():
fld = Field(
name="bla",
keep_raw=False,
tokenizer="split",
numericalizer=hash,
allow_missing_data=True,
)
_, data_missing = fld.preprocess(None)[0]
_, data_exists = fld.preprocess("data_string")[0]
assert data_missing == (None, None)
assert data_exists == (None, ["data_string"])
fld.finalize()
assert fld.numericalize(data_missing) is None
assert np.all(fld.numericalize(data_exists) == np.array([hash("data_string")]))
def test_missing_values_custom_numericalize():
fld = Field(
name="test_field",
keep_raw=True,
tokenizer=None,
numericalizer=int,
allow_missing_data=True,
)
_, data_missing = fld.preprocess(None)[0]
_, data_exists = fld.preprocess("404")[0]
assert data_missing == (None, None)
assert data_exists == ("404", "404")
fld.finalize()
assert fld.numericalize(data_missing) is None
assert np.all(fld.numericalize(data_exists) == np.array([404]))
def test_field_vocab_no_tokenization():
vocab = Vocab(eager=True)
pretokenized_input1 = ["word", "words", "uttering"]
pretokenized_input2 = ["word", "words"]
pretokenized_input3 = ["word"]
pretokenized_input4 = ["word", "uttering"]
tokenized_field = Field("test_field", tokenizer=None, numericalizer=vocab)
_, data1 = tokenized_field.preprocess(pretokenized_input1)[0]
_, data2 = tokenized_field.preprocess(pretokenized_input2)[0]
_, data3 = tokenized_field.preprocess(pretokenized_input3)[0]
_, data4 = tokenized_field.preprocess(pretokenized_input4)[0]
tokenized_field.finalize()
expected_numericalization_1 = np.array([2, 3, 4])
_, tok1 = data1
assert np.all(vocab.numericalize(tok1) == expected_numericalization_1)
assert np.all(tokenized_field.numericalize(data1) == expected_numericalization_1)
expected_numericalization_2 = np.array([2, 3])
_, tok2 = data2
assert np.all(vocab.numericalize(tok2) == expected_numericalization_2)
assert np.all(tokenized_field.numericalize(data2) == expected_numericalization_2)
expected_numericalization_3 = np.array([2])
_, tok3 = data3
assert np.all(vocab.numericalize(tok3) == expected_numericalization_3)
assert np.all(tokenized_field.numericalize(data3) == expected_numericalization_3)
expected_numericalization_4 = np.array([2, 4])
_, tok4 = data4
assert np.all(vocab.numericalize(tok4) == expected_numericalization_4)
assert np.all(tokenized_field.numericalize(data4) == expected_numericalization_4)
