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import os | |
import shutil | |
import tempfile | |
import unittest | |
from fairseq import options | |
from fairseq.dataclass.utils import convert_namespace_to_omegaconf | |
from fairseq.data.data_utils import raise_if_valid_subsets_unintentionally_ignored | |
from .utils import create_dummy_data, preprocess_lm_data, train_language_model | |
def make_lm_config( | |
data_dir=None, | |
extra_flags=None, | |
task="language_modeling", | |
arch="transformer_lm_gpt2_tiny", | |
): | |
task_args = [task] | |
if data_dir is not None: | |
task_args += [data_dir] | |
train_parser = options.get_training_parser() | |
train_args = options.parse_args_and_arch( | |
train_parser, | |
[ | |
"--task", | |
*task_args, | |
"--arch", | |
arch, | |
"--optimizer", | |
"adam", | |
"--lr", | |
"0.0001", | |
"--max-tokens", | |
"500", | |
"--tokens-per-sample", | |
"500", | |
"--save-dir", | |
data_dir, | |
"--max-epoch", | |
"1", | |
] | |
+ (extra_flags or []), | |
) | |
cfg = convert_namespace_to_omegaconf(train_args) | |
return cfg | |
def write_empty_file(path): | |
with open(path, "w"): | |
pass | |
assert os.path.exists(path) | |
class TestValidSubsetsErrors(unittest.TestCase): | |
"""Test various filesystem, clarg combinations and ensure that error raising happens as expected""" | |
def _test_case(self, paths, extra_flags): | |
with tempfile.TemporaryDirectory() as data_dir: | |
[ | |
write_empty_file(os.path.join(data_dir, f"{p}.bin")) | |
for p in paths + ["train"] | |
] | |
cfg = make_lm_config(data_dir, extra_flags=extra_flags) | |
raise_if_valid_subsets_unintentionally_ignored(cfg) | |
def test_default_raises(self): | |
with self.assertRaises(ValueError): | |
self._test_case(["valid", "valid1"], []) | |
with self.assertRaises(ValueError): | |
self._test_case( | |
["valid", "valid1", "valid2"], ["--valid-subset", "valid,valid1"] | |
) | |
def partially_specified_valid_subsets(self): | |
with self.assertRaises(ValueError): | |
self._test_case( | |
["valid", "valid1", "valid2"], ["--valid-subset", "valid,valid1"] | |
) | |
# Fix with ignore unused | |
self._test_case( | |
["valid", "valid1", "valid2"], | |
["--valid-subset", "valid,valid1", "--ignore-unused-valid-subsets"], | |
) | |
def test_legal_configs(self): | |
self._test_case(["valid"], []) | |
self._test_case(["valid", "valid1"], ["--ignore-unused-valid-subsets"]) | |
self._test_case(["valid", "valid1"], ["--combine-val"]) | |
self._test_case(["valid", "valid1"], ["--valid-subset", "valid,valid1"]) | |
self._test_case(["valid", "valid1"], ["--valid-subset", "valid1"]) | |
self._test_case( | |
["valid", "valid1"], ["--combine-val", "--ignore-unused-valid-subsets"] | |
) | |
self._test_case( | |
["valid1"], ["--valid-subset", "valid1"] | |
) # valid.bin doesn't need to be ignored. | |
def test_disable_validation(self): | |
self._test_case([], ["--disable-validation"]) | |
self._test_case(["valid", "valid1"], ["--disable-validation"]) | |
def test_dummy_task(self): | |
cfg = make_lm_config(task="dummy_lm") | |
raise_if_valid_subsets_unintentionally_ignored(cfg) | |
def test_masked_dummy_task(self): | |
cfg = make_lm_config(task="dummy_masked_lm") | |
raise_if_valid_subsets_unintentionally_ignored(cfg) | |
class TestCombineValidSubsets(unittest.TestCase): | |
def _train(self, extra_flags): | |
with self.assertLogs() as logs: | |
with tempfile.TemporaryDirectory("test_transformer_lm") as data_dir: | |
create_dummy_data(data_dir, num_examples=20) | |
preprocess_lm_data(data_dir) | |
shutil.copyfile(f"{data_dir}/valid.bin", f"{data_dir}/valid1.bin") | |
shutil.copyfile(f"{data_dir}/valid.idx", f"{data_dir}/valid1.idx") | |
train_language_model( | |
data_dir, | |
"transformer_lm", | |
["--max-update", "0", "--log-format", "json"] + extra_flags, | |
run_validation=False, | |
) | |
return [x.message for x in logs.records] | |
def test_combined(self): | |
flags = ["--combine-valid-subsets"] | |
logs = self._train(flags) | |
assert any(["valid1" in x for x in logs]) # loaded 100 examples from valid1 | |
assert not any(["valid1_ppl" in x for x in logs]) # metrics are combined | |
def test_subsets(self): | |
flags = ["--valid-subset", "valid,valid1"] | |
logs = self._train(flags) | |
assert any(["valid_ppl" in x for x in logs]) # loaded 100 examples from valid1 | |
assert any(["valid1_ppl" in x for x in logs]) # metrics are combined | |