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import unittest
from onmt.translate.translation_server import ServerModel, TranslationServer
import os
from textwrap import dedent
import torch
from onmt.translate.translator import Translator
TEST_DIR = os.path.dirname(os.path.abspath(__file__))
class TestServerModel(unittest.TestCase):
def test_deferred_loading_model_and_unload(self):
model_id = 0
opt = {"models": ["test_model.pt"]}
model_root = TEST_DIR
sm = ServerModel(opt, model_id, model_root=model_root, load=False)
self.assertFalse(sm.loaded)
sm.load()
self.assertTrue(sm.loaded)
self.assertIsInstance(sm.translator, Translator)
sm.unload()
self.assertFalse(sm.loaded)
def test_load_model_on_init_and_unload(self):
model_id = 0
opt = {"models": ["test_model.pt"]}
model_root = TEST_DIR
sm = ServerModel(opt, model_id, model_root=model_root, load=True)
self.assertTrue(sm.loaded)
self.assertIsInstance(sm.translator, Translator)
sm.unload()
self.assertFalse(sm.loaded)
def test_tokenizing_with_no_tokenizer_fails(self):
model_id = 0
opt = {"models": ["test_model.pt"]}
model_root = TEST_DIR
sm = ServerModel(opt, model_id, model_root=model_root, load=True)
with self.assertRaises(ValueError):
sm.tokenize("hello world")
def test_detokenizing_with_no_tokenizer_fails(self):
model_id = 0
opt = {"models": ["test_model.pt"]}
model_root = TEST_DIR
sm = ServerModel(opt, model_id, model_root=model_root, load=True)
with self.assertRaises(ValueError):
sm.detokenize("hello world")
def test_source_features(self):
model_id = 0
opt = {"models": ["test_model.pt"]}
model_root = TEST_DIR
sm = ServerModel(
opt,
model_id,
model_root=model_root,
load=True,
features_opt={
"n_src_feats": 1,
"src_feats_defaults": "0",
"reversible_tokenization": "joiner",
},
)
feats = sm.maybe_transform_feats("hello world.", "hello world ■.", ["0 1"])
self.assertEqual(feats, ["0 1 1"])
preprocessed = sm.maybe_preprocess({"src": "hello│0 world│1"})
self.assertEqual(preprocessed["seg"], ["hello world"])
self.assertEqual(preprocessed["src_feats"], [["0 1"]])
def test_passing_source_features_without_proper_configuration(self):
model_id = 0
opt = {"models": ["test_model.pt"]}
model_root = TEST_DIR
sm = ServerModel(opt, model_id, model_root=model_root, load=True)
with self.assertRaises(AssertionError):
sm.maybe_preprocess({"src": "hello│0 world│1"})
sm = ServerModel(
opt,
model_id,
model_root=model_root,
load=True,
features_opt={
"n_src_feats": 2,
"src_feats_defaults": "0│0",
"reversible_tokenization": "joiner",
},
)
with self.assertRaises(AssertionError):
sm.maybe_preprocess({"src": "hello│0 world│1"})
if torch.cuda.is_available():
def test_moving_to_gpu_and_back(self):
torch.cuda.set_device(torch.device("cuda", 0))
model_id = 0
opt = {"models": ["test_model.pt"]}
model_root = TEST_DIR
sm = ServerModel(opt, model_id, model_root=model_root, load=True)
for p in sm.translator.model.parameters():
self.assertEqual(p.device.type, "cpu")
sm.to_gpu()
for p in sm.translator.model.parameters():
self.assertEqual(p.device.type, "cuda")
self.assertEqual(p.device.index, 0)
sm.to_cpu()
for p in sm.translator.model.parameters():
self.assertEqual(p.device.type, "cpu")
def test_initialize_on_gpu_and_move_back(self):
torch.cuda.set_device(torch.device("cuda", 0))
model_id = 0
opt = {"models": ["test_model.pt"], "gpu": 0}
model_root = TEST_DIR
sm = ServerModel(opt, model_id, model_root=model_root, load=True)
for p in sm.translator.model.parameters():
self.assertEqual(p.device.type, "cuda")
self.assertEqual(p.device.index, 0)
sm.to_gpu()
for p in sm.translator.model.parameters():
self.assertEqual(p.device.type, "cuda")
self.assertEqual(p.device.index, 0)
sm.to_cpu()
for p in sm.translator.model.parameters():
self.assertEqual(p.device.type, "cpu")
if torch.cuda.device_count() > 1:
def test_initialize_on_nonzero_gpu_and_back(self):
torch.cuda.set_device(torch.device("cuda", 1))
model_id = 0
opt = {"models": ["test_model.pt"], "gpu": 1}
model_root = TEST_DIR
sm = ServerModel(opt, model_id, model_root=model_root, load=True)
for p in sm.translator.model.parameters():
self.assertEqual(p.device.type, "cuda")
self.assertEqual(p.device.index, 1)
sm.to_gpu()
for p in sm.translator.model.parameters():
self.assertEqual(p.device.type, "cuda")
self.assertEqual(p.device.index, 1)
sm.to_cpu()
for p in sm.translator.model.parameters():
self.assertEqual(p.device.type, "cpu")
def test_run(self):
model_id = 0
opt = {"models": ["test_model.pt"]}
model_root = TEST_DIR
sm = ServerModel(opt, model_id, model_root=model_root, load=True)
inp = [{"src": "hello how are you today"}, {"src": "good morning to you ."}]
results, scores, n_best, time, aligns, align_scores = sm.run(inp)
self.assertIsInstance(results, list)
for sentence_string in results:
self.assertIsInstance(sentence_string, str)
self.assertIsInstance(scores, list)
for elem in scores:
self.assertIsInstance(elem, float)
self.assertIsInstance(aligns, list)
for align_list in aligns:
for align_string in align_list:
if align_string is not None:
self.assertIsInstance(align_string, str)
for align_scores_list in align_scores:
for score_string in align_scores_list:
if score_string is not None:
self.assertIsInstance(align_string, str)
self.assertEqual(len(results), len(scores))
self.assertEqual(len(scores), len(inp) * n_best)
self.assertEqual(len(time), 1)
self.assertIsInstance(time, dict)
self.assertIn("translation", time)
class TestTranslationServer(unittest.TestCase):
# this could be considered an integration test because it touches
# the filesystem for the config file (and the models)
CFG_F = os.path.join(TEST_DIR, "test_translation_server_config_file.json")
def tearDown(self):
if os.path.exists(self.CFG_F):
os.remove(self.CFG_F)
def write(self, cfg):
with open(self.CFG_F, "w") as f:
f.write(cfg)
CFG_NO_LOAD = dedent(
"""\
{
"models_root": "%s",
"models": [
{
"id": 100,
"model": "test_model.pt",
"timeout": -1,
"on_timeout": "to_cpu",
"load": false,
"opt": {
"beam_size": 5
}
}
]
}
"""
% TEST_DIR
)
def test_start_without_initial_loading(self):
self.write(self.CFG_NO_LOAD)
sv = TranslationServer()
sv.start(self.CFG_F)
self.assertFalse(sv.models[100].loaded)
self.assertEqual(set(sv.models.keys()), {100})
CFG_LOAD = dedent(
"""\
{
"models_root": "%s",
"models": [
{
"id": 100,
"model": "test_model.pt",
"timeout": -1,
"on_timeout": "to_cpu",
"load": true,
"opt": {
"beam_size": 5
}
}
]
}
"""
% TEST_DIR
)
def test_start_with_initial_loading(self):
self.write(self.CFG_LOAD)
sv = TranslationServer()
sv.start(self.CFG_F)
self.assertTrue(sv.models[100].loaded)
self.assertEqual(set(sv.models.keys()), {100})
CFG_2_MODELS = dedent(
"""\
{
"models_root": "%s",
"models": [
{
"id": 100,
"model": "test_model.pt",
"timeout": -1,
"on_timeout": "to_cpu",
"load": true,
"opt": {
"beam_size": 5
}
},
{
"id": 1000,
"model": "test_model2.pt",
"timeout": -1,
"on_timeout": "to_cpu",
"load": false,
"opt": {
"beam_size": 5
}
}
]
}
"""
% TEST_DIR
)
def test_start_with_two_models(self):
self.write(self.CFG_2_MODELS)
sv = TranslationServer()
sv.start(self.CFG_F)
self.assertTrue(sv.models[100].loaded)
self.assertFalse(sv.models[1000].loaded)
self.assertEqual(set(sv.models.keys()), {100, 1000})
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