def test_config_to_json_string(self):
config = BertConfig(vocab_size_or_config_json_file=99, hidden_size=37)
obj = json.loads(config.to_json_string())
self.assertEqual(obj["vocab_size"], 99)
self.assertEqual(obj["hidden_size"], 37)
print(cosine_similarity([hidden['B00VAV2JH0'], hidden['B01EH4SV7S']]))
print(np.array(hidden['6301977467']) - np.array(hidden['B00JAQJMJ0']))
exit()
config = BertConfig(vocab_size_or_config_json_file=3573,
hidden_size=512,
num_hidden_layers=8,
num_attention_heads=8,
intermediate_size=1024,
hidden_act="gelu",
hidden_dropout_prob=0.1,
attention_probs_dropout_prob=0.1,
max_position_embeddings=128)
with open('bert_config.json', 'w') as f:
f.write(config.to_json_string())
exit()
time_interva = [-200, -110, 0, 23, 25, 54, 67, 90, 102, 104, 108, 190, 200]
time_interval = [
time_interva[i] - time_interva[i - 1] for i in range(1, len(time_interva))
]
time_interval.insert(0, 0)
print(time_interval)
split_idx = [0, len(time_interval)]
has_max_length = True
split_idx.sort()
i = 0
max_length = 4
min_length = 2
