def test_inference_masked_lm(self):
model = TFBertForPreTraining.from_pretrained(
"lysandre/tiny-bert-random")
input_ids = tf.constant([[0, 1, 2, 3, 4, 5]])
output = model(input_ids)[0]
expected_shape = [1, 6, 32000]
self.assertEqual(output.shape, expected_shape)
print(output[:, :3, :3])
expected_slice = tf.constant([[
[-0.05243197, -0.04498899, 0.05512108],
[-0.07444685, -0.01064632, 0.04352357],
[-0.05020351, 0.05530146, 0.00700043],
]])
tf.debugging.assert_near(output[:, :3, :3], expected_slice, atol=1e-4)
def test_inference_masked_lm(self):
model = TFBertForPreTraining.from_pretrained(
"lysandre/tiny-bert-random")
input_ids = tf.constant([[0, 1, 2, 3, 4, 5]])
output = model(input_ids)[0]
expected_shape = [1, 6, 10]
self.assertEqual(output.shape, expected_shape)
print(output[:, :3, :3])
expected_slice = tf.constant([[
[0.03706957, 0.10124919, 0.03616843],
[-0.06099961, 0.02266058, 0.00601412],
[-0.06066202, 0.05684517, 0.02038802],
]])
tf.debugging.assert_near(output[:, :3, :3], expected_slice, atol=1e-4)