|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| """Tests for processors.py."""
|
|
|
| from absl.testing import absltest
|
| import chex
|
| from clrs._src import processors
|
| import haiku as hk
|
| import jax.numpy as jnp
|
|
|
|
|
| class MemnetTest(absltest.TestCase):
|
|
|
| def test_simple_run_and_check_shapes(self):
|
|
|
| batch_size = 64
|
| vocab_size = 177
|
| embedding_size = 64
|
| sentence_size = 11
|
| memory_size = 320
|
| linear_output_size = 128
|
| num_hops = 2
|
| use_ln = True
|
|
|
| def forward_fn(queries, stories):
|
| model = processors.MemNetFull(
|
| vocab_size=vocab_size,
|
| embedding_size=embedding_size,
|
| sentence_size=sentence_size,
|
| memory_size=memory_size,
|
| linear_output_size=linear_output_size,
|
| num_hops=num_hops,
|
| use_ln=use_ln)
|
| return model._apply(queries, stories)
|
|
|
| forward = hk.transform(forward_fn)
|
|
|
| queries = jnp.ones([batch_size, sentence_size], dtype=jnp.int32)
|
| stories = jnp.ones([batch_size, memory_size, sentence_size],
|
| dtype=jnp.int32)
|
|
|
| key = hk.PRNGSequence(42)
|
| params = forward.init(next(key), queries, stories)
|
|
|
| model_output = forward.apply(params, None, queries, stories)
|
| chex.assert_shape(model_output, [batch_size, vocab_size])
|
| chex.assert_type(model_output, jnp.float32)
|
|
|
|
|
| if __name__ == '__main__':
|
| absltest.main()
|
|
|