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# Copyright 2021 DeepMind Technologies Limited. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""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()
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