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decoder_helpers_test.py
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# Copyright 2019 The Texar Authors. 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.
"""
Unit tests for Transformer decoder.
"""
import unittest
import torch
from texar.torch.modules.decoders.decoder_helpers import (
GreedyEmbeddingHelper, TopKSampleEmbeddingHelper, TopPSampleEmbeddingHelper)
class SamplerTest(unittest.TestCase):
r"""Tests decoder helper utilities.
"""
def setUp(self):
self.logits = torch.Tensor([[0.2, 0.2, 0.55, 0.05]])
# softmax values for above tensor is
# tensor([[0.2337, 0.2337, 0.3316, 0.2011]])
self.start_token = torch.LongTensor([1])
self.end_token = 2
def test_greedy_sampler(self):
"""Tests Greedy Sampler."""
sampler = GreedyEmbeddingHelper(start_tokens=self.start_token,
end_token=self.end_token)
index = sampler.sample(time=0, outputs=self.logits)
assert torch.equal(index, torch.argmax(self.logits, dim=1))
def test_top_k_sampler(self):
"""Tests Top-K Sampler."""
sampler = TopKSampleEmbeddingHelper(start_tokens=self.start_token,
end_token=self.end_token, top_k=1)
index = sampler.sample(time=0, outputs=self.logits)
assert torch.equal(index, torch.argmax(self.logits, dim=1))
def test_top_p_sampler(self):
"""Tests Top-P Sampler also known as Nucleus Sampler."""
sampler = TopPSampleEmbeddingHelper(start_tokens=self.start_token,
end_token=self.end_token, p=0.6)
index = sampler.sample(time=0, outputs=self.logits)
assert index.item() in [0, 1, 2]
if __name__ == "__main__":
unittest.main()