Spaces:
Runtime error
Runtime error
File size: 4,428 Bytes
a1d409e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 |
# coding=utf-8
# Copyright 2020 The HuggingFace Team Inc.
#
# 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 clone 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.
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class ConstraintTest(unittest.TestCase):
def test_input_types(self):
# For consistency across different places the DisjunctiveConstraint is called,
# dc.token_ids is a list of integers. It is also initialized only by integers.
cset = [[1, 2, 4], [1, 2, 3, 4]]
dc = DisjunctiveConstraint(cset)
self.assertTrue(isinstance(dc.token_ids, list))
with self.assertRaises(ValueError):
DisjunctiveConstraint(torch.LongTensor([[1, 2, 4], [1, 2, 3]]))
with self.assertRaises(ValueError):
DisjunctiveConstraint([torch.LongTensor([1, 2, 4]), torch.LongTensor([1, 2, 3, 4, 5])])
def test_check_illegal_input(self):
# We can't have constraints that are complete subsets of another. This leads to a preverse
# interpretation of "constraint fulfillment": does generating [1,2,3] fulfill the constraint?
# It would mean that it generated [1,2] which fulfills it, but it's in the middle of potentially
# fulfilling [1,2,3,4]. If we believe that [1,2,3] does fulfill the constraint, then the algorithm
# will necessarily never reach [1,2,3,4], giving users a false sense of control (better to just not allow it).
cset = [[1, 2], [1, 2, 3, 4]]
with self.assertRaises(ValueError):
DisjunctiveConstraint(cset) # fails here
def test_example_progression(self):
cset = [[1, 2, 3], [1, 2, 4]]
dc = DisjunctiveConstraint(cset)
stepped, completed, reset = dc.update(1)
desired = stepped is True and completed is False and reset is False
self.assertTrue(desired)
self.assertTrue(not dc.completed)
self.assertTrue(dc.current_seq == [1])
stepped, completed, reset = dc.update(2)
desired = stepped is True and completed is False and reset is False
self.assertTrue(desired)
self.assertTrue(not dc.completed)
self.assertTrue(dc.current_seq == [1, 2])
stepped, completed, reset = dc.update(3)
desired = stepped is True and completed is True and reset is False
self.assertTrue(desired)
self.assertTrue(dc.completed) # Completed!
self.assertTrue(dc.current_seq == [1, 2, 3])
def test_example_progression_unequal_three_mid_and_reset(self):
cset = [[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]
dc = DisjunctiveConstraint(cset)
stepped, completed, reset = dc.update(1)
self.assertTrue(not dc.completed)
self.assertTrue(dc.current_seq == [1])
stepped, completed, reset = dc.update(2)
self.assertTrue(not dc.completed)
self.assertTrue(dc.current_seq == [1, 2])
stepped, completed, reset = dc.update(4)
self.assertTrue(not dc.completed)
self.assertTrue(dc.current_seq == [1, 2, 4])
stepped, completed, reset = dc.update(5)
self.assertTrue(dc.completed) # Completed!
self.assertTrue(dc.current_seq == [1, 2, 4, 5])
dc.reset()
stepped, completed, reset = dc.update(1)
self.assertTrue(not dc.completed)
self.assertTrue(dc.remaining() == 3)
self.assertTrue(dc.current_seq == [1])
stepped, completed, reset = dc.update(2)
self.assertTrue(not dc.completed)
self.assertTrue(dc.remaining() == 2)
self.assertTrue(dc.current_seq == [1, 2])
stepped, completed, reset = dc.update(5)
self.assertTrue(dc.completed) # Completed!
self.assertTrue(dc.remaining() == 0)
self.assertTrue(dc.current_seq == [1, 2, 5])
|