File size: 4,731 Bytes
d596074 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 |
#!/usr/bin/env python3
# Copyright 2021 Xiaomi Corp. (authors: Fangjun Kuang)
#
# See ../../LICENSE for clarification regarding multiple authors
#
# 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.
import re
import k2
import pytest
import torch
from icefall.graph_compiler import CtcTrainingGraphCompiler
from icefall.lexicon import Lexicon
from icefall.utils import get_texts
@pytest.fixture
def lexicon():
"""
We use the following test data:
lexicon.txt
foo f o o
bar b a r
baz b a z
<UNK> SPN
phones.txt
<eps> 0
a 1
b 2
f 3
o 4
r 5
z 6
SPN 7
words.txt:
<eps> 0
foo 1
bar 2
baz 3
<UNK> 4
"""
L = k2.Fsa.from_str(
"""
0 0 7 4 0
0 7 -1 -1 0
0 1 3 1 0
0 3 2 2 0
0 5 2 3 0
1 2 4 0 0
2 0 4 0 0
3 4 1 0 0
4 0 5 0 0
5 6 1 0 0
6 0 6 0 0
7
""",
num_aux_labels=1,
)
L.labels_sym = k2.SymbolTable.from_str(
"""
a 1
b 2
f 3
o 4
r 5
z 6
SPN 7
"""
)
L.aux_labels_sym = k2.SymbolTable.from_str(
"""
foo 1
bar 2
baz 3
<UNK> 4
"""
)
ans = Lexicon.__new__(Lexicon)
ans.token_table = L.labels_sym
ans.word_table = L.aux_labels_sym
ans.L_inv = k2.arc_sort(L.invert_())
ans.disambig_pattern = re.compile(r"^#\d+$")
return ans
@pytest.fixture
def compiler(lexicon):
return CtcTrainingGraphCompiler(lexicon, device=torch.device("cpu"))
class TestCtcTrainingGraphCompiler(object):
@staticmethod
def test_convert_transcript_to_fsa(compiler, lexicon):
texts = ["bar foo", "baz ok"]
fsa = compiler.convert_transcript_to_fsa(texts)
labels0 = fsa[0].labels[:-1].tolist()
aux_labels0 = fsa[0].aux_labels[:-1]
aux_labels0 = aux_labels0[aux_labels0 != 0].tolist()
labels1 = fsa[1].labels[:-1].tolist()
aux_labels1 = fsa[1].aux_labels[:-1]
aux_labels1 = aux_labels1[aux_labels1 != 0].tolist()
labels0 = [lexicon.token_table[i] for i in labels0]
labels1 = [lexicon.token_table[i] for i in labels1]
aux_labels0 = [lexicon.word_table[i] for i in aux_labels0]
aux_labels1 = [lexicon.word_table[i] for i in aux_labels1]
assert labels0 == ["b", "a", "r", "f", "o", "o"]
assert aux_labels0 == ["bar", "foo"]
assert labels1 == ["b", "a", "z", "SPN"]
assert aux_labels1 == ["baz", "<UNK>"]
@staticmethod
def test_compile(compiler, lexicon):
texts = ["bar foo", "baz ok"]
decoding_graph = compiler.compile(texts)
input1 = ["b", "b", "<blk>", "<blk>", "a", "a", "r", "<blk>", "<blk>"]
input1 += ["f", "f", "<blk>", "<blk>", "o", "o", "<blk>", "o", "o"]
input2 = ["b", "b", "a", "a", "a", "<blk>", "<blk>", "z", "z"]
input2 += ["<blk>", "<blk>", "SPN", "SPN", "<blk>", "<blk>"]
lexicon.token_table._id2sym[0] == "<blk>"
lexicon.token_table._sym2id["<blk>"] = 0
input1 = [lexicon.token_table[i] for i in input1]
input2 = [lexicon.token_table[i] for i in input2]
fsa1 = k2.linear_fsa(input1)
fsa2 = k2.linear_fsa(input2)
fsas = k2.Fsa.from_fsas([fsa1, fsa2])
decoding_graph = k2.arc_sort(decoding_graph)
lattice = k2.intersect(decoding_graph, fsas, treat_epsilons_specially=False)
lattice = k2.connect(lattice)
aux_labels0 = lattice[0].aux_labels[:-1]
aux_labels0 = aux_labels0[aux_labels0 != 0].tolist()
aux_labels0 = [lexicon.word_table[i] for i in aux_labels0]
assert aux_labels0 == ["bar", "foo"]
aux_labels1 = lattice[1].aux_labels[:-1]
aux_labels1 = aux_labels1[aux_labels1 != 0].tolist()
aux_labels1 = [lexicon.word_table[i] for i in aux_labels1]
assert aux_labels1 == ["baz", "<UNK>"]
texts = get_texts(lattice)
texts = [[lexicon.word_table[i] for i in words] for words in texts]
assert texts == [["bar", "foo"], ["baz", "<UNK>"]]
|