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Commit d451b62f authored by Maja Jablonska's avatar Maja Jablonska
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Merge branch 'single-pytorch-module' of... 

Merge branch 'single-pytorch-module' of https://gitlab.clarin-pl.eu/syntactic-tools/combo-lightning into single-pytorch-module

# Conflicts:
#	combo/nn/regularizers/__init__.py
#	combo/nn/regularizers/regularizer.py
#	combo/nn/regularizers/regularizer_applicator.py
#	combo/polish_model_training.ipynb
#	tests/fixtures/train_vocabulary/deprel_labels.txt
#	tests/fixtures/train_vocabulary/feats_labels.txt
#	tests/fixtures/train_vocabulary/lemma_characters.txt
#	tests/fixtures/train_vocabulary/non_padded_namespaces.txt
#	tests/fixtures/train_vocabulary/token_characters.txt
#	tests/fixtures/train_vocabulary/upostag_labels.txt
#	tests/fixtures/train_vocabulary/xpostag_labels.txt
parents 56fb8006 c03bc141
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combo/nn/regularizers/__init__.py
+ 1
− 1
View file @ d451b62f
from .regularizers import *
from .regularizer_applicator import *
from .regularizer import *
combo/polish_model_training.ipynb
+ 120
− 93
View file @ d451b62f
%% Cell type:code id:b28c7d8bacb08d02 tags:
``` python
# The path where the training and validation datasets are stored
TRAINING_DATA_PATH: str = '/Users/majajablonska/Documents/PDB/PDBUD_train.conllu'
VALIDATION_DATA_PATH: str = '/Users/majajablonska/Documents/PDB/PDBUD_val.conllu'
# The path where the model can be saved to
SERIALIZATION_DIR: str = "/Users/majajablonska/Documents/Workspace/combotest"
```
%% Cell type:code id:initial_id tags:
``` python
from combo.predict import COMBO
from combo.combo_model import ComboModel
from combo.data.vocabulary import Vocabulary
from combo.models.encoder import ComboEncoder, ComboStackedBidirectionalLSTM
from combo.modules.text_field_embedders import BasicTextFieldEmbedder
from combo.nn.base import Linear
from combo.modules.token_embedders import CharacterBasedWordEmbedder, TransformersWordEmbedder
from combo.modules import FeedForwardPredictor
from combo.nn.activations import ReLUActivation, TanhActivation, LinearActivation
from combo.modules.dilated_cnn import DilatedCnnEncoder
from combo.data.tokenizers import LamboTokenizer, CharacterTokenizer
from combo.data.token_indexers import PretrainedTransformerIndexer, TokenConstPaddingCharactersIndexer, TokenFeatsIndexer, SingleIdTokenIndexer, PretrainedTransformerFixedMismatchedIndexer
from combo.data.dataset_readers import UniversalDependenciesDatasetReader
from combo.training.optimizer import Adam
import torch
from combo.data.dataset_loaders import SimpleDataLoader
from combo.modules.parser import DependencyRelationModel, HeadPredictionModel
from combo.modules.lemma import LemmatizerModel
from combo.modules.morpho import MorphologicalFeatures
from combo.nn.regularizers import Regularizer
from combo.nn.regularizers.regularizers import L2Regularizer
import pytorch_lightning as pl
from combo.training.trainable_combo import TrainableCombo
from itertools import chain
```
%% Cell type:code id:d74957f422f0b05b tags:
``` python
def default_const_character_indexer(namespace = None):
if namespace:
return TokenConstPaddingCharactersIndexer(
tokenizer=CharacterTokenizer(end_tokens=["__END__"],
start_tokens=["__START__"]),
min_padding_length=32,
namespace=namespace
)
else:
return TokenConstPaddingCharactersIndexer(
tokenizer=CharacterTokenizer(end_tokens=["__END__"],
start_tokens=["__START__"]),
min_padding_length=32
)
dataset_reader = UniversalDependenciesDatasetReader(
features=["token", "char"],
lemma_indexers={
"char": default_const_character_indexer("lemma_characters")
},
targets=["deprel", "head", "upostag", "lemma", "feats", "xpostag"],
token_indexers={
"char": default_const_character_indexer(),
"feats": TokenFeatsIndexer(),
"lemma": default_const_character_indexer(),
"token": PretrainedTransformerFixedMismatchedIndexer("bert-base-cased"),
"upostag": SingleIdTokenIndexer(
feature_name="pos_",
namespace="upostag"
),
"xpostag": SingleIdTokenIndexer(
feature_name="tag_",
namespace="xpostag"
)
},
use_sem=False
)
data_loader = SimpleDataLoader.from_dataset_reader(dataset_reader,
data_path=TRAINING_DATA_PATH,
batch_size=16,
batches_per_epoch=4,
shuffle=True)
val_data_loader = SimpleDataLoader.from_dataset_reader(dataset_reader,
data_path=VALIDATION_DATA_PATH,
batch_size=16,
batches_per_epoch=4,
shuffle=True)
vocabulary = Vocabulary.from_files('/Users/majajablonska/PycharmProjects/combo-lightning/tests/fixtures/train_vocabulary', padding_token='__PAD__', oov_token='_')
vocabulary = Vocabulary.from_instances_extended(
chain(data_loader.iter_instances(), val_data_loader.iter_instances()),
non_padded_namespaces=['head_labels'],
only_include_pretrained_words=False,
oov_token='_',
padding_token='__PAD__'
)
```
%% Output
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using `tokenizers` before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
%% Cell type:code id:fa724d362fd6bd23 tags:
``` python
seq_encoder = ComboEncoder(layer_dropout_probability=0.33,
stacked_bilstm=ComboStackedBidirectionalLSTM(
hidden_size=512,
input_size=164,
layer_dropout_probability=0.33,
num_layers=2,
recurrent_dropout_probability=0.33
))
```
%% Cell type:code id:f8a10f9892005fca tags:
``` python
char_words_embedder = CharacterBasedWordEmbedder(
dilated_cnn_encoder = DilatedCnnEncoder(
input_dim=64,
kernel_size=[3, 3, 3],
padding=[1, 2, 4],
stride=[1, 1, 1],
filters=[512, 256, 64],
dilation=[1, 2, 4],
activations=[ReLUActivation(), ReLUActivation(), LinearActivation()]
),
embedding_dim=64,
vocabulary=vocabulary
)
tokenizer = LamboTokenizer()
indexer = PretrainedTransformerIndexer('bert-base-cased')
data_loader.iter_instances()
```
%% Output
Using model LAMBO-UD_English-EWT
<generator object SimpleDataLoader.iter_instances at 0x7f8c5a6f9820>
<generator object SimpleDataLoader.iter_instances at 0x7fda39aaa5f0>
%% Cell type:code id:437d12054baaffa1 tags:
%% Cell type:code id:14413692656b68ac tags:
``` python
from nn import RegularizerApplicator
vocabulary.save_to_files('/Users/majajablonska/PycharmProjects/combo-lightning/tests/fixtures/train_vocabulary')
```
%% Output
Directory /Users/majajablonska/PycharmProjects/combo-lightning/tests/fixtures/train_vocabulary is not empty
%% Cell type:code id:437d12054baaffa1 tags:
``` python
model = ComboModel(
vocabulary=vocabulary,
dependency_relation=DependencyRelationModel(
vocabulary=vocabulary,
dependency_projection_layer=Linear(
activation=TanhActivation(),
dropout_rate=0.25,
in_features=1024,
out_features=128
),
head_predictor=HeadPredictionModel(
cycle_loss_n=0,
dependency_projection_layer=Linear(
activation=TanhActivation(),
in_features=1024,
out_features=512
),
head_projection_layer=Linear(
activation=TanhActivation(),
in_features=1024,
out_features=512
)
),
head_projection_layer=Linear(
activation=TanhActivation(),
dropout_rate=0.25,
in_features=1024,
out_features=128
),
vocab_namespace="deprel_labels"
),
lemmatizer=LemmatizerModel(
vocabulary=vocabulary,
activations=[ReLUActivation(), ReLUActivation(), ReLUActivation(), LinearActivation()],
char_vocab_namespace="token_characters",
dilation=[1, 2, 4, 1],
embedding_dim=256,
filters=[256, 256, 256],
input_projection_layer=Linear(
activation=TanhActivation(),
dropout_rate=0.25,
in_features=1024,
out_features=32
),
kernel_size=[3, 3, 3, 1],
lemma_vocab_namespace="lemma_characters",
padding=[1, 2, 4, 0],
stride=[1, 1, 1, 1]
),
loss_weights={
"deprel": 0.8,
"feats": 0.2,
"head": 0.2,
"lemma": 0.05,
"semrel": 0.05,
"upostag": 0.05,
"xpostag": 0.05
},
morphological_feat=MorphologicalFeatures(
vocabulary=vocabulary,
activations=[TanhActivation(), LinearActivation()],
dropout=[0.25, 0.],
hidden_dims=[128],
input_dim=1024,
num_layers=2,
vocab_namespace="feats_labels"
),
regularizer=RegularizerApplicator([
regularizer=Regularizer([
(".*conv1d.*", L2Regularizer(1e-6)),
(".*forward.*", L2Regularizer(1e-6)),
(".*backward.*", L2Regularizer(1e-6)),
(".*char_embed.*", L2Regularizer(1e-5))
]),
seq_encoder=ComboEncoder(
layer_dropout_probability=0.33,
stacked_bilstm=ComboStackedBidirectionalLSTM(
hidden_size=512,
input_size=164,
layer_dropout_probability=0.33,
num_layers=2,
recurrent_dropout_probability=0.33
)
),
text_field_embedder=BasicTextFieldEmbedder(
token_embedders={
"char": CharacterBasedWordEmbedder(
vocabulary=vocabulary,
dilated_cnn_encoder=DilatedCnnEncoder(
activations=[ReLUActivation(), ReLUActivation(), LinearActivation()],
dilation=[1, 2, 4],
filters=[512, 256, 64],
input_dim=64,
kernel_size=[3, 3, 3],
padding=[1, 2, 4],
stride=[1, 1, 1],
),
embedding_dim=64
),
"token": TransformersWordEmbedder("allegro/herbert-base-cased", projection_dim=100)
}
),
upos_tagger=FeedForwardPredictor.from_vocab(
vocabulary=vocabulary,
activations=[TanhActivation(), LinearActivation()],
dropout=[0.25, 0.],
hidden_dims=[64],
input_dim=1024,
num_layers=2,
vocab_namespace="upostag_labels"
),
xpos_tagger=FeedForwardPredictor.from_vocab(
vocabulary=vocabulary,
activations=[TanhActivation(), LinearActivation()],
dropout=[0.25, 0.],
hidden_dims=[64],
input_dim=1024,
num_layers=2,
vocab_namespace="xpostag_labels"
),
serialization_dir=SERIALIZATION_DIR
)
```
%% Output
Some weights of the model checkpoint at allegro/herbert-base-cased were not used when initializing BertModel: ['cls.predictions.transform.dense.weight', 'cls.predictions.transform.dense.bias', 'cls.sso.sso_relationship.weight', 'cls.sso.sso_relationship.bias', 'cls.predictions.bias', 'cls.predictions.decoder.weight', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.decoder.bias']
Some weights of the model checkpoint at allegro/herbert-base-cased were not used when initializing BertModel: ['cls.predictions.transform.dense.bias', 'cls.predictions.decoder.bias', 'cls.predictions.decoder.weight', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.sso.sso_relationship.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.bias', 'cls.sso.sso_relationship.weight']
- This IS expected if you are initializing BertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing BertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
%% Cell type:code id:e131e0ec75dc6927 tags:
``` python
data_loader.index_with(vocabulary)
a = 0
for i in data_loader:
break
```
%% Cell type:code id:195c71fcf8170ff tags:
``` python
val_data_loader.index_with(vocabulary)
```
%% Cell type:code id:28167c868e2f7292 tags:
``` python
model.set_training_configuration(optimizer_type=Adam,
optimizer_kwargs={'betas': [0.9, 0.9], 'lr': 0.002},
validation_metrics=['EM'])
```
%% Cell type:code id:cefc5173154d1605 tags:
``` python
nlp = TrainableCombo(model, torch.optim.Adam,
optimizer_kwargs={'betas': [0.9, 0.9], 'lr': 0.002},
validation_metrics=['EM'])
trainer = pl.Trainer(max_epochs=1,
default_root_dir=SERIALIZATION_DIR,
gradient_clip_val=5)
```
%% Output
GPU available: False, used: False
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
/Users/majajablonska/miniconda/envs/combo/lib/python3.9/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:67: UserWarning: Starting from v1.9.0, `tensorboardX` has been removed as a dependency of the `pytorch_lightning` package, due to potential conflicts with other packages in the ML ecosystem. For this reason, `logger=True` will use `CSVLogger` as the default logger, unless the `tensorboard` or `tensorboardX` packages are found. Please `pip install lightning[extra]` or one of them to enable TensorBoard support by default
warning_cache.warn(
%% Cell type:code id:e5af131bae4b1a33 tags:
``` python
trainer.fit(model=model, train_dataloaders=data_loader, val_dataloaders=val_data_loader)
trainer.fit(model=nlp, train_dataloaders=data_loader, val_dataloaders=val_data_loader)
```
%% Output
| Name | Type | Params
----------------------------------------------------------------
0 | text_field_embedder | BasicTextFieldEmbedder | 125 M
1 | seq_encoder | ComboEncoder | 9.1 M
2 | lemmatizer | LemmatizerModel | 715 K
3 | upos_tagger | FeedForwardPredictor | 66.8 K
4 | xpos_tagger | FeedForwardPredictor | 122 K
5 | morphological_feat | MorphologicalFeatures | 153 K
6 | dependency_relation | DependencyRelationModel | 1.3 M
----------------------------------------------------------------
| Name | Type | Params
-------------------------------------
0 | model | ComboModel | 136 M
-------------------------------------
12.1 M Trainable params
124 M Non-trainable params
136 M Total params
546.115 Total estimated model params size (MB)
/Users/majajablonska/miniconda/envs/combo/lib/python3.9/site-packages/pytorch_lightning/utilities/data.py:76: UserWarning: Trying to infer the `batch_size` from an ambiguous collection. The batch size we found is 16. To avoid any miscalculations, use `self.log(..., batch_size=batch_size)`.
warning_cache.warn(
/Users/majajablonska/miniconda/envs/combo/lib/python3.9/site-packages/pytorch_lightning/loops/fit_loop.py:280: PossibleUserWarning: The number of training batches (4) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.
rank_zero_warn(
`Trainer.fit` stopped: `max_epochs=1` reached.
%% Cell type:code id:3e23413c86063183 tags:
``` python
predictor = COMBO(model, dataset_reader)
```
%% Cell type:code id:d555d7f0223a624b tags:
``` python
a = predictor("Cześć, jestem psem.")
```
%% Cell type:code id:a68cd3861e1ceb67 tags:
``` python
print("{:15} {:15} {:10} {:10} {:10}".format('TOKEN', 'LEMMA', 'UPOS', 'HEAD', 'DEPREL'))
for token in a.tokens:
print("{:15} {:15} {:10} {:10} {:10}".format(token.text, token.lemma, token.upostag, token.head, token.deprel))
```
%% Output
TOKEN LEMMA UPOS HEAD DEPREL
Cześć, ?????? NOUN 0 root
jestem ????? NOUN 1 punct
psem. ????a NOUN 1 punct
jestem ?????? NOUN 1 punct
psem. ????? NOUN 1 punct
%% Cell type:code id:d0f43f4493218b5 tags:
``` python
from modules.archival import archive
```
%% Cell type:code id:ec92aa5bb5bb3605 tags:
``` python
archive(model, '/Users/majajablonska/Documents/combo', data_loader, val_data_loader)
```
%% Output
'/Users/majajablonska/Documents/combo'
%% Cell type:code id:953bd53cccd5f890 tags:
``` python
```
......
tests/fixtures/train_vocabulary/deprel_labels.txt deleted 100644 → 0
+ 0
− 68
View file @ 56fb8006
_
punct
case
amod
root
nsubj
obl
nmod
conj
obj
advmod
cc
nmod:arg
obl:arg
mark
iobj
advmod:emph
expl:pv
acl
xcomp
det
advmod:neg
fixed
advcl
cop
acl:relcl
flat
ccomp
appos
aux:clitic
parataxis:obj
amod:flat
det:poss
aux:pass
nummod
aux
nummod:gov
nsubj:pass
nmod:flat
obl:cmpr
ccomp:obj
obl:agent
parataxis:insert
aux:cnd
nmod:poss
det:numgov
xcomp:pred
list
vocative
det:nummod
ccomp:cleft
cc:preconj
csubj
advcl:cmpr
discourse:intj
orphan
advcl:relcl
flat:foreign
aux:imp
advmod:arg
xcomp:cleft
xcomp:subj
dep
nmod:pred
discourse
csubj:pass
obl:orphan
nummod:flat
tests/fixtures/train_vocabulary/feats_labels.txt deleted 100644 → 0
+ 0
− 173
View file @ 56fb8006
_
Number=Sing
Gender=Masc
Gender=Fem
Number=Plur
Case=Gen
Animacy=Inan
Voice=Act
Case=Nom
VerbForm=Fin
Mood=Ind
AdpType=Prep
Aspect=Imp
Animacy=Hum
Degree=Pos
Gender=Neut
Case=Acc
PunctType=Peri
PunctType=Comm
Variant=Short
Case=Loc
Person=3
Aspect=Perf
Tense=Pres
Tense=Past
PronType=Prs
Case=Ins
Polarity=Pos
Person=1
Reflex=Yes
VerbForm=Part
PronType=Dem
PunctType=Dash
VerbForm=Inf
Variant=Long
Voice=Pass
Polarity=Neg
VerbForm=Vnoun
Case=Dat
PrepCase=Npr
NumForm=Digit
Tense=Fut
PunctType=Quot
Animacy=Nhum
PronType=Rel
Abbr=Yes
Person=2
PronType=Ind
PronType=Int
Number=Ptan
Poss=Yes
PunctType=Brck
Degree=Cmp
VerbType=Quasi
NumType=Card
NumForm=Word
VerbForm=Conv
PronType=Tot
PunctType=Qest
NumType=Ord
PunctType=Colo
ConjType=Comp
PrepCase=Pre
PunctSide=Fin
PunctSide=Ini
NumType=Sets
Degree=Sup
PronType=Neg
Person=0
ConjType=Pred
Mood=Imp
Number[psor]=Sing
Number[psor]=Plur
PunctType=Excl
PartType=Int
VerbType=Mod
Case=Voc
Hyph=Yes
PartType=Mod
PunctType=Semi
Foreign=Yes
NumForm=Roman
AdpType=Post
PunctType=Slsh
PunctType=Elip
Polite=Depr
ConjType=Oper
Number=None
Gender=None
Gender=None
Number=None
Case=None
Animacy=None
Voice=None
Case=None
VerbForm=None
Mood=None
AdpType=None
Aspect=None
Animacy=None
Degree=None
Gender=None
Case=None
PunctType=None
PunctType=None
Variant=None
Case=None
Person=None
Aspect=None
Tense=None
Tense=None
PronType=None
Case=None
Polarity=None
Person=None
Reflex=None
VerbForm=None
PronType=None
PunctType=None
VerbForm=None
Variant=None
Voice=None
Polarity=None
VerbForm=None
Case=None
PrepCase=None
NumForm=None
Tense=None
PunctType=None
Animacy=None
PronType=None
Abbr=None
Person=None
PronType=None
PronType=None
Number=None
Poss=None
PunctType=None
Degree=None
VerbType=None
NumType=None
NumForm=None
VerbForm=None
PronType=None
PunctType=None
NumType=None
PunctType=None
ConjType=None
PrepCase=None
PunctSide=None
PunctSide=None
NumType=None
Degree=None
PronType=None
Person=None
ConjType=None
Mood=None
Number[psor]=None
Number[psor]=None
PunctType=None
PartType=None
VerbType=None
Case=None
Hyph=None
PartType=None
PunctType=None
Foreign=None
NumForm=None
AdpType=None
PunctType=None
PunctType=None
Polite=None
ConjType=None
tests/fixtures/train_vocabulary/lemma_characters.txt deleted 100644 → 0
+ 0
− 125
View file @ 56fb8006
_
__START__
__END__
a
o
i
e
z
n
r
w
y
s
t
k
ć
d
p
c
m
l
b
u
j
.
,
ł
g
ż
ę
ó
ś
ą
h
-
f
ń
"
0
1
P
S
?
:
ź
2
K
M
A
W
B
9
)
(
R
3
J
I
5
C
E
G
T
4
–
L
N
8
D
6
!
Z
7
H
O
_
F
U
/
;
v
V
”
„
X
Ł
Ś
x
—
[
]
Ż
'
Y
q
…
’
Q
“
+
é
ö
»
«
@
ü
í
&
š
á
É
è
>
<
˝
ä
Ć
*
Ó
ţ
•
à
ñ
○
`
tests/fixtures/train_vocabulary/non_padded_namespaces.txt deleted 100644 → 0
+ 0
− 1
View file @ 56fb8006
head_labels
tests/fixtures/train_vocabulary/token_characters.txt deleted 100644 → 0
+ 0
− 138
View file @ 56fb8006
_
__START__
__END__
a
i
e
o
z
n
r
w
s
c
y
t
d
k
p
m
u
j
l
ł
b
.
g
,
ę
ą
h
ż
ó
ś
ć
-
P
f
W
ń
S
N
M
K
"
C
T
D
A
Z
J
O
0
B
1
R
I
?
:
E
2
G
ź
U
9
L
)
(
3
5
4
–
8
F
H
6
!
7
Ś
/
;
V
v
Ł
Ż
Y
”
„
X
'
%
x
—
[
]
q
Ą
’
…
Ó
Q
“
Ę
Ć
+
Ń
é
@
ö
»
«
°
*
Ź
í
ü
&
$
š
á
É
è
>
<
˝
`
ä
_
ţ
•
µ
≥
Ü
à
ñ
μ
○
§
tests/fixtures/train_vocabulary/upostag_labels.txt deleted 100644 → 0
+ 0
− 18
View file @ 56fb8006
_
NOUN
PUNCT
VERB
ADP
ADJ
PRON
PROPN
ADV
PART
CCONJ
DET
AUX
SCONJ
NUM
X
INTJ
SYM
tests/fixtures/train_vocabulary/xpostag_labels.txt deleted 100644 → 0
+ 0
− 879
View file @ 56fb8006
_
interp
part
conj
fin:sg:ter:imperf
subst:sg:gen:f
prep:loc:nwok
comp
subst:sg:nom:m1
subst:sg:gen:m3
subst:sg:nom:f
prep:loc
prep:gen
adv:pos
adv
prep:acc
subst:sg:acc:f
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subst:sg:loc:f
subst:sg:acc:m3
prep:gen:nwok
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prep:inst:nwok
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subst:pl:gen:m1
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pred
praet:sg:f:imperf
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subst:sg:acc:m1
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subst:pl:loc:m3
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ger:sg:gen:n:perf:aff
adj:pl:nom:m1:pos
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dig
adj:sg:acc:n:pos
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ger:sg:acc:n:perf:aff
ppas:sg:nom:f:perf:aff
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ppron3:sg:gen:m1:ter:akc:npraep
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fin:pl:ter:perf
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adj:pl:loc:n:pos
siebie:dat
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ppron3:sg:gen:f:ter:akc:npraep
ppas:sg:nom:m3:perf:aff
ger:sg:nom:n:perf:aff
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ger:sg:nom:n:imperf:aff
ppas:sg:nom:m1:perf:aff
subst:pl:acc:n:pt
praet:pl:f:imperf
ppron3:sg:dat:m1:ter:nakc:npraep
praet:pl:f:perf
adja
fin:sg:pri:perf
ger:sg:acc:n:imperf:aff
bedzie:pl:ter:imperf
ppron12:sg:dat:m1:pri:nakc
subst:pl:inst:m1
impt:sg:sec:perf
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ger:sg:loc:n:perf:aff
ppron3:sg:acc:m1:ter:nakc:npraep
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num:pl:nom:f:congr:ncol
subst:pl:dat:m1
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ppron3:sg:acc:f:ter:akc:npraep
subst:pl:gen:m2
adv:sup
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num:pl:gen:m3:congr
subst:sg:voc:m1
adj:sg:acc:m1:pos
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subst:sg:acc:m2
ppron12:sg:acc:m1:pri:akc
ppas:sg:nom:f:imperf:aff
interj
ppas:pl:nom:m3:perf:aff
ppron3:pl:gen:m1:ter:akc:npraep
adj:pl:inst:f:pos
impt:sg:sec:imperf
ppas:sg:nom:n:perf:aff
praet:pl:m3:imperf
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subst:pl:gen:n:col
num:pl:acc:m3:rec:ncol
siebie:gen
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ppas:pl:nom:f:perf:aff
ppron12:sg:nom:m1:pri
ppron3:sg:nom:m1:ter:akc:npraep
ger:sg:loc:n:imperf:aff
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ppas:pl:nom:m1:perf:aff
num:pl:acc:m3:congr:ncol
ger:sg:inst:n:perf:aff
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ppron12:pl:dat:m1:pri
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ppas:sg:gen:f:perf:aff
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ppron3:sg:nom:f:ter:akc:npraep
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ppron12:pl:acc:m1:pri
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num:pl:gen:m3:congr:ncol
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praet:pl:n:perf
pact:pl:gen:f:imperf:aff
subst:sg:nom:n:col
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ppas:pl:gen:m3:perf:aff
ppron3:sg:dat:f:ter:akc:npraep
ppron3:sg:acc:m3:ter:nakc:npraep
ppas:sg:acc:m3:perf:aff
num:pl:nom:m1:rec
num:pl:acc:f:rec
ppron12:pl:gen:m1:pri
ppas:pl:nom:m3:imperf:aff
subst:pl:nom:m1:pt
frag
fin:sg:sec:perf
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siebie:inst
ppas:sg:nom:m3:imperf:aff
ppas:pl:nom:n:perf:aff
ppas:sg:gen:m3:perf:aff
pact:pl:gen:m3:imperf:aff
ppron3:sg:gen:m3:ter:akc:npraep
ppron12:sg:gen:m1:pri:akc
siebie:acc
ppron3:pl:gen:f:ter:akc:npraep
praet:sg:m1:imperf:nagl
pact:sg:nom:m1:imperf:aff
ppas:sg:acc:f:perf:aff
aglt:sg:sec:imperf:nwok
ger:sg:inst:n:imperf:aff
pact:sg:gen:m3:imperf:aff
ppron3:pl:dat:m1:ter:akc:npraep
num:pl:nom:f:rec
ppas:sg:inst:f:perf:aff
subst:pl:acc:n:col
ppron12:sg:dat:m1:sec:nakc
ppas:pl:nom:f:imperf:aff
subst:pl:dat:f
num:pl:nom:f:rec:ncol
ppas:pl:acc:m3:perf:aff
subst:pl:acc:m2
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ign
ppas:sg:loc:m3:perf:aff
pact:sg:acc:m3:imperf:aff
bedzie:sg:pri:imperf
adj:sg:nom:f:com
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ppron3:pl:gen:m1:ter:akc:praep
ppas:pl:gen:n:perf:aff
subst:sg:loc:m1
ppron3:pl:nom:m1:ter:akc:npraep
num:pl:acc:n:rec:ncol
pact:sg:acc:f:imperf:aff
adj:pl:inst:m1:pos
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ppron3:pl:acc:m1:ter:akc:npraep
bedzie:pl:pri:imperf
pact:pl:nom:f:imperf:aff
ppas:pl:acc:f:perf:aff
num:pl:acc:m3:congr
num:pl:nom:m1:congr:ncol
num:pl:nom:m3:congr
winien:sg:f:imperf
ppron3:sg:inst:m1:ter:akc:praep
ppron3:sg:gen:m1:ter:akc:praep
pact:pl:acc:m3:imperf:aff
ppron3:pl:gen:m3:ter:akc:npraep
ppron12:sg:dat:f:pri:nakc
ppron12:pl:nom:m1:pri
ppas:sg:nom:m1:imperf:aff
pact:pl:gen:n:imperf:aff
fin:pl:sec:imperf
praet:sg:m2:perf
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pant:perf
ppron3:pl:acc:m3:ter:akc:npraep
ppas:sg:loc:f:perf:aff
num:pl:acc:f:congr:ncol
ppron12:sg:acc:m1:sec:nakc
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num:pl:gen:f:congr:ncol
impt:pl:pri:perf
ppron12:sg:acc:f:pri:akc
ppron12:sg:nom:m1:sec
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ppron3:pl:acc:f:ter:akc:npraep
num:pl:acc:m2:rec
winien:sg:m1:imperf
ppron3:sg:gen:f:ter:akc:praep
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num:pl:acc:f:rec:ncol
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ppas:sg:nom:n:imperf:aff
ppas:sg:gen:f:imperf:aff
num:pl:loc:m3:congr:ncol
winien:pl:m1:imperf
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ppron3:sg:loc:f:ter:akc:praep
ppas:pl:gen:m1:perf:aff
siebie:loc
ppron12:sg:nom:f:pri
ppas:pl:inst:f:perf:aff
ppas:sg:inst:m3:perf:aff
ppron3:sg:nom:m3:ter:akc:npraep
ppas:pl:gen:f:imperf:aff
ppas:pl:nom:n:imperf:aff
num:pl:gen:f:congr
subst:sg:acc:n:col
adjp:gen
winien:sg:n:imperf
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pact:pl:nom:m1:imperf:aff
subst:sg:loc:m2
praet:sg:m2:imperf
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ppas:pl:gen:m3:imperf:aff
subst:pl:inst:n:col
num:pl:nom:m3:congr:ncol
num:pl:acc:m1:rec
ppas:pl:nom:m1:imperf:aff
praet:sg:m1:perf:nagl
subst:pl:loc:n:col
ppron3:sg:inst:f:ter:akc:praep
ppron3:sg:gen:n:ter:akc:npraep
subst:pl:loc:m1
adj:sg:acc:f:com
num:pl:nom:m2:congr:ncol
adj:sg:nom:m1:com
num:sg:acc:m3:rec
num:pl:nom:n:rec:col
prep:acc:wok
subst:sg:voc:f
pact:pl:acc:n:imperf:aff
ppron3:pl:nom:f:ter:akc:npraep
ppas:sg:gen:n:perf:aff
num:pl:loc:f:congr:ncol
ppas:sg:acc:n:perf:aff
subst:pl:dat:n:ncol
ppron3:pl:gen:n:ter:akc:npraep
ppas:pl:inst:n:perf:aff
ppas:pl:acc:n:perf:aff
ppron3:pl:inst:m1:ter:akc:praep
num:pl:acc:m1:rec:ncol
num:pl:loc:m3:congr
ppas:sg:loc:n:perf:aff
aglt:pl:sec:imperf:nwok
pact:sg:nom:n:imperf:aff
ppron3:sg:loc:m3:ter:akc:praep
adj:sg:gen:n:com
adj:pl:dat:m3:pos
ppron3:sg:gen:m1:ter:nakc:npraep
pact:sg:inst:m3:imperf:aff
ppron3:pl:acc:n:ter:akc:npraep
adj:sg:dat:n:pos
bedzie:sg:sec:imperf
adj:sg:gen:f:com
winien:sg:m3:imperf
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ppron3:sg:acc:f:ter:akc:praep
num:pl:gen:m1:congr:ncol
adj:pl:dat:n:pos
adj:sg:nom:m3:com
adj:sg:nom:m3:sup
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pact:pl:nom:n:imperf:aff
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pact:sg:gen:m1:imperf:aff
ppron3:pl:gen:f:ter:akc:praep
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ppron3:sg:loc:m1:ter:akc:praep
ger:sg:dat:n:imperf:aff
num:pl:gen:n:congr:ncol
adj:pl:nom:f:com
ppron3:sg:acc:m1:ter:akc:praep
num:pl:nom:m3:rec:ncol
adj:sg:loc:m2:pos
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num:pl:gen:m1:congr
ppron3:pl:nom:m3:ter:akc:npraep
pact:sg:inst:f:imperf:aff
num:pl:nom:n:rec:ncol
ppas:pl:loc:m3:perf:aff
ppas:sg:gen:m3:imperf:aff
winien:pl:m3:imperf
num:pl:gen:m3:rec
impt:pl:pri:imperf
ppron12:sg:dat:f:sec:nakc
subst:pl:inst:m2
ppas:pl:loc:f:perf:aff
pact:sg:acc:n:imperf:aff
impt:pl:sec:imperf
ppron12:pl:dat:m1:sec
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adj:sg:nom:n:sup
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adj:sg:gen:f:sup
adj:sg:gen:m3:com
num:pl:gen:m2:congr
ppron12:sg:acc:f:sec:nakc
ppron12:sg:gen:f:pri:akc
ppron12:pl:inst:m1:pri
ppron3:sg:acc:m2:ter:nakc:npraep
pact:sg:loc:m3:imperf:aff
praet:sg:m3:imperf:nagl
adj:sg:loc:m1:pos
ppas:sg:nom:m2:perf:aff
ppron3:pl:gen:n:ter:akc:praep
adj:sg:acc:n:com
adj:pl:nom:m3:com
ppron12:sg:inst:m1:pri
fin:pl:sec:perf
adj:sg:acc:m3:com
ppas:sg:acc:m3:imperf:aff
ppron3:sg:acc:n:ter:akc:npraep
adj:sg:inst:m2:pos
num:pl:inst:m3:congr:ncol
num:pl:loc:n:congr:ncol
ppron3:sg:gen:m3:ter:akc:praep
num:pl:acc:f:congr
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ppas:pl:acc:m3:imperf:aff
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ppas:pl:inst:m3:perf:aff
num:pl:inst:f:congr:ncol
ppron3:pl:gen:m3:ter:akc:praep
pact:sg:acc:m1:imperf:aff
ppas:sg:gen:n:imperf:aff
ppron3:sg:nom:n:ter:akc:npraep
praet:pl:m2:imperf
ppron12:pl:gen:m1:sec
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adj:pl:gen:m3:sup
ppas:sg:inst:n:perf:aff
ppas:sg:acc:f:imperf:aff
ger:pl:gen:n:perf:aff
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ppron12:sg:acc:m1:sec:akc
ppron12:sg:loc:m1:pri
praet:pl:m2:perf
ppas:pl:gen:n:imperf:aff
sym
adj:pl:gen:f:com
ppas:sg:loc:m3:imperf:aff
subst:sg:loc:n:col
ppron3:pl:inst:f:ter:akc:praep
ppas:sg:acc:m1:perf:aff
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num:pl:loc:f:congr
num:pl:acc:n:rec
num:pl:nom:n:congr:ncol
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num:pl:acc:n:congr:ncol
ppron3:pl:loc:f:ter:akc:praep
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ppas:sg:gen:m1:perf:aff
pact:pl:inst:f:imperf:aff
adj:pl:nom:m1:com
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adj:sg:loc:m3:sup
adj:sg:loc:f:com
adj:sg:voc:m1:pos
praet:sg:m1:imperf:agl
pact:sg:loc:n:imperf:aff
pact:pl:loc:f:imperf:aff
ppron3:pl:nom:n:ter:akc:npraep
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adj:sg:acc:f:sup
adj:pl:gen:m3:com
ppron3:sg:gen:m2:ter:akc:npraep
adj:pl:loc:m1:pos
adj:pl:acc:m3:com
ppron3:pl:loc:m3:ter:akc:praep
adj:pl:acc:m2:pos
ppron12:sg:nom:f:sec
ppron12:sg:gen:m1:sec:akc
pact:pl:loc:n:imperf:aff
adj:sg:gen:m3:sup
ppas:pl:acc:m1:perf:aff
ppron3:sg:gen:m3:ter:nakc:npraep
num:sg:acc:f:rec
ppas:pl:nom:m2:perf:aff
ppas:pl:loc:n:imperf:aff
num:pl:inst:m3:congr
ppron12:pl:acc:m1:sec
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winien:pl:n:imperf
num:sg:acc:n:rec:ncol
num:pl:nom:m1:rec:col
ppas:pl:loc:n:perf:aff
ppas:sg:loc:n:imperf:aff
ppas:sg:inst:m1:perf:aff
adj:pl:acc:m3:sup
ppron3:pl:loc:n:ter:akc:praep
adj:pl:nom:f:sup
adj:sg:acc:m3:sup
adjc
ppas:sg:inst:f:imperf:aff
pact:pl:loc:m3:imperf:aff
ppron12:sg:dat:m1:pri:akc
num:pl:nom:n:rec
ppron12:sg:inst:m1:sec
pact:pl:inst:m3:imperf:aff
ppas:sg:loc:f:imperf:aff
ppron3:sg:dat:m3:ter:nakc:npraep
ppas:sg:inst:n:imperf:aff
ppas:pl:loc:m3:imperf:aff
adj:pl:nom:m1:sup
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num:sg:acc:n:rec
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num:sg:nom:m3:rec
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praet:sg:m1:perf:agl
ppron3:pl:loc:m1:ter:akc:praep
ppron12:sg:inst:f:pri
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num:pl:gen:n:congr
romandig
ger:pl:nom:n:imperf:aff
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num:pl:gen:m2:congr:ncol
ppron3:sg:dat:m2:ter:nakc:npraep
ppas:sg:inst:m3:imperf:aff
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num:pl:inst:f:congr
num:pl:inst:m1:congr:ncol
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ppas:pl:inst:f:imperf:aff
ppron12:sg:inst:f:sec
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ppron3:sg:gen:n:ter:akc:praep
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ppron12:sg:dat:m1:sec:akc
ppron12:sg:loc:f:pri
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ppron12:pl:nom:m1:sec
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num:sg:nom:n:rec:ncol
bedzie:pl:sec:imperf
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pact:pl:nom:m2:imperf:aff
ppas:sg:nom:m2:imperf:aff
pact:pl:dat:f:imperf:aff
ppron3:pl:inst:m3:ter:akc:praep
ppron3:pl:acc:n:ter:akc:praep
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ppron3:sg:inst:m3:ter:akc:praep
ppron3:sg:gen:n:ter:nakc:npraep
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ppron12:sg:gen:m1:sec:nakc
ppas:pl:nom:m3:perf:neg
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ppron3:sg:dat:m1:ter:akc:npraep
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num:pl:nom:m2:rec:ncol
num:pl:acc:m2:rec:ncol
ppron3:sg:loc:n:ter:akc:praep
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num:pl:acc:m1:rec:col
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ppron3:pl:inst:f:ter:akc:npraep
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