diff --git a/README.md b/README.md
index f25edd21049195dc60f6a66de5fad3d5e339744b..d67918d9c7f8e156835f9b61873599f03f733a0d 100644
--- a/README.md
+++ b/README.md
@@ -24,7 +24,7 @@ Examples (for clarity without training/validation data paths):
* train on gpu 0
```bash
- combo --mode train --cuda_davice 0
+ combo --mode train --cuda_device 0
```
* use pretrained embeddings:
@@ -42,13 +42,13 @@ Examples (for clarity without training/validation data paths):
* predict only dependency tree:
```bash
- combo --mode train --targets head --targets deprel
+ combo --mode train --targets head,deprel
```
* use part-of-speech tags for predicting only dependency tree
```bash
- combo --mode train --targets head --targets deprel --features token --features char --features upostag
+ combo --mode train --targets head,deprel --features token,char,upostag
```
Advanced configuration: [Configuration](#configuration)
diff --git a/combo/data/dataset.py b/combo/data/dataset.py
index 386e40262e0446159c2a48c8957984bdedd110eb..7a98841fd0d352e8b9f98d58c9fe30d5cc1f5e18 100644
--- a/combo/data/dataset.py
+++ b/combo/data/dataset.py
@@ -69,7 +69,7 @@ class UniversalDependenciesDatasetReader(allen_data.DatasetReader):
@overrides
def _read(self, file_path: str) -> Iterable[allen_data.Instance]:
- file_path = [file_path] if len(file_path.split(":")) == 0 else file_path.split(":")
+ file_path = [file_path] if len(file_path.split(",")) == 0 else file_path.split(",")
for conllu_file in file_path:
with open(conllu_file, "r") as file:
diff --git a/combo/main.py b/combo/main.py
index e0e3ac3ad6d4ff452d73faecdac99e3bff572031..366fa93fe7ac94ee74f076987d159ba63b8af0d2 100644
--- a/combo/main.py
+++ b/combo/main.py
@@ -17,6 +17,8 @@ from combo.data import dataset
from combo.utils import checks
logger = logging.getLogger(__name__)
+_FEATURES = ["token", "char", "upostag", "xpostag", "lemma", "feats"]
+_TARGETS = ["deprel", "feats", "head", "lemma", "upostag", "xpostag", "semrel", "sent"]
FLAGS = flags.FLAGS
flags.DEFINE_enum(name="mode", default=None, enum_values=["train", "predict"],
@@ -30,9 +32,9 @@ flags.DEFINE_string(name="output_file", default="output.log",
# Training flags
flags.DEFINE_list(name="training_data_path", default="./tests/fixtures/example.conllu",
- help="Training data path")
+ help="Training data path(s)")
flags.DEFINE_list(name="validation_data_path", default="",
- help="Validation data path")
+ help="Validation data path(s)")
flags.DEFINE_string(name="pretrained_tokens", default="",
help="Pretrained tokens embeddings path")
flags.DEFINE_integer(name="embedding_dim", default=300,
@@ -42,14 +44,12 @@ flags.DEFINE_integer(name="num_epochs", default=400,
flags.DEFINE_integer(name="word_batch_size", default=2500,
help="Minimum words in batch")
flags.DEFINE_string(name="pretrained_transformer_name", default="",
- help="Pretrained transformer model name (see transformers from HuggingFace library for list of"
+ help="Pretrained transformer model name (see transformers from HuggingFace library for list of "
"available models) for transformers based embeddings.")
-flags.DEFINE_multi_enum(name="features", default=["token", "char"],
- enum_values=["token", "char", "upostag", "xpostag", "lemma", "feats"],
- help="Features used to train model (required 'token' and 'char')")
-flags.DEFINE_multi_enum(name="targets", default=["deprel", "feats", "head", "lemma", "upostag", "xpostag"],
- enum_values=["deprel", "feats", "head", "lemma", "upostag", "xpostag", "semrel", "sent"],
- help="Targets of the model (required `deprel` and `head`)")
+flags.DEFINE_list(name="features", default=["token", "char"],
+ help=f"Features used to train model (required 'token' and 'char'). Possible values: {_FEATURES}.")
+flags.DEFINE_list(name="targets", default=["deprel", "feats", "head", "lemma", "upostag", "xpostag"],
+ help=f"Targets of the model (required `deprel` and `head`). Possible values: {_TARGETS}.")
flags.DEFINE_string(name="serialization_dir", default=None,
help="Model serialization directory (default - system temp dir).")
flags.DEFINE_boolean(name="tensorboard", default=False,
@@ -189,10 +189,22 @@ def _get_ext_vars(finetuning: bool = False) -> Dict:
def main():
"""Parse flags."""
+ flags.register_validator(
+ "features",
+ lambda values: all(
+ value in _FEATURES for value in values),
+ message="Flags --features contains unknown value(s)."
+ )
flags.register_validator(
"mode",
lambda value: value is not None,
message="Flag --mode must be set with either `predict` or `train` value")
+ flags.register_validator(
+ "targets",
+ lambda values: all(
+ value in _TARGETS for value in values),
+ message="Flag --targets contains unknown value(s)."
+ )
app.run(run)
diff --git a/config.template.jsonnet b/config.template.jsonnet
index 0f12d8ff5f4a70526bba3356db698a52723aa161..f12c3bd1ba29b690e0f4328137d6da796706591c 100644
--- a/config.template.jsonnet
+++ b/config.template.jsonnet
@@ -3,10 +3,10 @@
########################################################################################
# Training data path, str
# Must be in CONNLU format (or it's extended version with semantic relation field).
-# Can accepted multiple paths when concatenated with ':', "path1:path2"
+# Can accepted multiple paths when concatenated with ',', "path1,path2"
local training_data_path = std.extVar("training_data_path");
# Validation data path, str
-# Can accepted multiple paths when concatenated with ':', "path1:path2"
+# Can accepted multiple paths when concatenated with ',', "path1,path2"
local validation_data_path = if std.length(std.extVar("validation_data_path")) > 0 then std.extVar("validation_data_path");
# Path to pretrained tokens, str or null
local pretrained_tokens = if std.length(std.extVar("pretrained_tokens")) > 0 then std.extVar("pretrained_tokens");
@@ -36,13 +36,13 @@ local embedding_dim = std.parseInt(std.extVar("embedding_dim"));
local predictors_dropout = 0.25;
# Xpostag embedding dimension, int
# (discarded if xpostag not in features)
-local xpostag_dim = 100;
+local xpostag_dim = 32;
# Upostag embedding dimension, int
# (discarded if upostag not in features)
-local upostag_dim = 100;
+local upostag_dim = 32;
# Feats embedding dimension, int
# (discarded if feats not in featres)
-local feats_dim = 100;
+local feats_dim = 32;
# Lemma embedding dimension, int
# (discarded if lemma not in features)
local lemma_char_dim = 64;
diff --git a/setup.py b/setup.py
index bb402c8f9dae2c06df51b9b94aa571ad0c0be2dc..44a26199d0f4a53c7008f14cc00e8e07aeb140a9 100644
--- a/setup.py
+++ b/setup.py
@@ -3,11 +3,11 @@ from setuptools import find_packages, setup
REQUIREMENTS = [
'absl-py==0.9.0',
- 'allennlp==1.0.0rc4',
+ 'allennlp==1.0.0rc5',
'conllu==2.3.2',
'joblib==0.14.1',
'jsonnet==0.15.0',
- 'overrides==2.8.0',
+ 'overrides==3.0.0',
'tensorboard==2.1.0',
'torch==1.5.0',
'torchvision==0.6.0',