From 0b1d38f0c187e2ca5b3f38928ffc0c243fbdf0d7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Marcin=20W=C4=85troba?= <markowanga@gmail.com>
Date: Mon, 16 Jan 2023 01:40:21 +0100
Subject: [PATCH] download_dataset command
---
experiment/pipeline_process_flair_upos.py | 4 +-
new_experiment/add_to_queue_pipeline.py | 37 +-
.../pipeline/pipeline_process_flair_upos.py | 32 +
.../pipeline_process_wikineural_ner_wer.py | 4 -
.../pipeline_process_word_embedding_wer.py | 6 +-
new_experiment/utils/property_helper.py | 8 +
new_experiment/worker_pipeline.py | 6 +
poetry.lock | 934 +++++++++++++++++-
pyproject.toml | 1 -
.../task/classic_wer_metric_task.py | 10 +-
.../task/embedding_wer_metrics_task.py | 47 +-
11 files changed, 1052 insertions(+), 37 deletions(-)
create mode 100644 new_experiment/pipeline/pipeline_process_flair_upos.py
diff --git a/experiment/pipeline_process_flair_upos.py b/experiment/pipeline_process_flair_upos.py
index 91059fc..1ab7f6c 100644
--- a/experiment/pipeline_process_flair_upos.py
+++ b/experiment/pipeline_process_flair_upos.py
@@ -6,6 +6,7 @@ from experiment.sentence_wer_processor.flair_upos_multi_transformers_wer_process
FlairUposMultiTransformersWerProcessorBase
from experiment.sentence_wer_processor.wikineural_multilingual_ner_transformers_wer_processor_base import \
WikineuralMultilingualNerTransformersWerProcessorBase
+from new_experiment.utils.property_helper import PropertyHelper
from sziszapangma.core.transformer.web_embedding_transformer import WebEmbeddingTransformer
from sziszapangma.integration.experiment_manager import ExperimentManager
from sziszapangma.integration.task.classic_wer_metric_task import ClassicWerMetricTask
@@ -26,8 +27,7 @@ def run_word_wer_pipeline(dataset_name: str, asr_name: str):
require_update=False
)
],
- experiment_repository=get_repository(dataset_name),
- relation_manager_provider=record_provider
+ experiment_repository=get_repository(dataset_name)
)
experiment_processor.process()
diff --git a/new_experiment/add_to_queue_pipeline.py b/new_experiment/add_to_queue_pipeline.py
index 29eb7d1..c8d5253 100644
--- a/new_experiment/add_to_queue_pipeline.py
+++ b/new_experiment/add_to_queue_pipeline.py
@@ -6,15 +6,28 @@ import pika
from minio import Minio
from pika.adapters.blocking_connection import BlockingChannel
-COMMANDS = ['run_word_wer_classic_pipeline', 'run_word_wer_embedding_pipeline', 'run_spacy_dep_tag_wer_pipeline',
- 'run_spacy_ner_wer_pipeline', 'run_spacy_pos_wer_pipeline']
+COMMANDS = [
+ 'run_word_wer_classic_pipeline',
+ 'run_word_wer_embedding_pipeline',
+ # 'run_spacy_dep_tag_wer_pipeline',
+ # 'run_spacy_ner_wer_pipeline',
+ # 'run_spacy_pos_wer_pipeline',
+ 'run_wikineural_ner_pipeline',
+ 'run_flair_upos_multi_pipeline'
+]
LANGUAGES = ['nl', 'fr', 'de', 'it', 'pl', 'es', 'en']
WHISPER_ASR_MODEL = ['tiny', 'base', 'small', 'medium', 'large-v2']
-DATASETS = [
- 'google_fleurs',
- 'minds14',
- 'voxpopuli'
-]
+DATASETS_BASE = ['google_fleurs', 'minds14', 'voxpopuli']
+DATASETS = [f'{language}_{dataset}' for dataset in DATASETS_BASE for language in LANGUAGES]
+
+
+def get_asrs_for_dataset(full_dataset_name: str) -> List[str]:
+ language_code = full_dataset_name[:2]
+ asrs = [f'whisper_{whisper_variant}' for whisper_variant in WHISPER_ASR_MODEL]
+ asrs.append(get_hf_facebook_wav2vec2_model_by_language_code(language_code))
+ if language_code in ['de', 'en', 'es', 'fr', 'it']:
+ asrs.append(f'nvidia_stt_{language_code}_conformer_transducer_large')
+ return asrs
def get_all_datasets() -> List[str]:
@@ -96,6 +109,13 @@ def add_nvidia(channel: BlockingChannel):
add_to_queue(dataset_name, asr_name, command, channel, 'asr_benchmark_experiments')
+def add_all(channel: BlockingChannel):
+ for dataset_name in DATASETS:
+ for asr_name in get_asrs_for_dataset(dataset_name):
+ for command in COMMANDS:
+ add_to_queue(dataset_name, asr_name, command, channel, 'asr_benchmark_experiments')
+
+
def main():
parameters = pika.URLParameters(
'amqps://rabbit_user:kz6m4972OUHFmtUcPOHx4kF3Lj6yw7lo@rabbit-asr-benchmarks.theliver.pl:5671/')
@@ -104,7 +124,8 @@ def main():
# add_whisper(channel)
# add_facebook_hf_wav2vec2_asr(channel)
# add_facebook_hf_wav2vec2_pipeline(channel)
- add_nvidia(channel)
+ # add_nvidia(channel)
+ add_all(channel)
connection.close()
diff --git a/new_experiment/pipeline/pipeline_process_flair_upos.py b/new_experiment/pipeline/pipeline_process_flair_upos.py
new file mode 100644
index 0000000..13f1b43
--- /dev/null
+++ b/new_experiment/pipeline/pipeline_process_flair_upos.py
@@ -0,0 +1,32 @@
+import argparse
+
+from experiment.const_pipeline_names import GOLD_TRANSCRIPT
+from experiment.experiment_dependency_provider import get_record_provider, get_repository
+from experiment.sentence_wer_processor.flair_upos_multi_transformers_wer_processor_base import \
+ FlairUposMultiTransformersWerProcessorBase
+from experiment.sentence_wer_processor.wikineural_multilingual_ner_transformers_wer_processor_base import \
+ WikineuralMultilingualNerTransformersWerProcessorBase
+from new_experiment.utils.property_helper import PropertyHelper
+from sziszapangma.core.transformer.web_embedding_transformer import WebEmbeddingTransformer
+from sziszapangma.integration.experiment_manager import ExperimentManager
+from sziszapangma.integration.task.classic_wer_metric_task import ClassicWerMetricTask
+from sziszapangma.integration.task.embedding_wer_metrics_task import EmbeddingWerMetricsTask
+
+
+def run_flair_upos_multi_pipeline(dataset_name: str, asr_name: str):
+ record_provider = get_record_provider(dataset_name)
+ experiment_processor = ExperimentManager(
+ record_id_iterator=record_provider,
+ processing_tasks=[
+ FlairUposMultiTransformersWerProcessorBase(
+ gold_transcript_property_name=GOLD_TRANSCRIPT,
+ asr_property_name=PropertyHelper.asr_result(asr_name),
+ alignment_property_name=PropertyHelper.pos_alignment(asr_name, 'flair_upos_multi'),
+ wer_property_name=PropertyHelper.pos_metrics(asr_name, 'flair_upos_multi'),
+ task_name=f'FlairUposMultiTransformersWerProcessorBase___{dataset_name}___{asr_name}',
+ require_update=False
+ )
+ ],
+ experiment_repository=get_repository(dataset_name)
+ )
+ experiment_processor.process()
diff --git a/new_experiment/pipeline/pipeline_process_wikineural_ner_wer.py b/new_experiment/pipeline/pipeline_process_wikineural_ner_wer.py
index 3675fc9..0ce5301 100644
--- a/new_experiment/pipeline/pipeline_process_wikineural_ner_wer.py
+++ b/new_experiment/pipeline/pipeline_process_wikineural_ner_wer.py
@@ -27,7 +27,3 @@ def run_wikineural_ner_pipeline(dataset_name: str, asr_name: str):
experiment_repository=repository
)
experiment_processor.process()
-
-
-if __name__ == '__main__':
- run_wikineural_ner_pipeline('de_minds14', 'whisper_tiny')
diff --git a/new_experiment/pipeline/pipeline_process_word_embedding_wer.py b/new_experiment/pipeline/pipeline_process_word_embedding_wer.py
index 9026787..7deba73 100644
--- a/new_experiment/pipeline/pipeline_process_word_embedding_wer.py
+++ b/new_experiment/pipeline/pipeline_process_word_embedding_wer.py
@@ -15,10 +15,12 @@ def run_word_wer_embedding_pipeline(dataset_name: str, asr_name: str):
task_name=f'EmbeddingWerMetricsTask___{dataset_name}___{asr_name}',
asr_property_name=PropertyHelper.asr_result(asr_name),
gold_transcript_property_name=PropertyHelper.get_gold_transcript_words(),
- metrics_property_name=PropertyHelper.word_wer_embeddings_metrics(asr_name),
require_update=False,
embedding_transformer=FasttextEmbeddingTransformer(dataset_name[:2]),
- alignment_property_name=PropertyHelper.word_wer_embeddings_alignment(asr_name)
+ embeddings_alignment_property_name=PropertyHelper.word_wer_embeddings_alignment(asr_name),
+ embeddings_metrics_property_name=PropertyHelper.word_wer_embeddings_metrics(asr_name),
+ soft_alignment_property_name=PropertyHelper.word_wer_soft_alignment(asr_name),
+ soft_metrics_property_name=PropertyHelper.word_wer_soft_metrics(asr_name)
)
],
experiment_repository=repository
diff --git a/new_experiment/utils/property_helper.py b/new_experiment/utils/property_helper.py
index 41bddca..e2fab76 100644
--- a/new_experiment/utils/property_helper.py
+++ b/new_experiment/utils/property_helper.py
@@ -51,3 +51,11 @@ class PropertyHelper:
@staticmethod
def word_wer_embeddings_metrics(asr_name: str) -> str:
return f'{asr_name}__word_wer_embeddings_metrics'
+
+ @staticmethod
+ def word_wer_soft_alignment(asr_name: str) -> str:
+ return f'{asr_name}__word_wer_soft_alignment'
+
+ @staticmethod
+ def word_wer_soft_metrics(asr_name: str) -> str:
+ return f'{asr_name}__word_wer_soft_metrics'
diff --git a/new_experiment/worker_pipeline.py b/new_experiment/worker_pipeline.py
index 27dbc61..3679444 100644
--- a/new_experiment/worker_pipeline.py
+++ b/new_experiment/worker_pipeline.py
@@ -1,8 +1,10 @@
import json
+from new_experiment.pipeline.pipeline_process_flair_upos import run_flair_upos_multi_pipeline
from new_experiment.pipeline.pipeline_process_spacy_dep_tag_wer import run_spacy_dep_tag_wer_pipeline
from new_experiment.pipeline.pipeline_process_spacy_ner_wer import run_spacy_ner_wer_pipeline
from new_experiment.pipeline.pipeline_process_spacy_pos_wer import run_spacy_pos_wer_pipeline
+from new_experiment.pipeline.pipeline_process_wikineural_ner_wer import run_wikineural_ner_pipeline
from new_experiment.pipeline.pipeline_process_word_classic_wer import run_word_wer_classic_pipeline
from new_experiment.pipeline.pipeline_process_word_embedding_wer import run_word_wer_embedding_pipeline
from new_experiment.queue_base import process_queue
@@ -26,6 +28,10 @@ def process_message(body: bytes):
run_spacy_ner_wer_pipeline(dataset, asr_name)
elif task == 'run_spacy_pos_wer_pipeline':
run_spacy_pos_wer_pipeline(dataset, asr_name)
+ elif task == 'run_wikineural_ner_pipeline':
+ run_wikineural_ner_pipeline(dataset, asr_name)
+ elif task == 'run_flair_upos_multi_pipeline':
+ run_flair_upos_multi_pipeline(dataset, asr_name)
else:
raise Exception(f"Bad message {message_dict}")
diff --git a/poetry.lock b/poetry.lock
index e465bba..5e58799 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -613,6 +613,25 @@ urllib3 = ">=1.25.4,<1.27"
[package.extras]
crt = ["awscrt (==0.14.0)"]
+[[package]]
+name = "bpemb"
+version = "0.3.4"
+description = "Byte-pair embeddings in 275 languages"
+category = "main"
+optional = false
+python-versions = "*"
+files = [
+ {file = "bpemb-0.3.4-py3-none-any.whl", hash = "sha256:585c5e72208d117cd46887fc57e70e3caec92e3def2178bc5156c55b87b3d4c0"},
+ {file = "bpemb-0.3.4.tar.gz", hash = "sha256:c4d330c00bf4ce36a72735d16c825f80320871ba698c1e9c705a3c81b4b9c133"},
+]
+
+[package.dependencies]
+gensim = "*"
+numpy = "*"
+requests = "*"
+sentencepiece = "*"
+tqdm = "*"
+
[[package]]
name = "catalogue"
version = "2.0.8"
@@ -849,6 +868,18 @@ click = "*"
prompt-toolkit = "*"
six = "*"
+[[package]]
+name = "cloudpickle"
+version = "2.2.0"
+description = "Extended pickling support for Python objects"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+files = [
+ {file = "cloudpickle-2.2.0-py3-none-any.whl", hash = "sha256:7428798d5926d8fcbfd092d18d01a2a03daf8237d8fcdc8095d256b8490796f0"},
+ {file = "cloudpickle-2.2.0.tar.gz", hash = "sha256:3f4219469c55453cfe4737e564b67c2a149109dabf7f242478948b895f61106f"},
+]
+
[[package]]
name = "colorama"
version = "0.4.6"
@@ -924,6 +955,93 @@ files = [
[package.dependencies]
six = "*"
+[[package]]
+name = "conllu"
+version = "4.5.2"
+description = "CoNLL-U Parser parses a CoNLL-U formatted string into a nested python dictionary"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+files = [
+ {file = "conllu-4.5.2-py2.py3-none-any.whl", hash = "sha256:660e7305b25d1993404e17197c1a17a08f2214ae780d9a7d69361274aaea260d"},
+ {file = "conllu-4.5.2.tar.gz", hash = "sha256:7c581c0d12fcdd546cbf69050063c37312de28dd3048c3f144ec5b851e71891c"},
+]
+
+[[package]]
+name = "contourpy"
+version = "1.0.7"
+description = "Python library for calculating contours of 2D quadrilateral grids"
+category = "main"
+optional = false
+python-versions = ">=3.8"
+files = [
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win32 = ["pywin32"]
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reference = "HEAD"
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+python-versions = "*"
+files = [
+ {file = "Wikipedia-API-0.5.8.tar.gz", hash = "sha256:065c6541e7480b95b14b9607c243fbce6aefe084e6dc58e41ffb313aec472fcd"},
+ {file = "Wikipedia_API-0.5.8-py3-none-any.whl", hash = "sha256:f124cb59fef0c635fa3818d33025f4cd3daa4a119314728653959c0ede328813"},
+]
+
+[package.dependencies]
+requests = "*"
+
[[package]]
name = "wrapt"
version = "1.14.1"
@@ -6142,4 +7074,4 @@ testing = ["flake8 (<5)", "func-timeout", "jaraco.functools", "jaraco.itertools"
[metadata]
lock-version = "2.0"
python-versions = ">=3.8,<3.12"
-content-hash = "db5e937e072440888cfbd5f39f302932dddf5b43ad94fdddc6c7c88841f89700"
+content-hash = "656814b0de860bfc94bd884768add476dad31953c0181dd6871fb79257d0293b"
diff --git a/pyproject.toml b/pyproject.toml
index 92a8240..5d89515 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -21,7 +21,6 @@ spacy = "^3.4.4"
pysoundfile = "^0.9.0.post1"
datasets = "^2.8.0"
torchaudio = "^0.13.1"
-#flair = "^0.11.3"
whisper = {git = "https://github.com/openai/whisper.git"}
ffmpeg-python = "^0.2.0"
pydub = "^0.25.1"
diff --git a/sziszapangma/integration/task/classic_wer_metric_task.py b/sziszapangma/integration/task/classic_wer_metric_task.py
index 2a17809..e50f2c6 100644
--- a/sziszapangma/integration/task/classic_wer_metric_task.py
+++ b/sziszapangma/integration/task/classic_wer_metric_task.py
@@ -11,8 +11,6 @@ from sziszapangma.integration.task.task_util import TaskUtil
from sziszapangma.model.model import Word
from sziszapangma.model.relation_manager import RelationManager
-_CLASSIC_WER = "classic_wer"
-
class ClassicWerMetricTask(ProcessingTask):
_metrics_property_name: str
@@ -59,7 +57,7 @@ class ClassicWerMetricTask(ProcessingTask):
[AlignmentStepMapper.to_json_dict(it) for it in alignment_steps],
)
experiment_repository.update_property_for_key(
- record_id, self._metrics_property_name, self.calculate_metrics(alignment_steps)
+ record_id, self._metrics_property_name, self.calculate_wer_metric(alignment_steps)
)
def _get_alignment(
@@ -69,8 +67,6 @@ class ClassicWerMetricTask(ProcessingTask):
reference=gold_transcript, hypothesis=asr_transcript
)
- def calculate_metrics(self, alignment_steps: List[AlignmentStep]) -> Dict[str, Any]:
+ def calculate_wer_metric(self, alignment_steps: List[AlignmentStep]) -> float:
"""Calculate all metrics for data sample."""
- metrics = dict()
- metrics[_CLASSIC_WER] = self._wer_calculator.calculate_wer(alignment_steps)
- return metrics
+ return self._wer_calculator.calculate_wer(alignment_steps)
diff --git a/sziszapangma/integration/task/embedding_wer_metrics_task.py b/sziszapangma/integration/task/embedding_wer_metrics_task.py
index 099773a..317a27a 100644
--- a/sziszapangma/integration/task/embedding_wer_metrics_task.py
+++ b/sziszapangma/integration/task/embedding_wer_metrics_task.py
@@ -17,8 +17,10 @@ _WORD = "word"
class EmbeddingWerMetricsTask(ProcessingTask):
- _metrics_property_name: str
- _alignment_property_name: str
+ _soft_metrics_property_name: str
+ _soft_alignment_property_name: str
+ _embeddings_metrics_property_name: str
+ _embeddings_alignment_property_name: str
_gold_transcript_property_name: str
_embedding_transformer: CachedEmbeddingTransformer
_alignment_embedding_calculator: AlignmentEmbeddingCalculator
@@ -30,28 +32,34 @@ class EmbeddingWerMetricsTask(ProcessingTask):
task_name: str,
gold_transcript_property_name: str,
asr_property_name: str,
- metrics_property_name: str,
- alignment_property_name: str,
+ soft_metrics_property_name: str,
+ soft_alignment_property_name: str,
+ embeddings_metrics_property_name: str,
+ embeddings_alignment_property_name: str,
require_update: bool,
embedding_transformer: EmbeddingTransformer,
):
super().__init__(task_name, require_update)
self._gold_transcript_property_name = gold_transcript_property_name
self._asr_property_name = asr_property_name
- self._metrics_property_name = metrics_property_name
self._embedding_transformer = CachedEmbeddingTransformer(embedding_transformer)
self._alignment_embedding_calculator = AlignmentEmbeddingCalculator(
self._embedding_transformer
)
self._alignment_soft_calculator = AlignmentSoftCalculator(self._embedding_transformer)
self._wer_calculator = WerCalculator()
- self._alignment_property_name = alignment_property_name
+ self._soft_metrics_property_name = soft_metrics_property_name
+ self._soft_alignment_property_name = soft_alignment_property_name
+ self._embeddings_metrics_property_name = embeddings_metrics_property_name
+ self._embeddings_alignment_property_name = embeddings_alignment_property_name
def skip_for_record(self, record_id: str, experiment_repository: ExperimentRepository) -> bool:
- return (
- experiment_repository.get_property_for_key(record_id, self._metrics_property_name)
- is not None
- )
+ properties = [self._soft_metrics_property_name, self._soft_alignment_property_name,
+ self._embeddings_metrics_property_name, self._embeddings_alignment_property_name]
+ return all([
+ experiment_repository.get_property_for_key(record_id, it) is not None
+ for it in properties
+ ])
@staticmethod
def filter_empty_words(words: List[Word]) -> List[Word]:
@@ -87,11 +95,26 @@ class EmbeddingWerMetricsTask(ProcessingTask):
wer_results = {"soft_wer": soft_wer, "embedding_wer": embedding_wer}
print(wer_results)
+ # experiment_repository.update_property_for_key(
+ # record_id, self._alignment_property_name, alignment_results
+ # )
+ # experiment_repository.update_property_for_key(
+ # record_id, self._metrics_property_name, wer_results
+ # )
+ experiment_repository.update_property_for_key(
+ record_id=record_id, property_name=self._soft_alignment_property_name,
+ property_value=[AlignmentStepMapper.to_json_dict(it) for it in soft_alignment]
+ )
+ experiment_repository.update_property_for_key(
+ record_id=record_id, property_name=self._embeddings_alignment_property_name,
+ property_value=[AlignmentStepMapper.to_json_dict(it) for it in embedding_alignment]
+ )
experiment_repository.update_property_for_key(
- record_id, self._alignment_property_name, alignment_results
+ record_id=record_id, property_name=self._soft_metrics_property_name, property_value=soft_wer
)
experiment_repository.update_property_for_key(
- record_id, self._metrics_property_name, wer_results
+ record_id=record_id, property_name=self._embeddings_metrics_property_name,
+ property_value=embedding_wer
)
self._embedding_transformer.clear()
--
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