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* Add support for large numbers (>999,999,999,999,999)
Signed-off-by: Anand Joseph <anajoseph@nvidia.com>
* Update cache folder in Jenkinsfile
Signed-off-by: Anand Joseph <anajoseph@nvidia.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Increase mem size for CI tests
Signed-off-by: Anand Joseph <anajoseph@nvidia.com>
* Updating shmem for docker to deal with memory overflow
Signed-off-by: Anand Joseph <anajoseph@nvidia.com>
* Ensure large au cardinal graph is used only if deterministic
Signed-off-by: Anand Joseph <anajoseph@nvidia.com>
* Make comma mandatory in cardinals
Signed-off-by: Anand Joseph <anajoseph@nvidia.com>
* Run FST cache generation and Pytests in separate stages
Signed-off-by: Anand Joseph <anajoseph@nvidia.com>
* Fix stage
Signed-off-by: Anand Joseph <anajoseph@nvidia.com>
* Change cache folder
Signed-off-by: Anand Joseph <anajoseph@nvidia.com>
---------
Signed-off-by: Anand Joseph <anajoseph@nvidia.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
sh 'CUDA_VISIBLE_DEVICES="" python nemo_text_processing/text_normalization/normalize.py --text="1" --cache_dir /home/jenkinsci/TestData/text_norm/ci/grammars/02-01-23-1'
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sh 'CUDA_VISIBLE_DEVICES="" python nemo_text_processing/text_normalization/normalize.py --text="1" --cache_dir /home/jenkinsci/TestData/text_norm/ci/grammars/02-01-23-3'
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}
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}
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stage('En ITN grammars') {
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stage('L0: En TN non-deterministic grammars') {
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steps {
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sh 'CUDA_VISIBLE_DEVICES="" python nemo_text_processing/inverse_text_normalization/inverse_normalize.py --language en --text="twenty" --cache_dir /home/jenkinsci/TestData/text_norm/ci/grammars/02-01-23-1'
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sh 'CUDA_VISIBLE_DEVICES="" python nemo_text_processing/text_normalization/normalize_with_audio.py --text="1" --cache_dir /home/jenkinsci/TestData/text_norm/ci/grammars/02-01-23-3'
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}
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}
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stage('Test En non-deterministic TN & Run all En TN/ITN tests (restore grammars from cache)') {
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stage('L0: En ITN grammars') {
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steps {
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sh 'CUDA_VISIBLE_DEVICES="" pytest tests/nemo_text_processing/en/ -m "not pleasefixme" --cpu --tn_cache_dir /home/jenkinsci/TestData/text_norm/ci/grammars/02-01-23-1'
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sh 'CUDA_VISIBLE_DEVICES="" python nemo_text_processing/inverse_text_normalization/inverse_normalize.py --language en --text="twenty" --cache_dir /home/jenkinsci/TestData/text_norm/ci/grammars/02-01-23-3'
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}
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}
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}
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}
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stage('L1: TN/ITN Tests CPU') {
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when {
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anyOf {
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branch 'main'
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changeRequest target: 'main'
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}
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}
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failFast true
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parallel {
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stage('L1: Test En non-deterministic TN & Run all En TN/ITN tests (restore grammars from cache)') {
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steps {
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sh 'CUDA_VISIBLE_DEVICES="" pytest tests/nemo_text_processing/en/ -m "not pleasefixme" --cpu --tn_cache_dir /home/jenkinsci/TestData/text_norm/ci/grammars/02-01-23-3'
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}
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}
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}
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}
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stage('L2: NeMo text processing') {
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when {
@@ -82,7 +99,7 @@ pipeline {
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stage('L2: Eng TN') {
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steps {
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sh 'TIME=`date +"%Y-%m-%d-%T"` && NORM_OUTPUT_DIR=/home/jenkinsci/TestData/text_norm/output_${TIME} && \
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cd tools/text_processing_deployment && python pynini_export.py --output=$NORM_OUTPUT_DIR --grammars=tn_grammars --cache_dir /home/jenkinsci/TestData/text_norm/ci/grammars/02-01-23-1 --language=en && ls -R $NORM_OUTPUT_DIR && echo ".far files created "|| exit 1'
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cd tools/text_processing_deployment && python pynini_export.py --output=$NORM_OUTPUT_DIR --grammars=tn_grammars --cache_dir /home/jenkinsci/TestData/text_norm/ci/grammars/02-01-23-3 --language=en && ls -R $NORM_OUTPUT_DIR && echo ".far files created "|| exit 1'
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sh 'TIME=`date +"%Y-%m-%d-%T"` && NORM_OUTPUT_DIR=/home/jenkinsci/TestData/text_norm/output_${TIME} && mkdir $NORM_OUTPUT_DIR && \
Copy file name to clipboardExpand all lines: tests/nemo_text_processing/en/data_text_normalization/test_cases_cardinal.txt
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@@ -15,3 +15,4 @@
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1234567890123124~one two three four five six seven eight nine zero one two three one two four
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978-0~nine hundred and seventy eight - zero
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004~zero zero four
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124,444,234,854,823,834,553~one hundred twenty four quintillion four hundred forty four quadrillion two hundred thirty four trillion eight hundred fifty four billion eight hundred twenty three million eight hundred thirty four thousand five hundred and fifty three
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