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cicd-main copy.yml
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# Copyright (c) 2020-2021, NVIDIA CORPORATION.
#
# 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.
name: "CICD NeMo"
on:
pull_request:
branches:
- 'main'
- 'r**'
types: [ labeled ]
workflow_dispatch:
inputs:
test_to_run:
required: false
default: all
type: string
description: Comma-separated list of tests to run. Use "all" to run the full test suite.
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
jobs:
pre-flight:
runs-on: ubuntu-latest
outputs:
test_to_run: ${{ steps.test_to_run.outputs.main }}
all: ${{ steps.all.outputs.main }}
event_name: ${{ steps.github-event.outputs.main }}
steps:
- name: Parse test_to_run
id: test_to_run
run: |
parsed_string=$(echo ${{ inputs.test_to_run || 'all' }} | jq -c --raw-input 'split(",")')
echo "main=${parsed_string}" | tee -a "$GITHUB_OUTPUT"
- name: Parse all
id: all
run: |
echo "main=${{ contains(fromJSON(steps.test_to_run.outputs.main), 'all') }}" | tee -a "$GITHUB_OUTPUT"
- name: Infer github event
id: github-event
run: |
echo "main=${{ github.event_name }}" | tee -a "$GITHUB_OUTPUT"
cicd-test-container-build:
if: ${{ github.event.label.name == 'Run CICD' || needs.pre-flight.outputs.event_name == 'workflow_dispatch' }}
uses: NVIDIA/NeMo-FW-CI-templates/.github/workflows/[email protected]
needs: pre-flight
with:
image-name: nemo_container
dockerfile: Dockerfile.ci
image-label: nemo-core
build-args: |
IMAGE_LABEL=nemo-core
prune-filter-timerange: 24h
cicd-test-container-setup:
needs: [cicd-test-container-build, pre-flight]
runs-on: self-hosted-azure-builder
if: ${{ github.event.label.name == 'Run CICD' || github.event_name == 'workflow_dispatch' }}
outputs:
test_to_run: ${{ needs.pre-flight.outputs.test_to_run }}
all: ${{ needs.pre-flight.outputs.all }}
steps:
- name: Run some checks
run: |
docker run --rm --device=/dev/nvidia0 --gpus all --shm-size=8g --env TRANSFORMERS_OFFLINE=0 --env HYDRA_FULL_ERROR=1 --env PYTHONUNBUFFERED=1 nemoci.azurecr.io/nemo_container:${{ github.run_id }} bash -c '\
# PyTorch Lightning version
python -c "import lightning.pytorch; print(lightning.pytorch.__version__)"
# PyTorch Lightning DDP Checks
CUDA_VISIBLE_DEVICES="0,1" python "tests/core_ptl/check_for_ranks.py"
# Basic Import Checks
python -c "import nemo.collections.asr as nemo_asr"
python -c "import nemo.collections.nlp as nemo_nlp"
python -c "import nemo.collections.nlp as nemo_nlp; nemo_nlp.modules.get_tokenizer_list()"
python -c "import nemo.collections.tts as nemo_tts"
python setup.py style
python tests/check_copyright_header.py --dir .
# These checks are not crucial
exit 0
'
### \'\'
# L0: GPU unit tests
L0_Unit_Tests_GPU_ASR:
needs: [cicd-test-container-setup]
uses: ./.github/workflows/_test_template.yml
if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_GPU_ASR') || needs.cicd-test-container-setup.outputs.all == 'true'
with:
RUNNER: self-hosted-azure
TIMEOUT: 20
# TODO: remove this hack
SCRIPT: |
python -c "from nemo.collections.asr.models import ASRModel" && NEMO_NUMBA_MINVER=0.53 pytest tests/collections/asr -m "not pleasefixme" --cov-report=term --cov=nemo/collections/asr --with_downloads
# L0_Unit_Tests_GPU_Audio:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_GPU_Audio') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# TIMEOUT: 20
# SCRIPT: |
# NEMO_NUMBA_MINVER=0.53 pytest tests/collections/audio -m "not pleasefixme" --with_downloads
# L0_Unit_Tests_GPU_Common:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_GPU_Common') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# NEMO_NUMBA_MINVER=0.53 pytest tests/collections/common -m "not pleasefixme" --with_downloads
# L0_Unit_Tests_GPU_LLM:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_GPU_LLM') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# NEMO_NUMBA_MINVER=0.53 pytest tests/collections/llm -m "not pleasefixme" --with_downloads
# L0_Unit_Tests_GPU_Multimodal:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_GPU_Multimodal') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# NEMO_NUMBA_MINVER=0.53 pytest tests/collections/multimodal -m "not pleasefixme" --with_downloads
# L0_Unit_Tests_GPU_NLP:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_GPU_NLP') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# NEMO_NUMBA_MINVER=0.53 pytest tests/collections/nlp -m "not pleasefixme" --with_downloads
# L0_Unit_Tests_GPU_TTS:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_GPU_TTS') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# NEMO_NUMBA_MINVER=0.53 pytest tests/collections/tts -m "not pleasefixme" --with_downloads
# OPTIONAL_L0_Unit_Tests_GPU_Core:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'OPTIONAL_L0_Unit_Tests_GPU_Core') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# TIMEOUT: 20
# SCRIPT: |
# NEMO_NUMBA_MINVER=0.53 pytest tests/core -m "not pleasefixme" --with_downloads
# IS_OPTIONAL: true
# L0_Unit_Tests_GPU_Hydra:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_GPU_Hydra') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# NEMO_NUMBA_MINVER=0.53 pytest tests/hydra -m "not pleasefixme" --with_downloads
# L0_Unit_Tests_GPU_Lightning:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_GPU_Lightning') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# NEMO_NUMBA_MINVER=0.53 pytest tests/lightning -m "not pleasefixme" --with_downloads
# L0_Unit_Tests_GPU_Others:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_GPU_Others') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# NEMO_NUMBA_MINVER=0.53 pytest -m "not pleasefixme" --with_downloads \
# --ignore=tests/collections/asr \
# --ignore=tests/collections/audio \
# --ignore=tests/collections/common \
# --ignore=tests/collections/llm \
# --ignore=tests/collections/multimodal \
# --ignore=tests/collections/nlp \
# --ignore=tests/collections/tts \
# --ignore=tests/core \
# --ignore=tests/core_ptl \
# --ignore=tests/hydra \
# --ignore=tests/lightning \
# --ignore=tests/utils
# L0: CPU unit tests
L0_Unit_Tests_CPU_ASR:
needs: [cicd-test-container-setup]
uses: ./.github/workflows/_test_template.yml
if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_CPU_ASR') || needs.cicd-test-container-setup.outputs.all == 'true'
with:
RUNNER: self-hosted-azure-cpu
TIMEOUT: 20
SCRIPT: |
CUDA_VISIBLE_DEVICES="" NEMO_NUMBA_MINVER=0.53 pytest tests/collections/asr -m "not pleasefixme" --cpu --with_downloads --cov-report=term --cov=nemo/collections/asr --relax_numba_compat
COVERAGE:
runs-on: self-hosted-azure-cpu
container: nemoci.azurecr.io/nemo_container:${{ github.run_id }}
needs:
- L0_Unit_Tests_CPU_ASR
# - L0_Unit_Tests_GPU_ASR
steps:
- name: Download artifacts
uses: actions/download-artifact@v4
with:
path: ${{ github.run_id }}
- name: Combine
shell: bash -x -e -u -o pipefail {0}
run: |
pip install coverage
cd ${{ github.run_id }}
ls -al .
ls -al coverage-*/
coverage combine $(ls -d coverage-*/*/)
coverage report
# L0_Unit_Tests_CPU_Audio:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_CPU_Audio') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-cpu
# SCRIPT: |
# CUDA_VISIBLE_DEVICES="" NEMO_NUMBA_MINVER=0.53 pytest tests/collections/audio -m "not pleasefixme" --cpu --with_downloads --relax_numba_compat
# L0_Unit_Tests_CPU_Common:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_CPU_Common') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-cpu
# TIMEOUT: 20
# SCRIPT: |
# CUDA_VISIBLE_DEVICES="" NEMO_NUMBA_MINVER=0.53 pytest tests/collections/common -m "not pleasefixme" --cpu --with_downloads --relax_numba_compat
# L0_Unit_Tests_CPU_LLM:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_CPU_LLM') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-cpu
# SCRIPT: |
# CUDA_VISIBLE_DEVICES="" NEMO_NUMBA_MINVER=0.53 pytest tests/collections/llm -m "not pleasefixme" --cpu --with_downloads --relax_numba_compat
# L0_Unit_Tests_CPU_Multimodal:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_CPU_Multimodal') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-cpu
# SCRIPT: |
# CUDA_VISIBLE_DEVICES="" NEMO_NUMBA_MINVER=0.53 pytest tests/collections/multimodal -m "not pleasefixme" --cpu --with_downloads --relax_numba_compat
# L0_Unit_Tests_CPU_NLP:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_CPU_NLP') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# TIMEOUT: 20
# SCRIPT: |
# CUDA_VISIBLE_DEVICES="" NEMO_NUMBA_MINVER=0.53 pytest tests/collections/nlp -m "not pleasefixme" --cpu --with_downloads --relax_numba_compat
# L0_Unit_Tests_CPU_TTS:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_CPU_TTS') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-cpu
# SCRIPT: |
# CUDA_VISIBLE_DEVICES="" NEMO_NUMBA_MINVER=0.53 pytest tests/collections/tts -m "not pleasefixme" --cpu --with_downloads --relax_numba_compat
# L0_Unit_Tests_CPU_Core:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_CPU_Core') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-cpu
# TIMEOUT: 20
# SCRIPT: |
# CUDA_VISIBLE_DEVICES="" NEMO_NUMBA_MINVER=0.53 pytest tests/core tests/core_ptl -m "not pleasefixme" --cpu --with_downloads --relax_numba_compat
# L0_Unit_Tests_CPU_Hydra:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_CPU_Hydra') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-cpu
# SCRIPT: |
# CUDA_VISIBLE_DEVICES="" NEMO_NUMBA_MINVER=0.53 pytest tests/hydra -m "not pleasefixme" --cpu --with_downloads --relax_numba_compat
# L0_Unit_Tests_CPU_Lightning:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_CPU_Lightning') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-cpu
# SCRIPT: |
# CUDA_VISIBLE_DEVICES="" NEMO_NUMBA_MINVER=0.53 pytest tests/lightning -m "not pleasefixme" --cpu --with_downloads --relax_numba_compat
# L0_Unit_Tests_CPU_Others:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Unit_Tests_CPU_Others') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-cpu
# SCRIPT: |
# CUDA_VISIBLE_DEVICES="" NEMO_NUMBA_MINVER=0.53 pytest -m "not pleasefixme" --cpu --with_downloads --relax_numba_compat \
# --ignore=tests/collections/asr \
# --ignore=tests/collections/audio \
# --ignore=tests/collections/common \
# --ignore=tests/collections/llm \
# --ignore=tests/collections/multimodal \
# --ignore=tests/collections/nlp \
# --ignore=tests/collections/tts \
# --ignore=tests/core \
# --ignore=tests/core_ptl \
# --ignore=tests/hydra \
# --ignore=tests/lightning \
# --ignore=tests/utils
# L0_Setup_Test_Data_And_Models:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L0_Setup_Test_Data_And_Models') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# python -m tests.setup --save_dir /home/TestData/nlp
# # - name: L2: Multimodal Imagen Train
# # L2: Community LLM Checkpoints tests
# L2_Community_LLM_Checkpoints_tests_Bert:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Community_LLM_Checkpoints_tests_Bert') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# python scripts/checkpoint_converters/convert_bert_hf_to_nemo.py \
# --input_name_or_path /home/TestData/nlp/megatron_ir/sbert/hf_model/bert-base-uncased \
# --output_path /tmp/nlp_megatron_ir_sbert/sbert.nemo
# L2_Community_LLM_Checkpoints_tests_Mamba2:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Community_LLM_Checkpoints_tests_Mamba2') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# python scripts/checkpoint_converters/convert_mamba2_pyt_to_nemo.py \
# --input_name_or_path /home/TestData/nlp/megatron_mamba/model_optim_rng.pt \
# --output_path /tmp/nlp_megatron_mamba/converted_mamba.nemo \
# --precision=bf16 \
# --mamba_ssm_ngroups 1
# L2_Community_LLM_Checkpoints_tests_Llama:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Community_LLM_Checkpoints_tests_Llama') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# CUDA_VISIBLE_DEVICES=0 python scripts/checkpoint_converters/convert_llama_hf_to_nemo.py \
# --input_name_or_path=/home/TestData/nlp/megatron_llama/llama-ci-hf-tiny \
# --output_path=/tmp/nlp_megatron_llama/llama_ci.nemo \
# --precision=16
# L2_Community_LLM_Checkpoints_tests_Llama3:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Community_LLM_Checkpoints_tests_Llama3') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# CUDA_VISIBLE_DEVICES=0 python scripts/checkpoint_converters/convert_llama_hf_to_nemo.py \
# --input_name_or_path=/home/TestData/nlp/megatron_llama/llama3-ci-hf \
# --output_path=/tmp/nlp_megatron_llama_llama3-ci-hf/llama3_ci.nemo \
# --precision=16
# L2_Community_LLM_Checkpoints_tests_StarCoder:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Community_LLM_Checkpoints_tests_StarCoder') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# mkdir -p /tmp/nlp_megatron_gpt_starcoder-ci-hf/
# python scripts/checkpoint_converters/convert_starcoder_hf_to_nemo.py \
# --input_name_or_path /home/TestData/nlp/megatron_gpt/starcoder-ci-hf \
# --output_path /tmp/nlp_megatron_gpt_starcoder-ci-hf/
# L2_Community_LLM_Checkpoints_tests_Falcon:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Community_LLM_Checkpoints_tests_Falcon') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# python scripts/checkpoint_converters/convert_falcon_hf_to_nemo.py \
# --input_name_or_path /home/TestData/nlp/megatron_gpt/falcon-ci-hf \
# --output_path /tmp/nlp_megatron_gpt_falcon-ci-hf/falcon_ci.nemo
# # L2: Community llava multimodal Checkpoints tests
# L2_Community_vita_Checkpoints_tests_Llama3:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Community_vita_Checkpoints_tests_Llama3') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# mkdir /tmp/${{ github.run_id }}
# export PYTHONPATH=/home/TestData/multimodal/video_neva/LLaVA:$PYTHONPATH
# CUDA_VISIBLE_DEVICES=0 python examples/multimodal/multimodal_llm/neva/convert_llava_to_neva.py \
# --in-file /home/TestData/multimodal/video_neva/Llama-3-VILA1.5-8B/llm \
# --mm-projector-ckpt-dir /home/TestData/multimodal/video_neva/Llama-3-VILA1.5-8B/mm_projector \
# --mm-vision-tower /home/TestData/multimodal/video_neva/Llama-3-VILA1.5-8B/vision_tower \
# --tokenizer-model /home/TestData/multimodal/video_neva/vita-tokenizer/ \
# --config-file vita_config.yaml \
# --out-file=/tmp/${{ github.run_id }}/llama3_ci.nemo \
# --model-type VITA \
# --conv-template llama_3
# # this test is using a 7B model which is too large for GitHub CI
# # replace the model in this test with a toy model or move the test
# # to the nightly CI
# # OPTIONAL_L2_Community_LLM_Checkpoints_tests_Baichuan2:
# # needs: [cicd-test-container-setup]
# # runs-on: self-hosted-azure
# # container:
# # image: nemoci.azurecr.io/nemo_container:${{ github.run_id }}
# # options:
# # # --user 0:128
# # --device=/dev/nvidia0
# # --gpus all
# # --shm-size=8g
# # --env TRANSFORMERS_OFFLINE=0
# # --env HYDRA_FULL_ERROR=1
# # --volume /mnt/datadrive/TestData:/home/TestData
# # steps:
# # - name: Checkout repository
# # uses: actions/checkout@v4
# # - run: |
# # python scripts/checkpoint_converters/convert_baichuan2_hf_to_nemo.py \
# # --input_name_or_path=/home/TestData/nlp/megatron_gpt/Baichuan2-7B-Base \
# # --output_path=/home/TestData/nlp/megatron_gpt/Baichuan2-7B-Base/ci.nemo
# # rm -f /home/TestData/nlp/megatron_gpt/Baichuan2-7B-Base/ci.nemo
# # - uses: "NVIDIA/NeMo/.github/actions/cancel-workflow@main"
# # if: "failure()"
# L2_PTQ_Llama2_FP8:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_PTQ_Llama2_FP8') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# CUDA_VISIBLE_DEVICES=0 python scripts/checkpoint_converters/convert_llama_hf_to_nemo.py \
# --input_name_or_path=/home/TestData/nlp/megatron_llama/llama-ci-hf-tiny \
# --output_path=/tmp/nlp_megatron_llama/llama_ci.nemo \
# --precision=16
# python examples/nlp/language_modeling/megatron_gpt_ptq.py \
# model.restore_from_path=/tmp/nlp_megatron_llama/llama_ci.nemo \
# model.tensor_model_parallel_size=2 \
# trainer.devices=2 \
# quantization.calib_dataset=/home/TestData/nlp/test_quantization/test.json \
# quantization.algorithm=fp8 \
# quantization.num_calib_size=8 \
# inference.batch_size=2 \
# export.inference_tensor_parallel=2 \
# export.sample_output=False \
# export.save_path=/tmp/nlp_megatron_llama_eo/ci_fp8.qnemo
# AFTER_SCRIPT: |
# rm -rf /tmp/nlp_megatron_llama_eo/ci_fp8.qnemo
# # OPTIONAL_L2_QAT_Llama2_INT4:
# # needs: [cicd-test-container-setup]
# # runs-on: self-hosted-azure
# # timeout-minutes: 10
# # container:
# # image: nemoci.azurecr.io/nemo_container:${{ github.run_id }}
# # options:
# # # --user 0:128
# # --device=/dev/nvidia0
# # --gpus all
# # --shm-size=8g
# # --env TRANSFORMERS_OFFLINE=0
# # --env HYDRA_FULL_ERROR=1
# # --volume /mnt/datadrive/TestData:/home/TestData
# # steps:
# # - name: Checkout repository
# # uses: actions/checkout@v4
# # - run: |
# # python examples/nlp/language_modeling/tuning/megatron_gpt_qat.py \
# # quantization.algorithm=int4 \
# # quantization.num_calib_size=8 \
# # trainer.devices=1 \
# # trainer.num_nodes=1 \
# # trainer.max_steps=4 \
# # trainer.val_check_interval=4 \
# # +trainer.limit_val_batches=2 \
# # exp_manager.explicit_log_dir=llama2_qat_results \
# # model.restore_from_path=/home/TestData/nlp/megatron_llama/llama_ci.nemo \
# # model.tensor_model_parallel_size=1 \
# # model.pipeline_model_parallel_size=1 \
# # model.global_batch_size=2 \
# # model.data.train_ds.file_names=[/home/TestData/nlp/megatron_sft/quarel.jsonl] \
# # model.data.train_ds.concat_sampling_probabilities=[1.0] \
# # model.data.validation_ds.file_names=[/home/TestData/nlp/megatron_sft/quarel.jsonl]
# # rm -rf llama2_qat_results
# L2_Distill_Llama2:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Distill_Llama2') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# python examples/nlp/language_modeling/megatron_gpt_distillation.py \
# trainer.devices=2 \
# trainer.num_nodes=1 \
# trainer.precision=bf16 \
# trainer.max_steps=5 \
# trainer.log_every_n_steps=5 \
# trainer.val_check_interval=5 \
# trainer.limit_val_batches=2 \
# model.restore_from_path=/home/TestData/nlp/megatron_llama/llama_ci.nemo \
# model.kd_teacher_restore_from_path=/home/TestData/nlp/megatron_llama/llama_ci.nemo \
# model.tensor_model_parallel_size=2 \
# model.pipeline_model_parallel_size=1 \
# model.micro_batch_size=1 \
# model.global_batch_size=4 \
# model.optim.name=distributed_fused_adam \
# model.optim.sched.warmup_steps=1 \
# model.data.data_prefix=[1.0,/home/TestData/nlp/megatron_gpt/data/gpt/simple_wiki_gpt_preproc_text_document] \
# model.data.index_mapping_dir=examples/nlp/language_modeling/gpt_index_mappings \
# exp_manager.exp_dir=/tmp/megatron_llama_distill
# L2_Prune_Width_Llama2:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Prune_Width_Llama2') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# python examples/nlp/language_modeling/megatron_gpt_prune.py \
# trainer.devices=2 \
# trainer.num_nodes=1 \
# trainer.precision=bf16 \
# model.restore_from_path=/home/TestData/nlp/megatron_llama/llama_ci.nemo \
# model.tensor_model_parallel_size=1 \
# model.pipeline_model_parallel_size=2 \
# prune.num_calib_size=8 \
# prune.ffn_hidden_size=192 \
# prune.num_attention_heads=2 \
# prune.num_query_groups=2 \
# prune.hidden_size=128 \
# export.save_path=/tmp/ci_prune_width.nemo
# L2_Prune_Depth_Llama2:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Prune_Depth_Llama2') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# python examples/nlp/language_modeling/megatron_gpt_prune.py \
# trainer.devices=2 \
# trainer.num_nodes=1 \
# trainer.precision=bf16 \
# model.restore_from_path=/home/TestData/nlp/megatron_llama/llama_ci.nemo \
# model.tensor_model_parallel_size=2 \
# model.pipeline_model_parallel_size=1 \
# 'prune.drop_layers=[1]' \
# export.save_path=/tmp/ci_prune_depth.nemo
# # L2: ASR dev run
# ASR_dev_run_Speech_to_Text:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'ASR_dev_run_Speech_to_Text') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-gpus-1
# SCRIPT: |
# python examples/asr/asr_ctc/speech_to_text_ctc.py \
# model.train_ds.manifest_filepath=/home/TestData/an4_dataset/an4_train.json \
# model.validation_ds.manifest_filepath=/home/TestData/an4_dataset/an4_val.json \
# trainer.devices=1 \
# trainer.accelerator="gpu" \
# +trainer.fast_dev_run=True \
# exp_manager.exp_dir=/tmp/speech_to_text_results
# ASR_dev_run_Speech_to_Text_WPE_-_CitriNet:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'ASR_dev_run_Speech_to_Text_WPE_-_CitriNet') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-gpus-1
# SCRIPT: |
# python examples/asr/asr_ctc/speech_to_text_ctc_bpe.py \
# --config-path="../conf/citrinet/" --config-name="config_bpe" \
# model.train_ds.manifest_filepath=/home/TestData/an4_dataset/an4_train.json \
# model.validation_ds.manifest_filepath=/home/TestData/an4_dataset/an4_val.json \
# model.tokenizer.dir="/home/TestData/asr_tokenizers/an4_wpe_128/" \
# model.tokenizer.type="wpe" \
# trainer.devices=1 \
# trainer.accelerator="gpu" \
# +trainer.fast_dev_run=True \
# exp_manager.exp_dir=/tmp/speech_to_text_wpe_results
# ASR_dev_run_Speech_Pre-training_-_CitriNet:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'ASR_dev_run_Speech_Pre-training_-_CitriNet') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-gpus-1
# SCRIPT: |
# python examples/asr/speech_pretraining/speech_pre_training.py \
# --config-path="../conf/ssl/citrinet/" --config-name="citrinet_ssl_ci" \
# model.train_ds.manifest_filepath=/home/TestData/an4_dataset/an4_train.json \
# model.validation_ds.manifest_filepath=/home/TestData/an4_dataset/an4_val.json \
# trainer.devices=1 \
# trainer.accelerator="gpu" \
# +trainer.fast_dev_run=True \
# exp_manager.exp_dir=/tmp/speech_pre_training_results
# ASR_dev_run_Speech_To_Text_Finetuning:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'ASR_dev_run_Speech_To_Text_Finetuning') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-gpus-1
# SCRIPT: |
# python examples/asr/speech_to_text_finetune.py \
# --config-path="conf/asr_finetune" --config-name="speech_to_text_finetune" \
# model.train_ds.manifest_filepath=/home/TestData/an4_dataset/an4_train.json \
# model.validation_ds.manifest_filepath=/home/TestData/an4_dataset/an4_val.json \
# init_from_nemo_model=/home/TestData/asr/stt_en_fastconformer_transducer_large.nemo \
# model.tokenizer.update_tokenizer=False \
# trainer.devices=1 \
# trainer.accelerator="gpu" \
# +trainer.fast_dev_run=True \
# exp_manager.exp_dir=/tmp/speech_finetuning_results
# ASR_dev_run_Speech_To_Text_HF_Finetuning:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'ASR_dev_run_Speech_To_Text_HF_Finetuning') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-gpus-1
# SCRIPT: |-
# python examples/asr/speech_to_text_finetune.py \
# --config-path="conf/asr_finetune" --config-name="speech_to_text_hf_finetune" \
# ~model.train_ds.hf_data_cfg \
# model.train_ds.num_workers=1 \
# model.train_ds.batch_size=2 model.validation_ds.batch_size=2 \
# model.train_ds.streaming=true \
# +model.train_ds.hf_data_cfg.path="librispeech_asr" \
# +model.train_ds.hf_data_cfg.name=null \
# +model.train_ds.hf_data_cfg.split="test.clean" \
# +model.train_ds.hf_data_cfg.streaming=true \
# +model.train_ds.hf_data_cfg.trust_remote_code=True \
# ~model.validation_ds.hf_data_cfg \
# model.validation_ds.streaming=true \
# +model.validation_ds.hf_data_cfg.path="librispeech_asr" \
# +model.validation_ds.hf_data_cfg.name=null \
# +model.validation_ds.hf_data_cfg.split="test.clean" \
# +model.validation_ds.hf_data_cfg.streaming=true \
# +model.validation_ds.hf_data_cfg.trust_remote_code=True \
# ~model.test_ds \
# init_from_nemo_model=/home/TestData/asr/stt_en_fastconformer_transducer_large.nemo \
# model.tokenizer.update_tokenizer=False \
# model.optim.sched.warmup_steps=0 \
# +model.optim.sched.max_steps=3 \
# trainer.max_epochs=null \
# trainer.devices=1 \
# trainer.accelerator="gpu" \
# +trainer.fast_dev_run=True \
# exp_manager.exp_dir=/tmp/speech_finetuning_results
# ASR_dev_run_Speech_to_Text_WPE_-_Conformer:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'ASR_dev_run_Speech_to_Text_WPE_-_Conformer') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-gpus-1
# SCRIPT: |
# python examples/asr/asr_ctc/speech_to_text_ctc_bpe.py \
# --config-path="../conf/conformer" --config-name="conformer_ctc_bpe" \
# model.train_ds.manifest_filepath=/home/TestData/an4_dataset/an4_train.json \
# model.validation_ds.manifest_filepath=/home/TestData/an4_dataset/an4_val.json \
# model.tokenizer.dir="/home/TestData/asr_tokenizers/an4_wpe_128/" \
# model.tokenizer.type="wpe" \
# model.train_ds.batch_size=4 \
# model.validation_ds.batch_size=4 \
# trainer.devices=1 \
# trainer.accelerator="gpu" \
# +trainer.fast_dev_run=True \
# exp_manager.exp_dir=/tmp/speech_to_text_wpe_conformer_results
# # L2: ASR dev run - part two
# ASR_dev_run-part_two_Speech_to_Text_WPE_-_Squeezeformer:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'ASR_dev_run-part_two_Speech_to_Text_WPE_-_Squeezeformer') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-gpus-1
# SCRIPT: |
# python examples/asr/asr_ctc/speech_to_text_ctc_bpe.py \
# --config-path="../conf/squeezeformer" --config-name="squeezeformer_ctc_bpe" \
# model.train_ds.manifest_filepath=/home/TestData/an4_dataset/an4_train.json \
# model.validation_ds.manifest_filepath=/home/TestData/an4_dataset/an4_val.json \
# model.tokenizer.dir="/home/TestData/asr_tokenizers/an4_wpe_128/" \
# model.tokenizer.type="wpe" \
# model.encoder.d_model=144 \
# model.train_ds.batch_size=4 \
# model.validation_ds.batch_size=4 \
# trainer.devices=1 \
# trainer.accelerator="gpu" \
# +trainer.fast_dev_run=True \
# exp_manager.exp_dir=/tmp/speech_to_text_wpe_squeezeformer_results
# L2_Speech_to_Text_EMA:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Speech_to_Text_EMA') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# python examples/asr/asr_ctc/speech_to_text_ctc.py \
# model.train_ds.manifest_filepath=/home/TestData/an4_dataset/an4_train.json \
# model.validation_ds.manifest_filepath=/home/TestData/an4_dataset/an4_val.json \
# trainer.devices=2 \
# trainer.accelerator="gpu" \
# +trainer.fast_dev_run=True \
# +exp_manager.ema.enable=True \
# exp_manager.exp_dir=/tmp/speech_to_text_results
# L2_Speech_to_Text_AED:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Speech_to_Text_AED') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-gpus-1
# SCRIPT: |
# python examples/asr/speech_multitask/speech_to_text_aed.py \
# model.prompt_format=canary \
# model.model_defaults.asr_enc_hidden=256 \
# model.model_defaults.lm_dec_hidden=256 \
# model.encoder.n_layers=12 \
# model.transf_encoder.num_layers=0 \
# model.transf_decoder.config_dict.num_layers=12 \
# model.train_ds.manifest_filepath=/home/TestData/asr/manifests/canary/an4_canary_train.json \
# model.train_ds.batch_duration=60 \
# model.train_ds.use_bucketing=false \
# model.train_ds.shuffle_buffer_size=100 \
# model.train_ds.num_workers=0 \
# +model.train_ds.text_field="answer" \
# +model.train_ds.lang_field="target_lang" \
# model.validation_ds.manifest_filepath=/home/TestData/asr/manifests/canary/an4_canary_val.json \
# +model.validation_ds.text_field="answer" \
# +model.validation_ds.lang_field="target_lang" \
# model.validation_ds.num_workers=0 \
# model.test_ds.manifest_filepath=/home/TestData/asr/manifests/canary/an4_canary_val.json \
# +model.test_ds.text_field="answer" \
# +model.test_ds.lang_field="target_lang" \
# model.test_ds.num_workers=0 \
# spl_tokens.model_dir=/home/TestData/asr_tokenizers/canary/canary_spl_tokenizer_v32 \
# model.tokenizer.langs.en.dir=/home/TestData/asr_tokenizers/canary/en/tokenizer_spe_bpe_v1024_max_4 \
# model.tokenizer.langs.en.type=bpe \
# ++model.tokenizer.langs.es.dir=/home/TestData/asr_tokenizers/canary/es/tokenizer_spe_bpe_v1024_max_4 \
# ++model.tokenizer.langs.es.type=bpe \
# trainer.devices=1 \
# trainer.accelerator="gpu" \
# +trainer.fast_dev_run=True \
# exp_manager.exp_dir=/tmp/speech_to_text_aed_results
# # L2: Speaker dev run
# L2_Speaker_dev_run_Speaker_Recognition:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Speaker_dev_run_Speaker_Recognition') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-gpus-1
# SCRIPT: |
# python examples/speaker_tasks/recognition/speaker_reco.py \
# model.train_ds.batch_size=10 \
# model.validation_ds.batch_size=2 \
# model.train_ds.manifest_filepath=/home/TestData/an4_speaker/train.json \
# model.validation_ds.manifest_filepath=/home/TestData/an4_speaker/dev.json \
# model.decoder.num_classes=2 \
# trainer.max_epochs=10 \
# trainer.devices=1 \
# trainer.accelerator="gpu" \
# +trainer.fast_dev_run=True \
# exp_manager.exp_dir=/tmp/speaker_recognition_results
# L2_Speaker_dev_run_Speaker_Diarization:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Speaker_dev_run_Speaker_Diarization') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-gpus-1
# SCRIPT: |
# python examples/speaker_tasks/diarization/neural_diarizer/multiscale_diar_decoder.py \
# model.diarizer.speaker_embeddings.model_path=titanet_large \
# model.train_ds.batch_size=5 \
# model.validation_ds.batch_size=5 \
# model.train_ds.emb_dir=examples/speaker_tasks/diarization/speaker_diarization_results \
# model.validation_ds.emb_dir=examples/speaker_tasks/diarization/speaker_diarization_results \
# model.train_ds.manifest_filepath=/home/TestData/an4_diarizer/simulated_train/msdd_data.50step.json \
# model.validation_ds.manifest_filepath=/home/TestData/an4_diarizer/simulated_valid/msdd_data.50step.json \
# trainer.devices=1 \
# trainer.accelerator="gpu" \
# +trainer.fast_dev_run=True \
# exp_manager.exp_dir=/tmp/speaker_diarization_results
# L2_Speaker_dev_run_EndtoEnd_Speaker_Diarization_Sortformer:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Speaker_dev_run_EndtoEnd_Speaker_Diarization_Sortformer') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-gpus-1
# SCRIPT: |
# python examples/speaker_tasks/diarization/neural_diarizer/sortformer_diar_train.py \
# trainer.devices="[0]" \
# batch_size=3 \
# model.train_ds.manifest_filepath=/home/TestData/an4_diarizer/simulated_train/eesd_train_tiny.json \
# model.validation_ds.manifest_filepath=/home/TestData/an4_diarizer/simulated_valid/eesd_valid_tiny.json \
# exp_manager.exp_dir=/tmp/speaker_diarization_results \
# +trainer.fast_dev_run=True
# L2_Speaker_dev_run_EndtoEnd_Diarizer_Inference:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Speaker_dev_run_EndtoEnd_Diarizer_Inference') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# python examples/speaker_tasks/diarization/neural_diarizer/e2e_diarize_speech.py \
# model_path=/home/TestData/an4_diarizer/diar_sortformer_4spk-v1-tiny.nemo \
# dataset_manifest=/home/TestData/an4_diarizer/simulated_valid/eesd_valid_tiny.json \
# batch_size=1
# L2_Speaker_dev_run_Speech_to_Label:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Speaker_dev_run_Speech_to_Label') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-gpus-1
# SCRIPT: |
# python examples/asr/speech_classification/speech_to_label.py \
# model.train_ds.manifest_filepath=/home/TestData/speech_commands/train_manifest.json \
# model.validation_ds.manifest_filepath=/home/TestData/speech_commands/test_manifest.json \
# model.test_ds.manifest_filepath=/home/TestData/speech_commands/test_manifest.json \
# trainer.devices=1 \
# trainer.accelerator="gpu" \
# +trainer.fast_dev_run=True \
# model.preprocessor._target_=nemo.collections.asr.modules.AudioToMelSpectrogramPreprocessor \
# ~model.preprocessor.window_size \
# ~model.preprocessor.window_stride \
# ~model.preprocessor.window \
# ~model.preprocessor.n_mels \
# ~model.preprocessor.n_mfcc \
# ~model.preprocessor.n_fft \
# exp_manager.exp_dir=/tmp/speech_to_label_results
# L2_Speaker_dev_run_Speaker_Diarization_with_ASR_Inference:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Speaker_dev_run_Speaker_Diarization_with_ASR_Inference') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# python examples/speaker_tasks/diarization/clustering_diarizer/offline_diar_with_asr_infer.py \
# diarizer.manifest_filepath=/home/TestData/an4_diarizer/an4_manifest.json \
# diarizer.speaker_embeddings.model_path=/home/TestData/an4_diarizer/spkr.nemo \
# diarizer.speaker_embeddings.parameters.save_embeddings=True \
# diarizer.speaker_embeddings.parameters.window_length_in_sec=[1.5] \
# diarizer.speaker_embeddings.parameters.shift_length_in_sec=[0.75] \
# diarizer.speaker_embeddings.parameters.multiscale_weights=[1.0] \
# diarizer.asr.model_path=QuartzNet15x5Base-En \
# diarizer.asr.parameters.asr_based_vad=True \
# diarizer.out_dir=/tmp/speaker_diarization_asr_results
# L2_Speaker_dev_run_Clustering_Diarizer_Inference:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Speaker_dev_run_Clustering_Diarizer_Inference') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# python examples/speaker_tasks/diarization/clustering_diarizer/offline_diar_infer.py \
# diarizer.manifest_filepath=/home/TestData/an4_diarizer/an4_manifest.json \
# diarizer.speaker_embeddings.model_path=/home/TestData/an4_diarizer/spkr.nemo \
# diarizer.speaker_embeddings.parameters.save_embeddings=True \
# diarizer.speaker_embeddings.parameters.window_length_in_sec=1.5 \
# diarizer.speaker_embeddings.parameters.shift_length_in_sec=0.75 \
# diarizer.speaker_embeddings.parameters.multiscale_weights=null \
# diarizer.vad.model_path=/home/TestData/an4_diarizer/MatchboxNet_VAD_3x2.nemo \
# diarizer.out_dir=/tmp/clustering_diarizer_results
# L2_Speaker_dev_run_Neural_Diarizer_Inference:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Speaker_dev_run_Neural_Diarizer_Inference') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# python examples/speaker_tasks/diarization/neural_diarizer/multiscale_diar_decoder_infer.py \
# diarizer.manifest_filepath=/home/TestData/an4_diarizer/an4_manifest.json \
# diarizer.msdd_model.model_path=/home/TestData/an4_diarizer/diar_msdd_telephonic.nemo \
# diarizer.speaker_embeddings.parameters.save_embeddings=True \
# diarizer.vad.model_path=/home/TestData/an4_diarizer/MatchboxNet_VAD_3x2.nemo \
# diarizer.out_dir=/tmp/neural_diarizer_results
# L2_Speaker_dev_run_Multispeaker_ASR_Data_Simulation:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_Speaker_dev_run_Multispeaker_ASR_Data_Simulation') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure
# SCRIPT: |
# python tools/speech_data_simulator/multispeaker_simulator.py \
# --config-path=conf --config-name=data_simulator.yaml \
# data_simulator.random_seed=42 \
# data_simulator.manifest_filepath=/home/TestData/LibriSpeechShort/dev-clean-align-short.json \
# data_simulator.outputs.output_dir=/tmp/test_simulator \
# data_simulator.session_config.num_sessions=2 \
# data_simulator.session_config.session_length=60
# # L2: ASR Multi-dataloader dev run
# L2_ASR_Multi-dataloader_dev_run_Speech_to_Text_multi-dataloader:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_ASR_Multi-dataloader_dev_run_Speech_to_Text_multi-dataloader') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-gpus-1
# SCRIPT: |
# python examples/asr/asr_ctc/speech_to_text_ctc.py \
# model.train_ds.manifest_filepath=/home/TestData/an4_dataset/an4_train.json \
# model.validation_ds.manifest_filepath=[/home/TestData/an4_dataset/an4_val.json,/home/TestData/an4_dataset/an4_val.json] \
# trainer.devices=1 \
# trainer.accelerator="gpu" \
# trainer.max_epochs=1 \
# trainer.max_steps=1 \
# +trainer.num_sanity_val_steps=1 \
# exp_manager.exp_dir=/tmp/speech_to_text_results
# L2_ASR_Multi-dataloader_dev_run_Speech_to_Label_multi-dataloader:
# needs: [cicd-test-container-setup]
# uses: ./.github/workflows/_test_template.yml
# if: contains(fromJSON(needs.cicd-test-container-setup.outputs.test_to_run), 'L2_ASR_Multi-dataloader_dev_run_Speech_to_Label_multi-dataloader') || needs.cicd-test-container-setup.outputs.all == 'true'
# with:
# RUNNER: self-hosted-azure-gpus-1
# SCRIPT: |
# python examples/asr/speech_classification/speech_to_label.py \
# model.train_ds.manifest_filepath=/home/TestData/speech_commands/train_manifest.json \
# model.validation_ds.manifest_filepath=[/home/TestData/speech_commands/test_manifest.json,/home/TestData/speech_commands/test_manifest.json] \
# trainer.devices=1 \
# trainer.accelerator="gpu" \