Fix #3609: Remove references to TaskCluster from ci_scripts/

This commit is contained in:
Alexandre Lissy 2021-04-13 16:33:41 +02:00
Родитель f6becabc28
Коммит b578ebe2fc
16 изменённых файлов: 162 добавлений и 162 удалений

74
.github/workflows/macOS-amd64.yml поставляемый
Просмотреть файл

@ -5,8 +5,8 @@ on:
branches:
- master
env:
TASKCLUSTER_TASK_DIR: ${{ github.workspace }}
TASKCLUSTER_ARTIFACTS: ${{ github.workspace }}/artifacts
CI_TASK_DIR: ${{ github.workspace }}
CI_ARTIFACTS_DIR: ${{ github.workspace }}/artifacts
MACOSX_DEPLOYMENT_TARGET: "10.10"
jobs:
swig_macOS:
@ -352,7 +352,7 @@ jobs:
models: ["test", "prod"]
bitrate: ["8k", "16k"]
env:
TASKCLUSTER_TMP_DIR: ${{ github.workspace }}/tmp/
CI_TMP_DIR: ${{ github.workspace }}/tmp/
DEEPSPEECH_PROD_MODEL: https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.3/output_graph.pb
DEEPSPEECH_PROD_MODEL_MMAP: https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.3/output_graph.pbmm
DEEPSPEECH_TEST_MODEL: ${{ github.workspace }}/tmp/output_graph.pb
@ -364,17 +364,17 @@ jobs:
- uses: actions/download-artifact@v2
with:
name: "native_client.${{ matrix.build-flavor }}.tar.xz"
path: ${{ env.TASKCLUSTER_TMP_DIR }}
path: ${{ env.CI_TMP_DIR }}
- run: |
cd ${{ env.TASKCLUSTER_TMP_DIR }}
cd ${{ env.CI_TMP_DIR }}
mkdir ds && cd ds && tar xf ../native_client.tar.xz
- uses: actions/download-artifact@v2
with:
name: "test-model.${{ matrix.build-flavor }}-${{ matrix.bitrate }}.zip"
path: ${{ env.TASKCLUSTER_TMP_DIR }}
path: ${{ env.CI_TMP_DIR }}
if: matrix.models == 'test'
- run: |
ls -hal ${{ env.TASKCLUSTER_TMP_DIR }}/
ls -hal ${{ env.CI_TMP_DIR }}/
if: matrix.models == 'test'
- uses: ./.github/actions/run-tests
with:
@ -394,7 +394,7 @@ jobs:
models: ["test", "prod"]
bitrate: ["8k", "16k"]
env:
TASKCLUSTER_TMP_DIR: ${{ github.workspace }}/tmp/
CI_TMP_DIR: ${{ github.workspace }}/tmp/
DEEPSPEECH_PROD_MODEL: https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.3/output_graph.pb
DEEPSPEECH_PROD_MODEL_MMAP: https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.3/output_graph.pbmm
DEEPSPEECH_TEST_MODEL: ${{ github.workspace }}/tmp/output_graph.pb
@ -409,18 +409,18 @@ jobs:
- uses: actions/download-artifact@v2
with:
name: "deepspeech-${{ matrix.build-flavor }}-${{ matrix.python-version }}.whl"
path: ${{ env.TASKCLUSTER_TMP_DIR }}
path: ${{ env.CI_TMP_DIR }}
- uses: actions/download-artifact@v2
with:
name: "test-model.${{ matrix.build-flavor }}-${{ matrix.bitrate }}.zip"
path: ${{ env.TASKCLUSTER_TMP_DIR }}
path: ${{ env.CI_TMP_DIR }}
if: matrix.models == 'test'
- run: |
ls -hal ${{ env.TASKCLUSTER_TMP_DIR }}/
ls -hal ${{ env.CI_TMP_DIR }}/
if: matrix.models == 'test'
- run: |
ls -hal ${{ env.TASKCLUSTER_TMP_DIR }}/
pip3 install --only-binary :all: --upgrade ${{ env.TASKCLUSTER_TMP_DIR }}/deepspeech*.whl
ls -hal ${{ env.CI_TMP_DIR }}/
pip3 install --only-binary :all: --upgrade ${{ env.CI_TMP_DIR }}/deepspeech*.whl
- uses: ./.github/actions/run-tests
with:
runtime: "python"
@ -469,7 +469,7 @@ jobs:
models: ["test"]
bitrate: ["16k"]
env:
TASKCLUSTER_TMP_DIR: ${{ github.workspace }}/tmp/
CI_TMP_DIR: ${{ github.workspace }}/tmp/
DEEPSPEECH_PROD_MODEL: https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.3/output_graph.pb
DEEPSPEECH_PROD_MODEL_MMAP: https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.3/output_graph.pbmm
DEEPSPEECH_TEST_MODEL: ${{ github.workspace }}/tmp/output_graph.pb
@ -484,18 +484,18 @@ jobs:
- uses: actions/download-artifact@v2
with:
name: "deepspeech_intermediate-${{ matrix.build-flavor }}.tgz"
path: ${{ env.TASKCLUSTER_TMP_DIR }}
path: ${{ env.CI_TMP_DIR }}
- uses: actions/download-artifact@v2
with:
name: "test-model.${{ matrix.build-flavor }}-${{ matrix.bitrate }}.zip"
path: ${{ env.TASKCLUSTER_TMP_DIR }}
path: ${{ env.CI_TMP_DIR }}
if: matrix.models == 'test'
- run: |
ls -hal ${{ env.TASKCLUSTER_TMP_DIR }}/
ls -hal ${{ env.CI_TMP_DIR }}/
if: matrix.models == 'test'
- run: |
ls -hal ${{ env.TASKCLUSTER_TMP_DIR }}/
npm install ${{ env.TASKCLUSTER_TMP_DIR }}/deepspeech*.tgz
ls -hal ${{ env.CI_TMP_DIR }}/
npm install ${{ env.CI_TMP_DIR }}/deepspeech*.tgz
- uses: ./.github/actions/run-tests
with:
runtime: "node"
@ -514,7 +514,7 @@ jobs:
models: ["test"]
bitrate: ["16k"]
env:
TASKCLUSTER_TMP_DIR: ${{ github.workspace }}/tmp/
CI_TMP_DIR: ${{ github.workspace }}/tmp/
DEEPSPEECH_PROD_MODEL: https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.3/output_graph.pb
DEEPSPEECH_PROD_MODEL_MMAP: https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.3/output_graph.pbmm
DEEPSPEECH_TEST_MODEL: ${{ github.workspace }}/tmp/output_graph.pb
@ -529,18 +529,18 @@ jobs:
- uses: actions/download-artifact@v2
with:
name: "deepspeech_intermediate-${{ matrix.build-flavor }}.tgz"
path: ${{ env.TASKCLUSTER_TMP_DIR }}
path: ${{ env.CI_TMP_DIR }}
- uses: actions/download-artifact@v2
with:
name: "test-model.${{ matrix.build-flavor }}-${{ matrix.bitrate }}.zip"
path: ${{ env.TASKCLUSTER_TMP_DIR }}
path: ${{ env.CI_TMP_DIR }}
if: matrix.models == 'test'
- run: |
ls -hal ${{ env.TASKCLUSTER_TMP_DIR }}/
ls -hal ${{ env.CI_TMP_DIR }}/
if: matrix.models == 'test'
- run: |
ls -hal ${{ env.TASKCLUSTER_TMP_DIR }}/
npm install ${{ env.TASKCLUSTER_TMP_DIR }}/deepspeech*.tgz
ls -hal ${{ env.CI_TMP_DIR }}/
npm install ${{ env.CI_TMP_DIR }}/deepspeech*.tgz
- run: |
npm install electron@${{ matrix.electronjs-version }}
- uses: ./.github/actions/run-tests
@ -563,7 +563,7 @@ jobs:
models: ["test", "prod"]
bitrate: ["8k", "16k"]
env:
TASKCLUSTER_TMP_DIR: ${{ github.workspace }}/tmp/
CI_TMP_DIR: ${{ github.workspace }}/tmp/
DEEPSPEECH_PROD_MODEL: https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.3/output_graph.pb
DEEPSPEECH_PROD_MODEL_MMAP: https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.3/output_graph.pbmm
DEEPSPEECH_TEST_MODEL: ${{ github.workspace }}/tmp/output_graph.pb
@ -578,18 +578,18 @@ jobs:
- uses: actions/download-artifact@v2
with:
name: "deepspeech-${{ matrix.build-flavor }}.tgz"
path: ${{ env.TASKCLUSTER_TMP_DIR }}
path: ${{ env.CI_TMP_DIR }}
- uses: actions/download-artifact@v2
with:
name: "test-model.${{ matrix.build-flavor }}-${{ matrix.bitrate }}.zip"
path: ${{ env.TASKCLUSTER_TMP_DIR }}
path: ${{ env.CI_TMP_DIR }}
if: matrix.models == 'test'
- run: |
ls -hal ${{ env.TASKCLUSTER_TMP_DIR }}/
ls -hal ${{ env.CI_TMP_DIR }}/
if: matrix.models == 'test'
- run: |
ls -hal ${{ env.TASKCLUSTER_TMP_DIR }}/
npm install ${{ env.TASKCLUSTER_TMP_DIR }}/deepspeech*.tgz
ls -hal ${{ env.CI_TMP_DIR }}/
npm install ${{ env.CI_TMP_DIR }}/deepspeech*.tgz
- uses: ./.github/actions/run-tests
with:
runtime: "node"
@ -608,7 +608,7 @@ jobs:
models: ["test", "prod"]
bitrate: ["8k", "16k"]
env:
TASKCLUSTER_TMP_DIR: ${{ github.workspace }}/tmp/
CI_TMP_DIR: ${{ github.workspace }}/tmp/
DEEPSPEECH_PROD_MODEL: https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.3/output_graph.pb
DEEPSPEECH_PROD_MODEL_MMAP: https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.3/output_graph.pbmm
DEEPSPEECH_TEST_MODEL: ${{ github.workspace }}/tmp/output_graph.pb
@ -623,18 +623,18 @@ jobs:
- uses: actions/download-artifact@v2
with:
name: "deepspeech-${{ matrix.build-flavor }}.tgz"
path: ${{ env.TASKCLUSTER_TMP_DIR }}
path: ${{ env.CI_TMP_DIR }}
- uses: actions/download-artifact@v2
with:
name: "test-model.${{ matrix.build-flavor }}-${{ matrix.bitrate }}.zip"
path: ${{ env.TASKCLUSTER_TMP_DIR }}
path: ${{ env.CI_TMP_DIR }}
if: matrix.models == 'test'
- run: |
ls -hal ${{ env.TASKCLUSTER_TMP_DIR }}/
ls -hal ${{ env.CI_TMP_DIR }}/
if: matrix.models == 'test'
- run: |
ls -hal ${{ env.TASKCLUSTER_TMP_DIR }}/
npm install ${{ env.TASKCLUSTER_TMP_DIR }}/deepspeech*.tgz
ls -hal ${{ env.CI_TMP_DIR }}/
npm install ${{ env.CI_TMP_DIR }}/deepspeech*.tgz
- run: |
npm install electron@${{ matrix.electronjs-version }}
- uses: ./.github/actions/run-tests

Просмотреть файл

@ -24,26 +24,26 @@ set_ldc_sample_filename()
download_model_prod()
{
local _model_source_file=$(basename "${model_source}")
${WGET} "${model_source}" -O - | gunzip --force > "${TASKCLUSTER_TMP_DIR}/${_model_source_file}"
${WGET} "${model_source}" -O - | gunzip --force > "${CI_TMP_DIR}/${_model_source_file}"
local _model_source_mmap_file=$(basename "${model_source_mmap}")
${WGET} "${model_source_mmap}" -O - | gunzip --force > "${TASKCLUSTER_TMP_DIR}/${_model_source_mmap_file}"
${WGET} "${model_source_mmap}" -O - | gunzip --force > "${CI_TMP_DIR}/${_model_source_mmap_file}"
}
download_data()
{
cp ${DS_DSDIR}/data/smoke_test/*.wav ${TASKCLUSTER_TMP_DIR}/
cp ${DS_DSDIR}/data/smoke_test/pruned_lm.scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer
cp ${DS_DSDIR}/data/smoke_test/pruned_lm.bytes.scorer ${TASKCLUSTER_TMP_DIR}/kenlm.bytes.scorer
cp ${DS_DSDIR}/data/smoke_test/*.wav ${CI_TMP_DIR}/
cp ${DS_DSDIR}/data/smoke_test/pruned_lm.scorer ${CI_TMP_DIR}/kenlm.scorer
cp ${DS_DSDIR}/data/smoke_test/pruned_lm.bytes.scorer ${CI_TMP_DIR}/kenlm.bytes.scorer
cp -R ${DS_DSDIR}/native_client/test ${TASKCLUSTER_TMP_DIR}/test_sources
cp -R ${DS_DSDIR}/native_client/test ${CI_TMP_DIR}/test_sources
}
download_material()
{
download_data
ls -hal ${TASKCLUSTER_TMP_DIR}/${model_name} ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} ${TASKCLUSTER_TMP_DIR}/LDC93S1*.wav
ls -hal ${CI_TMP_DIR}/${model_name} ${CI_TMP_DIR}/${model_name_mmap} ${CI_TMP_DIR}/LDC93S1*.wav
}
maybe_install_xldd()
@ -81,9 +81,9 @@ verify_bazel_rebuild()
exit 1
fi;
mkdir -p ${TASKCLUSTER_ARTIFACTS} || true
mkdir -p ${CI_ARTIFACTS_DIR} || true
cp ${DS_DSDIR}/tensorflow/bazel*.log ${TASKCLUSTER_ARTIFACTS}/
cp ${DS_DSDIR}/tensorflow/bazel*.log ${CI_ARTIFACTS_DIR}/
spurious_rebuilds=$(grep 'Executing action' "${bazel_explain_file}" | grep 'Compiling' | grep -v -E 'no entry in the cache|[for host]|unconditional execution is requested|Executing genrule //native_client:workspace_status|Compiling native_client/workspace_status.cc|Linking native_client/libdeepspeech.so' | wc -l)
if [ "${spurious_rebuilds}" -ne 0 ]; then
@ -95,8 +95,8 @@ verify_bazel_rebuild()
tar xf ${DS_ROOT_TASK}/bazel-ckd-ds.tar --strip-components=4 -C ${DS_DSDIR}/ckd/tensorflow/
echo "Making a diff between CKD files"
mkdir -p ${TASKCLUSTER_ARTIFACTS}
diff -urNw ${DS_DSDIR}/ckd/tensorflow/ ${DS_ROOT_TASK}/ckd/ds/ | tee ${TASKCLUSTER_ARTIFACTS}/ckd.diff
mkdir -p ${CI_ARTIFACTS_DIR}
diff -urNw ${DS_DSDIR}/ckd/tensorflow/ ${DS_ROOT_TASK}/ckd/ds/ | tee ${CI_ARTIFACTS_DIR}/ckd.diff
rm -fr ${DS_DSDIR}/ckd/tensorflow/ ${DS_ROOT_TASK}/ckd/ds/
else

Просмотреть файл

@ -9,9 +9,9 @@ if [ "${OS}" = "Linux" ]; then
export DS_CPU_COUNT=$(nproc)
fi;
if [ "${OS}" = "${TC_MSYS_VERSION}" ]; then
export DS_ROOT_TASK=${TASKCLUSTER_TASK_DIR}
export PYENV_ROOT="${TASKCLUSTER_TASK_DIR}/pyenv-root"
if [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
export DS_ROOT_TASK=${CI_TASK_DIR}
export PYENV_ROOT="${CI_TASK_DIR}/pyenv-root"
export PLATFORM_EXE_SUFFIX=.exe
export DS_CPU_COUNT=$(nproc)
@ -20,15 +20,15 @@ if [ "${OS}" = "${TC_MSYS_VERSION}" ]; then
fi;
if [ "${OS}" = "Darwin" ]; then
export DS_ROOT_TASK=${TASKCLUSTER_TASK_DIR}
export DS_ROOT_TASK=${CI_TASK_DIR}
export DS_CPU_COUNT=$(sysctl hw.ncpu |cut -d' ' -f2)
export PYENV_ROOT="${DS_ROOT_TASK}/pyenv-root"
export HOMEBREW_NO_AUTO_UPDATE=1
export BREW_URL=https://github.com/Homebrew/brew/tarball/2.2.17
export BUILDS_BREW="${TASKCLUSTER_TASK_DIR}/homebrew-builds"
export TESTS_BREW="${TASKCLUSTER_TASK_DIR}/homebrew-tests"
export BUILDS_BREW="${CI_TASK_DIR}/homebrew-builds"
export TESTS_BREW="${CI_TASK_DIR}/homebrew-tests"
export NVM_DIR=$TESTS_BREW/.nvm/ && mkdir -p $NVM_DIR
export PKG_CONFIG_PATH="${BUILDS_BREW}/lib/pkgconfig"
@ -42,12 +42,12 @@ if [ "${OS}" = "Darwin" ]; then
fi;
fi;
export TASKCLUSTER_ARTIFACTS=${TASKCLUSTER_ARTIFACTS:-/tmp/artifacts}
export TASKCLUSTER_TMP_DIR=${TASKCLUSTER_TMP_DIR:-/tmp}
export CI_ARTIFACTS_DIR=${CI_ARTIFACTS_DIR:-/tmp/artifacts}
export CI_TMP_DIR=${CI_TMP_DIR:-/tmp}
export ANDROID_TMP_DIR=/data/local/tmp
mkdir -p ${TASKCLUSTER_TMP_DIR} || true
mkdir -p ${CI_TMP_DIR} || true
export DS_TFDIR=${DS_ROOT_TASK}/tensorflow
export DS_DSDIR=${DS_ROOT_TASK}/
@ -70,7 +70,7 @@ if [ "${OS}" = "Darwin" ]; then
TAR="gtar"
fi
if [ "${OS}" = "${TC_MSYS_VERSION}" ]; then
if [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
WGET=/usr/bin/wget.exe
TAR=/usr/bin/tar.exe
XZ="xz -9 -T0 -c -"

Просмотреть файл

@ -14,7 +14,7 @@ assert_correct_inference()
status=$3
if [ "$status" -ne "0" ]; then
case "$(cat ${TASKCLUSTER_TMP_DIR}/stderr)" in
case "$(cat ${CI_TMP_DIR}/stderr)" in
*"incompatible with minimum version"*)
echo "Prod model too old for client, skipping test."
return 0
@ -22,7 +22,7 @@ assert_correct_inference()
*)
echo "Client failed to run:"
cat ${TASKCLUSTER_TMP_DIR}/stderr
cat ${CI_TMP_DIR}/stderr
return 1
;;
esac
@ -69,7 +69,7 @@ assert_working_inference()
fi;
if [ "$status" -ne "0" ]; then
case "$(cat ${TASKCLUSTER_TMP_DIR}/stderr)" in
case "$(cat ${CI_TMP_DIR}/stderr)" in
*"incompatible with minimum version"*)
echo "Prod model too old for client, skipping test."
return 0
@ -77,7 +77,7 @@ assert_working_inference()
*)
echo "Client failed to run:"
cat ${TASKCLUSTER_TMP_DIR}/stderr
cat ${CI_TMP_DIR}/stderr
return 1
;;
esac
@ -266,7 +266,7 @@ ensure_cuda_usage()
if [ "${_maybe_cuda}" = "cuda" ]; then
set +e
export TF_CPP_MIN_VLOG_LEVEL=1
ds_cuda=$(${DS_BINARY_PREFIX}${DS_BINARY_FILE} --model ${TASKCLUSTER_TMP_DIR}/${model_name} --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>&1 1>/dev/null)
ds_cuda=$(${DS_BINARY_PREFIX}${DS_BINARY_FILE} --model ${CI_TMP_DIR}/${model_name} --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>&1 1>/dev/null)
export TF_CPP_MIN_VLOG_LEVEL=
set -e
@ -278,7 +278,7 @@ ensure_cuda_usage()
check_versions()
{
set +e
ds_help=$(${DS_BINARY_PREFIX}deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name} --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>&1 1>/dev/null)
ds_help=$(${DS_BINARY_PREFIX}deepspeech --model ${CI_TMP_DIR}/${model_name} --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>&1 1>/dev/null)
set -e
assert_tensorflow_version "${ds_help}"
@ -309,12 +309,12 @@ check_runtime_electronjs()
run_tflite_basic_inference_tests()
{
set +e
phrase_pbmodel_nolm=$(${DS_BINARY_PREFIX}deepspeech --model ${DATA_TMP_DIR}/${model_name} --audio ${DATA_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_nolm=$(${DS_BINARY_PREFIX}deepspeech --model ${DATA_TMP_DIR}/${model_name} --audio ${DATA_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr)
set -e
assert_correct_ldc93s1 "${phrase_pbmodel_nolm}" "$?"
set +e
phrase_pbmodel_nolm=$(${DS_BINARY_PREFIX}deepspeech --model ${DATA_TMP_DIR}/${model_name} --audio ${DATA_TMP_DIR}/${ldc93s1_sample_filename} --extended 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_nolm=$(${DS_BINARY_PREFIX}deepspeech --model ${DATA_TMP_DIR}/${model_name} --audio ${DATA_TMP_DIR}/${ldc93s1_sample_filename} --extended 2>${CI_TMP_DIR}/stderr)
set -e
assert_correct_ldc93s1 "${phrase_pbmodel_nolm}" "$?"
}
@ -322,22 +322,22 @@ run_tflite_basic_inference_tests()
run_netframework_inference_tests()
{
set +e
phrase_pbmodel_nolm=$(DeepSpeechConsole.exe --model ${TASKCLUSTER_TMP_DIR}/${model_name} --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_nolm=$(DeepSpeechConsole.exe --model ${CI_TMP_DIR}/${model_name} --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr)
set -e
assert_working_ldc93s1 "${phrase_pbmodel_nolm}" "$?"
set +e
phrase_pbmodel_nolm=$(DeepSpeechConsole.exe --model ${TASKCLUSTER_TMP_DIR}/${model_name} --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} --extended yes 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_nolm=$(DeepSpeechConsole.exe --model ${CI_TMP_DIR}/${model_name} --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} --extended yes 2>${CI_TMP_DIR}/stderr)
set -e
assert_working_ldc93s1 "${phrase_pbmodel_nolm}" "$?"
set +e
phrase_pbmodel_nolm=$(DeepSpeechConsole.exe --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_nolm=$(DeepSpeechConsole.exe --model ${CI_TMP_DIR}/${model_name_mmap} --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr)
set -e
assert_working_ldc93s1 "${phrase_pbmodel_nolm}" "$?"
set +e
phrase_pbmodel_withlm=$(DeepSpeechConsole.exe --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_withlm=$(DeepSpeechConsole.exe --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr)
set -e
assert_working_ldc93s1_lm "${phrase_pbmodel_withlm}" "$?"
}
@ -345,22 +345,22 @@ run_netframework_inference_tests()
run_electronjs_inference_tests()
{
set +e
phrase_pbmodel_nolm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name} --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_nolm=$(deepspeech --model ${CI_TMP_DIR}/${model_name} --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr)
set -e
assert_working_ldc93s1 "${phrase_pbmodel_nolm}" "$?"
set +e
phrase_pbmodel_nolm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name} --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} --extended 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_nolm=$(deepspeech --model ${CI_TMP_DIR}/${model_name} --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} --extended 2>${CI_TMP_DIR}/stderr)
set -e
assert_working_ldc93s1 "${phrase_pbmodel_nolm}" "$?"
set +e
phrase_pbmodel_nolm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_nolm=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr)
set -e
assert_working_ldc93s1 "${phrase_pbmodel_nolm}" "$?"
set +e
phrase_pbmodel_withlm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_withlm=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr)
set -e
assert_working_ldc93s1_lm "${phrase_pbmodel_withlm}" "$?"
}
@ -368,30 +368,30 @@ run_electronjs_inference_tests()
run_basic_inference_tests()
{
set +e
deepspeech --model "" --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr
deepspeech --model "" --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr
set -e
grep "Missing model information" ${TASKCLUSTER_TMP_DIR}/stderr
grep "Missing model information" ${CI_TMP_DIR}/stderr
set +e
phrase_pbmodel_nolm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name} --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_nolm=$(deepspeech --model ${CI_TMP_DIR}/${model_name} --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
assert_correct_ldc93s1 "${phrase_pbmodel_nolm}" "$status"
set +e
phrase_pbmodel_nolm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name} --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} --extended 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_nolm=$(deepspeech --model ${CI_TMP_DIR}/${model_name} --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} --extended 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
assert_correct_ldc93s1 "${phrase_pbmodel_nolm}" "$status"
set +e
phrase_pbmodel_nolm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_nolm=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
assert_correct_ldc93s1 "${phrase_pbmodel_nolm}" "$status"
set +e
phrase_pbmodel_withlm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_withlm=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
assert_correct_ldc93s1_lm "${phrase_pbmodel_withlm}" "$status"
@ -402,13 +402,13 @@ run_all_inference_tests()
run_basic_inference_tests
set +e
phrase_pbmodel_nolm_stereo_44k=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --audio ${TASKCLUSTER_TMP_DIR}/LDC93S1_pcms16le_2_44100.wav 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_nolm_stereo_44k=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --audio ${CI_TMP_DIR}/LDC93S1_pcms16le_2_44100.wav 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
assert_correct_ldc93s1 "${phrase_pbmodel_nolm_stereo_44k}" "$status"
set +e
phrase_pbmodel_withlm_stereo_44k=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/LDC93S1_pcms16le_2_44100.wav 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_withlm_stereo_44k=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/LDC93S1_pcms16le_2_44100.wav 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
assert_correct_ldc93s1_lm "${phrase_pbmodel_withlm_stereo_44k}" "$status"
@ -416,12 +416,12 @@ run_all_inference_tests()
# Run down-sampling warning test only when we actually perform downsampling
if [ "${ldc93s1_sample_filename}" != "LDC93S1_pcms16le_1_8000.wav" ]; then
set +e
phrase_pbmodel_nolm_mono_8k=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --audio ${TASKCLUSTER_TMP_DIR}/LDC93S1_pcms16le_1_8000.wav 2>&1 1>/dev/null)
phrase_pbmodel_nolm_mono_8k=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --audio ${CI_TMP_DIR}/LDC93S1_pcms16le_1_8000.wav 2>&1 1>/dev/null)
set -e
assert_correct_warning_upsampling "${phrase_pbmodel_nolm_mono_8k}"
set +e
phrase_pbmodel_withlm_mono_8k=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/LDC93S1_pcms16le_1_8000.wav 2>&1 1>/dev/null)
phrase_pbmodel_withlm_mono_8k=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/LDC93S1_pcms16le_1_8000.wav 2>&1 1>/dev/null)
set -e
assert_correct_warning_upsampling "${phrase_pbmodel_withlm_mono_8k}"
fi;
@ -432,11 +432,11 @@ run_prod_concurrent_stream_tests()
local _bitrate=$1
set +e
output=$(python3 ${TASKCLUSTER_TMP_DIR}/test_sources/concurrent_streams.py \
--model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} \
--scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer \
--audio1 ${TASKCLUSTER_TMP_DIR}/LDC93S1_pcms16le_1_16000.wav \
--audio2 ${TASKCLUSTER_TMP_DIR}/new-home-in-the-stars-16k.wav 2>${TASKCLUSTER_TMP_DIR}/stderr)
output=$(python3 ${CI_TMP_DIR}/test_sources/concurrent_streams.py \
--model ${CI_TMP_DIR}/${model_name_mmap} \
--scorer ${CI_TMP_DIR}/kenlm.scorer \
--audio1 ${CI_TMP_DIR}/LDC93S1_pcms16le_1_16000.wav \
--audio2 ${CI_TMP_DIR}/new-home-in-the-stars-16k.wav 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
@ -452,19 +452,19 @@ run_prod_inference_tests()
local _bitrate=$1
set +e
phrase_pbmodel_withlm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_withlm=$(deepspeech --model ${CI_TMP_DIR}/${model_name} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
assert_correct_ldc93s1_prodmodel "${phrase_pbmodel_withlm}" "$status" "${_bitrate}"
set +e
phrase_pbmodel_withlm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_withlm=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
assert_correct_ldc93s1_prodmodel "${phrase_pbmodel_withlm}" "$status" "${_bitrate}"
set +e
phrase_pbmodel_withlm_stereo_44k=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/LDC93S1_pcms16le_2_44100.wav 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_withlm_stereo_44k=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/LDC93S1_pcms16le_2_44100.wav 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
assert_correct_ldc93s1_prodmodel_stereo_44k "${phrase_pbmodel_withlm_stereo_44k}" "$status"
@ -472,7 +472,7 @@ run_prod_inference_tests()
# Run down-sampling warning test only when we actually perform downsampling
if [ "${ldc93s1_sample_filename}" != "LDC93S1_pcms16le_1_8000.wav" ]; then
set +e
phrase_pbmodel_withlm_mono_8k=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/LDC93S1_pcms16le_1_8000.wav 2>&1 1>/dev/null)
phrase_pbmodel_withlm_mono_8k=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/LDC93S1_pcms16le_1_8000.wav 2>&1 1>/dev/null)
set -e
assert_correct_warning_upsampling "${phrase_pbmodel_withlm_mono_8k}"
fi;
@ -483,19 +483,19 @@ run_prodtflite_inference_tests()
local _bitrate=$1
set +e
phrase_pbmodel_withlm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_withlm=$(deepspeech --model ${CI_TMP_DIR}/${model_name} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
assert_correct_ldc93s1_prodtflitemodel "${phrase_pbmodel_withlm}" "$status" "${_bitrate}"
set +e
phrase_pbmodel_withlm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_withlm=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
assert_correct_ldc93s1_prodtflitemodel "${phrase_pbmodel_withlm}" "$status" "${_bitrate}"
set +e
phrase_pbmodel_withlm_stereo_44k=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/LDC93S1_pcms16le_2_44100.wav 2>${TASKCLUSTER_TMP_DIR}/stderr)
phrase_pbmodel_withlm_stereo_44k=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/LDC93S1_pcms16le_2_44100.wav 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
assert_correct_ldc93s1_prodtflitemodel_stereo_44k "${phrase_pbmodel_withlm_stereo_44k}" "$status"
@ -503,7 +503,7 @@ run_prodtflite_inference_tests()
# Run down-sampling warning test only when we actually perform downsampling
if [ "${ldc93s1_sample_filename}" != "LDC93S1_pcms16le_1_8000.wav" ]; then
set +e
phrase_pbmodel_withlm_mono_8k=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/LDC93S1_pcms16le_1_8000.wav 2>&1 1>/dev/null)
phrase_pbmodel_withlm_mono_8k=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/LDC93S1_pcms16le_1_8000.wav 2>&1 1>/dev/null)
set -e
assert_correct_warning_upsampling "${phrase_pbmodel_withlm_mono_8k}"
fi;
@ -512,13 +512,13 @@ run_prodtflite_inference_tests()
run_multi_inference_tests()
{
set +e -o pipefail
multi_phrase_pbmodel_nolm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name} --audio ${TASKCLUSTER_TMP_DIR}/ 2>${TASKCLUSTER_TMP_DIR}/stderr | tr '\n' '%')
multi_phrase_pbmodel_nolm=$(deepspeech --model ${CI_TMP_DIR}/${model_name} --audio ${CI_TMP_DIR}/ 2>${CI_TMP_DIR}/stderr | tr '\n' '%')
status=$?
set -e +o pipefail
assert_correct_multi_ldc93s1 "${multi_phrase_pbmodel_nolm}" "$status"
set +e -o pipefail
multi_phrase_pbmodel_withlm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/ 2>${TASKCLUSTER_TMP_DIR}/stderr | tr '\n' '%')
multi_phrase_pbmodel_withlm=$(deepspeech --model ${CI_TMP_DIR}/${model_name} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/ 2>${CI_TMP_DIR}/stderr | tr '\n' '%')
status=$?
set -e +o pipefail
assert_correct_multi_ldc93s1 "${multi_phrase_pbmodel_withlm}" "$status"
@ -528,7 +528,7 @@ run_hotword_tests()
{
DS_BINARY_FILE=${DS_BINARY_FILE:-"deepspeech"}
set +e
hotwords_decode=$(${DS_BINARY_PREFIX}${DS_BINARY_FILE} --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} --hot_words "foo:0.0,bar:-0.1" 2>${TASKCLUSTER_TMP_DIR}/stderr)
hotwords_decode=$(${DS_BINARY_PREFIX}${DS_BINARY_FILE} --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} --hot_words "foo:0.0,bar:-0.1" 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
assert_working_ldc93s1_lm "${hotwords_decode}" "$status"
@ -537,7 +537,7 @@ run_hotword_tests()
run_android_hotword_tests()
{
set +e
hotwords_decode=$(${DS_BINARY_PREFIX}deepspeech --model ${DATA_TMP_DIR}/${model_name} --scorer ${DATA_TMP_DIR}/kenlm.scorer --audio ${DATA_TMP_DIR}/${ldc93s1_sample_filename} --hot_words "foo:0.0,bar:-0.1" 2>${TASKCLUSTER_TMP_DIR}/stderr)
hotwords_decode=$(${DS_BINARY_PREFIX}deepspeech --model ${DATA_TMP_DIR}/${model_name} --scorer ${DATA_TMP_DIR}/kenlm.scorer --audio ${DATA_TMP_DIR}/${ldc93s1_sample_filename} --hot_words "foo:0.0,bar:-0.1" 2>${CI_TMP_DIR}/stderr)
status=$?
set -e
assert_correct_ldc93s1_lm "${hotwords_decode}" "$status"
@ -546,7 +546,7 @@ run_android_hotword_tests()
run_cpp_only_inference_tests()
{
set +e
phrase_pbmodel_withlm_intermediate_decode=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} --stream 1280 2>${TASKCLUSTER_TMP_DIR}/stderr | tail -n 1)
phrase_pbmodel_withlm_intermediate_decode=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} --stream 1280 2>${CI_TMP_DIR}/stderr | tail -n 1)
status=$?
set -e
assert_correct_ldc93s1_lm "${phrase_pbmodel_withlm_intermediate_decode}" "$status"
@ -555,13 +555,13 @@ run_cpp_only_inference_tests()
run_js_streaming_inference_tests()
{
set +e
phrase_pbmodel_withlm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} --stream 2>${TASKCLUSTER_TMP_DIR}/stderr | tail -n 1)
phrase_pbmodel_withlm=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} --stream 2>${CI_TMP_DIR}/stderr | tail -n 1)
status=$?
set -e
assert_correct_ldc93s1_lm "${phrase_pbmodel_withlm}" "$status"
set +e
phrase_pbmodel_withlm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} --stream --extended 2>${TASKCLUSTER_TMP_DIR}/stderr | tail -n 1)
phrase_pbmodel_withlm=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} --stream --extended 2>${CI_TMP_DIR}/stderr | tail -n 1)
status=$?
set -e
assert_correct_ldc93s1_lm "${phrase_pbmodel_withlm}" "$status"
@ -571,14 +571,14 @@ run_js_streaming_prod_inference_tests()
{
local _bitrate=$1
set +e
phrase_pbmodel_withlm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} --stream 2>${TASKCLUSTER_TMP_DIR}/stderr | tail -n 1)
phrase_pbmodel_withlm=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} --stream 2>${CI_TMP_DIR}/stderr | tail -n 1)
status=$?
set -e
assert_correct_ldc93s1_prodmodel "${phrase_pbmodel_withlm}" "$status" "${_bitrate}"
local _bitrate=$1
set +e
phrase_pbmodel_withlm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} --stream --extended 2>${TASKCLUSTER_TMP_DIR}/stderr | tail -n 1)
phrase_pbmodel_withlm=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} --stream --extended 2>${CI_TMP_DIR}/stderr | tail -n 1)
status=$?
set -e
assert_correct_ldc93s1_prodmodel "${phrase_pbmodel_withlm}" "$status" "${_bitrate}"
@ -588,14 +588,14 @@ run_js_streaming_prodtflite_inference_tests()
{
local _bitrate=$1
set +e
phrase_pbmodel_withlm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} --stream 2>${TASKCLUSTER_TMP_DIR}/stderr | tail -n 1)
phrase_pbmodel_withlm=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} --stream 2>${CI_TMP_DIR}/stderr | tail -n 1)
status=$?
set -e
assert_correct_ldc93s1_prodtflitemodel "${phrase_pbmodel_withlm}" "$status" "${_bitrate}"
local _bitrate=$1
set +e
phrase_pbmodel_withlm=$(deepspeech --model ${TASKCLUSTER_TMP_DIR}/${model_name_mmap} --scorer ${TASKCLUSTER_TMP_DIR}/kenlm.scorer --audio ${TASKCLUSTER_TMP_DIR}/${ldc93s1_sample_filename} --stream --extended 2>${TASKCLUSTER_TMP_DIR}/stderr | tail -n 1)
phrase_pbmodel_withlm=$(deepspeech --model ${CI_TMP_DIR}/${model_name_mmap} --scorer ${CI_TMP_DIR}/kenlm.scorer --audio ${CI_TMP_DIR}/${ldc93s1_sample_filename} --stream --extended 2>${CI_TMP_DIR}/stderr | tail -n 1)
status=$?
set -e
assert_correct_ldc93s1_prodtflitemodel "${phrase_pbmodel_withlm}" "$status" "${_bitrate}"

Просмотреть файл

@ -9,9 +9,9 @@ source $(dirname "$0")/asserts.sh
bitrate=$1
set_ldc_sample_filename "${bitrate}"
download_material "${TASKCLUSTER_TMP_DIR}/ds"
download_material "${CI_TMP_DIR}/ds"
export PATH=${TASKCLUSTER_TMP_DIR}/ds/:$PATH
export PATH=${CI_TMP_DIR}/ds/:$PATH
# Bytes output mode with LDC93S1 takes too long to converge so we simply test
# that loading the model won't crash

Просмотреть файл

@ -19,7 +19,7 @@ download_model_prod
download_material
export PATH=${TASKCLUSTER_TMP_DIR}/ds/:$PATH
export PATH=${CI_TMP_DIR}/ds/:$PATH
check_versions

Просмотреть файл

@ -11,7 +11,7 @@ set_ldc_sample_filename "${bitrate}"
download_data
export PATH=${TASKCLUSTER_TMP_DIR}/ds/:$PATH
export PATH=${CI_TMP_DIR}/ds/:$PATH
check_versions

Просмотреть файл

@ -13,13 +13,13 @@ model_source=${DEEPSPEECH_PROD_MODEL//.pb/.tflite}
model_name=$(basename "${model_source}")
model_name_mmap=$(basename "${model_source}")
model_source_mmap=${DEEPSPEECH_PROD_MODEL_MMAP//.pbmm/.tflite}
export DATA_TMP_DIR=${TASKCLUSTER_TMP_DIR}
export DATA_TMP_DIR=${CI_TMP_DIR}
download_model_prod
download_material "${TASKCLUSTER_TMP_DIR}/ds"
download_material "${CI_TMP_DIR}/ds"
export PATH=${TASKCLUSTER_TMP_DIR}/ds/:$PATH
export PATH=${CI_TMP_DIR}/ds/:$PATH
check_versions

Просмотреть файл

@ -12,11 +12,11 @@ set_ldc_sample_filename "${bitrate}"
model_source=${DEEPSPEECH_TEST_MODEL//.pb/.tflite}
model_name=$(basename "${model_source}")
model_name_mmap=$(basename "${model_source}")
export DATA_TMP_DIR=${TASKCLUSTER_TMP_DIR}
export DATA_TMP_DIR=${CI_TMP_DIR}
download_material "${TASKCLUSTER_TMP_DIR}/ds"
download_material "${CI_TMP_DIR}/ds"
export PATH=${TASKCLUSTER_TMP_DIR}/ds/:$PATH
export PATH=${CI_TMP_DIR}/ds/:$PATH
check_versions

Просмотреть файл

@ -11,11 +11,11 @@ set_ldc_sample_filename "${bitrate}"
model_source=${DEEPSPEECH_TEST_MODEL//.pb/.tflite}
model_name=$(basename "${model_source}")
export DATA_TMP_DIR=${TASKCLUSTER_TMP_DIR}
export DATA_TMP_DIR=${CI_TMP_DIR}
download_material "${TASKCLUSTER_TMP_DIR}/ds"
download_material "${CI_TMP_DIR}/ds"
export PATH=${TASKCLUSTER_TMP_DIR}/ds/:$PATH
export PATH=${CI_TMP_DIR}/ds/:$PATH
check_versions

Просмотреть файл

@ -9,9 +9,9 @@ source $(dirname "$0")/asserts.sh
bitrate=$1
set_ldc_sample_filename "${bitrate}"
download_material "${TASKCLUSTER_TMP_DIR}/ds"
download_material "${CI_TMP_DIR}/ds"
export PATH=${TASKCLUSTER_TMP_DIR}/ds/:$PATH
export PATH=${CI_TMP_DIR}/ds/:$PATH
check_versions

Просмотреть файл

@ -6,7 +6,7 @@ package_native_client()
{
tensorflow_dir=${DS_TFDIR}
deepspeech_dir=${DS_DSDIR}
artifacts_dir=${TASKCLUSTER_ARTIFACTS}
artifacts_dir=${CI_ARTIFACTS_DIR}
artifact_name=$1
if [ ! -d ${tensorflow_dir} -o ! -d ${deepspeech_dir} -o ! -d ${artifacts_dir} ]; then
@ -41,7 +41,7 @@ package_native_client_ndk()
{
deepspeech_dir=${DS_DSDIR}
tensorflow_dir=${DS_TFDIR}
artifacts_dir=${TASKCLUSTER_ARTIFACTS}
artifacts_dir=${CI_ARTIFACTS_DIR}
artifact_name=$1
arch_abi=$2
@ -74,7 +74,7 @@ package_native_client_ndk()
package_libdeepspeech_as_zip()
{
tensorflow_dir=${DS_TFDIR}
artifacts_dir=${TASKCLUSTER_ARTIFACTS}
artifacts_dir=${CI_ARTIFACTS_DIR}
artifact_name=$1
if [ ! -d ${tensorflow_dir} -o ! -d ${artifacts_dir} ]; then

Просмотреть файл

@ -5,19 +5,19 @@ set -xe
source $(dirname "$0")/all-vars.sh
source $(dirname "$0")/package-utils.sh
mkdir -p ${TASKCLUSTER_ARTIFACTS} || true
mkdir -p ${CI_ARTIFACTS_DIR} || true
cp ${DS_DSDIR}/tensorflow/bazel*.log ${TASKCLUSTER_ARTIFACTS}/
cp ${DS_DSDIR}/tensorflow/bazel*.log ${CI_ARTIFACTS_DIR}/
package_native_client "native_client.tar.xz"
package_libdeepspeech_as_zip "libdeepspeech.zip"
if [ -d ${DS_DSDIR}/wheels ]; then
cp ${DS_DSDIR}/wheels/* ${TASKCLUSTER_ARTIFACTS}/
cp ${DS_DSDIR}/native_client/javascript/deepspeech-*.tgz ${TASKCLUSTER_ARTIFACTS}/
cp ${DS_DSDIR}/wheels/* ${CI_ARTIFACTS_DIR}/
cp ${DS_DSDIR}/native_client/javascript/deepspeech-*.tgz ${CI_ARTIFACTS_DIR}/
fi;
if [ -f ${DS_DSDIR}/native_client/javascript/wrapper.tar.gz ]; then
cp ${DS_DSDIR}/native_client/javascript/wrapper.tar.gz ${TASKCLUSTER_ARTIFACTS}/
cp ${DS_DSDIR}/native_client/javascript/wrapper.tar.gz ${CI_ARTIFACTS_DIR}/
fi;

Просмотреть файл

@ -4,9 +4,9 @@ set -xe
source $(dirname $0)/tf-vars.sh
mkdir -p ${TASKCLUSTER_ARTIFACTS} || true
mkdir -p ${CI_ARTIFACTS_DIR} || true
cp ${DS_ROOT_TASK}/tensorflow/bazel_*.log ${TASKCLUSTER_ARTIFACTS} || true
cp ${DS_ROOT_TASK}/tensorflow/bazel_*.log ${CI_ARTIFACTS_DIR} || true
OUTPUT_ROOT="${DS_ROOT_TASK}/tensorflow/bazel-bin"
@ -19,12 +19,12 @@ for output_bin in \
tensorflow/lite/toco/toco;
do
if [ -f "${OUTPUT_ROOT}/${output_bin}" ]; then
cp ${OUTPUT_ROOT}/${output_bin} ${TASKCLUSTER_ARTIFACTS}/
cp ${OUTPUT_ROOT}/${output_bin} ${CI_ARTIFACTS_DIR}/
fi;
done;
if [ -f "${OUTPUT_ROOT}/tensorflow/lite/tools/benchmark/benchmark_model" ]; then
cp ${OUTPUT_ROOT}/tensorflow/lite/tools/benchmark/benchmark_model ${TASKCLUSTER_ARTIFACTS}/lite_benchmark_model
cp ${OUTPUT_ROOT}/tensorflow/lite/tools/benchmark/benchmark_model ${CI_ARTIFACTS_DIR}/lite_benchmark_model
fi
# It seems that bsdtar and gnutar are behaving a bit differently on the way
@ -42,21 +42,21 @@ fi;
# - /Users/build-user/TaskCluster/HeavyTasks/X/ (OSX)
# - C:\builds\tc-workdir\ (windows)
if [ "${OS}" = "${TC_MSYS_VERSION}" ]; then
if [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
export PATH=$PATH:'/c/Program Files/7-Zip/'
pushd ${DS_ROOT_TASK}
7z a '-xr!.\dls\' '-xr!.\tmp\' '-xr!.\msys64\' -snl -snh -so home.tar . | 7z a -si ${TASKCLUSTER_ARTIFACTS}/home.tar.xz
7z a '-xr!.\dls\' '-xr!.\tmp\' '-xr!.\msys64\' -snl -snh -so home.tar . | 7z a -si ${CI_ARTIFACTS_DIR}/home.tar.xz
popd
else
${TAR} -C ${DS_ROOT_TASK} ${TAR_EXCLUDE} -cf - . | ${XZ} > ${TASKCLUSTER_ARTIFACTS}/home.tar.xz
${TAR} -C ${DS_ROOT_TASK} ${TAR_EXCLUDE} -cf - . | ${XZ} > ${CI_ARTIFACTS_DIR}/home.tar.xz
fi
if [ "${OS}" = "Linux" ]; then
SHA_SUM_GEN="sha256sum"
elif [ "${OS}" = "${TC_MSYS_VERSION}" ]; then
elif [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
SHA_SUM_GEN="sha256sum"
elif [ "${OS}" = "Darwin" ]; then
SHA_SUM_GEN="shasum -a 256"
fi;
${SHA_SUM_GEN} ${TASKCLUSTER_ARTIFACTS}/* > ${TASKCLUSTER_ARTIFACTS}/checksums.txt
${SHA_SUM_GEN} ${CI_ARTIFACTS_DIR}/* > ${CI_ARTIFACTS_DIR}/checksums.txt

Просмотреть файл

@ -51,7 +51,7 @@ elif [ "${OS}" = "Darwin" ]; then
fi;
mkdir -p ${DS_ROOT_TASK}/bin || true
pushd ${DS_ROOT_TASK}/bin
if [ "${OS}" = "${TC_MSYS_VERSION}" ]; then
if [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
cp ${DS_ROOT_TASK}/dls/${BAZEL_INSTALL_FILENAME} ${DS_ROOT_TASK}/bin/bazel.exe
else
/bin/bash ${DS_ROOT_TASK}/dls/${BAZEL_INSTALL_FILENAME} ${BAZEL_INSTALL_FLAGS}
@ -104,7 +104,7 @@ if [ ! -z "${install_android}" ]; then
popd
fi
mkdir -p ${TASKCLUSTER_ARTIFACTS} || true
mkdir -p ${CI_ARTIFACTS_DIR} || true
# Taken from https://www.tensorflow.org/install/source

Просмотреть файл

@ -26,28 +26,28 @@ if [ "${OS}" = "Linux" ]; then
WGET=/usr/bin/wget
TAR=tar
XZ="pixz -9"
elif [ "${OS}" = "${TC_MSYS_VERSION}" ]; then
if [ -z "${TASKCLUSTER_TASK_DIR}" -o -z "${TASKCLUSTER_ARTIFACTS}" ]; then
elif [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
if [ -z "${CI_TASK_DIR}" -o -z "${CI_ARTIFACTS_DIR}" ]; then
echo "Inconsistent Windows setup: missing some vars."
echo "TASKCLUSTER_TASK_DIR=${TASKCLUSTER_TASK_DIR}"
echo "TASKCLUSTER_ARTIFACTS=${TASKCLUSTER_ARTIFACTS}"
echo "CI_TASK_DIR=${CI_TASK_DIR}"
echo "CI_ARTIFACTS_DIR=${CI_ARTIFACTS_DIR}"
exit 1
fi;
# Re-export with cygpath to make sure it is sane, otherwise it might trigger
# unobvious failures with cp etc.
export TASKCLUSTER_TASK_DIR="$(cygpath ${TASKCLUSTER_TASK_DIR})"
export TASKCLUSTER_ARTIFACTS="$(cygpath ${TASKCLUSTER_ARTIFACTS})"
export CI_TASK_DIR="$(cygpath ${CI_TASK_DIR})"
export CI_ARTIFACTS_DIR="$(cygpath ${CI_ARTIFACTS_DIR})"
export DS_ROOT_TASK=${TASKCLUSTER_TASK_DIR}
export DS_ROOT_TASK=${CI_TASK_DIR}
export BAZEL_VC='C:\Program Files (x86)\Microsoft Visual Studio\2019\BuildTools\VC'
export BAZEL_SH='C:\builds\tc-workdir\msys64\usr\bin\bash'
export TC_WIN_BUILD_PATH='C:\builds\tc-workdir\msys64\usr\bin;C:\Python36'
export MSYS2_ARG_CONV_EXCL='//'
mkdir -p ${TASKCLUSTER_TASK_DIR}/tmp/
export TEMP=${TASKCLUSTER_TASK_DIR}/tmp/
export TMP=${TASKCLUSTER_TASK_DIR}/tmp/
mkdir -p ${CI_TASK_DIR}/tmp/
export TEMP=${CI_TASK_DIR}/tmp/
export TMP=${CI_TASK_DIR}/tmp/
BAZEL_URL=https://github.com/bazelbuild/bazel/releases/download/3.1.0/bazel-3.1.0-windows-x86_64.exe
BAZEL_SHA256=776db1f4986dacc3eda143932f00f7529f9ee65c7c1c004414c44aaa6419d0e9
@ -59,14 +59,14 @@ elif [ "${OS}" = "${TC_MSYS_VERSION}" ]; then
TAR=/usr/bin/tar.exe
XZ="xz -9 -T0"
elif [ "${OS}" = "Darwin" ]; then
if [ -z "${TASKCLUSTER_TASK_DIR}" -o -z "${TASKCLUSTER_ARTIFACTS}" ]; then
if [ -z "${CI_TASK_DIR}" -o -z "${CI_ARTIFACTS_DIR}" ]; then
echo "Inconsistent OSX setup: missing some vars."
echo "TASKCLUSTER_TASK_DIR=${TASKCLUSTER_TASK_DIR}"
echo "TASKCLUSTER_ARTIFACTS=${TASKCLUSTER_ARTIFACTS}"
echo "CI_TASK_DIR=${CI_TASK_DIR}"
echo "CI_ARTIFACTS_DIR=${CI_ARTIFACTS_DIR}"
exit 1
fi;
export DS_ROOT_TASK=${TASKCLUSTER_TASK_DIR}
export DS_ROOT_TASK=${CI_TASK_DIR}
BAZEL_URL=https://github.com/bazelbuild/bazel/releases/download/3.1.0/bazel-3.1.0-installer-darwin-x86_64.sh
BAZEL_SHA256=5cfa97031b43432b3c742c80e2e01c41c0acdca7ba1052fc8cf1e291271bc9cd
@ -79,7 +79,7 @@ fi;
# /tmp/artifacts for docker-worker on linux,
# and task subdir for generic-worker on osx
export TASKCLUSTER_ARTIFACTS=${TASKCLUSTER_ARTIFACTS:-/tmp/artifacts}
export CI_ARTIFACTS_DIR=${CI_ARTIFACTS_DIR:-/tmp/artifacts}
### Define variables that needs to be exported to other processes
@ -98,7 +98,7 @@ fi;
export TF_ENABLE_XLA=0
if [ "${OS}" = "Linux" ]; then
TF_NEED_JEMALLOC=1
elif [ "${OS}" = "${TC_MSYS_VERSION}" ]; then
elif [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
TF_NEED_JEMALLOC=0
elif [ "${OS}" = "Darwin" ]; then
TF_NEED_JEMALLOC=0
@ -119,7 +119,7 @@ export TF_NEED_ROCM=0
# This should be gcc-5, hopefully. CUDA and TensorFlow might not be happy, otherwise.
export GCC_HOST_COMPILER_PATH=/usr/bin/gcc
if [ "${OS}" = "${TC_MSYS_VERSION}" ]; then
if [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
export PYTHON_BIN_PATH=C:/Python36/python.exe
else
if [ "${OS}" = "Linux" ]; then
@ -145,7 +145,7 @@ fi
# Build for generic amd64 platforms, no device-specific optimization
# See https://gcc.gnu.org/onlinedocs/gcc/x86-Options.html for targetting specific CPUs
if [ "${OS}" = "${TC_MSYS_VERSION}" ]; then
if [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
OPT_FLAGS="/arch:AVX"
else
OPT_FLAGS="-mtune=generic -march=x86-64 -msse -msse2 -msse3 -msse4.1 -msse4.2 -mavx"
@ -168,7 +168,7 @@ export BAZEL_OUTPUT_USER_ROOT
NVCC_COMPUTE="3.5"
### Define build parameters/env variables that we will re-ues in sourcing scripts.
if [ "${OS}" = "${TC_MSYS_VERSION}" ]; then
if [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
TF_CUDA_FLAGS="TF_CUDA_CLANG=0 TF_CUDA_VERSION=10.1 TF_CUDNN_VERSION=7.6.0 CUDNN_INSTALL_PATH=\"${CUDA_INSTALL_DIRECTORY}\" TF_CUDA_PATHS=\"${CUDA_INSTALL_DIRECTORY}\" TF_CUDA_COMPUTE_CAPABILITIES=\"${NVCC_COMPUTE}\""
else
TF_CUDA_FLAGS="TF_CUDA_CLANG=0 TF_CUDA_VERSION=10.1 TF_CUDNN_VERSION=7.6.0 CUDNN_INSTALL_PATH=\"${DS_ROOT_TASK}/DeepSpeech/CUDA\" TF_CUDA_PATHS=\"${DS_ROOT_TASK}/DeepSpeech/CUDA\" TF_CUDA_COMPUTE_CAPABILITIES=\"${NVCC_COMPUTE}\""
@ -186,7 +186,7 @@ fi
BAZEL_IOS_ARM64_FLAGS="--config=ios_arm64 --define=runtime=tflite --copt=-DTFLITE_WITH_RUY_GEMV"
BAZEL_IOS_X86_64_FLAGS="--config=ios_x86_64 --define=runtime=tflite --copt=-DTFLITE_WITH_RUY_GEMV"
if [ "${OS}" = "${TC_MSYS_VERSION}" ]; then
if [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
# Somehow, even with Python being in the PATH, Bazel on windows struggles
# with '/usr/bin/env python' ...
#