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shunping pushed a commit to branch resolution-too-deep
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The following commit(s) were added to refs/heads/resolution-too-deep by this
push:
new 39eb3a9ff26 Change tft upper bound.
39eb3a9ff26 is described below
commit 39eb3a9ff26f77651cb409323d2e379291eb715f
Author: Shunping Huang <[email protected]>
AuthorDate: Mon Jun 29 13:31:39 2026 -0400
Change tft upper bound.
---
.../beam_Inference_Python_Benchmarks_Dataflow.yml | 78 +++++++++++-----------
.../mltransform_generate_vocab_requirements.txt | 6 +-
2 files changed, 42 insertions(+), 42 deletions(-)
diff --git a/.github/workflows/beam_Inference_Python_Benchmarks_Dataflow.yml
b/.github/workflows/beam_Inference_Python_Benchmarks_Dataflow.yml
index 13d48c47df0..2b9d36f11fc 100644
--- a/.github/workflows/beam_Inference_Python_Benchmarks_Dataflow.yml
+++ b/.github/workflows/beam_Inference_Python_Benchmarks_Dataflow.yml
@@ -216,49 +216,49 @@ jobs:
# -PpythonVersion=3.10 \
#
-PloadTest.requirementsTxtFile=apache_beam/ml/inference/table_row_inference_requirements.txt
\
# '-PloadTest.args=${{
env.beam_Inference_Python_Benchmarks_Dataflow_test_arguments_10 }}
--autoscaling_algorithm=THROUGHPUT_BASED --max_num_workers=20
--metrics_table=result_table_row_inference_stream
--influx_measurement=result_table_row_inference_stream --mode=streaming
--input_subscription=projects/apache-beam-testing/subscriptions/table_row_inference_benchmark
--window_size_sec=60 --trigger_interval_sec=30 --timeout_ms=900000
--output_table=apache-beam-testing:beam_run_i [...]
- - name: Debug Dependency Resolution (Dry Run & Deptree)
- shell: bash
- run: |
- echo "=== Setting up Gradle virtualenv ==="
- ./gradlew :sdks:python:apache_beam:testing:load_tests:installGcpTest
--no-daemon \
- -Dorg.gradle.jvmargs=-Xms2g -Dorg.gradle.jvmargs=-Xmx6g
-Dorg.gradle.vfs.watch=false
+ # - name: Debug Dependency Resolution (Dry Run & Deptree)
+ # shell: bash
+ # run: |
+ # echo "=== Setting up Gradle virtualenv ==="
+ # ./gradlew
:sdks:python:apache_beam:testing:load_tests:installGcpTest --no-daemon \
+ # -Dorg.gradle.jvmargs=-Xms2g -Dorg.gradle.jvmargs=-Xmx6g
-Dorg.gradle.vfs.watch=false
- echo "=== Locating virtualenv ==="
- # Find the activate script inside build/gradleenv/
- ACTIVATE_SCRIPT=$(find build/gradleenv/ -name activate | head -n 1)
- if [ -z "$ACTIVATE_SCRIPT" ]; then
- echo "Error: Could not find virtualenv activate script!"
- exit 1
- fi
- echo "Found virtualenv: $ACTIVATE_SCRIPT"
- source "$ACTIVATE_SCRIPT"
+ # echo "=== Locating virtualenv ==="
+ # # Find the activate script inside build/gradleenv/
+ # ACTIVATE_SCRIPT=$(find build/gradleenv/ -name activate | head -n 1)
+ # if [ -z "$ACTIVATE_SCRIPT" ]; then
+ # echo "Error: Could not find virtualenv activate script!"
+ # exit 1
+ # fi
+ # echo "Found virtualenv: $ACTIVATE_SCRIPT"
+ # source "$ACTIVATE_SCRIPT"
- echo "=== Initial Packages in Gradle Env (pip freeze) ==="
- python3 -m pip freeze
+ # echo "=== Initial Packages in Gradle Env (pip freeze) ==="
+ # python3 -m pip freeze
- python3 -m pip install --upgrade pip
- python3 -m pip install pipdeptree
+ # python3 -m pip install --upgrade pip
+ # python3 -m pip install pipdeptree
- echo "=== Running pip install dry-run with report in Gradle env ==="
- # We use --dry-run and --report to see the resolution plan.
- # This might backtrack, so we run it and print the output.
- python3 -m pip install -r
sdks/python/apache_beam/examples/ml_transform/mltransform_generate_vocab_requirements.txt
--dry-run --report report.json -vv || true
- if [ -f report.json ]; then
- cat report.json
- fi
- echo "=== Installed Packages in Gradle Env ==="
- pipdeptree || true
- # - name: run MLTransform Generate Vocab Batch
- # uses: ./.github/actions/gradle-command-self-hosted-action
- # timeout-minutes: 180
- # with:
- # gradle-command: :sdks:python:apache_beam:testing:load_tests:run
- # arguments: |
- #
-PloadTest.mainClass=apache_beam.testing.benchmarks.inference.mltransform_generate_vocab_benchmark
\
- # -Prunner=DataflowRunner \
- # -PpythonVersion=3.10 \
- #
-PloadTest.requirementsTxtFile=apache_beam/examples/ml_transform/mltransform_generate_vocab_requirements.txt
\
- # '-PloadTest.args=${{
env.beam_Inference_Python_Benchmarks_Dataflow_test_arguments_11 }}
--job_name=benchmark-tests-mltransform-generate-vocab-batch-${{env.NOW_UTC}}'
+ # echo "=== Running pip install dry-run with report in Gradle env
==="
+ # # We use --dry-run and --report to see the resolution plan.
+ # # This might backtrack, so we run it and print the output.
+ # python3 -m pip install -r
sdks/python/apache_beam/examples/ml_transform/mltransform_generate_vocab_requirements.txt
--dry-run --report report.json -vv || true
+ # if [ -f report.json ]; then
+ # cat report.json
+ # fi
+ # echo "=== Installed Packages in Gradle Env ==="
+ # pipdeptree || true
+ - name: run MLTransform Generate Vocab Batch
+ uses: ./.github/actions/gradle-command-self-hosted-action
+ timeout-minutes: 180
+ with:
+ gradle-command: :sdks:python:apache_beam:testing:load_tests:run
+ arguments: |
+
-PloadTest.mainClass=apache_beam.testing.benchmarks.inference.mltransform_generate_vocab_benchmark
\
+ -Prunner=DataflowRunner \
+ -PpythonVersion=3.10 \
+
-PloadTest.requirementsTxtFile=apache_beam/examples/ml_transform/mltransform_generate_vocab_requirements.txt
\
+ '-PloadTest.args=${{
env.beam_Inference_Python_Benchmarks_Dataflow_test_arguments_11 }}
--job_name=benchmark-tests-mltransform-generate-vocab-batch-${{env.NOW_UTC}}'
# - name: run MLTransform One-Hot Encoding Batch
# uses: ./.github/actions/gradle-command-self-hosted-action
# timeout-minutes: 180
diff --git
a/sdks/python/apache_beam/examples/ml_transform/mltransform_generate_vocab_requirements.txt
b/sdks/python/apache_beam/examples/ml_transform/mltransform_generate_vocab_requirements.txt
index 4e00b3b4316..290de1ded73 100644
---
a/sdks/python/apache_beam/examples/ml_transform/mltransform_generate_vocab_requirements.txt
+++
b/sdks/python/apache_beam/examples/ml_transform/mltransform_generate_vocab_requirements.txt
@@ -18,9 +18,9 @@
# MLTransform TFT operations need a consistent TensorFlow Transform stack;
# otherwise workers can crash-loop with pandas/numpy ABI mismatches.
google-cloud-monitoring>=2.27.0
-tensorflow_transform>=1.14.0,<1.15.0
-tensorflow-metadata>=1.14.0,<1.15.0
-tfx-bsl>=1.14.0,<1.15.0
+tensorflow_transform>=1.15.0,<1.16.0
+tensorflow-metadata>=1.15.0,<1.16.0
+tfx-bsl>=1.15.0,<1.16.0
numpy<2
pandas<2
dill
