From 777d8893efcc59d46b5b720747a4909e84e475d0 Mon Sep 17 00:00:00 2001
From: Karthik Prasad <krp@meta.com>
Date: Mon, 4 Nov 2024 07:41:55 -0800
Subject: [PATCH] delete CircleCI configs since GithubActions CI are now live

Summary: Cleanup job after #620

Differential Revision: D53202231
---
 .circleci/config.yml        | 517 ------------------------------------
 .circleci/flake8_config.ini | 119 ---------
 2 files changed, 636 deletions(-)
 delete mode 100644 .circleci/config.yml
 delete mode 100644 .circleci/flake8_config.ini

diff --git a/.circleci/config.yml b/.circleci/config.yml
deleted file mode 100644
index 99f1f43f..00000000
--- a/.circleci/config.yml
+++ /dev/null
@@ -1,517 +0,0 @@
-version: 2.1
-
-# -------------------------------------------------------------------------------------
-# Commands
-# -------------------------------------------------------------------------------------
-
-commands:
-
-  py_3_9_setup:
-    description: "Install and switch to Python 3.9; also install pip and pytest."
-    steps:
-      - run:
-          name: "Setup Python v3.9 environment"
-          command: |
-            cd /opt/circleci/.pyenv && git pull && cd -
-            pyenv install -s 3.9.4
-            pyenv global 3.9.4
-            pyenv local 3.9.4
-            pyenv versions
-            echo "In venv: $(pyenv local) - $(python -V), $(pip -V)"
-            sudo "$(which python)" -m pip install --upgrade pip
-            sudo "$(which python)" -m pip install pytest
-            sudo "$(which python)" -m pip install coverage
-            sudo "$(which python)" -m pip install coveralls
-
-  run_nvidia_smi:
-    description: "Prints GPU capabilities from nvidia-smi"
-    steps:
-      - run:
-          name: "Run Nvidia-SMI"
-          command: |
-            nvidia-smi
-
-  pip_dev_install:
-    description: "Install dependencies via pip, including extra deps. Also supports more options, such as building on top of PyTorch nightly."
-    parameters:
-      args:
-        type: string
-        default: ""
-    steps:
-      - run:
-          name: "Install dependencies via pip"
-          command: ./scripts/install_via_pip.sh << parameters.args >>
-
-  lint_flake8:
-    description: "Lint with flake8"
-    steps:
-      - run:
-          name: "Lint with flake8"
-          command: flake8 --config ./.circleci/flake8_config.ini
-
-  lint_black:
-    description: "Lint with black"
-    steps:
-      - run:
-          name: "Lint with black"
-          command: black --check --diff --color .
-
-  isort:
-    description: "Check import order with isort"
-    steps:
-      - run:
-          name: "Check import order with isort"
-          command: isort -v -l 88 -o opacus --lines-after-imports 2 -m 3 --trailing-comma --check-only .
-
-  unit_tests:
-    description: "Run unit tests"
-    steps:
-      - run:
-          name: "Unit tests & doctests"
-          no_output_timeout: 1h
-          command: |
-            mkdir unittest-reports
-            coverage run -m pytest --doctest-modules -p conftest --junitxml=unittest-reports/junit.xml opacus
-            coverage report -i -m
-
-      - store_test_results:
-          path: unittest-reports
-      - store_artifacts:
-          path: unittest-reports
-
-  command_unit_tests_multi_gpu:
-    description: "Run multi gpu unit tests"
-    steps:
-      - run:
-          name: "Unit test multi_gpu"
-          no_output_timeout: 1h
-          command: |
-            mkdir unittest-multigpu-reports
-            coverage run -m unittest opacus.tests.multigpu_gradcheck.GradientComputationTest.test_gradient_correct
-            coverage report -i -m
-
-  coveralls_upload_parallel:
-    description: "upload coverage to coveralls"
-    steps:
-      - run:
-          name: "coveralls upload"
-          no_output_timeout: 5m
-          command: |
-            pip install coveralls --user
-            COVERALLS_PARALLEL=true COVERALLS_FLAG_NAME="${CIRCLE_JOB}" coveralls
-
-  mnist_integration_test:
-    description: "Runs MNIST example end to end"
-    parameters:
-      device:
-        default: "cpu"
-        type: string
-    steps:
-      - run:
-          name: MNIST example
-          command: |
-            mkdir -p runs/mnist/data
-            mkdir -p runs/mnist/test-reports
-            echo "Using $(python -V) ($(which python))"
-            echo "Using $(pip -V) ($(which pip))"
-            python examples/mnist.py --lr 0.25 --sigma 0.7 -c 1.5 --batch-size 64 --epochs 1 --data-root runs/mnist/data --n-runs 1 --device <<parameters.device>>
-            python -c "import torch; accuracy = torch.load('run_results_mnist_0.25_0.7_1.5_64_1.pt'); exit(0) if (accuracy[0]>0.78 and accuracy[0]<0.95) else exit(1)"
-          when: always
-      - store_test_results:
-          path: runs/mnist/test-reports
-      - store_artifacts:
-          path: runs/mnist/test-reports
-
-  mnist_lightning_integration_test:
-    description: "Runs MNIST-Lightning example end to end"
-    parameters:
-      device:
-        default: "cpu"
-        type: string
-    steps:
-      - run:
-          name: MNIST-Lightning example
-          command: |
-            mkdir -p runs/mnist/data
-            mkdir -p runs/mnist/test-reports
-            echo "Using $(python -V) ($(which python))"
-            echo "Using $(pip -V) ($(which pip))"
-            python examples/mnist_lightning.py fit --trainer.accelerator <<parameters.device>> --model.lr 0.25 --model.sigma 0.7 --model.max_per_sample_grad_norm 1.5 --model.sample_rate 0.004 --trainer.max_epochs 1 --data.data_dir runs/mnist/data --data.sample_rate 0.004
-            python -c "import torch; exit(0)"
-          when: always
-      - store_test_results:
-          path: runs/mnist-lightning/test-reports
-      - store_artifacts:
-          path: runs/mnist-lightning/test-reports
-
-  cifar10_integration_test:
-    description: "Runs CIFAR10 example end to end"
-    parameters:
-      device:
-        default: "cpu"
-        type: string
-    steps:
-      - run:
-          name: CIFAR10 example
-          command: |
-            mkdir -p runs/cifar10/data
-            mkdir -p runs/cifar10/logs
-            mkdir -p runs/cifar10/test-reports
-            echo "Using $(python -V) ($(which python))"
-            echo "Using $(pip -V) ($(which pip))"
-            pip install tensorboard
-            python examples/cifar10.py --lr 0.1 --sigma 1.5 -c 10 --batch-size 2000 --epochs 10 --data-root runs/cifar10/data --log-dir runs/cifar10/logs --device <<parameters.device>>
-            python -c "import torch; model = torch.load('model_best.pth.tar'); exit(0) if (model['best_acc1']>0.4 and model['best_acc1']<0.49) else exit(1)"
-            python examples/cifar10.py --lr 0.1 --sigma 1.5 -c 10 --batch-size 2000 --epochs 10 --data-root runs/cifar10/data --log-dir runs/cifar10/logs --device <<parameters.device>> --grad_sample_mode no_op
-            python -c "import torch; model = torch.load('model_best.pth.tar'); exit(0) if (model['best_acc1']>0.4 and model['best_acc1']<0.49) else exit(1)"
-          when: always
-      - store_test_results:
-          path: runs/cifar10/test-reports
-      - store_artifacts:
-          path: runs/cifar10/test-reports
-
-  dcgan_integration_test:
-    description: "Runs dcgan example end to end"
-    parameters:
-      device:
-        default: "cpu"
-        type: string
-    steps:
-      - run:
-          name: dcgan example
-          command: |
-            mkdir -p runs/dcgan/data
-            mkdir -p runs/dcgan/test-reports
-            echo "Using $(python -V) ($(which python))"
-            echo "Using $(pip -V) ($(which pip))"
-            python examples/dcgan.py --lr 2e-4 --sigma 0.7 -c 1.5 --batch-size 32 --epochs 1 --data-root runs/dcgan/data --device <<parameters.device>>
-          when: always
-      - store_test_results:
-          path: runs/dcgan/test-reports
-      - store_artifacts:
-          path: runs/dcgan/test-reports
-
-  imdb_integration_test:
-    description: "Runs imdb example end to end"
-    parameters:
-      device:
-        default: "cpu"
-        type: string
-    steps:
-      - run:
-          name: imdb example
-          command: |
-            mkdir -p runs/imdb/data
-            mkdir -p runs/imdb/test-reports
-            echo "Using $(python -V) ($(which python))"
-            echo "Using $(pip -V) ($(which pip))"
-            pip install --user datasets transformers
-            python examples/imdb.py --lr 0.02 --sigma 1.0 -c 1.0 --batch-size 64 --max-sequence-length 256 --epochs 2 --data-root runs/imdb/data --device <<parameters.device>>
-            python -c "import torch; accuracy = torch.load('run_results_imdb_classification.pt'); exit(0) if (accuracy>0.54 and accuracy<0.66) else exit(1)"
-          when: always
-      - store_test_results:
-          path: runs/imdb/test-reports
-      - store_artifacts:
-          path: runs/imdb/test-reports
-
-  charlstm_integration_test:
-    description: "Runs charlstm example end to end"
-    parameters:
-      device:
-        default: "cpu"
-        type: string
-    steps:
-      - run:
-          name: charlstm example
-          command: |
-            mkdir -p runs/charlstm/data
-            wget https://download.pytorch.org/tutorial/data.zip -O runs/charlstm/data/data.zip
-            unzip runs/charlstm/data/data.zip -d runs/charlstm/data
-            rm runs/charlstm/data/data.zip
-            mkdir -p runs/charlstm/test-reports
-            echo "Using $(python -V) ($(which python))"
-            echo "Using $(pip -V) ($(which pip))"
-            pip install scikit-learn
-            python examples/char-lstm-classification.py --epochs=20 --learning-rate=2.0 --hidden-size=128 --delta=8e-5 --batch-size 400 --n-layers=1 --sigma=1.0 --max-per-sample-grad-norm=1.5 --data-root="runs/charlstm/data/data/names/" --device=<<parameters.device>> --test-every 5
-            python -c "import torch; accuracy = torch.load('run_results_chr_lstm_classification.pt'); exit(0) if (accuracy>0.60 and accuracy<0.80) else exit(1)"
-          when: always
-      - store_test_results:
-          path: runs/charlstm/test-reports
-      - store_artifacts:
-          path: runs/charlstm/test-reports
-
-  benchmark_layers_integration_test:
-    description: "Runs benchmark end to end"
-    parameters:
-      device:
-        default: "cpu"
-        type: string
-      layers:
-        type: string
-      grad_sample_modes:
-        default: "baseline hooks"
-        type: string
-      report_column:
-        default: "hooks/baseline"
-        type: string
-      runtime_ratio_threshold:
-        type: string
-      memory_ratio_threshold:
-        type: string
-    steps:
-      - run:
-          name: benchmarks
-          command: |
-            mkdir -p benchmarks/results/raw
-            echo "Using $(python -V) ($(which python))"
-            echo "Using $(pip -V) ($(which pip))"
-            python benchmarks/run_benchmarks.py --batch_size 16 --layers <<parameters.layers>> --config_file ./benchmarks/config.json --root ./benchmarks/results/raw/ --cont
-            IFS=$' ';layers=(<<parameters.layers>>); rm -rf /tmp/report_layers; mkdir -p /tmp/report_layers; IFS=$'\n'; files=`( echo "${layers[*]}" ) | sed 's/.*/.\/benchmarks\/results\/raw\/&*/'`
-            cp -v ${files[@]} /tmp/report_layers
-            report_id=`IFS=$'-'; echo "${layers[*]}"`
-            python benchmarks/generate_report.py --path-to-results /tmp/report_layers --save-path benchmarks/results/report-${report_id}.csv --format csv
-            python benchmarks/generate_report.py --path-to-results /tmp/report_layers --save-path benchmarks/results/report-${report_id}.pkl --format pkl
-
-            python benchmarks/check_threshold.py --report-path "./benchmarks/results/report-"$report_id".pkl" --metric runtime --threshold <<parameters.runtime_ratio_threshold>>  --column <<parameters.report_column>>
-          when: always
-      - store_artifacts:
-          path: benchmarks/results/
-# -------------------------------------------------------------------------------------
-# Jobs
-# -------------------------------------------------------------------------------------
-
-jobs:
-
-  lint_py39_torch_release:
-    docker:
-      - image: cimg/python:3.9
-    steps:
-      - checkout
-      - pip_dev_install
-      - lint_flake8
-      - lint_black
-      - isort
-
-  unittest_py38_torch_release:
-    docker:
-      - image: cimg/python:3.8
-    steps:
-      - checkout
-      - pip_dev_install
-      - unit_tests
-
-  unittest_py39_torch_release:
-    docker:
-      - image: cimg/python:3.9
-    steps:
-      - checkout
-      - pip_dev_install
-      - unit_tests
-
-  unittest_py39_torch_nightly:
-    docker:
-      - image: cimg/python:3.9
-    steps:
-      - checkout
-      - pip_dev_install:
-          args: "-n"
-      - unit_tests
-
-  prv_accountant_values:
-    docker:
-      - image: cimg/python:3.9
-    steps:
-      - checkout
-      - py_3_9_setup
-      - pip_dev_install
-      - run:
-          name: "Unit test prv accountant"
-          no_output_timeout: 1h
-          command: |
-            python -m unittest opacus.tests.prv_accountant
-
-  integrationtest_py39_torch_release_cpu:
-    docker:
-      - image: cimg/python:3.9
-    steps:
-      - checkout
-      - py_3_9_setup
-      - pip_dev_install
-      - mnist_integration_test:
-          device: "cpu"
-
-  integrationtest_py39_torch_release_cuda:
-    machine:
-      resource_class: gpu.nvidia.small.multi
-      image: linux-cuda-12:default
-    steps:
-      - checkout
-      - py_3_9_setup
-      - pip_dev_install
-      - run_nvidia_smi
-      - mnist_integration_test:
-          device: "cuda"
-      - cifar10_integration_test:
-          device: "cuda"
-      - imdb_integration_test:
-          device: "cuda"
-      - charlstm_integration_test:
-          device: "cuda"
-      - dcgan_integration_test:
-          device: "cuda"
-
-  micro_benchmarks_py39_torch_release_cuda:
-    machine:
-      resource_class: gpu.nvidia.small.multi
-      image: linux-cuda-12:default
-    steps:
-      - checkout
-      - py_3_9_setup
-      - pip_dev_install
-      - run_nvidia_smi
-      - benchmark_layers_integration_test:
-          device: "cuda"
-          layers: "groupnorm instancenorm layernorm"
-          grad_sample_modes: "baseline hooks"
-          runtime_ratio_threshold: "3.0"
-          memory_ratio_threshold: "1.6"
-      - benchmark_layers_integration_test:
-          device: "cuda"
-          layers: "linear"
-          grad_sample_modes: "baseline hooks"
-          runtime_ratio_threshold: "3.6"
-          memory_ratio_threshold: "13.0"
-      - benchmark_layers_integration_test:
-          device: "cuda"
-          layers: "mha dpmha"
-          report_column: "dp_baseline/baseline"
-          grad_sample_modes: "baseline hooks"
-          runtime_ratio_threshold: "3.0"
-          memory_ratio_threshold: "1.6"
-      - benchmark_layers_integration_test:
-          device: "cuda"
-          layers: "mha dpmha"
-          report_column: "dp_hooks/baseline"
-          grad_sample_modes: "baseline hooks"
-          runtime_ratio_threshold: "3.5"
-          memory_ratio_threshold: "2.0"
-      - benchmark_layers_integration_test:
-          device: "cuda"
-          layers: "gru dpgru"
-          report_column: "dp_baseline/baseline"
-          grad_sample_modes: "baseline hooks"
-          runtime_ratio_threshold: "55.2"
-          memory_ratio_threshold: "1.2"
-      - benchmark_layers_integration_test:
-          device: "cuda"
-          layers: "gru dpgru"
-          report_column: "dp_hooks/baseline"
-          grad_sample_modes: "baseline hooks"
-          runtime_ratio_threshold: "140"
-          memory_ratio_threshold: "1.6"
-      - benchmark_layers_integration_test:
-          device: "cuda"
-          layers: "lstm dplstm"
-          report_column: "dp_baseline/baseline"
-          grad_sample_modes: "baseline hooks"
-          runtime_ratio_threshold: "48.6"
-          memory_ratio_threshold: "1.2"
-      - benchmark_layers_integration_test:
-          device: "cuda"
-          layers: "lstm dplstm"
-          report_column: "dp_hooks/baseline"
-          grad_sample_modes: "baseline hooks"
-          runtime_ratio_threshold: "126.0"
-          memory_ratio_threshold: "1.8"
-      - benchmark_layers_integration_test:
-          device: "cuda"
-          layers: "rnn dprnn"
-          report_column: "dp_baseline/baseline"
-          grad_sample_modes: "baseline hooks"
-          runtime_ratio_threshold: "21.4"
-          memory_ratio_threshold: "1.2"
-      - benchmark_layers_integration_test:
-          device: "cuda"
-          layers: "rnn dprnn"
-          report_column: "dp_hooks/baseline"
-          grad_sample_modes: "baseline hooks"
-          runtime_ratio_threshold: "98.5"
-          memory_ratio_threshold: "1.2"
-      - benchmark_layers_integration_test:
-          device: "cuda"
-          layers: "embedding"
-          grad_sample_modes: "baseline hooks"
-          runtime_ratio_threshold: "8.0"
-          memory_ratio_threshold: "15.0"
-
-  unittest_multi_gpu:
-    machine:
-      resource_class: gpu.nvidia.medium.multi
-      image: linux-cuda-12:default
-    steps:
-      - checkout
-      - py_3_9_setup
-      - pip_dev_install
-      - run_nvidia_smi
-      - command_unit_tests_multi_gpu
-
-  finish_coveralls_parallel:
-    docker:
-      - image: cimg/python:3.9
-    steps:
-      - run:
-          name: "finish coveralls parallel"
-          no_output_timeout: 5m
-          command: |
-            pip install coveralls --user
-            coveralls --finish
-
-
-aliases:
-
-  - &exclude_ghpages
-    branches:
-      ignore:
-        - gh-pages
-
-# -------------------------------------------------------------------------------------
-# Workflows
-# -------------------------------------------------------------------------------------
-
-workflows:
-  commit:
-    when:
-      not:
-        equal: [ scheduled_pipeline, << pipeline.trigger_source >> ]
-    jobs:
-      - lint_py39_torch_release:
-          filters: *exclude_ghpages
-      - unittest_py38_torch_release:
-          filters: *exclude_ghpages
-      - unittest_py39_torch_release:
-          filters: *exclude_ghpages
-      - unittest_py39_torch_nightly:
-          filters: *exclude_ghpages
-      - unittest_multi_gpu:
-          filters: *exclude_ghpages
-      - integrationtest_py39_torch_release_cpu:
-          filters: *exclude_ghpages
-      - integrationtest_py39_torch_release_cuda:
-          filters: *exclude_ghpages
-      - prv_accountant_values:
-          filters: *exclude_ghpages
-
-  nightly:
-    when:
-      equal: [ scheduled_pipeline, << pipeline.trigger_source >> ]
-    jobs:
-      - unittest_py39_torch_nightly:
-          filters: *exclude_ghpages
-      - integrationtest_py39_torch_release_cpu:
-          filters: *exclude_ghpages
-      - integrationtest_py39_torch_release_cuda:
-          filters: *exclude_ghpages
-      - lint_py39_torch_release:
-          filters: *exclude_ghpages
-      - micro_benchmarks_py39_torch_release_cuda:
-          filters: *exclude_ghpages
diff --git a/.circleci/flake8_config.ini b/.circleci/flake8_config.ini
deleted file mode 100644
index 988ed7f3..00000000
--- a/.circleci/flake8_config.ini
+++ /dev/null
@@ -1,119 +0,0 @@
-[flake8]
-select = B,C,E,F,P,W,B9
-max-line-length = 80
-# Main Explanation Docs: https://github.com/grantmcconnaughey/Flake8Rules
-ignore =
-  # Black conflicts and overlaps.
-  # Found in https://github.com/psf/black/issues/429
-  # B950: Line too long. (Use `arc lint`'s LINEWRAP instead)
-  B950,
-  # E111: Indentation is not a multiple of four.
-  E111,
-  # E115: Expected an indented block (comment).
-  E115,
-  # E117: Over-indented.
-  E117,
-  # E121: Continuation line under-indented for hanging indent.
-  E121,
-  # E122: Continuation line missing indentation or outdented.
-  E122,
-  # E123: Closing bracket does not match indentation of opening bracket's line.
-  E123,
-  # E124: Closing bracket does not match visual indentation.
-  E124,
-  # E125: Continuation line with same indent as next logical line.
-  E125,
-  # E126: Continuation line over-indented for hanging indent.
-  E126,
-  # E127: Continuation line over-indented for visual indent.
-  E127,
-  # E128: Continuation line under-indented for visual indent.
-  E128,
-  # E129: Visually indented line with same indent as next logical line.
-  E129,
-  # E201: Whitespace after '('.
-  E201,
-  # E202: Whitespace before ')'.
-  E202,
-  # E203: Whitespace before ':'.
-  E203,
-  # E221: Multiple spaces before operator.
-  E221,
-  # E222: Multiple spaces after operator.
-  E222,
-  # E225: Missing whitespace around operator.
-  E225,
-  # E226: Missing whitespace around arithmetic operator.
-  E226,
-  # E227: Missing whitespace around bitwise or shift operator.
-  E227,
-  # E231: Missing whitespace after ',', ';', or ':'.
-  E231,
-  # E241: Multiple spaces after ','.
-  E241,
-  # E251: Unexpected spaces around keyword / parameter equals.
-  E251,
-  # E261: At least two spaces before inline comment.
-  E261,
-  # E262: Inline comment should start with '# '.
-  E262,
-  # E265: Block comment should start with '# '.
-  E265,
-  # E271: Multiple spaces after keyword.
-  E271,
-  # E272: Multiple spaces before keyword.
-  E272,
-  # E301: Expected 1 blank line, found 0.
-  E301,
-  # E302: Expected 2 blank lines, found 0.
-  E302,
-  # E303: Too many blank lines (3).
-  E303,
-  # E305: Expected 2 blank lines after end of function or class.
-  E305,
-  # E306: Expected 1 blank line before a nested definition.
-  E306,
-  # E501: Line too long (82 > 79 characters).
-  E501,
-  # E502: The backslash is redundant between brackets.
-  E502,
-  # E701: Multiple statements on one line (colon).
-  E701,
-  # E702: Multiple statements on one line (semicolon).
-  E702,
-  # E703: Statement ends with a semicolon.
-  E703,
-  # E704: Multiple statements on one line (def).
-  E704,
-  # W291: Trailing whitespace.
-  W291,
-  # W292: No newline at end of file.
-  W292,
-  # W293: Blank line contains whitespace.
-  W293,
-  # W391: Blank line at end of file.
-  W391,
-
-  # Too opinionated.
-  # E265: Block comment should start with '# '.
-  E265,
-  # E266: Too many leading '#' for block comment.
-  E266,
-  # E402: Module level import not at top of file.
-  E402,
-  # E722: Do not use bare except, specify exception instead. (Duplicate of B001)
-  E722,
-  # F811: Redefinition of unused name from line n.
-  F811,
-  # P207: (Duplicate of B003)
-  P207,
-  # P208: (Duplicate of C403)
-  P208,
-  # W503: Line break occurred before a binary operator.
-  W503
-
-exclude =
-  .hg,
-  __pycache__,
-
-max-complexity = 12