diff --git a/.circleci/config.yml b/.circleci/config.yml index 93f523027..23bcc6fe7 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -6,7 +6,7 @@ orbs: executors: python-executor: docker: - - image: cimg/python:3.11.1 + - image: cimg/python:3.11 working_directory: ~/repo @@ -339,53 +339,53 @@ jobs: when: always command: bash <(curl -s https://codecov.io/bash) -cF python -trainer_test2: - <<: *defaults - steps: - - attach_workspace: - at: ~/repo - - restore_cache: # ensure this step occurs *before* installing dependencies - key: requirements-v2-{{ .Branch }}-{{ checksum "requirements.txt" }} - - - run: - name: install dependencies - command: | - pip install pipenv - pip install --force-reinstall --upgrade --quiet -r requirements.txt - pip install coverage - python setup.py develop --no-deps - - save_cache: - key: requirements-v2-{{ .Branch }}-{{ checksum "requirements.txt" }} - paths: - - ~/.local - - - run: - name: Trainer tests 2 - when: always - command: | - echo -e 'running trainer_lstm_test \n ' - coverage run flood_forecast/trainer.py -p tests/lstm_test.json - echo -e 'running trainer_multi_test \n' - coverage run flood_forecast/trainer.py -p tests/multi_test.json - echo -e 'running trainer_full_transformer_test \n' - coverage run flood_forecast/trainer.py -p tests/full_transformer.json - echo -e 'running da_rnn_test \n' - coverage run flood_forecast/trainer.py -p tests/da_rnn.json - echo -e 'running auto test \n' - coverage run flood_forecast/meta_train.py -p tests/auto_encoder.json - echo -e 'running trainer_decoder_test \n' - coverage run flood_forecast/trainer.py -p tests/decoder_test.json - - store_test_results: - path: test-results - - - store_artifacts: - path: test-results - destination: test-results-trainer - - - run: - name: upload results - when: always - command: bash <(curl -s https://codecov.io/bash) -cF python + trainer_test2: + <<: *defaults + steps: + - attach_workspace: + at: ~/repo + - restore_cache: # ensure this step occurs *before* installing dependencies + key: requirements-v2-{{ .Branch }}-{{ checksum "requirements.txt" }} + + - run: + name: install dependencies + command: | + pip install pipenv + pip install --force-reinstall --upgrade --quiet -r requirements.txt + pip install coverage + python setup.py develop --no-deps + - save_cache: + key: requirements-v2-{{ .Branch }}-{{ checksum "requirements.txt" }} + paths: + - ~/.local + + - run: + name: Trainer tests 2 + when: always + command: | + echo -e 'running trainer_lstm_test \n ' + coverage run flood_forecast/trainer.py -p tests/lstm_test.json + echo -e 'running trainer_multi_test \n' + coverage run flood_forecast/trainer.py -p tests/multi_test.json + echo -e 'running trainer_full_transformer_test \n' + coverage run flood_forecast/trainer.py -p tests/full_transformer.json + echo -e 'running da_rnn_test \n' + coverage run flood_forecast/trainer.py -p tests/da_rnn.json + echo -e 'running auto test \n' + coverage run flood_forecast/meta_train.py -p tests/auto_encoder.json + echo -e 'running trainer_decoder_test \n' + coverage run flood_forecast/trainer.py -p tests/decoder_test.json + - store_test_results: + path: test-results + + - store_artifacts: + path: test-results + destination: test-results-trainer + + - run: + name: upload results + when: always + command: bash <(curl -s https://codecov.io/bash) -cF python plot_test: <<: *defaults @@ -458,7 +458,7 @@ workflows: - trainer_test1: requires: - setup_and_install - -trainer_test2: + - trainer_test2: requires: - setup_and_install diff --git a/docs/source/inference.rst b/docs/source/inference.rst index 1fc82cf97..419c4f440 100644 --- a/docs/source/inference.rst +++ b/docs/source/inference.rst @@ -1,9 +1,8 @@ Inference ========================= -This API makes it easy to run inference on trained PyTorchForecast modules. To use this code you -need three main files: your model's configuration file, a CSV containing your data, and a path to -your model weights. +The Flow Forecast Inference API makes it easy to run inference on trained PyTorchForecast modules. To use this code you +need three main files: your model's configuration file, a CSV containing your data, and a path to your model weights. .. code-block:: python :caption: example initialization