reqs

2026-06-27 20:19:35 +08:00 · 2022-11-20 12:44:42 +08:00
parent c8631eb40d
commit d4e0cda175
10 changed files with 1038 additions and 505 deletions
@@ -1,105 +0,0 @@
-# Salesforce Open Source Community Code of Conduct
-
-## About the Code of Conduct
-
-Equality is a core value at Salesforce. We believe a diverse and inclusive
-community fosters innovation and creativity, and are committed to building a
-culture where everyone feels included.
-
-Salesforce open-source projects are committed to providing a friendly, safe, and
-welcoming environment for all, regardless of gender identity and expression,
-sexual orientation, disability, physical appearance, body size, ethnicity, nationality, 
-race, age, religion, level of experience, education, socioeconomic status, or 
-other similar personal characteristics.
-
-The goal of this code of conduct is to specify a baseline standard of behavior so
-that people with different social values and communication styles can work
-together effectively, productively, and respectfully in our open source community.
-It also establishes a mechanism for reporting issues and resolving conflicts.
-
-All questions and reports of abusive, harassing, or otherwise unacceptable behavior
-in a Salesforce open-source project may be reported by contacting the Salesforce
-Open Source Conduct Committee at ossconduct@salesforce.com.
-
-## Our Pledge
-
-In the interest of fostering an open and welcoming environment, we as
-contributors and maintainers pledge to making participation in our project and
-our community a harassment-free experience for everyone, regardless of gender 
-identity and expression, sexual orientation, disability, physical appearance, 
-body size, ethnicity, nationality, race, age, religion, level of experience, education, 
-socioeconomic status, or other similar personal characteristics.
-
-## Our Standards
-
-Examples of behavior that contributes to creating a positive environment
-include:
-
-* Using welcoming and inclusive language
-* Being respectful of differing viewpoints and experiences
-* Gracefully accepting constructive criticism
-* Focusing on what is best for the community
-* Showing empathy toward other community members
-
-Examples of unacceptable behavior by participants include:
-
-* The use of sexualized language or imagery and unwelcome sexual attention or
-advances
-* Personal attacks, insulting/derogatory comments, or trolling
-* Public or private harassment
-* Publishing, or threatening to publish, others' private information—such as
-a physical or electronic address—without explicit permission
-* Other conduct which could reasonably be considered inappropriate in a
-professional setting
-* Advocating for or encouraging any of the above behaviors
-
-## Our Responsibilities
-
-Project maintainers are responsible for clarifying the standards of acceptable
-behavior and are expected to take appropriate and fair corrective action in
-response to any instances of unacceptable behavior.
-
-Project maintainers have the right and responsibility to remove, edit, or
-reject comments, commits, code, wiki edits, issues, and other contributions
-that are not aligned with this Code of Conduct, or to ban temporarily or
-permanently any contributor for other behaviors that they deem inappropriate,
-threatening, offensive, or harmful.
-
-## Scope
-
-This Code of Conduct applies both within project spaces and in public spaces
-when an individual is representing the project or its community. Examples of
-representing a project or community include using an official project email
-address, posting via an official social media account, or acting as an appointed
-representative at an online or offline event. Representation of a project may be
-further defined and clarified by project maintainers.
-
-## Enforcement
-
-Instances of abusive, harassing, or otherwise unacceptable behavior may be
-reported by contacting the Salesforce Open Source Conduct Committee 
-at ossconduct@salesforce.com. All complaints will be reviewed and investigated 
-and will result in a response that is deemed necessary and appropriate to the 
-circumstances. The committee is obligated to maintain confidentiality with 
-regard to the reporter of an incident. Further details of specific enforcement 
-policies may be posted separately.
-
-Project maintainers who do not follow or enforce the Code of Conduct in good
-faith may face temporary or permanent repercussions as determined by other
-members of the project's leadership and the Salesforce Open Source Conduct 
-Committee.
-
-## Attribution
-
-This Code of Conduct is adapted from the [Contributor Covenant][contributor-covenant-home],
-version 1.4, available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html. 
-It includes adaptions and additions from [Go Community Code of Conduct][golang-coc], 
-[CNCF Code of Conduct][cncf-coc], and [Microsoft Open Source Code of Conduct][microsoft-coc].
-
-This Code of Conduct is licensed under the [Creative Commons Attribution 3.0 License][cc-by-3-us].
-
-[contributor-covenant-home]: https://www.contributor-covenant.org (https://www.contributor-covenant.org/)
-[golang-coc]: https://golang.org/conduct
-[cncf-coc]: https://github.com/cncf/foundation/blob/master/code-of-conduct.md
-[microsoft-coc]: https://opensource.microsoft.com/codeofconduct/
-[cc-by-3-us]: https://creativecommons.org/licenses/by/3.0/us/
@@ -1,6 +1,6 @@
 Fork note:

-Interested by the results on the Exchange data I'm digging deeper, plotting, extending, and replicating the exchange reults. See `scratch.ipynb`
+Interested by the results on the Exchange data I'm digging deeper, plotting, extending, and replicating the exchange reults. See `scratch.ipynb` for plots. See mjc_notes for my notes.


 ----
@@ -1,7 +0,0 @@
-## Security
-
-Please report any security issue to [security@salesforce.com](mailto:security@salesforce.com)
-as soon as it is discovered. This library limits its runtime dependencies in
-order to reduce the total cost of ownership as much as can be, but all consumers
-should remain vigilant and have their security stakeholders review all third-party
-products (3PP) like this one and their dependencies.
@@ -1,3 +1,4 @@
+# install environment
 ```sh
 # try with pip torch WORKS!
 export PROJ=deeptime
@@ -7,8 +8,10 @@ mamba install -y ipykernel pip ipywidgets
 pip install torch==1.10.0+cu113 torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113
 # 117 does not exist yet
 python -m ipykernel install --user --name $PROJ
-pip install gin-config fire pandas matplotlib numpy scikit-learn einops tensorboard
+pip install gin-config fire pandas matplotlib numpy scikit-learn einops tensorboard yapf
+pip install tsai

+# note that I've also recorded the env in requirements

 python -m experiments.forecast --config_path=storage/experiments/Exchange/192S/repeat=0/config.gin run >> storage/experiments/Exchange/192S/repeat=0/instance.log 2>&1%
 ```
@@ -0,0 +1,27 @@
+#!/bin/bash
+set -e -x
+# This script will document the requirements for multiple conda environments
+# It will capture the requirements in multiple ways each of which has pros and cons
+
+# inputs
+PROJECT_NAMES='deeptime'
+
+for PROJECT_NAME in $PROJECT_NAMES
+do
+    echo $PROJECT_NAME
+    PYTHON_INTERPRETER=~/miniforge3/envs/$PROJECT_NAME/bin/python
+    # minimal requirement, simpler, but no versions or pip
+    conda env export --no-builds --from-history > requirements/environment.min.yaml
+    # extensive requirements including pip and information overload
+    conda env export > requirements/environment.max.yaml
+    # requirements in a modified pip spec, usefull for dependabot and so on
+    $PYTHON_INTERPRETER -m pip freeze > requirements/pip.conda.txt
+done
+
+# inputs
+for PROJECT_NAME in $PROJECT_NAMES
+do
+    echo $PROJECT_NAME
+    # conda lock is good for not overspecifying version, but it misses pip
+    cd requirements && conda-lock -f environment.max.yaml -p linux-64
+done
@@ -0,0 +1,196 @@
+name: deeptime
+channels:
+  - conda-forge
+  - pytorch
+dependencies:
+  - _libgcc_mutex=0.1=conda_forge
+  - _openmp_mutex=4.5=2_gnu
+  - appdirs=1.4.4=pyh9f0ad1d_0
+  - asttokens=2.1.0=pyhd8ed1ab_0
+  - attrs=22.1.0=pyh71513ae_1
+  - backcall=0.2.0=pyh9f0ad1d_0
+  - backports=1.0=py_2
+  - backports.functools_lru_cache=1.6.4=pyhd8ed1ab_0
+  - brotlipy=0.7.0=py38h0a891b7_1005
+  - bzip2=1.0.8=h7f98852_4
+  - ca-certificates=2022.9.24=ha878542_0
+  - cachecontrol=0.12.12=pyhd8ed1ab_1
+  - cachy=0.3.0=pyhd8ed1ab_1
+  - cffi=1.15.1=py38h4a40e3a_2
+  - charset-normalizer=2.1.1=pyhd8ed1ab_0
+  - click=8.1.3=unix_pyhd8ed1ab_2
+  - click-default-group=1.2.2=pyhd8ed1ab_1
+  - clikit=0.6.2=pyh9f0ad1d_0
+  - conda-lock=1.2.1=pyhd8ed1ab_1
+  - crashtest=0.3.1=pyhd8ed1ab_0
+  - cryptography=38.0.3=py38h80a4ca7_0
+  - dbus=1.13.6=h5008d03_3
+  - debugpy=1.6.3=py38hfa26641_1
+  - decorator=5.1.1=pyhd8ed1ab_0
+  - distlib=0.3.6=pyhd8ed1ab_0
+  - ensureconda=1.4.3=pyhd8ed1ab_0
+  - entrypoints=0.4=pyhd8ed1ab_0
+  - executing=1.2.0=pyhd8ed1ab_0
+  - expat=2.5.0=h27087fc_0
+  - filelock=3.8.0=pyhd8ed1ab_0
+  - gettext=0.21.1=h27087fc_0
+  - html5lib=1.1=pyh9f0ad1d_0
+  - idna=3.4=pyhd8ed1ab_0
+  - importlib-metadata=5.0.0=pyha770c72_1
+  - importlib_metadata=5.0.0=hd8ed1ab_1
+  - importlib_resources=5.10.0=pyhd8ed1ab_0
+  - ipykernel=6.17.1=pyh210e3f2_0
+  - ipython=8.6.0=pyh41d4057_1
+  - ipywidgets=8.0.2=pyhd8ed1ab_1
+  - jaraco.classes=3.2.3=pyhd8ed1ab_0
+  - jedi=0.18.1=pyhd8ed1ab_2
+  - jeepney=0.8.0=pyhd8ed1ab_0
+  - jinja2=3.1.2=pyhd8ed1ab_1
+  - jsonschema=4.17.0=pyhd8ed1ab_0
+  - jupyter_client=7.4.7=pyhd8ed1ab_0
+  - jupyter_core=5.0.0=py38h578d9bd_0
+  - jupyterlab_widgets=3.0.3=pyhd8ed1ab_0
+  - keyring=23.11.0=py38h578d9bd_0
+  - ld_impl_linux-64=2.39=hc81fddc_0
+  - libffi=3.4.2=h7f98852_5
+  - libgcc-ng=12.2.0=h65d4601_19
+  - libglib=2.74.1=h606061b_1
+  - libgomp=12.2.0=h65d4601_19
+  - libiconv=1.17=h166bdaf_0
+  - libnsl=2.0.0=h7f98852_0
+  - libsodium=1.0.18=h36c2ea0_1
+  - libsqlite=3.40.0=h753d276_0
+  - libstdcxx-ng=12.2.0=h46fd767_19
+  - libuuid=2.32.1=h7f98852_1000
+  - libzlib=1.2.13=h166bdaf_4
+  - markupsafe=2.1.1=py38h0a891b7_2
+  - matplotlib-inline=0.1.6=pyhd8ed1ab_0
+  - more-itertools=9.0.0=pyhd8ed1ab_0
+  - msgpack-python=1.0.4=py38h43d8883_1
+  - nbformat=5.7.0=pyhd8ed1ab_0
+  - ncurses=6.3=h27087fc_1
+  - nest-asyncio=1.5.6=pyhd8ed1ab_0
+  - openssl=3.0.7=h166bdaf_0
+  - packaging=21.3=pyhd8ed1ab_0
+  - parso=0.8.3=pyhd8ed1ab_0
+  - pastel=0.2.1=pyhd8ed1ab_0
+  - pcre2=10.40=hc3806b6_0
+  - pexpect=4.8.0=pyh1a96a4e_2
+  - pickleshare=0.7.5=py_1003
+  - pip=22.3.1=pyhd8ed1ab_0
+  - pkginfo=1.8.3=pyhd8ed1ab_0
+  - pkgutil-resolve-name=1.3.10=pyhd8ed1ab_0
+  - platformdirs=2.5.2=pyhd8ed1ab_1
+  - prompt-toolkit=3.0.32=pyha770c72_0
+  - psutil=5.9.4=py38h0a891b7_0
+  - ptyprocess=0.7.0=pyhd3deb0d_0
+  - pure_eval=0.2.2=pyhd8ed1ab_0
+  - pycparser=2.21=pyhd8ed1ab_0
+  - pydantic=1.10.2=py38h0a891b7_1
+  - pygments=2.13.0=pyhd8ed1ab_0
+  - pylev=1.4.0=pyhd8ed1ab_0
+  - pyopenssl=22.1.0=pyhd8ed1ab_0
+  - pyparsing=3.0.9=pyhd8ed1ab_0
+  - pyrsistent=0.19.2=py38h0a891b7_0
+  - pysocks=1.7.1=pyha2e5f31_6
+  - python=3.8.13=ha86cf86_0_cpython
+  - python-dateutil=2.8.2=pyhd8ed1ab_0
+  - python-fastjsonschema=2.16.2=pyhd8ed1ab_0
+  - python_abi=3.8=2_cp38
+  - pyyaml=6.0=py38h0a891b7_5
+  - pyzmq=24.0.1=py38hfc09fa9_1
+  - readline=8.1.2=h0f457ee_0
+  - requests=2.28.1=pyhd8ed1ab_1
+  - ruamel.yaml=0.17.21=py38h0a891b7_2
+  - ruamel.yaml.clib=0.2.7=py38h0a891b7_0
+  - secretstorage=3.3.3=py38h578d9bd_1
+  - setuptools=65.5.1=pyhd8ed1ab_0
+  - six=1.16.0=pyh6c4a22f_0
+  - sqlite=3.40.0=h4ff8645_0
+  - stack_data=0.6.1=pyhd8ed1ab_0
+  - tk=8.6.12=h27826a3_0
+  - tomli=2.0.1=pyhd8ed1ab_0
+  - tomlkit=0.11.6=pyha770c72_0
+  - toolz=0.12.0=pyhd8ed1ab_0
+  - tornado=6.2=py38h0a891b7_1
+  - traitlets=5.5.0=pyhd8ed1ab_0
+  - typing=3.10.0.0=pyhd8ed1ab_0
+  - typing-extensions=4.4.0=hd8ed1ab_0
+  - typing_extensions=4.4.0=pyha770c72_0
+  - virtualenv=20.16.7=py38h578d9bd_0
+  - wcwidth=0.2.5=pyh9f0ad1d_2
+  - webencodings=0.5.1=py_1
+  - wheel=0.38.4=pyhd8ed1ab_0
+  - widgetsnbextension=4.0.3=pyhd8ed1ab_0
+  - xz=5.2.6=h166bdaf_0
+  - yaml=0.2.5=h7f98852_2
+  - zeromq=4.3.4=h9c3ff4c_1
+  - zipp=3.10.0=pyhd8ed1ab_0
+  - pip:
+    - absl-py==1.3.0
+    - blis==0.7.9
+    - cachetools==5.2.0
+    - catalogue==2.0.8
+    - certifi==2022.9.24
+    - confection==0.0.3
+    - contourpy==1.0.6
+    - cycler==0.11.0
+    - cymem==2.0.7
+    - einops==0.6.0
+    - fastai==2.7.10
+    - fastcore==1.5.27
+    - fastdownload==0.0.7
+    - fastprogress==1.0.3
+    - fire==0.4.0
+    - fonttools==4.38.0
+    - gin-config==0.5.0
+    - google-auth==2.14.1
+    - google-auth-oauthlib==0.4.6
+    - grpcio==1.50.0
+    - imbalanced-learn==0.9.1
+    - joblib==1.2.0
+    - kiwisolver==1.4.4
+    - langcodes==3.3.0
+    - llvmlite==0.39.1
+    - markdown==3.4.1
+    - matplotlib==3.6.2
+    - murmurhash==1.0.9
+    - numba==0.56.4
+    - numpy==1.23.4
+    - oauthlib==3.2.2
+    - pandas==1.5.1
+    - pathy==0.8.1
+    - pillow==9.3.0
+    - preshed==3.0.8
+    - protobuf==3.20.3
+    - pyasn1==0.4.8
+    - pyasn1-modules==0.2.8
+    - pyts==0.12.0
+    - pytz==2022.6
+    - requests-oauthlib==1.3.1
+    - rsa==4.9
+    - scikit-learn==1.1.3
+    - scipy==1.9.3
+    - sklearn==0.0.post1
+    - smart-open==5.2.1
+    - spacy==3.4.3
+    - spacy-legacy==3.0.10
+    - spacy-loggers==1.0.3
+    - srsly==2.4.5
+    - tensorboard==2.11.0
+    - tensorboard-data-server==0.6.1
+    - tensorboard-plugin-wit==1.8.1
+    - termcolor==2.1.0
+    - thinc==8.1.5
+    - threadpoolctl==3.1.0
+    - torch==1.10.0+cu113
+    - torchaudio==0.10.0+cu113
+    - torchvision==0.11.1+cu113
+    - tqdm==4.64.1
+    - tsai==0.3.4
+    - typer==0.7.0
+    - urllib3==1.26.12
+    - wasabi==0.10.1
+    - werkzeug==2.2.2
+    - yapf==0.32.0
+prefix: /home/wassname/miniforge3/envs/deeptime
@@ -0,0 +1,13 @@
+name: deeptime
+channels:
+  - conda-forge
+  - pytorch
+dependencies:
+  - python=3.8
+  - ipykernel
+  - pip
+  - ipywidgets
+  - ca-certificates
+  - openssl
+  - conda-lock
+prefix: /home/wassname/miniforge3/envs/deeptime
@@ -0,0 +1,152 @@
+absl-py==1.3.0
+appdirs @ file:///home/conda/feedstock_root/build_artifacts/appdirs_1603108395799/work
+asttokens @ file:///home/conda/feedstock_root/build_artifacts/asttokens_1667325728359/work
+attrs @ file:///home/conda/feedstock_root/build_artifacts/attrs_1659291887007/work
+backcall @ file:///home/conda/feedstock_root/build_artifacts/backcall_1592338393461/work
+backports.functools-lru-cache @ file:///home/conda/feedstock_root/build_artifacts/backports.functools_lru_cache_1618230623929/work
+blis==0.7.9
+brotlipy @ file:///home/conda/feedstock_root/build_artifacts/brotlipy_1666764652625/work
+CacheControl @ file:///home/conda/feedstock_root/build_artifacts/cachecontrol_1666900955882/work
+cachetools==5.2.0
+cachy @ file:///home/conda/feedstock_root/build_artifacts/cachy_1664983268779/work
+catalogue==2.0.8
+certifi==2022.9.24
+cffi @ file:///home/conda/feedstock_root/build_artifacts/cffi_1666754696558/work
+charset-normalizer @ file:///home/conda/feedstock_root/build_artifacts/charset-normalizer_1661170624537/work
+click @ file:///home/conda/feedstock_root/build_artifacts/click_1666798198223/work
+click-default-group @ file:///home/conda/feedstock_root/build_artifacts/click-default-group_1618938707830/work
+clikit @ file:///home/conda/feedstock_root/build_artifacts/clikit_1591735638473/work
+conda_lock @ file:///home/conda/feedstock_root/build_artifacts/conda-lock_1666901122549/work
+confection==0.0.3
+contourpy==1.0.6
+crashtest @ file:///home/conda/feedstock_root/build_artifacts/crashtest_1643220351006/work
+cryptography @ file:///home/conda/feedstock_root/build_artifacts/cryptography_1667422951827/work
+cycler==0.11.0
+cymem==2.0.7
+debugpy @ file:///home/conda/feedstock_root/build_artifacts/debugpy_1666826399851/work
+decorator @ file:///home/conda/feedstock_root/build_artifacts/decorator_1641555617451/work
+distlib @ file:///home/conda/feedstock_root/build_artifacts/distlib_1668356257807/work
+einops==0.6.0
+ensureconda @ file:///home/conda/feedstock_root/build_artifacts/ensureconda_1657719435160/work
+entrypoints @ file:///home/conda/feedstock_root/build_artifacts/entrypoints_1643888246732/work
+executing @ file:///home/conda/feedstock_root/build_artifacts/executing_1667317341051/work
+fastai==2.7.10
+fastcore==1.5.27
+fastdownload==0.0.7
+fastjsonschema @ file:///home/conda/feedstock_root/build_artifacts/python-fastjsonschema_1663619548554/work/dist
+fastprogress==1.0.3
+filelock @ file:///home/conda/feedstock_root/build_artifacts/filelock_1660129891014/work
+fire==0.4.0
+fonttools==4.38.0
+gin-config==0.5.0
+google-auth==2.14.1
+google-auth-oauthlib==0.4.6
+grpcio==1.50.0
+html5lib @ file:///home/conda/feedstock_root/build_artifacts/html5lib_1592930327044/work
+idna @ file:///home/conda/feedstock_root/build_artifacts/idna_1663625384323/work
+imbalanced-learn==0.9.1
+importlib-metadata @ file:///home/conda/feedstock_root/build_artifacts/importlib-metadata_1666781969417/work
+importlib-resources @ file:///home/conda/feedstock_root/build_artifacts/importlib_resources_1665204935269/work
+ipykernel @ file:///home/conda/feedstock_root/build_artifacts/ipykernel_1668027051105/work
+ipython @ file:///home/conda/feedstock_root/build_artifacts/ipython_1667140637743/work
+ipywidgets @ file:///home/conda/feedstock_root/build_artifacts/ipywidgets_1662482321563/work
+jaraco.classes @ file:///home/conda/feedstock_root/build_artifacts/jaraco.classes_1667024629799/work
+jedi @ file:///home/conda/feedstock_root/build_artifacts/jedi_1659959867326/work
+jeepney @ file:///home/conda/feedstock_root/build_artifacts/jeepney_1649085214306/work
+Jinja2 @ file:///home/conda/feedstock_root/build_artifacts/jinja2_1654302431367/work
+joblib==1.2.0
+jsonschema @ file:///home/conda/feedstock_root/build_artifacts/jsonschema-meta_1667361745641/work
+jupyter_client @ file:///home/conda/feedstock_root/build_artifacts/jupyter_client_1668623095912/work
+jupyter_core @ file:///home/conda/feedstock_root/build_artifacts/jupyter_core_1668030817979/work
+jupyterlab-widgets @ file:///home/conda/feedstock_root/build_artifacts/jupyterlab_widgets_1662157840858/work
+keyring @ file:///home/conda/feedstock_root/build_artifacts/keyring_1667696733557/work
+kiwisolver==1.4.4
+langcodes==3.3.0
+llvmlite==0.39.1
+Markdown==3.4.1
+MarkupSafe @ file:///home/conda/feedstock_root/build_artifacts/markupsafe_1666770195345/work
+matplotlib==3.6.2
+matplotlib-inline @ file:///home/conda/feedstock_root/build_artifacts/matplotlib-inline_1660814786464/work
+more-itertools @ file:///home/conda/feedstock_root/build_artifacts/more-itertools_1666110321141/work
+msgpack @ file:///home/conda/feedstock_root/build_artifacts/msgpack-python_1666755129593/work
+murmurhash==1.0.9
+nbformat @ file:///home/conda/feedstock_root/build_artifacts/nbformat_1665426034066/work
+nest-asyncio @ file:///home/conda/feedstock_root/build_artifacts/nest-asyncio_1664684991461/work
+numba==0.56.4
+numpy==1.23.4
+oauthlib==3.2.2
+packaging @ file:///home/conda/feedstock_root/build_artifacts/packaging_1637239678211/work
+pandas==1.5.1
+parso @ file:///home/conda/feedstock_root/build_artifacts/parso_1638334955874/work
+pastel @ file:///home/conda/feedstock_root/build_artifacts/pastel_1640899049124/work
+pathy==0.8.1
+pexpect @ file:///home/conda/feedstock_root/build_artifacts/pexpect_1667297516076/work
+pickleshare @ file:///home/conda/feedstock_root/build_artifacts/pickleshare_1602536217715/work
+Pillow==9.3.0
+pkginfo @ file:///home/conda/feedstock_root/build_artifacts/pkginfo_1654782790443/work
+pkgutil_resolve_name @ file:///home/conda/feedstock_root/build_artifacts/pkgutil-resolve-name_1633981968097/work
+platformdirs @ file:///home/conda/feedstock_root/build_artifacts/platformdirs_1657729053205/work
+preshed==3.0.8
+prompt-toolkit @ file:///home/conda/feedstock_root/build_artifacts/prompt-toolkit_1667565496306/work
+protobuf==3.20.3
+psutil @ file:///home/conda/feedstock_root/build_artifacts/psutil_1667885878918/work
+ptyprocess @ file:///home/conda/feedstock_root/build_artifacts/ptyprocess_1609419310487/work/dist/ptyprocess-0.7.0-py2.py3-none-any.whl
+pure-eval @ file:///home/conda/feedstock_root/build_artifacts/pure_eval_1642875951954/work
+pyasn1==0.4.8
+pyasn1-modules==0.2.8
+pycparser @ file:///home/conda/feedstock_root/build_artifacts/pycparser_1636257122734/work
+pydantic @ file:///home/conda/feedstock_root/build_artifacts/pydantic_1666754940883/work
+Pygments @ file:///home/conda/feedstock_root/build_artifacts/pygments_1660666458521/work
+pylev @ file:///home/conda/feedstock_root/build_artifacts/pylev_1641226376343/work
+pyOpenSSL @ file:///home/conda/feedstock_root/build_artifacts/pyopenssl_1665350324128/work
+pyparsing @ file:///home/conda/feedstock_root/build_artifacts/pyparsing_1652235407899/work
+pyrsistent @ file:///home/conda/feedstock_root/build_artifacts/pyrsistent_1667498687040/work
+PySocks @ file:///home/conda/feedstock_root/build_artifacts/pysocks_1661604839144/work
+python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1626286286081/work
+pyts==0.12.0
+pytz==2022.6
+PyYAML @ file:///home/conda/feedstock_root/build_artifacts/pyyaml_1666772387080/work
+pyzmq @ file:///home/conda/feedstock_root/build_artifacts/pyzmq_1666828534876/work
+requests @ file:///home/conda/feedstock_root/build_artifacts/requests_1661872987712/work
+requests-oauthlib==1.3.1
+rsa==4.9
+ruamel.yaml @ file:///home/conda/feedstock_root/build_artifacts/ruamel.yaml_1666827402316/work
+ruamel.yaml.clib @ file:///home/conda/feedstock_root/build_artifacts/ruamel.yaml.clib_1666808054364/work
+scikit-learn==1.1.3
+scipy==1.9.3
+SecretStorage @ file:///home/conda/feedstock_root/build_artifacts/secretstorage_1666848709093/work
+six @ file:///home/conda/feedstock_root/build_artifacts/six_1620240208055/work
+sklearn==0.0.post1
+smart-open==5.2.1
+spacy==3.4.3
+spacy-legacy==3.0.10
+spacy-loggers==1.0.3
+srsly==2.4.5
+stack-data @ file:///home/conda/feedstock_root/build_artifacts/stack_data_1668260892666/work
+tensorboard==2.11.0
+tensorboard-data-server==0.6.1
+tensorboard-plugin-wit==1.8.1
+termcolor==2.1.0
+thinc==8.1.5
+threadpoolctl==3.1.0
+tomli @ file:///home/conda/feedstock_root/build_artifacts/tomli_1644342247877/work
+tomlkit @ file:///home/conda/feedstock_root/build_artifacts/tomlkit_1666864188602/work
+toolz @ file:///home/conda/feedstock_root/build_artifacts/toolz_1657485559105/work
+torch==1.10.0+cu113
+torchaudio==0.10.0+cu113
+torchvision==0.11.1+cu113
+tornado @ file:///home/conda/feedstock_root/build_artifacts/tornado_1666788592778/work
+tqdm==4.64.1
+traitlets @ file:///home/conda/feedstock_root/build_artifacts/traitlets_1666115969632/work
+tsai==0.3.4
+typer==0.7.0
+typing_extensions @ file:///home/conda/feedstock_root/build_artifacts/typing_extensions_1665144421445/work
+urllib3==1.26.12
+virtualenv @ file:///home/conda/feedstock_root/build_artifacts/virtualenv_1668364244370/work
+wasabi==0.10.1
+wcwidth @ file:///home/conda/feedstock_root/build_artifacts/wcwidth_1600965781394/work
+webencodings==0.5.1
+Werkzeug==2.2.2
+widgetsnbextension @ file:///home/conda/feedstock_root/build_artifacts/widgetsnbextension_1662157836868/work
+yapf==0.32.0
+zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1666647772197/work
@@ -1,194 +0,0 @@
-# %%
-
-import os
-from os.path import join
-import math
-import logging
-from typing import Callable, Optional, Union, Dict, Tuple
-
-from matplotlib import pyplot as plt
-
-import gin
-from fire import Fire
-import numpy as np
-import torch
-from torch.utils.data import DataLoader
-from torch import optim
-from torch import nn
-
-from experiments.base import Experiment
-from data.datasets import ForecastDataset
-from models import get_model
-from utils.checkpoint import Checkpoint
-from utils.ops import default_device, to_tensor
-from utils.losses import get_loss_fn
-from utils.metrics import calc_metrics
-
-from experiments.forecast import get_data
-gin.enter_interactive_mode()
-# %%
-
-
-gin.clear_config()
-# gin.parse_config(open("storage/experiments/Exchange/96M/repeat=0/config.gin"))
-gin.parse_config(open("storage/experiments/Exchange/96Mplus/repeat=0/config.gin"))
-
-# %%
-train_set, train_loader = get_data(flag='train', batch_size=16)
-# x, _, _, _ =train_set[0]
-# x = x * 1.0
-
-# %%
-# x -= x[0]
-# x /= x.std()
-# plt.plot(x)
-# # %%
-
-
-# %%
-model = get_model("deeptime2",
-                    dim_size=train_set.data_x.shape[1],
-                    datetime_feats=train_set.timestamps.shape[-1]).to(default_device())
-model.load_state_dict(torch.load('storage/experiments/Exchange/96Mplus/repeat=0/model.pth'))
-model = model.eval()
-
-# %%
-b = train_set[1]
-b = [bb[None, :] for bb in b]
-x, y, x_time, y_time = map(to_tensor, b)
-with torch.no_grad():
-    forecast = model(x, x_time, y_time)
-# %%
-
-
-# %%
-plt.title('inception inr')
-import matplotlib.colors as mcolors
-colors = list(mcolors.BASE_COLORS.keys())
-l = x.shape[1]
-forecast2 = forecast[0].detach().cpu().numpy()
-x2 = x[0].cpu()
-y2 = y[0].cpu()
-i_past = list(range(l))
-i_future = list(range(l, l*2))
-for i in range(x.shape[-1]):
-    plt.plot(range(l), x2[:, i], c=colors[i])
-for i in range(x.shape[-1]):
-    plt.plot(range(l, l*2), y2[:, i], c=colors[i])
-for i in range(x.shape[-1]):
-    plt.plot(range(l, l*2), forecast2[:, i], c=colors[i], linestyle='--')
-
-# %%
-gin.clear_config()
-gin.parse_config(open("storage/experiments/Exchange/96M/repeat=0/config.gin"))
-
-train_set, train_loader = get_data(flag='train', batch_size=16)
-
-model = get_model("deeptime",
-                    dim_size=train_set.data_x.shape[1],
-                    datetime_feats=train_set.timestamps.shape[-1]).to(default_device())
-model.load_state_dict(torch.load('storage/experiments/Exchange/96M/repeat=0/model.pth'))
-model = model.eval()
-
-
-b = train_set[1]
-b = [bb[None, :] for bb in b]
-x, y, x_time, y_time = map(to_tensor, b)
-with torch.no_grad():
-    forecast = model(x, x_time, y_time)
-
-
-plt.title('mlp inr')
-import matplotlib.colors as mcolors
-colors = list(mcolors.BASE_COLORS.keys())
-l = x.shape[1]
-forecast2 = forecast[0].detach().cpu().numpy()
-x2 = x[0].cpu()
-y2 = y[0].cpu()
-i_past = list(range(l))
-i_future = list(range(l, l*2))
-for i in range(x.shape[-1]):
-    plt.plot(range(l), x2[:, i], c=colors[i])
-for i in range(x.shape[-1]):
-    plt.plot(range(l, l*2), y2[:, i], c=colors[i])
-for i in range(x.shape[-1]):
-    plt.plot(range(l, l*2), forecast2[:, i], c=colors[i], linestyle='--')
-# %%
-
-
-gin.clear_config()
-gin.parse_config(open("storage/experiments/Exchange/96Mplus2/repeat=0/config.gin"))
-
-train_set, train_loader = get_data(flag='train', batch_size=16)
-
-model = get_model("deeptime2",
-                    dim_size=train_set.data_x.shape[1],
-                    datetime_feats=train_set.timestamps.shape[-1]).to(default_device())
-model.load_state_dict(torch.load('storage/experiments/Exchange/96Mplus2/repeat=0/model.pth'))
-model = model.eval()
-
-
-b = train_set[1]
-b = [bb[None, :] for bb in b]
-x, y, x_time, y_time = map(to_tensor, b)
-with torch.no_grad():
-    forecast = model(x, x_time, y_time)
-
-
-plt.title('inception inr')
-import matplotlib.colors as mcolors
-colors = list(mcolors.BASE_COLORS.keys())
-l = x.shape[1]
-forecast2 = forecast[0].detach().cpu().numpy()
-x2 = x[0].cpu()
-y2 = y[0].cpu()
-l2 = y.shape[1]
-i_past = list(range(l))
-i_future = list(range(l, l+l2))
-for i in range(x.shape[-1]):
-    plt.plot(i_past, x2[:, i], c=colors[i])
-for i in range(x.shape[-1]):
-    plt.plot(i_future, y2[:, i], c=colors[i])
-for i in range(x.shape[-1]):
-    plt.plot(i_future, forecast2[:, i], c=colors[i], linestyle='--')
-
-# %%
-
-
-gin.clear_config()
-gin.parse_config(open("storage/experiments/Exchange/96M2/repeat=0/config.gin"))
-
-train_set, train_loader = get_data(flag='train', batch_size=16)
-
-model = get_model("deeptime",
-                    dim_size=train_set.data_x.shape[1],
-                    datetime_feats=train_set.timestamps.shape[-1]).to(default_device())
-model.load_state_dict(torch.load('storage/experiments/Exchange/96M2/repeat=0/model.pth'))
-model = model.eval()
-
-
-b = train_set[1]
-b = [bb[None, :] for bb in b]
-x, y, x_time, y_time = map(to_tensor, b)
-with torch.no_grad():
-    forecast = model(x, x_time, y_time)
-
-
-plt.title('mlp inr2')
-import matplotlib.colors as mcolors
-colors = list(mcolors.BASE_COLORS.keys())
-l = x.shape[1]
-forecast2 = forecast[0].detach().cpu().numpy()
-x2 = x[0].cpu()
-y2 = y[0].cpu()
-l2 = y.shape[1]
-i_past = list(range(l))
-i_future = list(range(l, l+l2))
-for i in range(x.shape[-1]):
-    plt.plot(i_past, x2[:, i], c=colors[i])
-for i in range(x.shape[-1]):
-    plt.plot(i_future, y2[:, i], c=colors[i])
-for i in range(x.shape[-1]):
-    plt.plot(i_future, forecast2[:, i], c=colors[i], linestyle='--')
-
-# %%