Microservices-Based-Algorithmic-Trading-System
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Upgrade: Bump mlflow from 1.4.0 to 2.3.1 in /dockerfile_mlflowserver
Bumps mlflow from 1.4.0 to 2.3.1.
Release notes
Sourced from mlflow's releases.
MLflow 2.3.1 is a patch release containing bug fixes and a security patch for https://github.com/mlflow/mlflow/security/advisories/GHSA-83fm-w79m-64r5. If you are using
mlflow server
ormlflow ui
, we recommend upgrading to MLflow 2.3.1 as soon as possible.Security patches:
- [Security] Fix critical LFI attack vulnerability by disabling the ability to provide relative paths in registered model sources (#8281,
@BenWilson2
)Bug fixes:
- [Tracking] Fix an issue causing file and model uploads to hang on Databricks (#8348,
@harupy
)- [Tracking / Model Registry] Fix an issue causing file and model downloads to hang on Databricks (#8350,
@dbczumar
)- [Scoring] Fix regression in schema enforcement for model serving when using the
inputs
format for inference (#8326,@BenWilson2
)- [Model Registry] Fix regression in model naming parsing where special characters were not accepted in model names (#8322,
@arpitjasa-db
)- [Recipes] Fix card rendering with the pandas profiler to handle columns containing all null values (#8263,
@sunishsheth2009
)MLflow 2.3.0 includes several major features and improvements
Features:
- [Models] Introduce a new
transformers
named flavor (#8236, #8181, #8086,@BenWilson2
)- [Models] Introduce a new
openai
named flavor (#8191, #8155,@harupy
)- [Models] Introduce a new
langchain
named flavor (#8251, #8197,@liangz1
,@sunishsheth2009
)- [Models] Add support for
Pytorch
andLightning
2.0 (#8072,@shrinath-suresh
)- [Tracking] Add support for logging LLM input, output, and prompt artifacts (#8234, #8204,
@sunishsheth2009
)- [Tracking] Add support for HTTP Basic Auth in the MLflow tracking server (#8130,
@gabrielfu
)- [Tracking] Add support for
search_model_versions
to high-level fluent API (#8223,@mariusschlegel
)- [Artifacts] Add support for parallelized artifact downloads (#8116,
@apurva-koti
)- [Artifacts] Add support for parallelized artifact uploads for AWS (#8003,
@harupy
)- [Artifacts] Add content type headers to artifact upload requests for the
HttpArtifactRepository
(#8048,@WillEngler
)- [Model Registry] Added alias support to MLflow client (#8164, #8094, #8055
@arpitjasa-db
)- [UI] Add support for custom domain git providers (#7933,
@gusghrlrl101
)- [Scoring] Add plugin support for customization of MLflow serving endpoints (#7757,
@jmahlik
)- [Scoring] Add support to MLflow serving that allows configuration of multiple inference workers (#8035,
@M4nouel
)- [Sagemaker] Add support for asynchronous inference configuration on Sagemaker (#8009,
@thomasbell1985
)- [Build] Remove
shap
as a core dependency of MLflow (#8199,@jmahlik
)Bug fixes:
- [Models] Fix a bug with
tensorflow
autologging for models with multiple inputs (#8097,@jaume-ferrarons
)- [Recipes] Fix a bug with
Pandas
2.0 updates for profiler rendering of datetime types (#7925,@sunishsheth2009
)- [Tracking] Prevent exceptions from being raised if a parameter is logged with an existing key whose value is identical to the logged parameter (#8038,
@AdamStelmaszczyk
)- [Tracking] Fix an issue with deleting experiments in the FileStore backend (#8178,
@mariusschlegel
)- [Tracking] Fix a UI bug where the "Source Run" field in the Model Version page points to an incorrect set of artifacts (#8156,
@WeichenXu123
)- [Tracking] Fix a bug wherein renaming a run reverts its current lifecycle status to
UNFINISHED
(#8154,@WeichenXu123
)- [Tracking] Fix a bug where a file URI could be used as a model version source (#8126,
@harupy
)- [Projects] Fix an issue with MLflow projects that have submodules contained within a project (#8050,
@kota-iizuka
)- [Examples] Fix
lightning
hyperparameter tuning examples (#8039,@BenWilson2
)- [Server-infra] Fix bug with Cache-Control headers for static server files (#8016,
@jmahlik
)Documentation updates:
... (truncated)
Changelog
Sourced from mlflow's changelog.
2.3.1 (2023-04-27)
MLflow 2.3.1 is a patch release containing the following bug fixes and changes:
Bug fixes:
- [Security] Fix critical LFI attack vulnerability by disabling the ability to provide relative paths in registered model sources (#8281,
@BenWilson2
)
- If you are using
mlflow server
ormlflow ui
, we recommend upgrading to MLflow 2.3.1 as soon as possible. For more details, see https://github.com/mlflow/mlflow/security/advisories/GHSA-xg73-94fp-g449.- [Tracking] Fix an issue causing file and model uploads to hang on Databricks (#8348,
@harupy
)- [Tracking / Model Registry] Fix an issue causing file and model downloads to hang on Databricks (#8350,
@dbczumar
)- [Scoring] Fix regression in schema enforcement for model serving when using the
inputs
format for inference (#8326,@BenWilson2
)- [Model Registry] Fix regression in model naming parsing where special characters were not accepted in model names (#8322,
@arpitjasa-db
)- [Recipes] Fix card rendering with the pandas profiler to handle columns containing all null values (#8263,
@sunishsheth2009
)Documentation updates:
- [Docs] Add an H2O pyfunc usage example to the models documentation (#8292,
@ericvincent18
)- [Examples] Add a TensorFlow Core 2.x API usage example (#8235,
@dheerajnbhat
)Small bug fixes and documentation updates:
#8324, #8325,
@smurching
; #8313,@dipanjank
; #8323,@liangz1
; #8331, #8328, #8319, #8316, #8308, #8293, #8289, #8283, #8284, #8285, #8282, #8241, #8270, #8272, #8271, #8268,@harupy
; #8312, #8294, #8295, #8279, #8267,@BenWilson2
; #8290,@jinzhang21
; #8257,@WeichenXu123
; #8307,@arpitjasa-db
2.3.0 (2023-04-18)
MLflow 2.3.0 includes several major features and improvements
Features:
- [Models] Introduce a new
transformers
named flavor (#8236, #8181, #8086,@BenWilson2
)- [Models] Introduce a new
openai
named flavor (#8191, #8155,@harupy
)- [Models] Introduce a new
langchain
named flavor (#8251, #8197,@liangz1
,@sunishsheth2009
)- [Models] Add support for
Pytorch
andLightning
2.0 (#8072,@shrinath-suresh
)- [Tracking] Add support for logging LLM input, output, and prompt artifacts (#8234, #8204,
@sunishsheth2009
)- [Tracking] Add support for HTTP Basic Auth in the MLflow tracking server (#8130,
@gabrielfu
)- [Tracking] Add
search_model_versions
to the fluent API (#8223,@mariusschlegel
)- [Artifacts] Add support for parallelized artifact downloads (#8116,
@apurva-koti
)- [Artifacts] Add support for parallelized artifact uploads for AWS (#8003,
@harupy
)- [Artifacts] Add content type headers to artifact upload requests for the
HttpArtifactRepository
(#8048,@WillEngler
)- [Model Registry] Add alias support for logged models within Model Registry (#8164, #8094, #8055
@arpitjasa-db
)- [UI] Add support for custom domain git providers (#7933,
@gusghrlrl101
)- [Scoring] Add plugin support for customization of MLflow serving endpoints (#7757,
@jmahlik
)- [Scoring] Add support to MLflow serving that allows configuration of multiple inference workers (#8035,
@M4nouel
)- [Sagemaker] Add support for asynchronous inference configuration on Sagemaker (#8009,
@thomasbell1985
)- [Build] Remove
shap
as a core dependency of MLflow (#8199,@jmahlik
)Bug fixes:
- [Models] Fix a bug with
tensorflow
autologging for models with multiple inputs (#8097,@jaume-ferrarons
)- [Recipes] Fix a bug with
Pandas
2.0 updates for profiler rendering of datetime types (#7925,@sunishsheth2009
)
... (truncated)
Commits
95dc319
Make a short sleep to avoid busy waiting (#8354)cb5cc36
Use separate thread pool executors when uploading chunks to avoid deadlock (#...2b50b88
Revert (#8351)af38edf
Handle slashes in_validate_non_local_source_contains_relative_paths
(#8338)9e35947
Remove virtualenv environment if we encounter unexpected error (#8328)2470fd1
Create a new request session in each process (#8331)b7d8406
Merge branch 'master' into branch-2.3cef03da
Fix regression in schema enforcement (#8326)ef7b6ed
Update parse model URI to prevent breaking old cases while supporting aliases...64270e2
Improve UC model registry client error messages when specifying nonexistent s...- Additional commits viewable in compare view
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