Tensorflowonspark

Latest version: v2.2.5

Safety actively analyzes 629436 Python packages for vulnerabilities to keep your Python projects secure.

Scan your dependencies

Page 2 of 4

2.1.3

- Detect TF version w/o importing to avoid runtime initialization before GPU allocation.

2.1.2

- Use `tf.config.list_physical_devices()` to avoid TF runtime initialization.

2.1.1

- added `compat.is_gpu_available()` method to use:
- `tf.config.list_logical_devices('GPU')` (for TF2.1)
- `tf.test.is_cuda_available()` (for earlier versions of TF).
- added ability to launch TensorBoard on `chief:0` or `master:0` nodes (for small clusters without `worker` nodes).

2.1.0

- Added `compat` module to manage minor API changes in TensorFlow.
- Added compatibility for TF2.1.0rc0 (exporting saved_models and configuring auto-shard policy)
- Re-introduced compatibility for TF1.x (except support for InputMode.TENSORFLOW in the ML Pipeline API).
- Added TFParallel class for parallelized single-node inferencing via Spark executors.
- Updated examples for TF API changes.
- Updated to use module-level loggers.

2.0.0

- initial release compatible with TensorFlow 2.x.
- API changes:
- removed `TFNode.start_cluster_server`, which is not required for `tf.keras` and `tf.estimator`.
- removed `TFNode.export_saved_model`, which can be replaced by TF native APIs now.
- added `TFNodeContext.num_workers` to count `master`, `chief`, and `worker` nodes.
- Spark ML Pipeline API changes:
- Scala API has been removed for now, since the Java library for TensorFlow 2.0 is not available yet.
- removed `InputMode.TENSORFLOW` support for ML Pipelines, since the input data is always a Spark DataFrame for this API.
- added `HasMasterNode` and `HasGraceSecs` params.
- removed optional `export_fn` argument for Spark ML `TFEstimator` (use TF export APIs instead).
- added standard default values for `signature_def_key` and `tag_set` for Spark ML `TFModel`.
- modified inferencing code in `TFModel` for TF2.x APIs.
- older TF 1.x examples have been replaced with TF 2.x compatible examples.

1.4.4

- last expected release compatible with TensorFlow 1.x (aside from any critical fixes), since the `master` branch will be moving to TF 2.0 compatibility.
- handle multiple outputs with signaturedef (thanks to markromedia).
- handle exceptions after data feeding.
- moved API docs to sphinx_rtd_theme.
- updated to Spark 2.4.4.

Page 2 of 4

© 2024 Safety CLI Cybersecurity Inc. All Rights Reserved.