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Release TF-DF 1.4.0 and YDF 1.5.0
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PiperOrigin-RevId: 545230857
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rstz authored and copybara-github committed Jul 3, 2023
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17 changes: 17 additions & 0 deletions CHANGELOG.md
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## HEAD

## 1.4.0 - 2023-07-03

### Features

- Support for multi-task learning.
- New tutorial for TF-DF <--> TF.js
- Support for uplift modeling in the model inspector.
- New tutorial for Uplift modeling.
- Bump Bazel version to 6.1.0.

### Fix

- Regex to generate Bazel workspace.
- Remove warning when converting Keras -> YDF.
- Fixed default hyperparameter issue Github #172.
- Various documentation issues fixed.

## 1.3.0 - 2023-03-23

### Features
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2 changes: 1 addition & 1 deletion configure/setup.py
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from setuptools.command.install import install
from setuptools.dist import Distribution

_VERSION = "1.3.0"
_VERSION = "1.4.0"

with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
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2 changes: 1 addition & 1 deletion documentation/known_issues.md
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Expand Up @@ -46,7 +46,7 @@ The following table shows the compatibility between

tensorflow_decision_forests | tensorflow
--------------------------- | ---------------
1.3.0 | 2.12.0
1.3.0 - 1.4.0 | 2.12.0
1.1.0 - 1.2.0 | 2.11.0
1.0.0 - 1.0.1 | 2.10.0 - 2.10.1
0.2.6 - 0.2.7 | 2.9.1
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2 changes: 1 addition & 1 deletion tensorflow_decision_forests/__init__.py
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"""

__version__ = "1.3.0"
__version__ = "1.4.0"
__author__ = "Mathieu Guillame-Bert"

compatible_tf_versions = ["2.12.0"]
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16 changes: 6 additions & 10 deletions tensorflow_decision_forests/keras/wrappers_pre_generated.py
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Expand Up @@ -1050,10 +1050,12 @@ class GradientBoostedTreesModel(core.CoreModel):
values are: - `DEFAULT`: Select the loss automatically according to the
task and label statistics. - `BINOMIAL_LOG_LIKELIHOOD`: Binomial log
likelihood. Only valid for binary classification. - `SQUARED_ERROR`: Least
square loss. Only valid for regression. - `MULTINOMIAL_LOG_LIKELIHOOD`:
Multinomial log likelihood i.e. cross-entropy. Only valid for binary or
multi-class classification. - `LAMBDA_MART_NDCG5`: LambdaMART with NDCG5.
- `XE_NDCG_MART`: Cross Entropy Loss NDCG. See arxiv.org/abs/1911.09798.
square loss. Only valid for regression. - `POISSON`: Poisson log
likelihood loss. Mainly used for counting problems. Only valid for
regression. - `MULTINOMIAL_LOG_LIKELIHOOD`: Multinomial log likelihood
i.e. cross-entropy. Only valid for binary or multi-class classification. -
`LAMBDA_MART_NDCG5`: LambdaMART with NDCG5. - `XE_NDCG_MART`: Cross
Entropy Loss NDCG. See arxiv.org/abs/1911.09798.
Default: "DEFAULT".
max_depth: Maximum depth of the tree. `max_depth=1` means that all trees
will be roots. Negative values are ignored. Default: 6.
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class HyperparameterOptimizerModel(core.CoreModel):
r"""Hyperparameter Optimizer learning algorithm.
Usage example:
```python
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support_partial_cache_dataset_format=False
)


class MultitaskerModel(core.CoreModel):
r"""Multitasker learning algorithm.
Usage example:
```python
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support_partial_cache_dataset_format=False
)


class RandomForestModel(core.CoreModel):
r"""Random Forest learning algorithm.
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2 changes: 1 addition & 1 deletion tools/start_compile_docker.sh
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# ./tools/start_compile_docker.sh
#
# # Compile and test TF-DF.
# RUN_TESTS=1 PY_VERSION=3.8 TF_VERSION=2.11.0 ./tools/test_bazel.sh
# RUN_TESTS=1 PY_VERSION=3.8 TF_VERSION=2.12.0 ./tools/test_bazel.sh
#
# # Create a Pip package for a specific version of python.
# ./tools/build_pip_package.sh python3.8
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2 changes: 0 additions & 2 deletions tools/test_bazel.sh
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Expand Up @@ -177,8 +177,6 @@ else
TEST_RULES="//tensorflow_decision_forests/component/...:all //tensorflow_decision_forests/contrib/...:all //tensorflow_decision_forests/keras/...:all"
fi

ls -l -a

# Build library
time ${BAZEL} ${STARTUP_FLAGS} build ${BUILD_RULES} ${FLAGS}

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