Prepare release of TF-DF 1.9.2 and PYDF 0.6.0

PiperOrigin-RevId: 650123651

CHANGELOG.md

@@ -1,5 +1,12 @@
 # Changelog
 
+## 1.9.2 - 2024-07-04
+
+### Fix
+
+-   Fix compatibility with TF 2.16.2.
+-   Fix build.
+
 ## 1.9.1 - 2024-05-07
 
 ### Fix

WORKSPACE

@@ -11,9 +11,9 @@ load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
 # absl used by tensorflow.
 http_archive(
     name = "org_tensorflow",
-    strip_prefix = "tensorflow-2.16.1",
-    sha256 = "c729e56efc945c6df08efe5c9f5b8b89329c7c91b8f40ad2bb3e13900bd4876d",
-    urls = ["https://github.com/tensorflow/tensorflow/archive/v2.16.1.tar.gz"],
+    strip_prefix = "tensorflow-2.16.2",
+    sha256 = "023849bf253080cb1e4f09386f5eb900492da2288274086ed6cfecd6d99da9eb",
+    urls = ["https://github.com/tensorflow/tensorflow/archive/v2.16.2.tar.gz"],
     # Starting with TF 2.14, disable hermetic Python builds.
     patch_args = ["-p1"],
     patches = ["//third_party/tensorflow:tf.patch"],

configure/setup.py

@@ -18,19 +18,20 @@
 """
 
 import platform
+import sys
 import setuptools
 from setuptools.command.install import install
 from setuptools.dist import Distribution
 
-_VERSION = "1.9.1"
+_VERSION = "1.9.2"
 
 with open("README.md", "r", encoding="utf-8") as fh:
   long_description = fh.read()
 
 REQUIRED_PACKAGES = [
     "numpy",
     "pandas",
-    "tensorflow~=2.16.1",
+    "tensorflow==2.16.2",
     "six",
     "absl_py",
     "wheel",
@@ -57,31 +58,26 @@ def is_pure(self):
     return False
 
 
-try:
-  from wheel.bdist_wheel import bdist_wheel as _bdist_wheel
-
-  class bdist_wheel(_bdist_wheel):
-
-    def finalize_options(self):
-      _bdist_wheel.finalize_options(self)
-      self.root_is_pure = False
-
-    def get_tag(self):
-      python, abi, plat = _bdist_wheel.get_tag(self)
-      if platform.system() == "Darwin":
-        # Uncomment on of the lines below to adapt the platform string when
-        # cross-compiling.
-        plat = "macosx_12_0_arm64"
-        # plat = "macosx_10_15_x86_64"
-        pass
-      return python, abi, plat
-
-except ImportError:
-  bdist_wheel = None
+if "bdist_wheel" in sys.argv:
+  if "--plat-name" not in sys.argv:
+    if platform.system() == "Darwin":
+      idx = sys.argv.index("bdist_wheel") + 1
+      sys.argv.insert(idx, "--plat-name")
+      if platform.processor() == "arm":
+        sys.argv.insert(idx + 1, "macosx_10_15_x86_64")
+      elif platform.processor() == "i386":
+        sys.argv.insert(idx + 1, "macosx_12_0_arm64")
+      else:
+        raise ValueError(f"Unknown processor {platform.processor()}")
+    else:
+      print("Not on MacOS")
+  else:
+    print("PLAT-NAME Supplied")
+else:
+  print("NO BDIST_WHEEL")
 
 setuptools.setup(
     cmdclass={
-        "bdist_wheel": bdist_wheel,
         "install": InstallPlatlib,
     },
     name="tensorflow_decision_forests",

documentation/known_issues.md

@@ -54,6 +54,7 @@ The following table shows the compatibility between
 
 tensorflow_decision_forests | tensorflow
 --------------------------- | ---------------
+1.9.2                       | 2.16.2
 1.9.1                       | 2.16.1
 1.9.0                       | 2.16.1
 1.8.0 - 1.8.1               | 2.15.0

tensorflow_decision_forests/__init__.py

@@ -51,10 +51,10 @@
 ```
 """
 
-__version__ = "1.9.1"
+__version__ = "1.9.2"
 __author__ = "Mathieu Guillame-Bert"
 
-compatible_tf_versions = ["2.16.1"]
+compatible_tf_versions = ["2.16.2"]
 __git_version__ = "HEAD"  # Modify for release build.
 
 from tensorflow_decision_forests.tensorflow import check_version

tensorflow_decision_forests/keras/wrappers_pre_generated.py

@@ -289,7 +289,7 @@ class CartModel(core.CoreModel):
       value for Random Forest: `sqrt(number of input attributes)` in case of
       classification and `number_of_input_attributes / 3` in case of regression.
       If `num_candidate_attributes=-1`, all the attributes are tested. Default:
-      0.
+      -1.
     num_candidate_attributes_ratio: Ratio of attributes tested at each node. If
       set, it is equivalent to `num_candidate_attributes =
       number_of_input_features x num_candidate_attributes_ratio`. The possible
@@ -308,7 +308,7 @@ class CartModel(core.CoreModel):
       training. This solution is faster but consumes much more memory than
       IN_NODE. - IN_NODE: The features are sorted just before being used in the
       node. This solution is slow but consumes little amount of memory. .
-      Default: "PRESORT".
+      Default: "IN_NODE".
     sparse_oblique_max_num_projections: For sparse oblique splits i.e.
       `split_axis=SPARSE_OBLIQUE`. Maximum number of projections (applied after
       the num_projections_exponent). Oblique splits try out
@@ -420,11 +420,11 @@ def __init__(
       mhld_oblique_sample_attributes: Optional[bool] = None,
       min_examples: Optional[int] = 5,
       missing_value_policy: Optional[str] = "GLOBAL_IMPUTATION",
-      num_candidate_attributes: Optional[int] = 0,
+      num_candidate_attributes: Optional[int] = -1,
       num_candidate_attributes_ratio: Optional[float] = -1.0,
       pure_serving_model: Optional[bool] = False,
       random_seed: Optional[int] = 123456,
-      sorting_strategy: Optional[str] = "PRESORT",
+      sorting_strategy: Optional[str] = "IN_NODE",
       sparse_oblique_max_num_projections: Optional[int] = None,
       sparse_oblique_normalization: Optional[str] = None,
       sparse_oblique_num_projections_exponent: Optional[float] = None,

tools/test_bazel.sh

@@ -26,7 +26,7 @@
 #
 # Usage example
 #
-#   RUN_TESTS=1 PY_VERSION=3.9 TF_VERSION=2.16.1 ./tools/test_bazel.sh
+#   RUN_TESTS=1 PY_VERSION=3.9 TF_VERSION=2.16.2 ./tools/test_bazel.sh
 
 set -vex