✅ Update dependency check.

.github/workflows/test.yml

@@ -35,7 +35,7 @@ jobs:
     strategy:
       matrix:
         group: [ 1, 2, 3 ]
-        tensorflow_version: [2.2, 2.3, 2.4, 2.5]
+        tensorflow_version: [2.1, 2.2, 2.3, 2.4, 2.5]
     steps:
       - uses: actions/checkout@v2
       - name: Set up Python 3.8

kashgari/__init__.py

@@ -12,25 +12,40 @@
 """
 
 import os
-from typing import Dict, Any
+from distutils.version import LooseVersion
+from typing import Any, Dict
 
 os.environ['TF_KERAS'] = '1'
 os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
 
 custom_objects: Dict[str, Any] = {}
 
+def check_tfa_version(tf_version):
+    if LooseVersion(tf_version) < '2.2.0':
+        return '0.9.1'
+    elif LooseVersion(tf_version) < '2.3.0':
+        return '0.11.2'
+    else:
+        return '0.13.0'
+
+
+def dependency_check() -> None:
+    import tensorflow as tf
+    tfa_version = check_tfa_version(tf_version=tf.__version__)
+    try:
+        import tensorflow_addons as tfa
+    except:
+        raise ImportError(
+            "Kashgari request tensorflow_addons, please install via the "
+            f"`$pip install tensorflow_addons=={tfa_version}`"
+            )
+
+dependency_check()
+
+from kashgari import corpus, embeddings, layers, macros, processors, tasks, utils
 from kashgari.__version__ import __version__
 from kashgari.macros import config
-from kashgari import layers
-from kashgari import corpus
-from kashgari import embeddings
-from kashgari import macros
-from kashgari import processors
-from kashgari import tasks
-from kashgari import utils
-
-from kashgari.utils.dependency_check import dependency_check
 
 custom_objects = layers.resigter_custom_layers(custom_objects)
 
-dependency_check()
+