using bert/version.py for setup.py

.travis.yml

@@ -19,7 +19,7 @@ install:
     - pip install --upgrade pip setuptools
     - pip install 'tensorflow >= 1.14.0'
     - pip install -r requirements.txt
-    - pip install coverage pep8 nose nose-exclude
+    - pip install -r requirements-dev.txt
 
 # command to run tests
 # require 100% coverage (not including test files) to pass Travis CI test

MANIFEST.in

@@ -1,4 +1,3 @@
 include requirements-dev.txt
 include requirements.txt
 include README.rst
-include version

bert/__init__.py

@@ -4,10 +4,11 @@
 #
 from __future__ import division, absolute_import, print_function
 
+from .version import __version__
+
 from .attention import AttentionLayer
 from .layer import Layer
 from .model import BertModelLayer
 
 from .loader import StockBertConfig, load_stock_weights, params_from_pretrained_ckpt
 from .tokenization import FullTokenizer
-

bert/version.py

@@ -0,0 +1 @@
+__version__ = "0.3.5"

setup.py

@@ -4,11 +4,18 @@
 # created by kpe on 22.10.2018 at 11:46
 #
 
-from setuptools import setup, find_packages
+from setuptools import setup, find_packages, convert_path
 
 
-with open("version", "r") as fh:
-    __version__ = fh.read().strip()
+def _version():
+    ns = {}
+    with open(convert_path("bert/version.py"), "r") as fh:
+        exec(fh.read(), ns)
+    return ns['__version__']
+
+
+__version__ = _version()
+
 
 with open("README.rst", "r") as fh:
     long_description = fh.read()

tests/test_attention.py

@@ -0,0 +1,25 @@
+# coding=utf-8
+#
+# created by kpe on 30.Jul.2019 at 16:41
+#
+
+from __future__ import absolute_import, division, print_function
+
+
+import unittest
+
+import bert
+
+import tensorflow as tf
+
+tf.enable_eager_execution()
+
+
+class TestAttention(unittest.TestCase):
+
+    def test_attention(self):
+        am = bert.AttentionLayer.create_attention_mask(from_shape=[2, 3, 5],   # B,S,..
+                                                       input_mask=[[2], [1]]   # B,seq_len
+                                                       )
+        print(am)  # [batch_size, from_seq_len, seq_len]
+