v1.3.1

README.md

@@ -126,12 +126,9 @@ t2t-decoder \
   --output_dir=$TRAIN_DIR \
   --decode_hparams="beam_size=$BEAM_SIZE,alpha=$ALPHA" \
   --decode_from_file=$DECODE_FILE
-  --decode_to_file=translation.en
-```
-
-# Eval BLEU
 
-t2t-bleu --translation=translation.en --reference=ref-translation.de
+cat $DECODE_FILE.$MODEL.$HPARAMS.beam$BEAM_SIZE.alpha$ALPHA.decodes
+```
 
 ---
 

docs/example_life.md

@@ -75,7 +75,7 @@ hooks in the `Problem` class and the model's `HParams` object (typically
 registered in the model's file and specified by the `--hparams_set` flag).
 
 The entire input pipeline is implemented with the new `tf.data.Dataset` API
-(previously `tf.contrib.data.Dataset`).
+(previously `tf.data.Dataset`).
 
 The key function in the codebase for the input pipeline is
 [`data_reader.input_pipeline`](https://github.com/tensorflow/tensor2tensor/tree/master/tensor2tensor/utils/data_reader.py).

setup.py

@@ -5,7 +5,7 @@
 
 setup(
     name='tensor2tensor',
-    version='1.3.0',
+    version='1.3.1',
     description='Tensor2Tensor',
     author='Google Inc.',
     author_email='[email protected]',
@@ -15,16 +15,14 @@
     package_data={
         'tensor2tensor.data_generators': ['test_data/*'],
         'tensor2tensor.visualization': [
-            'attention.js',
-            'TransformerVisualization.ipynb'
+            'attention.js', 'TransformerVisualization.ipynb'
         ],
     },
     scripts=[
         'tensor2tensor/bin/t2t-trainer',
         'tensor2tensor/bin/t2t-datagen',
         'tensor2tensor/bin/t2t-decoder',
         'tensor2tensor/bin/t2t-make-tf-configs',
-        'tensor2tensor/bin/t2t-bleu',
     ],
     install_requires=[
         'bz2file',
@@ -35,8 +33,8 @@
         'six',
     ],
     extras_require={
-        'tensorflow': ['tensorflow>=1.3.0'],
-        'tensorflow_gpu': ['tensorflow-gpu>=1.3.0'],
+        'tensorflow': ['tensorflow>=1.4.0'],
+        'tensorflow_gpu': ['tensorflow-gpu>=1.4.0'],
         'tests': ['pytest', 'h5py', 'mock'],
     },
     classifiers=[
@@ -46,4 +44,5 @@
         'License :: OSI Approved :: Apache Software License',
         'Topic :: Scientific/Engineering :: Artificial Intelligence',
     ],
-    keywords='tensorflow machine learning',)
+    keywords='tensorflow machine learning',
+)

tensor2tensor/bin/t2t-decoder

@@ -46,10 +46,7 @@ import tensorflow as tf
 flags = tf.flags
 FLAGS = flags.FLAGS
 
-flags.DEFINE_string("output_dir", "",
-                    "Training directory where the latest checkpoint is used.")
-flags.DEFINE_string("checkpoint_path", None,
-                    "Path to the model checkpoint. Overrides output_dir.")
+flags.DEFINE_string("output_dir", "", "Training directory to load from.")
 flags.DEFINE_string("decode_from_file", None,
                     "Path to the source file for decoding")
 flags.DEFINE_string("decode_to_file", None,
@@ -93,7 +90,7 @@ def main(_):
     decoding.decode_interactively(estimator, decode_hp)
   elif FLAGS.decode_from_file:
     decoding.decode_from_file(estimator, FLAGS.decode_from_file, decode_hp,
-                              FLAGS.decode_to_file, checkpoint_path=FLAGS.checkpoint_path)
+                              FLAGS.decode_to_file)
   else:
     decoding.decode_from_dataset(
         estimator,