made a few changes for BACKWARD COMPATIBILITY with tf 1.12

borisgin · borisgin · commit 6e8835f55cff · 2019-02-01T18:20:41.000-08:00
Signed-off-by: borisgin &lt;boris.ginsburg@gmail.com&gt;
diff --git a/open_seq2seq/data/speech2text/speech2text.py b/open_seq2seq/data/speech2text/speech2text.py
@@ -16,8 +16,10 @@
 from .speech_utils import get_speech_features_from_file, get_speech_features
 import sentencepiece as spm
 
-
-np.fft.restore_all()
+# numpy.fft with MKL bug
+# see https://github.com/IntelPython/mkl_fft/issues/11
+if hasattr(np.fft, 'restore_all'):
+  np.fft.restore_all()
 
 class Speech2TextDataLayer(DataLayer):
   """Speech-to-text data layer class."""
diff --git a/open_seq2seq/data/text2text/text2text.py b/open_seq2seq/data/text2text/text2text.py
@@ -11,7 +11,8 @@
 from open_seq2seq.data.text2text.t2t import _read_and_batch_from_files
 from open_seq2seq.data.text2text.tokenizer import PAD_ID
 
-tf.compat.v1.disable_eager_execution()
+# if hasattr(tf.compat, 'v1'):
+#   tf.compat.v1.disable_eager_execution()
 
 class SpecialTextTokens(Enum):
   PAD_ID = 0  # special padding token
@@ -162,7 +163,7 @@ def _pad2eight(self, lst, do_pad_eight):
       return lst + [SpecialTextTokens.PAD_ID.value] * (8 - len(lst) % 8)
 
   def _src_token_to_id(self, line):
-    tokens = line.numpy().decode("utf-8").split(self._delimiter)
+    tokens = line.decode("utf-8").split(self._delimiter) #line.numpy().
     if self._use_start_token:
       return np.array(self._pad2eight([SpecialTextTokens.S_ID.value] + \
              [self.src_seq2idx.get(token, SpecialTextTokens.UNK_ID.value) for token in tokens[:self.max_len-2]] + \
@@ -173,7 +174,7 @@ def _src_token_to_id(self, line):
                                       [SpecialTextTokens.EOS_ID.value], self._pad_lengths_to_eight), dtype="int32")
 
   def _tgt_token_to_id(self, line):
-    tokens = line.numpy().decode("utf-8").split(self._delimiter)
+    tokens = line.decode("utf-8").split(self._delimiter) #line.numpy().
     if self._use_start_token:
       return np.array(self._pad2eight([SpecialTextTokens.S_ID.value] + \
              [self.tgt_seq2idx.get(token, SpecialTextTokens.UNK_ID.value) for token in tokens[:self.max_len-2]] + \
@@ -197,14 +198,14 @@ def build_graph(self):
         _targets = _targets.shard(num_shards=self._num_workers,
                                   index=self._worker_id)
 
-      _sources = _sources.map(lambda line: tf.py_function(func=self._src_token_to_id, inp=[line],
-                                     Tout=[tf.int32]), # stateful=False),
+      _sources = _sources.map(lambda line: tf.py_func(func=self._src_token_to_id, inp=[line],
+                                     Tout=[tf.int32], stateful=False),
              num_parallel_calls=self._map_parallel_calls) \
         .map(lambda tokens: (tokens, tf.size(tokens)),
              num_parallel_calls=self._map_parallel_calls)
 
-      _targets = _targets.map(lambda line: tf.py_function(func=self._tgt_token_to_id, inp=[line],
-                                     Tout=[tf.int32]),# stateful=False),
+      _targets = _targets.map(lambda line: tf.py_func(func=self._tgt_token_to_id, inp=[line],
+                                     Tout=[tf.int32], stateful=False),
              num_parallel_calls=self._map_parallel_calls) \
         .map(lambda tokens: (tokens, tf.size(tokens)),
              num_parallel_calls=self._map_parallel_calls)
diff --git a/open_seq2seq/losses/ctc_loss.py b/open_seq2seq/losses/ctc_loss.py
@@ -37,8 +37,8 @@ def __init__(self, params, model, name="ctc_loss"):
     super(CTCLoss, self).__init__(params, model, name)
     self._mask_nan = self.params.get("mask_nan", True)
     # this loss can only operate in full precision
-    if self.params['dtype'] != tf.float32:
-      deco_print("Warning: defaulting CTC loss to work in float32")
+    # if self.params['dtype'] != tf.float32:
+    #   deco_print("Warning: defaulting CTC loss to work in float32")
     self.params['dtype'] = tf.float32
 
   def _compute_loss(self, input_dict):
diff --git a/run.py b/run.py
@@ -8,7 +8,8 @@
 import sys
 import tensorflow as tf
 
-tf.compat.v1.disable_eager_execution()
+if hasattr(tf.compat, 'v1'):
+  tf.compat.v1.disable_eager_execution()
 
 from open_seq2seq.utils.utils import deco_print, get_base_config, create_model,\
                                      create_logdir, check_logdir, \
