remove DataParallelFeedInput, as dataparallel inference now relies on QueueInput

tensorpack/input_source/input_source.py

@@ -23,7 +23,7 @@ from ..utils.develop import log_deprecated
 from ..callbacks.base import Callback
 from ..callbacks.graph import RunOp
 
-__all__ = ['PlaceholderInput', 'FeedInput', 'DataParallelFeedInput',
+__all__ = ['PlaceholderInput', 'FeedInput',
            'FeedfreeInput',
            'QueueInput', 'BatchQueueInput',
            'DummyConstantInput', 'TensorInput',
@@ -99,64 +99,6 @@ class FeedInput(InputSource):
         return [self._cb]
 
 
-class DataParallelFeedInput(FeedInput):
-    """
-    Input by feeding k datapoints to k copies of placeholders located on k towers.
-    """
-
-    class _DataParallelFeedCallback(Callback):
-        def __init__(self, ds, placeholders_per_tower):
-            self._ds = ds
-            self._itr = self._ds.get_data()
-            self._placehdrs_per_tower = placeholders_per_tower
-            self._nr_tower = len(self._placehdrs_per_tower)
-
-        def _reset(self):
-            self._ds.reset_state()
-            self._itr = self._ds.get_data()
-
-        def _before_run(self, _):
-            cnt = self._nr_tower
-            feed = {}
-            for t in range(cnt):
-                dp = next(self._itr)
-                f = dict(zip(self._placehdrs_per_tower[t], dp))
-                feed.update(f)
-            return tf.train.SessionRunArgs(fetches=[], feed_dict=feed)
-
-    def __init__(self, ds, tower_names):
-        super(DataParallelFeedInput, self).__init__(ds)
-        self._tower_names = tower_names
-        self._nr_tower = len(tower_names)
-
-    def _setup(self, inputs):
-        self._placehdrs_per_tower = []
-        for tname in self._tower_names:
-            # build a list of placeholders for each tower
-            self._placehdrs_per_tower.append(
-                [v.build_placeholder(prefix=tname + '/') for v in inputs])
-        self._cb = self._DataParallelFeedCallback(self._iter_ds, self._placehdrs_per_tower)
-
-    def _get_input_tensors(self):
-        # return placeholders for each tower
-        ctx = get_current_tower_context()
-        return self._placehdrs_per_tower[ctx.index]
-
-    def next_feed(self, cnt=1):
-        """
-        Args:
-            cnt: how many towers to feed to.
-        """
-        cnt = int(cnt)
-        assert cnt < self._nr_tower
-        feed = {}
-        for t in range(cnt):
-            dp = next(self._cb._itr)
-            f = dict(zip(self._placehdrs_per_tower[t], dp))
-            feed.update(f)
-        return feed
-
-
 class FeedfreeInput(InputSource):
     """ Abstract base for input without feed,
     e.g. by queue or other operations. """