clean-up legacy placeholder methods in ModelDesc

scripts/dump-model-params.py

@@ -10,6 +10,7 @@ import imp
 
 from tensorpack import TowerContext, logger
 from tensorpack.tfutils import sessinit, varmanip
+from tensorpack.graph_builder.input_source import PlaceholderInput
 
 parser = argparse.ArgumentParser()
 parser.add_argument('--config', help='config file')
@@ -26,7 +27,9 @@ with tf.Graph().as_default() as G:
         MODEL = imp.load_source('config_script', args.config).Model
         M = MODEL()
         with TowerContext('', is_training=False):
-            M.build_graph(M.get_reused_placehdrs())
+            input = PlaceholderInput()
+            input.setup(M.get_inputs_desc())
+            M.build_graph(input)
     else:
         tf.train.import_meta_graph(args.meta)
 

tensorpack/graph_builder/model_desc.py

@@ -93,32 +93,6 @@ class InputDesc(
 class ModelDescBase(object):
     """ Base class for a model description.
     """
-
-    # TODO remove this method? Now mainly used in predict/
-    @memoized
-    def get_reused_placehdrs(self):
-        """
-        Create or return (if already created) raw input TF placeholders in the graph.
-
-        Returns:
-            list[tf.Tensor]: the list of input placeholders in the graph.
-        """
-        return [v.build_placeholder_reuse() for v in self.get_inputs_desc()]
-
-    def build_placeholders(self, prefix=''):
-        """
-        For each InputDesc, create new placeholders with optional prefix and
-        return them. Useful when building new towers.
-
-        Returns:
-            list[tf.Tensor]: the list of built placeholders.
-        """
-        inputs = self.get_inputs_desc()
-        ret = []
-        for v in inputs:
-            ret.append(v.build_placeholder(prefix))
-        return ret
-
     @memoized
     def get_inputs_desc(self):
         """

tensorpack/graph_builder/predictor_factory.py

@@ -8,6 +8,7 @@ from ..tfutils.common import get_op_tensor_name, get_tensors_by_names
 from ..tfutils.tower import TowerContext
 from ..tfutils.collection import freeze_collection
 from ..utils.naming import TOWER_FREEZE_KEYS
+from .input_source import PlaceholderInput
 
 __all__ = ['PredictorFactory']
 
@@ -62,9 +63,9 @@ class PredictorFactory(object):
                 TowerContext(tower_name, is_training=False), \
                 freeze_collection(TOWER_FREEZE_KEYS):
             if input is None:
-                input = self._model.get_reused_placehdrs()
-            else:
-                input = input.get_input_tensors()
+                input = PlaceholderInput()
+                input.setup(self._model.get_inputs_desc())
+            input = input.get_input_tensors()
             assert isinstance(input, (list, tuple)), input
             self._model.build_graph(input)
 

tensorpack/predict/base.py

@@ -9,6 +9,7 @@ import six
 
 from ..tfutils.common import get_tensors_by_names
 from ..tfutils.tower import TowerContext
+from ..graph_builder.input_source import PlaceholderInput
 
 __all__ = ['PredictorBase', 'AsyncPredictorBase',
            'OnlinePredictor', 'OfflinePredictor',
@@ -127,9 +128,10 @@ class OfflinePredictor(OnlinePredictor):
         """
         self.graph = config._maybe_create_graph()
         with self.graph.as_default():
-            input_placehdrs = config.model.get_reused_placehdrs()
+            input = PlaceholderInput()
+            input.setup(config.model.get_inputs_desc())
             with TowerContext('', is_training=False):
-                config.model.build_graph(input_placehdrs)
+                config.model.build_graph(input)
 
             input_tensors = get_tensors_by_names(config.input_names)
             output_tensors = get_tensors_by_names(config.output_names)

tensorpack/tfutils/export.py

@@ -10,6 +10,7 @@ This simplifies the process of exporting a model for TensorFlow serving.
 import tensorflow as tf
 from ..utils import logger
 from ..graph_builder.model_desc import ModelDesc
+from ..graph_builder.input_source import PlaceholderInput
 from ..tfutils import TowerContext, sessinit
 
 
@@ -61,7 +62,8 @@ class ModelExport(object):
         logger.info('[export] prepare new model export')
         super(ModelExport, self).__init__()
         self.model = model
-        self.placehdrs = self.model.get_reused_placehdrs()
+        self.input = PlaceholderInput()
+        self.input.setup(self.model.get_inputs_desc())
         self.output_names = output_names
         self.input_names = input_names
 
@@ -87,7 +89,7 @@ class ModelExport(object):
         """
         logger.info('[export] build model for %s' % checkpoint)
         with TowerContext('', is_training=False):
-            self.model._build_graph(self.placehdrs)
+            self.model._build_graph(self.input)
 
             self.sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True))
             # load values from latest checkpoint