Clearly define the argument of `build_graph`

tensorpack/RL/README.md

+
+## DEPRECATED
+
+Please use gym or other APIs.

tensorpack/graph_builder/model_desc.py

@@ -9,6 +9,7 @@ import tensorflow as tf
 import six
 
 from ..utils.argtools import memoized
+from ..utils.develop import log_deprecated
 from ..tfutils.gradproc import FilterNoneGrad
 from ..tfutils.tower import get_current_tower_context
 from ..input_source import InputSource
@@ -96,15 +97,17 @@ class ModelDescBase(object):
         Build the whole symbolic graph.
 
         Args:
-            args (list[tf.Tensor]): a list of tensors,
-                that match the list of :class:`InputDesc` defined by ``_get_inputs``.
+            args ([tf.Tensor]): a list of tensors,
+                that matches the list of :class:`InputDesc` defined by ``_get_inputs``.
         """
         if len(args) == 1:
             arg = args[0]
             if isinstance(arg, InputSource):
                 inputs = arg.get_input_tensors()  # remove in the future?
+                log_deprecated("build_graph(InputSource)", "Call with tensors in positional args instead.")
             elif isinstance(arg, (list, tuple)):
                 inputs = arg
+                log_deprecated("build_graph([Tensor])", "Call with positional args instead.")
             else:
                 inputs = [arg]
         else:
@@ -163,7 +166,7 @@ class ModelDesc(ModelDescBase):
         raise NotImplementedError()
 
     def _build_graph_get_cost(self, *inputs):
-        self.build_graph(inputs)
+        self.build_graph(*inputs)
         return self.get_cost()
 
     def _build_graph_get_grads(self, *inputs):

tensorpack/tfutils/export.py

@@ -89,7 +89,7 @@ class ModelExport(object):
         """
         logger.info('[export] build model for %s' % checkpoint)
         with TowerContext('', is_training=False):
-            self.model.build_graph(self.input)
+            self.model.build_graph(*self.input.get_input_tensors())
 
             self.sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True))
             # load values from latest checkpoint
@@ -129,8 +129,6 @@ class ModelExport(object):
                 outputs=outputs_signature,
                 method_name=tf.saved_model.signature_constants.PREDICT_METHOD_NAME)
 
-            # legacy_init_op = tf.group(tf.tables_initializer(), name='legacy_init_op')
-
             builder.add_meta_graph_and_variables(
                 self.sess, tags,
                 signature_def_map={signature_name: prediction_signature})

tensorpack/train/base.py

@@ -86,7 +86,7 @@ class Trainer(object):
             self._config = config
             self.inputs_desc = config.model.get_inputs_desc()
             self.tower_func = TowerFuncWrapper(
-                lambda *inputs: config.model.build_graph(inputs),
+                lambda *inputs: config.model.build_graph(*inputs),
                 self.inputs_desc)
             self._main_tower_vs_name = ""
 

tensorpack/trainv1/base.py

@@ -123,7 +123,7 @@ class Trainer(object):
         if self.model is not None:
 
             def f(*inputs):
-                self.model.build_graph(inputs)
+                self.model.build_graph(*inputs)
 
             """
             Only to mimic new trainer interafce on inference.