Minor bug fixes

src/config/SCC_21.yaml

@@ -5,8 +5,3 @@ defaults:
   - _self_
 data:
   downsample: 0
-mode:
-  optimizer:
-    loss_balance_scheme: light
-
-

src/utils/core/larcvio/larcv_fetcher.py

@@ -9,7 +9,6 @@
 import logging
 logger = logging.getLogger("cosmictagger")
 
-from larcv.config_builder import ConfigBuilder
 
 class larcv_fetcher(object):
 
@@ -95,6 +94,7 @@ def prepare_cosmic_sample(self, name, input_file, batch_size, color=None):
                 raise Exception(f"File {input_file} not found")
 
 
+            from larcv.config_builder import ConfigBuilder
             cb = ConfigBuilder()
             cb.set_parameter([str(input_file)], "InputFiles")
             cb.set_parameter(5, "ProcessDriver", "IOManager", "Verbosity")
@@ -159,9 +159,9 @@ def prepare_cosmic_sample(self, name, input_file, batch_size, color=None):
 
             self._larcv_interface.prepare_manager(name, io_config, batch_size, data_keys, color=color)
 
-
-            if self.mode == "inference":
-                self._larcv_interface.set_next_index(name, start_index)
+            #
+            # if self.mode == "inference":
+            #     self._larcv_interface.set_next_index(name, start_index)
 
             # This queues up the next data
             # self._larcv_interface.prepare_next(name)

src/utils/tensorflow2/distributed_trainer.py

@@ -47,11 +47,13 @@ def __init__(self, args):
         self._size            = hvd.size()
 
     def init_optimizer(self):
+
                 # with tf.variable_scope("hvd"):
 
         #     # In the distributed case, we may want a learning rate behavior:
         #     self._learning_rate = self.generate_learning_rate(self.args.learning_rate, self._global_step)
         tf_trainer.init_optimizer(self)
+        if self.args.mode.name != ModeKind.train: return
 
         # Wrap the optimizer it in horovod:
         # self._opt = hvd.DistributedOptimizer(self._opt)