remove batch.id

replaced in tensorflow predict node debug statments with the request. This better indicates
the roi being predicted on.
replaced in snapshot node with an internal counter

gunpowder/batch.py

@@ -44,17 +44,7 @@ class Batch(Freezable):
             Contains all graphs that have been requested for this batch.
     """
 
-    __next_id = multiprocessing.Value("L")
-
-    @staticmethod
-    def get_next_id():
-        with Batch.__next_id.get_lock():
-            next_id = Batch.__next_id.value
-            Batch.__next_id.value += 1
-        return next_id
-
     def __init__(self):
-        self.id = Batch.get_next_id()
         self.profiling_stats = ProfilingStats()
         self.arrays = {}
         self.graphs = {}

gunpowder/nodes/snapshot.py

@@ -74,7 +74,7 @@ def __init__(
         self,
         dataset_names,
         output_dir="snapshots",
-        output_filename="{id}.zarr",
+        output_filename="{iteration}.zarr",
         every=1,
         additional_request=None,
         compression_type=None,
@@ -97,6 +97,7 @@ def __init__(
             self.dataset_dtypes = dataset_dtypes
 
         self.mode = "w"
+        self.id = 0
 
     def write_if(self, batch):
         """To be implemented in subclasses.
@@ -157,6 +158,7 @@ def prepare(self, request):
         return deps
 
     def process(self, batch, request):
+        self.id += 1
         if self.record_snapshot and self.write_if(batch):
             try:
                 os.makedirs(self.output_dir)
@@ -166,7 +168,7 @@ def process(self, batch, request):
             snapshot_name = os.path.join(
                 self.output_dir,
                 self.output_filename.format(
-                    id=str(batch.id).zfill(8), iteration=int(batch.iteration or 0)
+                    id=str(self.id).zfill(8), iteration=int(batch.iteration or self.id)
                 ),
             )
             logger.info("saving to %s" % snapshot_name)

gunpowder/tensorflow/nodes/predict.py

@@ -112,7 +112,7 @@ def predict(self, batch, request):
                     break
 
             if can_skip:
-                logger.info("Skipping batch %i (all inputs are 0)" % batch.id)
+                logger.info(f"Skipping batch for request: {request} (all inputs are 0)")
 
                 for name, array_key in self.outputs.items():
                     shape = self.shared_output_arrays[name].shape
@@ -124,7 +124,7 @@ def predict(self, batch, request):
 
                 return
 
-        logger.debug("predicting in batch %i", batch.id)
+        logger.debug(f"predicting for request: {request}")
 
         output_tensors = self.__collect_outputs(request)
         input_data = self.__collect_provided_inputs(batch)
@@ -160,7 +160,7 @@ def predict(self, batch, request):
             spec.roi = request[array_key].roi
             batch.arrays[array_key] = Array(output_data[array_key], spec)
 
-        logger.debug("predicted in batch %i", batch.id)
+        logger.debug("predicted")
 
     def __predict(self):
         """The background predict process."""