Fix merge conficts

src/server/backend.py

@@ -1,6 +1,10 @@
 """Code for serving bloom blocks via hivemind-server"""
 from queue import Empty
+<<<<<<< HEAD
 from typing import Sequence, Tuple, Dict, Any, Optional
+=======
+from typing import Sequence, Tuple, Dict, Any
+>>>>>>> 79a9ff2b2ea0c2601e3670f9a28e84e8a511247d
 
 import torch
 from hivemind import use_hivemind_log_handler, BatchTensorDescriptor
@@ -14,6 +18,34 @@ from src.server.cache import MemoryCache
 use_hivemind_log_handler("in_root_logger")
 logger = get_logger(__file__)
 
+<<<<<<< HEAD
+
+class InferenceTaskPool(TaskPool):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+
+        assert self.min_batch_size == 1, "min_batch_size in InferenceTaskPool cannot be greater 1"
+
+    def iterate_minibatches(self, *args, **kwargs):
+        """Form minibatches by grouping one or more tasks together up to self.max_batch_size"""
+
+        while True:
+            try:
+                logger.debug(f"{self.name} getting next task")
+                task = self.tasks.get(timeout=self.timeout)
+            except Empty:
+                logger.warning(f"Timeout reached but batch doesn't contain >={self.min_batch_size} elements yet")
+                continue
+
+            try:
+                if task.future.set_running_or_notify_cancel():
+                    yield [task]
+            except InvalidStateError as e:
+                logger.debug(f"Failed to add task to batch: {task.future} raised {e}")
+=======
+MAX_LENGTH = 2048
+>>>>>>> 79a9ff2b2ea0c2601e3670f9a28e84e8a511247d
+
 
 class InferenceTaskPool(TaskPool):
     def __init__(self, *args, **kwargs):