update v1.1.0

scepter/modules/data/dataset/base_dataset.py

@@ -82,6 +82,8 @@ class BaseDataset(Dataset, metaclass=ABCMeta):
                                                overwrite=False)
         self.worker_id = worker_id
         self.logger = self.worker_logger
+        self.local_we["seed"] += (worker_id + we.rank)
+        self.seed = self.local_we["seed"]
         we.set_env(self.local_we)
 
     @abstractmethod

scepter/modules/data/dataset/registry.py

@@ -258,6 +258,8 @@ class DataObject(object):
             if sampler_name == 'MixtureOfSamplers':
                 subsampler_configs = self.data_sampler_config.get(
                     'SUB_SAMPLERS', [])
+                keep_order = self.data_sampler_config.get(
+                    'KEEP_ORDER', False)
                 subsamplers = list()
                 subsampler_probs = list()
                 for ssconfig in subsampler_configs:
@@ -277,7 +279,7 @@ class DataObject(object):
                     subsampler_probs.append(prob)
                 self.batch_sampler = MixtureOfSamplers(subsamplers,
                                                        subsampler_probs, rank,
-                                                       seed)
+                                                       seed, keep_order = keep_order)
             elif sampler_name == 'MultiLevelBatchSampler':
                 self.batch_sampler = self._instantiate_multi_level_batch_sampler(
                     self.data_sampler_config, self.batch_size, rank, seed)

scepter/modules/data/sampler/sampler.py

@@ -523,12 +523,15 @@ class MultiLevelBatchSampler(BaseSampler):
 class MixtureOfSamplers(BaseSampler):
     para_dict = {'SUB_SAMPLERS': []}
 
-    def __init__(self, samplers, probabilities, rank=0, seed=8888):
+    def __init__(self, samplers, probabilities, rank=0, seed=8888, keep_order = False):
         self.samplers = samplers
         self.iterators = [iter(u) for u in samplers]
         self.probabilities = probabilities
         self.seed = seed
-        self.rng = np.random.default_rng(seed + rank)
+        if keep_order:
+            self.rng = np.random.default_rng(seed)
+        else:
+            self.rng = np.random.default_rng(seed + rank)
 
     def __iter__(self):
         while True: