Config parameters fixes

README.md

@@ -39,7 +39,7 @@ If possible, one can flush the filesystem caches in order to properly capture de
   ```
 Finally, run the benchmark with ```iostat``` profiling, listing the io devices you would like to trace.
   ```bash
-  mpirun -np 8 python3 src/dlio_benchmark.py workload=unet3d ++workload.workflow.profiling=True ++workload.profiling.profiler=iostat ++workload.profiling.io_devices_to_trace=[sda,sdb]
+  mpirun -np 8 python3 src/dlio_benchmark.py workload=unet3d ++workload.workflow.profiling=True ++workload.profiling.profiler=iostat ++workload.profiling.iostat_devices=[sda,sdb]
   ```
 
 All the outputs will be stored in ```hydra_log/unet3d/$DATE-$TIME``` folder. To post process the data, one can do

configs/workload/unet3d.yaml

@@ -28,4 +28,4 @@ train:
 
 evaluation: 
   eval_time: 11.572
-  epochs_between_evals: 2
+  epochs_between_evals: 2

src/reader/hdf5_stimulate.py

@@ -101,7 +101,7 @@ def read(self, epoch_number):
                                      num_parallel_calls=self.read_threads)
         #dataset = dataset.cache()
         if self.memory_shuffle != Shuffle.OFF:
-            if self.memory_shuffle != Shuffle.SEED:
+            if self.memory_shuffle == Shuffle.SEED:
                 dataset = dataset.shuffle(buffer_size=self.shuffle_size,
                                           seed=self.seed)
             else:

src/reader/tf_data_loader_reader.py

@@ -71,7 +71,7 @@ def read(self, epoch_number):
         dataset = dataset.map(self._tf_parse_function, num_parallel_calls=self.read_threads)
 
         if self.memory_shuffle != Shuffle.OFF:
-            if self.memory_shuffle != Shuffle.SEED:
+            if self.memory_shuffle == Shuffle.SEED:
                 dataset = dataset.shuffle(buffer_size=self.shuffle_size,
                                           seed=self.seed)
             else:

src/reader/tf_reader.py

@@ -78,7 +78,7 @@ def read(self, epoch_number):
         dataset = dataset.map(self._tf_parse_function, num_parallel_calls=self.computation_threads)
 
         if self.memory_shuffle != Shuffle.OFF:
-            if self.memory_shuffle != Shuffle.SEED:
+            if self.memory_shuffle == Shuffle.SEED:
                 dataset = dataset.shuffle(buffer_size=self.shuffle_size,
                                           seed=self.seed)
             else:

src/utils/config.py

@@ -220,9 +220,9 @@ def LoadConfig(args, config):
     if 'profiling' in config: 
         if 'profiler' in config['profiling']:
             args.profiler = Profiler(config['profiling']['profiler'])
-        if 'devices' in config['profiling']:
+        if 'iostat_devices' in config['profiling']:
             args.iostat_devices = config['profiling']['iostat_devices']
-            if isinstance(args.io_devices_to_trace, str):
+            if isinstance(args.iostat_devices, str):
                 args.iostat_devices = [args.iostat_devices]
         if 'darshan_preload' in config['profiling']:
             args.darshan_preload = config['profiling']['darshan_preload']