remove conformer oom fixes from this branch

algorithmic_efficiency/workloads/librispeech_conformer/workload.py

@@ -67,8 +67,7 @@ def train_stddev(self):
 
   @property
   def max_allowed_runtime_sec(self) -> int:
-    return 122136 # ~34h extended max_allowed_run_time for conformer OOM issue
-
+    return 61_068  # ~17 hours
 
   @property
   def eval_period_time_sec(self) -> int:

submission_runner.py

@@ -50,7 +50,6 @@
 
 # disable only for deepspeech if it works fine for other workloads.
 os.environ['XLA_FLAGS'] = '--xla_gpu_enable_triton_gemm=false'
-os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'max_split_size_mb:256'
 
 # TODO(znado): make a nicer registry of workloads that lookup in.
 BASE_WORKLOADS_DIR = workloads.BASE_WORKLOADS_DIR
@@ -216,8 +215,10 @@ def train_once(
     model_params, model_state = workload.init_model_fn(
         model_init_rng, dropout_rate, aux_dropout_rate)
     if FLAGS.framework == 'pytorch' and FLAGS.torch_compile:
-      compile_error_workloads = ['ogbg', 'criteo1tb', 'librispeech_conformer']
-      eager_backend_workloads = ['librispeech_deepspeech']
+      compile_error_workloads = ['ogbg', 'criteo1tb']
+      eager_backend_workloads = [
+          'librispeech_conformer', 'librispeech_deepspeech'
+      ]
       aot_eager_backend_workloads = []
       if FLAGS.workload in compile_error_workloads:
         logging.warning(
@@ -601,7 +602,6 @@ def main(_):
   # Prevent OOM on librispeech conformer.
   if FLAGS.workload == 'librispeech_conformer':
     os.environ['XLA_PYTHON_CLIENT_MEM_FRACTION'] = '0.85'
-    os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'max_split_size_mb:256'
 
   # Extend path according to framework.
   workload_metadata['workload_path'] = os.path.join(