From dacc3421aef9bd35e53220f74200a497bef74a5e Mon Sep 17 00:00:00 2001
From: schmitt <robin.schmitt1@rwth-aachen.de>
Date: Fri, 7 Mar 2025 10:42:13 +0100
Subject: [PATCH] update

---
 .../settings.py                               | 157 ++++++++++++++++++
 1 file changed, 157 insertions(+)
 create mode 100644 users/schmitt/experiments/exp2024_08_27_flipped_conformer/settings.py

diff --git a/users/schmitt/experiments/exp2024_08_27_flipped_conformer/settings.py b/users/schmitt/experiments/exp2024_08_27_flipped_conformer/settings.py
new file mode 100644
index 000000000..e01d6099c
--- /dev/null
+++ b/users/schmitt/experiments/exp2024_08_27_flipped_conformer/settings.py
@@ -0,0 +1,157 @@
+import getpass
+import multiprocessing
+import os
+import sys
+
+sys.path.append("/usr/local/cache-manager")
+
+WORK_DIR = "work"
+IMPORT_PATHS = ["config", "recipe", "recipe/"]
+
+
+def engine():
+  from sisyphus.localengine import LocalEngine
+  from sisyphus.engine import EngineSelector
+  from sisyphus.simple_linux_utility_for_resource_management_engine import (
+    SimpleLinuxUtilityForResourceManagementEngine,
+  )
+
+  return EngineSelector(
+    engines={
+      "short": LocalEngine(cpus=multiprocessing.cpu_count()),
+      "long": SimpleLinuxUtilityForResourceManagementEngine(
+        default_rqmt={"cpu": 1, "mem": 1, "time": 1}
+      ),
+    },
+    default_engine="long",
+  )
+
+
+MAIL_ADDRESS = getpass.getuser()
+
+WAIT_PERIOD_CACHE = 8
+WAIT_PERIOD_JOB_FS_SYNC = 8
+
+JOB_CLEANUP_KEEP_WORK = True
+JOB_AUTO_CLEANUP = False
+# JOB_FINAL_LOG = "finished.tar.gz"
+
+SHOW_JOB_TARGETS = False
+PRINT_ERROR_TASKS = 0
+PRINT_ERROR_LINES = 10
+
+# RASR_ROOT = "/u/berger/repositories/rasr_versions/gen_seq2seq_dev/"
+RASR_ROOT = "/u/schmitt/src/rasr_versions/gen_seq2seq_dev"
+RASR_ARCH = "linux-x86_64-standard"
+SCTK_PATH = "/u/beck/programs/sctk-2.4.0/bin/"
+RETURNN_ROOT = "/u/schmitt/src/returnn_new"
+
+SHOW_JOB_TARGETS = False
+SHOW_VIS_NAME_IN_MANAGER = False
+
+DEFAULT_ENVIRONMENT_KEEP = {
+  "CUDA_VISIBLE_DEVICES",
+  "LD_LIBRARY_PATH",
+  "HOME",
+  "HOST",
+  "PWD",
+  "USER",
+}
+
+DEFAULT_ENVIRONMENT_SET["HOME"] = "/u/schmitt"
+
+TMP_PREFIX = "/var/tmp/"
+DEFAULT_ENVIRONMENT_SET["TMPDIR"] = TMP_PREFIX
+DEFAULT_ENVIRONMENT_SET["TMP"] = TMP_PREFIX
+
+DEFAULT_ENVIRONMENT_SET["LD_LIBRARY_PATH"] = ":".join(
+  [
+    "/usr/local/lib/tensorflow/",
+    "/usr/local/lib/python3.8/dist-packages/tensorflow/",
+    "/usr/local/lib/python3.8/dist-packages/scipy/.libs",
+    "/usr/local/lib/python3.8/dist-packages/numpy.libs",
+    "/usr/local/lib/python3.10/dist-packages/tensorflow/",
+    "/usr/local/lib/python3.10/dist-packages/scipy/.libs",
+    "/usr/local/lib/python3.10/dist-packages/numpy.libs",
+    "/usr/local/cuda/extras/CUPTI/lib64",
+    "/usr/local/cuda/compat/lib",
+    "/usr/local/nvidia/lib",
+    "/usr/local/nvidia/lib64",
+    "/.singularity.d/libs",
+  ]
+)
+DEFAULT_ENVIRONMENT_SET["NUMBA_CACHE_DIR"] = "/var/tmp/numba_cache_{}/".format(os.environ["USER"])  # for librosa
+
+
+def check_engine_limits(current_rqmt, task):
+  """
+  i6 support for gpu_mem
+  """
+  current_rqmt["time"] = min(168, current_rqmt.get("time", 2))
+  if current_rqmt.get("gpu", 0) > 0 and "-p" not in current_rqmt.get(
+          "sbatch_args", []
+  ):
+    if "sbatch_args" not in current_rqmt:
+      current_rqmt["sbatch_args"] = []
+      
+    if current_rqmt.get("gpu_mem", 0) > 11:
+      current_rqmt["sbatch_args"] += ["-p", "gpu_24gb"]
+    else:
+      current_rqmt["sbatch_args"] += ["-p", "gpu_11gb"]
+
+  return current_rqmt
+
+
+def file_caching(path):
+  return "`cf %s`" % path
+
+
+def copy_cached_file(path):
+  from subprocess import run
+
+  src = path
+  trg = file_caching(path, is_output=True)
+  run(["cf", "-cp", src, trg])
+
+
+def copy_remote_file(path):
+  from subprocess import check_output
+
+  return check_output(["cf", path]).decode("utf-8")
+
+
+def worker_wrapper(job, task_name, call):
+  app_blacklist = {}
+
+  if type(job).__name__ in app_blacklist:
+    return call
+
+  binds = ["/work/asr4", "/work/asr3", "/work/common", "/work/tools", "/u/berger", "/u/zeineldeen", "/u/rossenbach",
+           "/u/beck", "/work/speech/tuske", "/u/zeyer", "/u/schmitt", "/u/atanas.gruev", "/u/zhou", "/work/smt4/thulke/schmitt"]
+  ts = {t.name(): t for t in job.tasks()}
+  t = ts[task_name]
+
+  app_call = [
+    "apptainer",
+    "exec",
+  ]
+
+  if t._rqmt.get("gpu", 0) > 0:
+    app_call += ["--nv"]
+
+  for path in binds:
+    app_call += ["-B", path]
+
+  if type(job).__name__ == "ReturnnForwardJob":
+    """
+    Problems with h5py version: with Simon's apptainer, the "labels" entry of hdf files stores bytes instead of strings.
+    This leads to problems with RETURNN's HDFDataset since it expects strings.
+    """
+    app_call += ["/work/asr3/zeyer/schmitt/apptainer/images/u16.sif", "python3", ]
+  else:
+  #  app_call += ["/work/asr4/berger/apptainer/images/i6_torch-2.2_onnx-1.16.sif", "python3", ]
+    app_call += ["/work/tools22/users/schmitt/apptainer/images/i6_torch-2.2_onnx-1.16.sif", "python3", ]
+
+  app_call += call[1:]
+
+  return app_call