No output audio via docker

[daveleigh22]

Hi,

I've tried on Ubuntu and Windows (Linux containers on windows) and I get feedback from the container, it downloads the stems model and is see contents in my model directory but then no files in the output directory.

The command i'm running:

docker run -v C:\t\input:/input -v C:\t\output:/output -v C:\t\model:/model -e MODEL_PATH=/model researchdeezer/spleeter separate -i /input/audio_1.mp3 -o /output

Thanks in advance,

[zevlag]

I have what appears to be the same problem. Running with --verbose I see the following:

DESKTOP:split zevlag$ docker run     -v $AUDIO_IN:/input     -v $AUDIO_OUT:/output     -v $MODEL_DIRECTORY:/model     -e MODEL_PATH=/model     researchdeezer/spleeter     separate -i /input/6831248722421364582.m4a -o /output --verbose

INFO:tensorflow:Using config: {'_model_dir': '/model/2stems', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': gpu_options {
  per_process_gpu_memory_fraction: 0.7
}
, '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_experimental_max_worker_delay_secs': None, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f1589821650>, '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}
INFO:tensorflow:Calling model_fn.
WARNING:tensorflow:From /usr/local/lib/python3.7/site-packages/spleeter/model/functions/unet.py:30: The name tf.keras.initializers.he_uniform is deprecated. Please use tf.compat.v1.keras.initializers.he_uniform instead.

INFO:tensorflow:Apply unet for vocals_spectrogram
INFO:tensorflow:Apply unet for accompaniment_spectrogram
INFO:tensorflow:Done calling model_fn.
WARNING:tensorflow:From /usr/local/lib/python3.7/site-packages/tensorflow/python/saved_model/signature_def_utils_impl.py:201: build_tensor_info (from tensorflow.python.saved_model.utils_impl) is deprecated and will be removed in a future version.
Instructions for updating:
This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.utils.build_tensor_info or tf.compat.v1.saved_model.build_tensor_info.
INFO:tensorflow:Signatures INCLUDED in export for Classify: None
INFO:tensorflow:Signatures INCLUDED in export for Regress: None
INFO:tensorflow:Signatures INCLUDED in export for Predict: ['serving_default']
INFO:tensorflow:Signatures INCLUDED in export for Train: None
INFO:tensorflow:Signatures INCLUDED in export for Eval: None
WARNING:tensorflow:From /usr/local/lib/python3.7/site-packages/tensorflow/python/training/saver.py:1276: checkpoint_exists (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version.
Instructions for updating:
Use standard file APIs to check for files with this prefix.
INFO:tensorflow:Restoring parameters from /model/2stems/model
2020-05-26 21:22:24.901135: W tensorflow/compiler/jit/mark_for_compilation_pass.cc:1412] (One-time warning): Not using XLA:CPU for cluster because envvar TF_XLA_FLAGS=--tf_xla_cpu_global_jit was not set.  If you want XLA:CPU, either set that envvar, or use experimental_jit_scope to enable XLA:CPU.  To confirm that XLA is active, pass --vmodule=xla_compilation_cache=1 (as a proper command-line flag, not via TF_XLA_FLAGS) or set the envvar XLA_FLAGS=--xla_hlo_profile.
INFO:tensorflow:Assets added to graph.
INFO:tensorflow:No assets to write.
INFO:tensorflow:SavedModel written to: /tmp/serving/temp-b'1590528138'/saved_model.pb
WARNING:tensorflow:From /usr/local/lib/python3.7/site-packages/tensorflow/contrib/predictor/saved_model_predictor.py:153: load (from tensorflow.python.saved_model.loader_impl) is deprecated and will be removed in a future version.
Instructions for updating:
This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.loader.load or tf.compat.v1.saved_model.load. There will be a new function for importing SavedModels in Tensorflow 2.0.
INFO:tensorflow:Restoring parameters from /tmp/serving/1590528138/variables/variables
2020-05-26 21:22:27.418302: W tensorflow/core/framework/allocator.cc:107] Allocation of 211680000 exceeds 10% of system memory.
2020-05-26 21:22:28.159911: W tensorflow/core/framework/allocator.cc:107] Allocation of 211680000 exceeds 10% of system memory.
2020-05-26 21:22:28.308913: W tensorflow/core/framework/allocator.cc:107] Allocation of 211705856 exceeds 10% of system memory.
2020-05-26 21:22:28.530976: W tensorflow/core/framework/allocator.cc:107] Allocation of 846725120 exceeds 10% of system memory.
2020-05-26 21:22:29.575600: W tensorflow/core/framework/allocator.cc:107] Allocation of 847138560 exceeds 10% of system memory.

[stewbawka]

Got this error too.. if you're using the docker engine on mac you can give more memory to it in preferences. It needs a good chunk of memory for larger input files, the sample mp3 is super tiny. I'm going to try alternate setup and install it through conda and give that a whirl instead.