Closed tinmodeHuang closed 3 years ago
patrickhart
commented
3 years ago Hello, this seems to be due to changes in the spektral library. EdgeConditionedConvdoes not seem to be available any longer. I will have a look into it and maybe remove spektral as the graph nets library provides enough capabilities.
patrickhart
commented
3 years ago Should be resolved by PR #85 Let us know if it works for you now!
tinmodeHuang
commented
3 years ago In this case, shall I find an alternative to EdgeConditionedConv in Spektral library for making sure of the model to works?
patrickhart
commented
3 years ago For now, I removed it from the master branch. A wide variety of graph neural networks can be implemented using the graphs-net library. As you do not seem to run the tfa_gnn example, this depends on the intended use-case. If you pull the master branch everything should work now (also the example you are trying to run)
tinmodeHuang
commented
3 years ago yeah, it works now! by the way, are there many behavior models in the bark-ml like those in the bark such as BehaviorMobilRuleBased which can be configured to other traffic participators?
patrickhart
commented
3 years ago Exactly, you can assign these models to other traffic participants in the scene (does not exclude the ego vehicle). For a closer look how these can be defined you can have a look e.g. here: https://github.com/bark-simulator/bark-ml/blob/87a8047abd36f28d5bad12c50e7156e75b6542c4/bark_ml/environments/blueprints/merging/merging.py#L82
Using the ParameterServer from BARK their behavior can be adapted.
patrickhart
commented
3 years ago As the problem seems to be solved, I am closing this issue for now.
tinmodeHuang
commented
3 years ago hey, @patrickhart . I want to run tfa_gnn.py in the training mode, and therefore the following modification has been done.
flags.DEFINE_enum("mode",
"train",
["train", "visualize", "evaluate"],
"Mode the configuration should be executed in.")but I got the error as follow:
Current thread 0x00007f76f8c6b740 (most recent call first):
File "/home/tinmode/bark-ml/bark_ml/python_wrapper/venv/lib/python3.7/site-packages/tensorflow/python/ops/gen_summary_ops.py", line 143 in create_summary_file_writer
File "/home/tinmode/bark-ml/bark_ml/python_wrapper/venv/lib/python3.7/site-packages/tensorflow/python/ops/summary_ops_v2.py", line 285 in __init__
File "/home/tinmode/bark-ml/bark_ml/python_wrapper/venv/lib/python3.7/site-packages/tensorflow/python/ops/summary_ops_v2.py", line 516 in create_file_writer_v2
File "/home/tinmode/.cache/bazel/_bazel_tinmode/0534ffbce5f0177dc35c2eb30e06c204/execroot/bark_ml/bazel-out/k8-fastbuild/bin/examples/tfa_gnn.runfiles/bark_ml/bark_ml/library_wrappers/lib_tf_agents/runners/tfa_runner.py", line 59 in SetupSummaryWriter
File "/home/tinmode/.cache/bazel/_bazel_tinmode/0534ffbce5f0177dc35c2eb30e06c204/execroot/bark_ml/bazel-out/k8-fastbuild/bin/examples/tfa_gnn.runfiles/bark_ml/examples/tfa_gnn.py", line 77 in run_configuration
File "/home/tinmode/bark-ml/bark_ml/python_wrapper/venv/lib/python3.7/site-packages/absl/app.py", line 251 in _run_main
File "/home/tinmode/bark-ml/bark_ml/python_wrapper/venv/lib/python3.7/site-packages/absl/app.py", line 303 in run
File "/home/tinmode/.cache/bazel/_bazel_tinmode/0534ffbce5f0177dc35c2eb30e06c204/execroot/bark_ml/bazel-out/k8-fastbuild/bin/examples/tfa_gnn.runfiles/bark_ml/examples/tfa_gnn.py", line 88 in <module>could you point me in the correct direction of cracking it?
patrickhart
commented
3 years ago is that the only error you get? Would be nice if you could provide more verbose logging. The example currently runs in the CI, but nevertheless I will additionally try running it locally.
EDIT: locally it seems to run for me. have you made sure to exactly install the requirements using the install.sh script?
tinmodeHuang
commented
3 years ago all info printed as follow:
INFO: Analyzed target //examples:tfa_gnn (0 packages loaded, 2 targets configured).
INFO: Found 1 target...
Target //examples:tfa_gnn up-to-date:
bazel-bin/examples/tfa_gnn
INFO: Elapsed time: 0.499s, Critical Path: 0.26s
INFO: 1 process: 1 internal.
INFO: Build completed successfully, 1 total action
INFO: Running command line: external/bazel_tools/tools/test/test-setup.sh examplINFO: Build completed successfully, 1 total action
exec ${PAGER:-/usr/bin/less} "$0" || exit 1
Executing tests from //examples:tfa_gnn
-----------------------------------------------------------------------------
2021-02-22 08:35:47.681869: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
WARNING:root:Argument blacklist is deprecated. Please use denylist.
WARNING:root:Argument blacklist is deprecated. Please use denylist.
I0222 08:35:49.831873 140148956641088 xodr_parser.py:318] Transforming PlanView with given offset
I0222 08:35:49.832876 140148956641088 xodr_parser.py:318] Transforming PlanView with given offset
WARNING: Logging before InitGoogleLogging() is written to STDERR
W0222 08:35:49.833972 12815 line.hpp:539] AppendLinesNoIntersect yields self intersecting line, will simplify it with 1e-06
W0222 08:35:49.836246 12815 line.hpp:539] AppendLinesNoIntersect yields self intersecting line, will simplify it with 1e-06
I0222 08:35:51.102321 140148956641088 graph_observer.py:72] GraphObserver configured with node attributes: ['x', 'y', 'theta', 'vel', 'goal_x', 'goal_y', 'goal_dx', 'goal_dy', 'goal_theta', 'goal_d', 'goal_vel']
I0222 08:35:51.102415 140148956641088 graph_observer.py:87] GraphObserver configured with edge attributes: ['dx', 'dy', 'dvel', 'dtheta']
2021-02-22 08:35:51.191214: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-02-22 08:35:51.191677: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2021-02-22 08:35:51.226737: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-22 08:35:51.227276: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: Quadro P2200 computeCapability: 6.1
coreClock: 1.493GHz coreCount: 10 deviceMemorySize: 4.94GiB deviceMemoryBandwidth: 186.45GiB/s
2021-02-22 08:35:51.227302: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-02-22 08:35:51.230018: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-02-22 08:35:51.230066: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-02-22 08:35:51.231103: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-02-22 08:35:51.231331: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-02-22 08:35:51.233914: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-02-22 08:35:51.234525: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2021-02-22 08:35:51.234656: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-02-22 08:35:51.234764: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-22 08:35:51.235188: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-22 08:35:51.235552: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-02-22 08:35:51.235826: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-02-22 08:35:51.236409: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-02-22 08:35:51.236496: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-22 08:35:51.236865: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: Quadro P2200 computeCapability: 6.1
coreClock: 1.493GHz coreCount: 10 deviceMemorySize: 4.94GiB deviceMemoryBandwidth: 186.45GiB/s
2021-02-22 08:35:51.236881: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-02-22 08:35:51.236898: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-02-22 08:35:51.236912: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-02-22 08:35:51.236926: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-02-22 08:35:51.236939: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-02-22 08:35:51.236955: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-02-22 08:35:51.236970: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2021-02-22 08:35:51.236985: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-02-22 08:35:51.237044: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-22 08:35:51.237452: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-22 08:35:51.237805: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-02-22 08:35:51.237830: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-02-22 08:35:51.508730: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-02-22 08:35:51.508746: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
2021-02-22 08:35:51.508750: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
2021-02-22 08:35:51.508938: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-22 08:35:51.509289: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-22 08:35:51.509696: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-22 08:35:51.509970: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4339 MB memory) -> physical GPU (device: 0, name: Quadro P2200, pci bus id: 0000:01:00.0, compute capability: 6.1)
2021-02-22 08:35:52.615242: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-02-22 08:35:52.737659: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2799925000 Hz
2021-02-22 08:35:52.939789: W tensorflow/core/grappler/optimizers/loop_optimizer.cc:906] Skipping loop optimization for Merge node with control input: cond/branch_executed/_32
2021-02-22 08:35:53.085557: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-02-22 08:35:53.249964: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-02-22 08:35:53.368112: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-02-22 08:36:13.117102: W tensorflow/core/grappler/optimizers/loop_optimizer.cc:906] Skipping loop optimization for Merge node with control input: cond/branch_executed/_32
2021-02-22 08:36:13.502343: W tensorflow/core/grappler/optimizers/loop_optimizer.cc:906] Skipping loop optimization for Merge node with control input: cond/branch_executed/_32
2021-02-22 08:36:13.886196: W tensorflow/core/grappler/optimizers/loop_optimizer.cc:906] Skipping loop optimization for Merge node with control input: cond/branch_executed/_32
2021-02-22 08:36:14.255450: W tensorflow/core/grappler/optimizers/loop_optimizer.cc:906] Skipping loop optimization for Merge node with control input: cond/branch_executed/_32
/home/tinmode/bark-ml/bark_ml/python_wrapper/venv/lib/python3.7/site-packages/gym/logger.py:30: UserWarning: WARN: Box bound precision lowered by casting to float32
warnings.warn(colorize('%s: %s'%('WARN', msg % args), 'yellow'))
WARNING:tensorflow:5 out of the last 5 calls to <function GraphNetwork.call at 0x7f75d5fb3440> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.
W0222 08:36:14.279514 140148956641088 def_function.py:126] 5 out of the last 5 calls to <function GraphNetwork.call at 0x7f75d5fb3440> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.
I0222 08:36:14.304891 140148956641088 common.py:980] No checkpoint available at
WARNING:tensorflow:From /home/tinmode/bark-ml/bark_ml/python_wrapper/venv/lib/python3.7/site-packages/tensorflow/python/autograph/operators/control_flow.py:1218: ReplayBuffer.get_next (from tf_agents.replay_buffers.replay_buffer) is deprecated and will be removed in a future version.
Instructions for updating:
Use `as_dataset(..., single_deterministic_pass=False) instead.
W0222 08:36:14.377789 140148956641088 api.py:479] From /home/tinmode/bark-ml/bark_ml/python_wrapper/venv/lib/python3.7/site-packages/tensorflow/python/autograph/operators/control_flow.py:1218: ReplayBuffer.get_next (from tf_agents.replay_buffers.replay_buffer) is deprecated and will be removed in a future version.
Instructions for updating:
Use `as_dataset(..., single_deterministic_pass=False) instead.
2021-02-22 08:36:14.739276: F tensorflow/core/framework/tensor.cc:673] Check failed: 1 == NumElements() (1 vs. 0)Must have a one element tensor
Fatal Python error: Aborted
Thread 0x00007f736705f700 (most recent call first):
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/multiprocessing/pool.py", line 470 in _handle_results
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 870 in run
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 926 in _bootstrap_inner
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 890 in _bootstrap
Thread 0x00007f7367860700 (most recent call first):
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/multiprocessing/pool.py", line 422 in _handle_tasks
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 870 in run
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 926 in _bootstrap_inner
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 890 in _bootstrap
Thread 0x00007f7494d1d700 (most recent call first):
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/multiprocessing/pool.py", line 413 in _handle_workers
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 870 in run
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 926 in _bootstrap_inner
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 890 in _bootstrap
Thread 0x00007f7496ffd700 (most recent call first):
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/multiprocessing/pool.py", line 110 in worker
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 870 in run
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 926 in _bootstrap_inner
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 890 in _bootstrap
Thread 0x00007f75d2f10700 (most recent call first):
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/multiprocessing/pool.py", line 470 in _handle_results
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 870 in run
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 926 in _bootstrap_inner
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 890 in _bootstrap
Thread 0x00007f75d3711700 (most recent call first):
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/multiprocessing/pool.py", line 422 in _handle_tasks
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 870 in run
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 926 in _bootstrap_inner
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 890 in _bootstrap
Thread 0x00007f75d3f12700 (most recent call first):
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/multiprocessing/pool.py", line 413 in _handle_workers
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 870 in run
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 926 in _bootstrap_inner
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 890 in _bootstrap
Thread 0x00007f75d4713700 (most recent call first):
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/multiprocessing/pool.py", line 110 in worker
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 870 in run
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 926 in _bootstrap_inner
File "/home/tinmode/anaconda3/envs/bark-ml/lib/python3.7/threading.py", line 890 in _bootstrap
Current thread 0x00007f76f8c6b740 (most recent call first):
File "/home/tinmode/bark-ml/bark_ml/python_wrapper/venv/lib/python3.7/site-packages/tensorflow/python/ops/gen_summary_ops.py", line 143 in create_summary_file_writer
File "/home/tinmode/bark-ml/bark_ml/python_wrapper/venv/lib/python3.7/site-packages/tensorflow/python/ops/summary_ops_v2.py", line 285 in __init__
File "/home/tinmode/bark-ml/bark_ml/python_wrapper/venv/lib/python3.7/site-packages/tensorflow/python/ops/summary_ops_v2.py", line 516 in create_file_writer_v2
File "/home/tinmode/.cache/bazel/_bazel_tinmode/0534ffbce5f0177dc35c2eb30e06c204/execroot/bark_ml/bazel-out/k8-fastbuild/bin/examples/tfa_gnn.runfiles/bark_ml/bark_ml/library_wrappers/lib_tf_agents/runners/tfa_runner.py", line 59 in SetupSummaryWriter
File "/home/tinmode/.cache/bazel/_bazel_tinmode/0534ffbce5f0177dc35c2eb30e06c204/execroot/bark_ml/bazel-out/k8-fastbuild/bin/examples/tfa_gnn.runfiles/bark_ml/examples/tfa_gnn.py", line 77 in run_configuration
File "/home/tinmode/bark-ml/bark_ml/python_wrapper/venv/lib/python3.7/site-packages/absl/app.py", line 251 in _run_main
File "/home/tinmode/bark-ml/bark_ml/python_wrapper/venv/lib/python3.7/site-packages/absl/app.py", line 303 in run
File "/home/tinmode/.cache/bazel/_bazel_tinmode/0534ffbce5f0177dc35c2eb30e06c204/execroot/bark_ml/bazel-out/k8-fastbuild/bin/examples/tfa_gnn.runfiles/bark_ml/examples/tfa_gnn.py", line 88 in <module>yes, I have. because the script can locally run in visualization mode.
patrickhart
commented
3 years ago This error seems like its platform/version specific. Here are a few things that I suggest:
tinmodeHuang
commented
3 years ago the tensorflow2.4 being in use, by the way, what is the CI?
patrickhart
commented
3 years ago CI = Continuous Integration
here is a Docker workflow: https://github.com/bark-simulator/bark-ml/blob/master/.github/workflows/main.yml
tinmodeHuang
commented
3 years ago the excessive number of tracings won't to be done after commenting out @tf.function(experimental_relax_shapes=True) in the graph_network.py and @tf.function in the interaction_wrapper.py. To be honest, I don't understood what the first 12th lines in the main.yml be used to do.
patrickhart
commented
3 years ago Contributions in form of improvements are always welcome!
The main.yml file sets up a Github workflow to run BARK-ML in a docker. This should be platform independent.
tinmodeHuang
commented
3 years ago although I tried to learn about the main.yml, it's too hard for a noob like me to know a lot about it in a short time. if convient, could you tell me how to use it for running BARK-ML in a docker.
patrickhart
commented
3 years ago May I ask what your overall goal is using BARK-ML, learning a behavior using graph neural networks?
I think this is not the right place, to give an introduction to Docker and how to execute python and executables within Docker. Once you are familiar with Docker it should become self-explanatory how to execute scripts.
tinmodeHuang
commented
3 years ago yes. I'm sorry for being eager, and thanks for your advice, I will spend more time being familiar with Docker.
It's too hard for me to figure out what was wrong, @patrickhart @klemense1 help me please!
my operations as follow:
the somethings printed as follow:
tinmode@tinmode-ThinkStation-K:~/bark-ml$ bash utils/install.sh
tinmode@tinmode-ThinkStation-K:~/bark-ml$ source utils/dev_into.sh
(venv) tinmode@tinmode-ThinkStation-K:~/bark-ml$ bazel run //examples:continuous_env
(venv) tinmode@tinmode-ThinkStation-K:~/bark-ml$ bazel run //examples:tfa