I'm trying to use XLA in TensorFlow using jit_compile=True, currently. However, the error looks like it cannot.
First of all, I tried simple code as below,
import tensorflow as tf
@tf.function(jit_compile=True)
def operation(a, b):
return a * b
And, I got an error as below,
(base) ***@MacBook-Pro folder % /Users/***/miniforge3/envs/testtf/bin/python /Users/***/workplace/research/folder/subfolder/test/test_jit_compile.py
Metal device set to: Apple M1 Pro
systemMemory: 32.00 GB
maxCacheSize: 10.67 GB
2023-01-11 12:45:18.794439: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:306] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.
2023-01-11 12:45:18.794689: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:272] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>)
2023-01-11 12:45:18.808796: W tensorflow/core/framework/op_kernel.cc:1830] OP_REQUIRES failed at xla_ops.cc:418 : NOT_FOUND: could not find registered platform with id: 0x10c7ba7e0
Traceback (most recent call last):
File "/Users/***/workplace/research/folder/subfolder/test/test_jit_compile.py", line 25, in <module>
print(operation(3, 4))
File "/Users/***/miniforge3/envs/testtf/lib/python3.8/site-packages/tensorflow/python/util/traceback_utils.py", line 153, in error_handler
raise e.with_traceback(filtered_tb) from None
File "/Users/***/miniforge3/envs/testtf/lib/python3.8/site-packages/tensorflow/python/eager/execute.py", line 52, in quick_execute
tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.NotFoundError: could not find registered platform with id: 0x10c7ba7e0 [Op:__inference_operation_5]
This seems like XLA did not register. Would you guide how to use jit_compile=True in this environment? I attached my environment as below also.
Package Version
----------------------- ---------
absl-py 1.3.0
astunparse 1.6.3
cachetools 5.2.1
certifi 2022.12.7
charset-normalizer 2.1.1
flatbuffers 23.1.4
gast 0.4.0
google-auth 2.16.0
google-auth-oauthlib 0.4.6
google-pasta 0.2.0
grpcio 1.42.0
h5py 3.6.0
idna 3.4
importlib-metadata 6.0.0
keras 2.11.0
libclang 15.0.6.1
Markdown 3.4.1
MarkupSafe 2.1.1
numpy 1.22.3
oauthlib 3.2.2
opt-einsum 3.3.0
packaging 23.0
pip 22.3.1
protobuf 3.19.6
pyasn1 0.4.8
pyasn1-modules 0.2.8
requests 2.28.1
requests-oauthlib 1.3.1
rsa 4.9
setuptools 65.6.3
six 1.16.0
tensorboard 2.11.0
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.8.1
tensorflow-estimator 2.11.0
tensorflow-macos 2.11.0
tensorflow-metal 0.7.0
termcolor 2.2.0
typing_extensions 4.4.0
urllib3 1.26.13
Werkzeug 2.2.2
wheel 0.37.1
wrapt 1.14.1
zipp 3.11.0
Thanks.
Topic:
App & System Services
SubTopic:
Hardware
Tags:
Apple Silicon
tensorflow-metal
Machine Learning