tensorflow UnknownError:图形执行错误: JIT编译失败。[Op:__inference_restored_function_body_9127]
tensorflow UnknownError:图形执行错误: JIT编译失败。[Op:__inference_restored_function_body_9127]
提问于 2022-11-25 01:13:14
我试着使用来自tensorflow中心的通用语句编码器。从集线器下载并提取通用句子编码器，当我试图预测一种感觉时，它显示出一个错误：
UnknownError:图形执行错误：
JIT编译失败。
import tensorflow_hub as hub
#loading downloaded and untarred universal sentence encoder
embed = hub.load("./universal-sentence-encoder_4/")
# passed as an array in embed()
Sentences = [
"How old are you"
]
embeddings = embed(Sentences)
print(embeddings)得到了错误
2022-11-25 06:29:46.006767: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 2630 MB memory: -> device: 0, name: NVIDIA GeForce GTX 1650, pci bus id: 0000:01:00.0, compute capability: 7.5
error: Can't find libdevice directory ${CUDA_DIR}/nvvm/libdevice
2022-11-25 06:29:50.652156: W tensorflow/core/framework/op_kernel.cc:1768] UNKNOWN: JIT compilation failed.
---------------------------------------------------------------------------
UnknownError Traceback (most recent call last)
Input In [1], in <cell line: 25>()
17 # Load pre-trained universal sentence encoder model
18 # embed = hub.load("https://tfhub.dev/google/universal-sentence-encoder/4")
19
20 # Sentences for which you want to create embeddings,
21 # passed as an array in embed()
22 Sentences = [
23 "How old are you"
24 ]
---> 25 embeddings = embed(Sentences)
27 # Printing embeddings of each sentence
28 print(embeddings)
File ~/miniconda3/envs/tf/lib/python3.10/site-packages/tensorflow/python/saved_model/load.py:704, in _call_attribute(instance, *args, **kwargs)
703 def _call_attribute(instance, *args, **kwargs):
--> 704 return instance.__call__(*args, **kwargs)
File ~/miniconda3/envs/tf/lib/python3.10/site-packages/tensorflow/python/util/traceback_utils.py:153, in filter_traceback.<locals>.error_handler(*args, **kwargs)
151 except Exception as e:
152 filtered_tb = _process_traceback_frames(e.__traceback__)
--> 153 raise e.with_traceback(filtered_tb) from None
154 finally:
155 del filtered_tb
File ~/miniconda3/envs/tf/lib/python3.10/site-packages/tensorflow/python/eager/execute.py:54, in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
52 try:
53 ctx.ensure_initialized()
---> 54 tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
55 inputs, attrs, num_outputs)
56 except core._NotOkStatusException as e:
57 if name is not None:
UnknownError: Graph execution error:
JIT compilation failed.
[[{{node EncoderDNN/EmbeddingLookup/EmbeddingLookupUnique/embedding_lookup/mod}}]] [Op:__inference_restored_function_body_4561]我该怎么修呢？我只想让它起作用。
Stack Overflow用户
发布于 2022-11-25 04:43:32
首先，在CPU后置、tf.estimators()和TensorFlow集线器需要专用硬件的情况下，使用GPU是一个错误。嵌入-4
示例:尝试将CUDA路径添加到操作系统的局部变量中，存在错误，请按照说明进行操作。显示未完成安装或安装的错误。
import tensorflow as tf
import tensorflow_hub as hub
"""""""""""""""""""""""""""""""""""""""""""""""""""""""""
[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]
None
"""""""""""""""""""""""""""""""""""""""""""""""""""""""""
physical_devices = tf.config.experimental.list_physical_devices('GPU')
assert len(physical_devices) > 0, "Not enough GPU hardware devices available"
config = tf.config.experimental.set_memory_growth(physical_devices[0], True)
print(physical_devices)
print(config)
embed = hub.load("https://tfhub.dev/google/universal-sentence-encoder/4")
embeddings = embed([
"The quick brown fox jumps over the lazy dog.",
"I am a sentence for which I would like to get its embedding"])
print(embeddings)输出:简单的嵌入层，字到序列的工作原理。
tf.Tensor(
[[-0.03133015 -0.06338634 -0.01607501 ... -0.03242781 -0.0457574
0.05370456]
[ 0.05080863 -0.01652433 0.0157378 ... 0.00976659 0.03170122
0.01788119]], shape=(2, 512), dtype=float32)页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/74567500
复制相关文章
相似问题
腾讯云开发者
