TinyML
来自Jack's Lab
（版本间的差异）
(→Quick Start) |
(→Quick Start) |
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| 第9行： | 第9行： | ||
<source lang=bash> | <source lang=bash> | ||
| − | $ pip3 install -i https://pypi.tuna.tsinghua.edu.cn/simple tensorflow-gpu==2. | + | $ pip3 install -i https://pypi.tuna.tsinghua.edu.cn/simple tensorflow-gpu==2.5.0 |
$ python3 | $ python3 | ||
2022年4月1日 (五) 10:25的版本
1 Overview
2 Quick Start
$ pip3 install -i https://pypi.tuna.tsinghua.edu.cn/simple tensorflow-gpu==2.5.0
$ python3
import tensorflow as tf
>>> print(tf.__version__)
2.5.0
>>> print('GPU: ', tf.test.is_gpu_available())
2022-04-01 03:24:13.099644: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1733] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce GTX 1050 computeCapability: 6.1
coreClock: 1.493GHz coreCount: 5 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s
2022-04-01 03:24:13.099980: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1871] Adding visible gpu devices: 0
2022-04-01 03:24:13.100248: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1258] Device interconnect StreamExecutor with strength 1 edge matrix:
2022-04-01 03:24:13.100459: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1264] 0
2022-04-01 03:24:13.100669: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1277] 0: N
2022-04-01 03:24:13.100967: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1418] Created TensorFlow device (/device:GPU:0 with 2779 MB memory) -> physical G
PU (device: 0, name: NVIDIA GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1)
GPU: True
>>> hello = tf.constant('Hello, Tensorflow!')
>>> print(hello)
tf.Tensor(b'Hello, Tensorflow!', shape=(), dtype=string)
