2022年4月2日 (六) 11:08的版本

1 Overview

• Easy Tensorflow TinyML on ESP32 and Arduino
• z-lib.org

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)

>>> from tensorflow.python.client import device_lib
>>> print(device_lib.list_local_devices())
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 12041451716771642396
, name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 2914163099
locality {
  bus_id: 1
  links {
  }
}
incarnation: 596105631149220834
physical_device_desc: "device: 0, name: NVIDIA GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1"
]