routine
This commit is contained in:
3
tf/docker-run.sh
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3
tf/docker-run.sh
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#!/bin/bash
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# nvcr.io/nvidia/tensorflow:24.12-tf2-py3
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docker run -itd --gpus all --name ail-tf -v /data/szh2/Project/AI-learning:/workspace/ail -p 58888:8888 nvcr.io/nvidia/tensorflow:24.12-tf2-py3 jupyter notebook --NotebookApp.token='12345678'
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112
tf/gpu.ipynb
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112
tf/gpu.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2025-01-09 10:12:54.526706: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
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"2025-01-09 10:12:54.541661: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
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"2025-01-09 10:12:54.560110: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8473] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
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"2025-01-09 10:12:54.565525: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1471] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
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"2025-01-09 10:12:54.578678: I tensorflow/core/platform/cpu_feature_guard.cc:211] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
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"To enable the following instructions: SSE3 SSE4.1 SSE4.2 AVX, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"b'Hello, TensorFlow!'\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2025-01-09 10:12:58.748603: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 1143 MB memory: -> device: 0, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:35:00.0, compute capability: 8.0\n",
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"2025-01-09 10:12:58.751140: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 78412 MB memory: -> device: 1, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:36:00.0, compute capability: 8.0\n",
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"2025-01-09 10:12:58.752975: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 78412 MB memory: -> device: 2, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:39:00.0, compute capability: 8.0\n",
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"2025-01-09 10:12:58.754821: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 78412 MB memory: -> device: 3, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:3d:00.0, compute capability: 8.0\n",
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"2025-01-09 10:12:58.756707: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /job:localhost/replica:0/task:0/device:GPU:4 with 78412 MB memory: -> device: 4, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:9c:00.0, compute capability: 8.0\n",
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"2025-01-09 10:12:58.758405: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /job:localhost/replica:0/task:0/device:GPU:5 with 78412 MB memory: -> device: 5, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:9d:00.0, compute capability: 8.0\n",
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"2025-01-09 10:12:58.760115: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /job:localhost/replica:0/task:0/device:GPU:6 with 78412 MB memory: -> device: 6, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:a0:00.0, compute capability: 8.0\n",
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"2025-01-09 10:12:58.761971: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /job:localhost/replica:0/task:0/device:GPU:7 with 77296 MB memory: -> device: 7, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:a4:00.0, compute capability: 8.0\n"
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]
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}
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],
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"source": [
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"import tensorflow as tf\n",
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"# 创建一个TensorFlow常量\n",
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"hello = tf.constant('Hello, TensorFlow!')\n",
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"# 将TensorFlow张量转换为NumPy数组\n",
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"numpy_array = hello.numpy()\n",
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"print(numpy_array) # 输出: b'Hello, TensorFlow!'"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"WARNING:tensorflow:From /tmp/ipykernel_137363/2801978163.py:2: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version.\n",
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"Instructions for updating:\n",
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"Use `tf.config.list_physical_devices('GPU')` instead.\n",
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"True\n",
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"[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU'), PhysicalDevice(name='/physical_device:GPU:1', device_type='GPU'), PhysicalDevice(name='/physical_device:GPU:2', device_type='GPU'), PhysicalDevice(name='/physical_device:GPU:3', device_type='GPU'), PhysicalDevice(name='/physical_device:GPU:4', device_type='GPU'), PhysicalDevice(name='/physical_device:GPU:5', device_type='GPU'), PhysicalDevice(name='/physical_device:GPU:6', device_type='GPU'), PhysicalDevice(name='/physical_device:GPU:7', device_type='GPU')] [PhysicalDevice(name='/physical_device:CPU:0', device_type='CPU')]\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2025-01-09 10:13:03.154945: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /device:GPU:0 with 1143 MB memory: -> device: 0, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:35:00.0, compute capability: 8.0\n",
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"2025-01-09 10:13:03.156613: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /device:GPU:1 with 78412 MB memory: -> device: 1, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:36:00.0, compute capability: 8.0\n",
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"2025-01-09 10:13:03.158071: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /device:GPU:2 with 78412 MB memory: -> device: 2, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:39:00.0, compute capability: 8.0\n",
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"2025-01-09 10:13:03.159472: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /device:GPU:3 with 78412 MB memory: -> device: 3, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:3d:00.0, compute capability: 8.0\n",
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"2025-01-09 10:13:03.161049: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /device:GPU:4 with 78412 MB memory: -> device: 4, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:9c:00.0, compute capability: 8.0\n",
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"2025-01-09 10:13:03.162507: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /device:GPU:5 with 78412 MB memory: -> device: 5, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:9d:00.0, compute capability: 8.0\n",
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"2025-01-09 10:13:03.163784: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /device:GPU:6 with 78412 MB memory: -> device: 6, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:a0:00.0, compute capability: 8.0\n",
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"2025-01-09 10:13:03.165104: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /device:GPU:7 with 77296 MB memory: -> device: 7, name: NVIDIA A800 80GB PCIe, pci bus id: 0000:a4:00.0, compute capability: 8.0\n"
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]
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}
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],
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"source": [
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"import tensorflow as tf\n",
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"print(tf.test.is_gpu_available())\n",
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"gpus = tf.config.experimental.list_physical_devices(device_type='GPU')\n",
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"cpus = tf.config.experimental.list_physical_devices(device_type='CPU')\n",
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"print(gpus, cpus)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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1
tf/requirements.txt
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1
tf/requirements.txt
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matplotlib
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import tensorflow as tf
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# 创建一个TensorFlow常量
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hello = tf.constant('Hello, TensorFlow!')
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# 将TensorFlow张量转换为NumPy数组
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numpy_array = hello.numpy()
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print(numpy_array) # 输出: b'Hello, TensorFlow!'
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