NVIDIA Jetson Nanoに TensorFlowをインストールする方法

user@user-desktop:~$ uname -a
Linux user-desktop 4.9.140-tegra #1 SMP PREEMPT Wed Mar 13 00:32:22 PDT 2019 aarch64 aarch64 aarch64 GNU/Linux

#!/bin/bash

# Prerequisites and Dependencies
# Install HDF5 as required by TensorFlow:
sudo apt-get -y install libhdf5-serial-dev hdf5-tools

# Install pip3.
sudo apt-get -y install python3-pip

# Install the following packages:
# $ pip3 install -U pip
sudo apt-get -y install zlib1g-dev zip libjpeg8-dev libhdf5-dev
sudo pip3 install -U numpy grpcio absl-py py-cpuinfo psutil portpicker grpcio six mock requests gast h5py astor termcolor

# Installing TensorFlow
# Install TensorFlow using the pip3 command. This command will install the latest version of TensorFlow.
# tensorflow_gpu-1.13.1+nv19.5-cp36-cp36m-linux_aarch64.whl (204.6MB)
sudo pip3 install --pre --extra-index-url https://developer.download.nvidia.com/compute/redist/jp/v42 tensorflow-gpu

# Installing collected packages: keras-preprocessing, protobuf, werkzeug, markdown, tensorboard, tensorflow-estimator, keras-applications, tensorflow-gpu
# Successfully installed keras-applications-1.0.7 keras-preprocessing-1.0.9 markdown-3.1 protobuf-3.8.0rc1 tensorboard-1.13.1 tensorflow-estimator-1.13.0 tensorflow-gpu-1.13.1+nv19.5 werkzeug-0.15.4

# Verifying The Installation
python3 -c "import tensorflow; print (tensorflow.__version__)"
# 1.13.1

python3 -c "import tensorflow; print (tensorflow.__file__)"
# local/lib/python3.6/dist-packages/tensorflow/__init__.py

# python2では動かない
python -c "import tensorflow; print (tensorflow.__file__)"
# Traceback (most recent call last):
#   File "<string>", line 1, in <module>
# ImportError: No module named tensorflow

cd
git clone https://github.com/hjptriplebee/deep_dream_tensorflow.git
cd deep_dream_tensorflow

python3 main.py --input nature_image.jpg --output nature_image_tf.jpg
python3 main.py --input paint.jpg --output paint_tf.jpg

user@user-desktop:~/deep_dream_tensorflow$ python3 main.py --input nature_image.jpg --output nature_image_tf.jpg
2019-05-21 20:55:11.265467: W tensorflow/core/platform/profile_utils/cpu_utils.cc:98] Failed to find bogomips in /proc/cpuinfo; cannot determine CPU frequency
2019-05-21 20:55:11.266324: I tensorflow/compiler/xla/service/service.cc:161] XLA service 0x196de670 executing computations on platform Host. Devices:
2019-05-21 20:55:11.266395: I tensorflow/compiler/xla/service/service.cc:168]   StreamExecutor device (0): <undefined>, <undefined>
2019-05-21 20:55:11.536313: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:965] ARM64 does not support NUMA - returning NUMA node zero
2019-05-21 20:55:11.536594: I tensorflow/compiler/xla/service/service.cc:161] XLA service 0x181b9e70 executing computations on platform CUDA. Devices:
2019-05-21 20:55:11.536654: I tensorflow/compiler/xla/service/service.cc:168]   StreamExecutor device (0): NVIDIA Tegra X1, Compute Capability 5.3
2019-05-21 20:55:11.537888: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0 with properties:
name: NVIDIA Tegra X1 major: 5 minor: 3 memoryClockRate(GHz): 0.9216
pciBusID: 0000:00:00.0
totalMemory: 3.87GiB freeMemory: 2.30GiB
2019-05-21 20:55:11.538213: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2019-05-21 20:55:22.196790: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-05-21 20:55:22.196859: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990]      0
2019-05-21 20:55:22.196885: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0:   N
2019-05-21 20:55:22.197112: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1504 MB memory) -> physical GPU (device: 0, name: NVIDIA Tegra X1, pci bus id: 0000:00:00.0, compute capability: 5.3)
WARNING:tensorflow:From main.py:55: FastGFile.__init__ (from tensorflow.python.platform.gfile) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.gfile.GFile.
octave num 1/4...
2019-05-21 20:55:27.698862: I tensorflow/stream_executor/dso_loader.cc:153] successfully opened CUDA library libcublas.so.10.0 locally
octave num 2/4...
octave num 3/4...
octave num 4/4...
2019-05-21 20:56:59.346721: W tensorflow/core/common_runtime/bfc_allocator.cc:211] Allocator (GPU_0_bfc) ran out of memory trying to allocate 799.03MiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
2019-05-21 20:57:00.097332: W tensorflow/core/common_runtime/bfc_allocator.cc:211] Allocator (GPU_0_bfc) ran out of memory trying to allocate 1.55GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.

# Performance model
# In order to check the current performance mode, issue:
sudo nvpmodel -q --verbose

# To change the mode to MAX-N, issue:
sudo nvpmodel -m 0

user@user-desktop:~/deep_dream_tensorflow$ python3 main.py --input paint.jpg --output paint_tf.jpg
2019-05-21 21:08:08.657361: W tensorflow/core/platform/profile_utils/cpu_utils.cc:98] Failed to find bogomips in /proc/cpuinfo; cannot determine CPU frequency
2019-05-21 21:08:08.658298: I tensorflow/compiler/xla/service/service.cc:161] XLA service 0x290c9b00 executing computations on platform Host. Devices:
2019-05-21 21:08:08.658370: I tensorflow/compiler/xla/service/service.cc:168]   StreamExecutor device (0): <undefined>, <undefined>
2019-05-21 21:08:08.758426: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:965] ARM64 does not support NUMA - returning NUMA node zero
2019-05-21 21:08:08.758710: I tensorflow/compiler/xla/service/service.cc:161] XLA service 0x27c86ea0 executing computations on platform CUDA. Devices:
2019-05-21 21:08:08.758791: I tensorflow/compiler/xla/service/service.cc:168]   StreamExecutor device (0): NVIDIA Tegra X1, Compute Capability 5.3
2019-05-21 21:08:08.759192: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0 with properties:
name: NVIDIA Tegra X1 major: 5 minor: 3 memoryClockRate(GHz): 0.9216
pciBusID: 0000:00:00.0
totalMemory: 3.87GiB freeMemory: 1.93GiB
2019-05-21 21:08:08.759265: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2019-05-21 21:08:09.841440: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-05-21 21:08:09.841520: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990]      0
2019-05-21 21:08:09.841552: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0:   N
2019-05-21 21:08:09.841746: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1507 MB memory) -> physical GPU (device: 0, name: NVIDIA Tegra X1, pci bus id: 0000:00:00.0, compute capability: 5.3)
WARNING:tensorflow:From main.py:55: FastGFile.__init__ (from tensorflow.python.platform.gfile) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.gfile.GFile.
octave num 1/4...
2019-05-21 21:08:14.882492: I tensorflow/stream_executor/dso_loader.cc:153] successfully opened CUDA library libcublas.so.10.0 locally
octave num 2/4...
Killed

user@user-desktop:~/deep_dream_tensorflow$ python3 main.py --input paint.jpg --output paint_tf.jpg
2019-05-21 21:10:29.272559: W tensorflow/core/platform/profile_utils/cpu_utils.cc:98] Failed to find bogomips in /proc/cpuinfo; cannot determine CPU frequency
2019-05-21 21:10:29.273762: I tensorflow/compiler/xla/service/service.cc:161] XLA service 0x37e9b00 executing computations on platform Host. Devices:
2019-05-21 21:10:29.273835: I tensorflow/compiler/xla/service/service.cc:168]   StreamExecutor device (0): <undefined>, <undefined>
2019-05-21 21:10:29.634529: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:965] ARM64 does not support NUMA - returning NUMA node zero
2019-05-21 21:10:29.634812: I tensorflow/compiler/xla/service/service.cc:161] XLA service 0x23a6ea0 executing computations on platform CUDA. Devices:
2019-05-21 21:10:29.634873: I tensorflow/compiler/xla/service/service.cc:168]   StreamExecutor device (0): NVIDIA Tegra X1, Compute Capability 5.3
2019-05-21 21:10:29.636113: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0 with properties:
name: NVIDIA Tegra X1 major: 5 minor: 3 memoryClockRate(GHz): 0.9216
pciBusID: 0000:00:00.0
totalMemory: 3.87GiB freeMemory: 2.19GiB
2019-05-21 21:10:29.636507: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2019-05-21 21:10:40.285432: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-05-21 21:10:40.285503: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990]      0
2019-05-21 21:10:40.285528: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0:   N
2019-05-21 21:10:40.285754: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1463 MB memory) -> physical GPU (device: 0, name: NVIDIA Tegra X1, pci bus id: 0000:00:00.0, compute capability: 5.3)
WARNING:tensorflow:From main.py:55: FastGFile.__init__ (from tensorflow.python.platform.gfile) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.gfile.GFile.
octave num 1/4...
2019-05-21 21:10:45.981006: I tensorflow/stream_executor/dso_loader.cc:153] successfully opened CUDA library libcublas.so.10.0 locally
octave num 2/4...
2019-05-21 21:11:41.665321: W tensorflow/core/common_runtime/bfc_allocator.cc:211] Allocator (GPU_0_bfc) ran out of memory trying to allocate 1.55GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
octave num 3/4...
2019-05-21 21:12:52.709882: W tensorflow/core/common_runtime/bfc_allocator.cc:211] Allocator (GPU_0_bfc) ran out of memory trying to allocate 1.55GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
octave num 4/4...
2019-05-21 21:14:53.198886: W tensorflow/core/common_runtime/bfc_allocator.cc:211] Allocator (GPU_0_bfc) ran out of memory trying to allocate 1.04GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
2019-05-21 21:14:54.771410: W tensorflow/core/common_runtime/bfc_allocator.cc:211] Allocator (GPU_0_bfc) ran out of memory trying to allocate 3.07GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
2019-05-21 21:14:55.450058: W tensorflow/core/common_runtime/bfc_allocator.cc:211] Allocator (GPU_0_bfc) ran out of memory trying to allocate 1.54GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.

user@user-desktop:~/deep_dream_tensorflow$ sudo nvpmodel -q --verbose

NVPM VERB: Config file: /etc/nvpmodel.conf
NVPM VERB: parsing done for /etc/nvpmodel.conf
NVPM VERB: Current mode: NV Power Mode: MAXN
0
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_0: PATH /sys/devices/system/cpu/cpu0/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_1: PATH /sys/devices/system/cpu/cpu1/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_2: PATH /sys/devices/system/cpu/cpu2/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_3: PATH /sys/devices/system/cpu/cpu3/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM CPU_A57: ARG MIN_FREQ: PATH /sys/devices/system/cpu/cpu0/cpufreq/scaling_min_freq: REAL_VAL: 102000 CONF_VAL: 0
NVPM VERB: PARAM CPU_A57: ARG MAX_FREQ: PATH /sys/devices/system/cpu/cpu0/cpufreq/scaling_max_freq: REAL_VAL: 1428000 CONF_VAL: 2147483647
NVPM VERB: PARAM GPU_POWER_CONTROL_ENABLE: ARG GPU_PWR_CNTL_EN: PATH /sys/devices/gpu.0/power/control: REAL_VAL: auto CONF_VAL: on
NVPM VERB: PARAM GPU: ARG MIN_FREQ: PATH /sys/devices/gpu.0/devfreq/57000000.gpu/min_freq: REAL_VAL: 76800000 CONF_VAL: 0
NVPM VERB: PARAM GPU: ARG MAX_FREQ: PATH /sys/devices/gpu.0/devfreq/57000000.gpu/max_freq: REAL_VAL: 921600000 CONF_VAL: 2147483647
NVPM VERB: PARAM GPU_POWER_CONTROL_DISABLE: ARG GPU_PWR_CNTL_DIS: PATH /sys/devices/gpu.0/power/control: REAL_VAL: auto CONF_VAL: auto
NVPM VERB: PARAM EMC: ARG MAX_FREQ: PATH /sys/kernel/nvpmodel_emc_cap/emc_iso_cap: REAL_VAL: 0 CONF_VAL: 0

user@user-desktop:~/deep_dream_tensorflow$ cat /etc/nvpmodel.conf
#
# Copyright (c) 2019, NVIDIA CORPORATION.  All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto.  Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
#
# FORMAT:
# < PARAM TYPE=PARAM_TYPE NAME=PARAM_NAME >
# ARG1_NAME ARG1_PATH_VAL
# ARG2_NAME ARG2_PATH_VAL
# ...
# This starts a section of PARAM definitions, in which each line
# has the syntax below:
# ARG_NAME ARG_PATH_VAL
# ARG_NAME is a macro name for argument value ARG_PATH_VAL.
# PARAM_TYPE can be FILE, or CLOCK.
#
# < POWER_MODEL ID=id_num NAME=mode_name >
# PARAM1_NAME ARG11_NAME ARG11_VAL
# PARAM1_NAME ARG12_NAME ARG12_VAL
# PARAM2_NAME ARG21_NAME ARG21_VAL
# ...
# This starts a section of POWER_MODEL configurations, followed by
# lines with parameter settings as the format below:
# PARAM_NAME ARG_NAME ARG_VAL
# PARAM_NAME and ARG_NAME are defined in PARAM definition sections.
# ARG_VAL is an integer for PARAM_TYPE of CLOCK, and -1 is taken
# as INT_MAX. ARG_VAL is a string for PARAM_TYPE of FILE.
# This file must contain at least one POWER_MODEL section.
#
# < PM_CONFIG DEFAULT=default_mode >
# This is a mandatory section to specify one of the defined power
# model as the default.

###########################
#                         #
# PARAM DEFINITIONS       #
#                         #
###########################

< PARAM TYPE=FILE NAME=CPU_ONLINE >
CORE_0 /sys/devices/system/cpu/cpu0/online
CORE_1 /sys/devices/system/cpu/cpu1/online
CORE_2 /sys/devices/system/cpu/cpu2/online
CORE_3 /sys/devices/system/cpu/cpu3/online

< PARAM TYPE=FILE NAME=GPU_POWER_CONTROL_ENABLE >
GPU_PWR_CNTL_EN /sys/devices/gpu.0/power/control

< PARAM TYPE=FILE NAME=GPU_POWER_CONTROL_DISABLE >
GPU_PWR_CNTL_DIS /sys/devices/gpu.0/power/control

< PARAM TYPE=CLOCK NAME=CPU_A57 >
FREQ_TABLE /sys/devices/system/cpu/cpu0/cpufreq/scaling_available_frequencies
MAX_FREQ /sys/devices/system/cpu/cpu0/cpufreq/scaling_max_freq
MIN_FREQ /sys/devices/system/cpu/cpu0/cpufreq/scaling_min_freq
FREQ_TABLE_KNEXT /sys/devices/system/cpu/cpu0/cpufreq/scaling_available_frequencies
MAX_FREQ_KNEXT /sys/devices/system/cpu/cpu0/cpufreq/scaling_max_freq
MIN_FREQ_KNEXT /sys/devices/system/cpu/cpu0/cpufreq/scaling_min_freq

< PARAM TYPE=CLOCK NAME=GPU >
FREQ_TABLE /sys/devices/gpu.0/devfreq/57000000.gpu/available_frequencies
MAX_FREQ /sys/devices/gpu.0/devfreq/57000000.gpu/max_freq
MIN_FREQ /sys/devices/gpu.0/devfreq/57000000.gpu/min_freq
FREQ_TABLE_KNEXT /sys/devices/17000000.gv11b/devfreq/devfreq0/available_frequencies
MAX_FREQ_KNEXT /sys/devices/gpu.0/devfreq/57000000.gpu/max_freq
MIN_FREQ_KNEXT /sys/devices/gpu.0/devfreq/57000000.gpu/min_freq

< PARAM TYPE=CLOCK NAME=EMC >
MAX_FREQ /sys/kernel/nvpmodel_emc_cap/emc_iso_cap
MAX_FREQ_KNEXT /sys/kernel/nvpmodel_emc_cap/emc_iso_cap

###########################
#                         #
# POWER_MODEL DEFINITIONS #
#                         #
###########################

# MAXN is the NONE power model to release all constraints
< POWER_MODEL ID=0 NAME=MAXN >
CPU_ONLINE CORE_0 1
CPU_ONLINE CORE_1 1
CPU_ONLINE CORE_2 1
CPU_ONLINE CORE_3 1
CPU_A57 MIN_FREQ  0
CPU_A57 MAX_FREQ -1
GPU_POWER_CONTROL_ENABLE GPU_PWR_CNTL_EN on
GPU MIN_FREQ  0
GPU MAX_FREQ -1
GPU_POWER_CONTROL_DISABLE GPU_PWR_CNTL_DIS auto
EMC MAX_FREQ 0

< POWER_MODEL ID=1 NAME=5W >
CPU_ONLINE CORE_0 1
CPU_ONLINE CORE_1 1
CPU_ONLINE CORE_2 0
CPU_ONLINE CORE_3 0
CPU_A57 MIN_FREQ  0
CPU_A57 MAX_FREQ 918000
GPU_POWER_CONTROL_ENABLE GPU_PWR_CNTL_EN on
GPU MIN_FREQ 0
GPU MAX_FREQ 640000000
GPU_POWER_CONTROL_DISABLE GPU_PWR_CNTL_DIS auto
EMC MAX_FREQ 1600000000

# mandatory section to configure the default mode
< PM_CONFIG DEFAULT=0 >

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