fischermario

pi@raspberrypi:~/mainflux $ sudo make dockers
docker build --build-arg SVC_NAME=users --tag=mainflux/users -f docker/Dockerfile .
Sending build context to Docker daemon  45.63MB
Step 1/8 : FROM golang:1.10-alpine AS builder
 ---> 3e259e2d90c3
Step 2/8 : ARG SVC_NAME
 ---> Using cache
 ---> c2da7c1d4fa2
Step 3/8 : WORKDIR /go/src/github.com/mainflux/mainflux
 ---> Using cache

fischermario

pi@raspberrypi:~/mainflux $ sudo docker build --tag=mainflux/dashflux -f dashflux/docker/Dockerfile dashflux
Sending build context to Docker daemon  560.1kB
Step 1/10 : FROM node:9.5 as node
9.5: Pulling from library/node
6b0aacdd0080: Pull complete 
bb8a07b6e86b: Pull complete 
f5179f817ea4: Pull complete 
737d0c16e7c3: Pull complete 
7489a002c214: Pull complete 
b90549247152: Pull complete 

fischermario

Error 405 after trying to provision a client

1. docker-compse result

Creating mainflux-things-db  ... done
Creating mainflux-nats       ... done
Creating mainflux-nginx      ... done
Creating mainflux-normalizer ... done
Creating mainflux-dashflux   ... done

fischermario

Using TensorFlow backend.
Loading network...
2018-04-25 21:40:00.962271: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-04-25 21:40:01.086140: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:898] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2018-04-25 21:40:01.086521: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1344] Found device 0 with properties: 
name: Quadro M500M major: 5 minor: 0 memoryClockRate(GHz): 1.124
pciBusID: 0000:06:00.0
totalMemory: 1.96GiB freeMemory: 1.55GiB
2018-04-25 21:40:01.086540: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1423] Adding visible gpu devices: 0
2018-04-25 21:40:01.696561: I tensorflow/core/common_runtime/gpu/gpu_device.cc:911] Device interconnect StreamExecutor with strength 1 edge matrix:

fischermario

[TensorRT] INFO: Added linear block of size 12845056
[TensorRT] INFO: Added linear block of size 12845056
[TensorRT] INFO: Added linear block of size 1605632
[TensorRT] INFO: Verifying engine construction was successful
[TensorRT] INFO: Allocating GPU buffers
[TensorRT] INFO: Registering postprocessor function table
[TensorRT] INFO: Detecting input data format
[TensorRT] INFO: Dectected data format NCHW
[TensorRT] INFO: Verifying data format is uniform accross all input layers
[TensorRT] INFO: Verifying batches are the expected data type

fischermario

daisy_1.jpg
daisy: 99.82%
daisy_2.jpg
daisy: 99.59%
daisy_3.jpg
daisy: 99.94%
dandelion_1.jpg
dandelion: 99.99%
dandelion_2.jpg
dandelion: 97.69%

fischermario

Using output node dense_2/Softmax
Converting to UFF graph
No. nodes: 98
[TensorRT] INFO: UFFParser: parsing input_1
[TensorRT] INFO: UFFParser: parsing block1_conv1/kernel
[TensorRT] INFO: UFFParser: parsing block1_conv1/convolution
[TensorRT] INFO: UFFParser: parsing block1_conv1/bias
[TensorRT] INFO: UFFParser: parsing block1_conv1/BiasAdd
[TensorRT] INFO: UFFParser: parsing block1_conv1/Relu
[TensorRT] INFO: UFFParser: parsing block1_conv2/kernel

fischermario

Using TensorFlow backend.
WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/learn/python/learn/datasets/base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Use the retry module or similar alternatives.
2018-04-25 21:27:47.392990: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-04-25 21:27:47.527610: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:898] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2018-04-25 21:27:47.528025: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1344] Found device 0 with properties: 
name: Quadro M500M major: 5 minor: 0 memoryClockRate(GHz): 1.124
pciBusID: 0000:06:00.0
totalMemory: 1.96GiB freeMemory: 1.55GiB

fischermario

#! /usr/bin/env python
# encoding: utf-8

# Copyright Steinwurf ApS 2011-2013.
# Distributed under the "STEINWURF RESEARCH LICENSE 1.0".
# See accompanying file LICENSE.rst or
# http://www.steinwurf.com/licensing

import kodo
import socket