Mercurial > repos > kls286 > chap_test_20230328

annotate MLaaS/demo.sh @ 0:cbbe42422d56 draft

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planemo upload for repository https://github.com/CHESSComputing/ChessAnalysisPipeline/tree/galaxy commit 1401a7e1ae007a6bda260d147f9b879e789b73e0-dirty
author kls286
date Tue, 28 Mar 2023 15:07:30 +0000
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0
cbbe42422d56 planemo upload for repository https://github.com/CHESSComputing/ChessAnalysisPipeline/tree/galaxy commit 1401a7e1ae007a6bda260d147f9b879e789b73e0-dirty
kls286
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1 #!/bin/bash
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2 # TFaaS host name
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3 turl=http://localhost:8083
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4 # location of files
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5 tdir=/home/vk/chess/TFaaS/models
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6 # we need the following files
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7 model_tarball=$tdir/model.tar.gz
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8 params_json=$tdir/vk/params.json
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9 input_json=$tdir/vk/input.json
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10 upload_json=$tdir/vk/upload.json
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11 model_pb=$tdir/vk/model.pb
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12 labels_txt=$tdir/vk/labels.txt
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13 tfaas_client=$tdir/tfaas_client.py
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14 hey=$tdir/hey-tools/hey_amd64
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15
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16 echo "### obtain any existing ML model"
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17 echo
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18 echo "$tfaas_client --url=$turl --models"
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19 echo
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20 $tfaas_client --url=$turl --models
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21 sleep 1
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22 echo
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23
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24 echo "### upload new ML model"
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25 echo
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26 echo "cat $upload_json"
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27 echo
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28 cat $upload_json
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29 echo
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30 echo "$tfaas_client --url=$turl --upload=$upload_json"
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31 $tfaas_client --url=$turl --upload=$upload_json
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32 echo
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33
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34 echo "### view if our model exists"
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35 echo
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36 echo "$tfaas_client --url=$turl --models"
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37 echo
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38 $tfaas_client --url=$turl --models
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39 sleep 2
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40 echo
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41
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42 echo "### view if our model exists, but use jq tool to get better view over JSON"
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43 echo
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44 echo "$tfaas_client --url=$turl --models | jq"
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45 echo
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46 $tfaas_client --url=$turl --models | jq
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47 sleep 2
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48 echo
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49
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50 echo "### let's obtain some prediction"
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51 echo
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52 echo "cat $input_json"
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53 echo
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54 cat $input_json
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55 echo
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56 echo "$tfaas_client --url=$turl --predict=$input_json"
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57 echo
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58 $tfaas_client --url=$turl --predict=$input_json
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59 sleep 2
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60 echo
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61
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62 echo "### let's delete our ML model named vk"
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63 echo
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64 echo "$tfaas_client --url=$turl --delete=vk"
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65 echo
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66 $tfaas_client --url=$turl --delete=vk
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67 sleep 1
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68 echo
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69
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70 echo "### lets view again available models"
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71 echo
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72 echo "$tfaas_client --url=$turl --models"
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73 echo
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74 $tfaas_client --url=$turl --models
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75 sleep 2
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76 echo
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77
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78 echo "### now let's use curl as CLI tool to communicate with TFaaS"
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79 echo
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80 sleep 5
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81
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82 echo "### Let's view our models"
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83 echo
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84 echo "curl -s $turl/models"
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85 echo
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86 curl -s $turl/models
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87 sleep 1
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88 echo
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89
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90 echo "### let's send POST HTTP request with our parameters to upload ML model"
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91 echo "### we provide $params_json"
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92 echo
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93 cat $params_json
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94 echo
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95 echo "### we provide $model_pb TF model"
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96 echo
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97 ls -al $model_pb
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98 echo
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99 echo "### and we provide our labels in $labels_txt file"
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100 echo
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101 cat $labels_txt
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102 echo
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103 echo "### now we make curl call"
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104 echo
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105 echo "curl -s -X POST $turl/upload -F 'name=vk' -F 'params=@$params_json' -F 'model=@$model_pb' -F 'labels=@$labels_txt'"
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106 echo
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107 curl -s -X POST $turl/upload -F 'name=vk' -F "params=@$params_json" -F "model=@$model_pb" -F "labels=@$labels_txt"
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108 sleep 1
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109 echo
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110
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111 echo "### Now we can view our models"
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112 echo
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113 echo "curl -s $turl/models | jq"
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114 echo
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115 curl -s $turl/models | jq
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116 echo
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117 sleep 2
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118
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119 echo "### And we can obtain our predictions using /json API"
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120 echo
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121 echo "curl -s -X POST $turl/json -H "Content-type: application/json" -d@$input_json"
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122 echo
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123 curl -s -X POST $turl/json -H "Content-type: application/json" -d@$input_json
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124 sleep 1
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125 echo
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126
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127 echo "### Now we can delete ML model using /delete end-point"
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128 echo
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129 echo "curl -s -X DELETE $turl/delete -F 'model=vk'"
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130 echo
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131 curl -s -X DELETE $turl/delete -F 'model=vk'
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132 sleep 1
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133 echo
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134
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135 echo "### Now we can view our models"
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136 echo
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137 echo "curl -s $turl/models"
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138 echo
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139 curl -s $turl/models
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140 echo
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141 sleep 1
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142
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143 $tfaas_client --url=$turl --upload=$upload_json
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144
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145 echo
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146 echo "### now let's use tar ball and upload it"
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147 echo
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148 ls -al $model_tarball
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149 tar tvfz $model_tarball
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150 sleep 5
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151
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152 echo "curl -v -X POST -H \"Content-Encoding: gzip\" -H \"content-type: application/octet-stream\" --data-binary @$model_tarball $turl/upload"
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153 curl -v -X POST -H"Content-Encoding: gzip" -H"content-type: application/octet-stream" --data-binary @$model_tarball $turl/upload
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154 sleep 1
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155 echo
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156
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157 echo "### Now we can view our models"
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158 echo
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159 echo "curl -s $turl/models | jq"
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160 echo
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161 curl -s $turl/models | jq
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162 echo
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163 sleep 2
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164
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165 echo "### And we can obtain our predictions using /json API"
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166 echo
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167 echo "curl -s -X POST $turl/json -H "Content-type: application/json" -d@$input_json"
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168 echo
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169 curl -s -X POST $turl/json -H "Content-type: application/json" -d@$input_json
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170 sleep 1
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171 echo
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172
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173 if [ -f $hey ]; then
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174 echo "### Now let's perform some stress tests"
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175 echo "### for that we'll use hey tool which will send number of concurrent requests to tfaas service"
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176 echo
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177 echo "$hey -m POST -H "Content-type: application/json" -D $input_json $turl/json"
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178 $hey -m POST -H "Content-type: application/json" -D $input_json $turl/json
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179 fi