1 | #!/usr/bin/env bash
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2 | #
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3 | # Quick test for a potential rewrite of mycpp.
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4 | #
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5 | # Usage:
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6 | # pea/TEST.sh <function name>
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7 |
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8 | set -o nounset
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9 | set -o pipefail
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10 | set -o errexit
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11 |
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12 | source test/common.sh # run-test-funcs
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13 | source devtools/common.sh
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14 |
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15 | source build/dev-shell.sh # find python3 in /wedge PATH component
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16 |
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17 | # This is just like the yapf problem in devtools/format.sh !
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18 | # Pea needs a newer version of MyPy -- one that supports 'math'
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19 | unset PYTHONPATH
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20 | export PYTHONPATH=.
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21 |
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22 | readonly MYPY_VENV='_tmp/mypy-venv'
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23 |
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24 | install-mypy() {
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25 | local venv=$MYPY_VENV
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26 |
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27 | rm -r -f -v $venv
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28 |
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29 | python3 -m venv $venv
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30 |
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31 | . $venv/bin/activate
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32 |
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33 | python3 -m pip install mypy
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34 |
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35 | # Says 1.5.1 (compiled: yes)
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36 | mypy-version
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37 | }
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38 |
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39 | mypy-version() {
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40 | . $MYPY_VENV/bin/activate
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41 | python3 -m mypy --version
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42 | }
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43 |
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44 | #
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45 | # Run Pea
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46 | #
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47 |
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48 | pea-main() {
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49 | pea/pea_main.py "$@"
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50 | }
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51 |
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52 | parse-one() {
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53 | pea-main parse "$@"
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54 | }
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55 |
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56 | translate-cpp() {
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57 | ### Used by mycpp/NINJA-steps.sh
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58 |
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59 | pea-main cpp "$@"
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60 | }
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61 |
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62 | all-files() {
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63 | # Can't run this on Soil because we only have build/py.sh py-source, not
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64 | # 'minimal'
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65 |
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66 | # Update this file with build/dynamic-deps.sh pea-hack
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67 |
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68 | cat pea/oils-typecheck.txt
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69 |
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70 | for path in */*.pyi; do
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71 | echo $path
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72 | done
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73 | }
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74 |
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75 | parse-all() {
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76 | time all-files | xargs --verbose -- $0 pea-main parse
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77 | }
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78 |
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79 | # Good illustration of "distributing your overhead"
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80 | #
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81 | # Total work goes up, while latency goes down. To a point. Then it goes back
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82 | # up.
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83 |
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84 | # batch size 30
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85 | #
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86 | # real 0m0.342s
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87 | # user 0m0.735s
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88 | # sys 0m0.059s
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89 | #
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90 | # batch size 20
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91 | #
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92 | # real 0m0.305s
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93 | # user 0m0.993s
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94 | # sys 0m0.081s
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95 | #
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96 | # batch size 15
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97 | #
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98 | # real 0m0.299s
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99 | # user 0m1.110s
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100 | # sys 0m0.123s
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101 | #
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102 | # batch size 10
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103 | #
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104 | # real 0m0.272s
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105 | # user 0m1.362s
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106 | # sys 0m0.145s
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107 |
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108 | batch-size() {
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109 | local num_files=$1
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110 |
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111 | local num_procs
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112 | num_procs=$(nproc)
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113 |
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114 | # Use (p-1) as a fudge so we don't end up more batches than processors
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115 | local files_per_process=$(( num_files / (num_procs - 1) ))
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116 |
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117 | echo "$num_procs $files_per_process"
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118 | }
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119 |
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120 | demo-par() {
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121 | ### Demo parallelism of Python processes
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122 |
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123 | local files
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124 | num_files=$(all-files | wc -l)
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125 |
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126 | # 103 files
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127 |
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128 | shopt -s lastpipe
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129 | batch-size $num_files | read num_procs optimal
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130 |
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131 | echo "Parsing $num_files files with $num_procs parallel processes"
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132 | echo "Optimal batch size is $optimal"
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133 |
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134 | echo
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135 |
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136 | echo 'All at once:'
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137 | time parse-all > /dev/null 2>&1
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138 | echo
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139 |
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140 | # 5 is meant to be suboptimal
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141 | for n in 50 30 20 10 5 $optimal; do
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142 | echo "batch size $n"
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143 | time all-files | xargs --verbose -P $num_procs -n $n -- \
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144 | $0 parse-one > /dev/null 2>&1
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145 | echo
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146 | done
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147 | }
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148 |
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149 | # - 0.40 secs to parse
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150 | # - 0.56 secs pickle, so that's 160 ms
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151 | # Then
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152 | #
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153 | # - 0.39 secs load pickle
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154 | #
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155 | # That's definitely slower than I want. It's 6.6 MB of data.
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156 | #
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157 | # So
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158 | # - parallel parsing can be done in <300 ms
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159 | # - parallel pickling
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160 | # - serial unpickling (reduce) in 390 ms
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161 | #
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162 | # So now we're at ~700 ms or so. Can we type check in 300 ms in pure Python?
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163 | #
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164 | # What if we compress the generated ASDL? Those are very repetitive.
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165 |
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166 | # Problem statement:
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167 |
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168 | _serial-pickle() {
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169 | mkdir -p _tmp
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170 | local tmp=_tmp/serial
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171 |
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172 | time all-files | xargs --verbose -- $0 pea-main dump-pickles > $tmp
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173 |
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174 | ls -l -h $tmp
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175 |
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176 | echo 'loading'
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177 | time pea-main load-pickles < $tmp
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178 | }
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179 |
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180 | # 1.07 seconds
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181 | serial-pickle() { time $0 _serial-pickle; }
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182 |
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183 | pickle-one() {
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184 | pea-main dump-pickles "$@" > _tmp/p/$$
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185 | }
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186 |
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187 | _par-pickle() {
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188 | local files
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189 | num_files=$(all-files | wc -l)
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190 |
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191 | shopt -s lastpipe
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192 | batch-size $num_files | read num_procs optimal
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193 |
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194 | local dir=_tmp/p
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195 | rm -r -f -v $dir
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196 | mkdir -p $dir
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197 |
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198 | time all-files | xargs --verbose -P $num_procs -n $optimal -- $0 pickle-one
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199 |
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200 | ls -l -h $dir
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201 |
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202 | # This takes 410-430 ms? Wow that's slow.
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203 | time cat $dir/* | pea-main load-pickles
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204 | }
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205 |
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206 | # Can get this down to ~700 ms
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207 | #
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208 | # Note parsing serially in a single process is 410 ms !!! So this is NOT a win
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209 | # unless we have more work besides parsing to parallelize.
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210 | #
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211 | # We can extract constants and forward declarations in parallel I suppose.
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212 | #
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213 | # BUT immutable string constants have to be de-duplciated! Though I guess that
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214 | # is a natural 'reduce' step.
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215 | #
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216 | # And we can even do implementation and prototypes in parallel too?
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217 | #
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218 | # I think the entire algorithm can be OPTIMISTIC without serialized type
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219 | # checking?
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220 | #
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221 | # I think
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222 | #
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223 | # a = 5
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224 | # b = a # do not know the type without a global algorithm
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225 | #
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226 | # Or I guess you can do type checking within a function. Functions require
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227 | # signatures. So yes let's do that in parallel.
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228 | #
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229 | # --
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230 | #
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231 | # The ideal way to do this would be to split Oils up into MODULES, like
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232 | #
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233 | # _debuild/
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234 | # builtin/
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235 | # core/
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236 | # data_lang/
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237 | # frontend/
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238 | # osh/
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239 | # ysh/
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240 | # Smaller: pgen2/ pylib/ tools/
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241 | #
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242 | # And modules are acyclic, and can compile on their own with dependencies. If
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243 | # you pick random .py files and spit out header files, I think they won't compile.
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244 | # The forward declarations and constants will work, but the prototype won't.
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245 |
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246 | par-pickle() { time $0 _par-pickle; }
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247 |
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248 | sum1() {
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249 | awk '{ sum += $1 } END { print sum }'
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250 | }
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251 |
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252 | sum-sizes() {
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253 | xargs -I {} -- find {} -printf '%s %p\n' | sum1
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254 | }
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255 |
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256 | size-ratio() {
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257 | # all-files
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258 | # echo _tmp/p/*
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259 |
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260 | # 1.96 MB of source code
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261 | all-files | sum-sizes
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262 |
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263 | # 7.13 MB of pickle files
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264 | # Weirdly echo _tmp/p/* doesn't work here
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265 | for f in _tmp/p/*; do echo $f; done | sum-sizes
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266 | }
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267 |
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268 | # Only 47 ms!
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269 | # I want the overhead to be less than 1 second:
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270 | # 1. parallel parsing + pickle
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271 | # 2. serial unpickle + type check
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272 | # 3. starting the process
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273 | #
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274 | # So unpickling is slow.
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275 |
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276 | osh-overhead() {
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277 | time bin/osh -c 'echo hi'
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278 | }
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279 |
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280 |
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281 | # MyPy dev version takes 10.2 seconds the first time (without their mypyc
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282 | # speedups)
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283 | #
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284 | # 0.150 seconds the second time, WITHOUT code changes
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285 | # 0.136 seconds
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286 |
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287 | # 4.1 seconds: whitespace change
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288 | # 3.9 seconds: again, and this is on my fast hoover machine
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289 |
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290 | # 5.0 seconds - Invalid type!
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291 | # 4.9 seconds - again invalid
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292 |
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293 |
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294 | mypy-compare() {
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295 | devtools/types.sh check-oils
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296 | }
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297 |
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298 | check-types() {
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299 |
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300 | # install-mypy creates this. May not be present in CI machine.
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301 | local activate=$MYPY_VENV/bin/activate
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302 | if test -f $activate; then
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303 | . $activate
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304 | fi
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305 |
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306 | time python3 -m mypy --strict pea/pea_main.py
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307 | }
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308 |
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309 | test-translate() {
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310 | translate-cpp bin/oils_for_unix.py
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311 | }
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312 |
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313 | test-syntax-error() {
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314 | set +o errexit
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315 |
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316 | # error in Python syntax
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317 | parse-one pea/testdata/py_err.py
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318 | assert $? -eq 1
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319 |
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320 | # error in signature
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321 | parse-one pea/testdata/sig_err.py
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322 | assert $? -eq 1
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323 |
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324 | # error in assignment
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325 | parse-one pea/testdata/assign_err.py
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326 | assert $? -eq 1
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327 | }
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328 |
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329 | run-tests() {
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330 | # Making this separate for soil/worker.sh
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331 |
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332 | echo 'Running test functions'
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333 | run-test-funcs
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334 | }
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335 |
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336 | "$@"
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