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aviks/langdetect-demo.ipynb

Created December 12, 2017 17:23
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Language Detection Demo
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langdetect-demo.ipynb
{
"cells": [
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"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"using Flux\n",
"using Flux: onehotbatch, reset!"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
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"outputs": [
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"data": {
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"(Any[:en, :it, :so, :fr, :es], ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j' … '3', '4', '5', '6', '7', '8', '9', ' ', '\\n', '_'], Chain(Dense(39, 15, NNlib.σ), Recur(LSTMCell(15, 15))), Dense(15, 5))"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"langs, alphabet, scanner, encoder = open(deserialize, \"model-som-0.25.jls\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
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"data": {
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"model (generic function with 1 method)"
]
},
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"metadata": {},
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}
],
"source": [
"function model(x)\n",
" state = scanner.(x.data)[end]\n",
" reset!(scanner)\n",
" softmax(encoder(state))\n",
"end"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
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"outputs": [
{
"data": {
"text/plain": [
"predict (generic function with 1 method)"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"predict(s) =\n",
" isempty(s) ?\n",
" softmax(ones(length(langs))) :\n",
" model(onehotbatch(normalize_string(s, casefold=true, stripmark=true), alphabet, '_')).data"
]
},
{
"cell_type": "code",
"execution_count": 6,
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"source": [
"predict(\"hello, world\")"
]
},
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"source": [
"using Plots, Interact"
]
},
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"<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:12; text-anchor:start;\" transform=\"rotate(0, 494.991, 52.311)\" x=\"494.991\" y=\"52.311\">Probability</text>\n",
"</g>\n",
"</svg>\n"
]
},
"execution_count": 8,
"metadata": {
"comm_id": "e0b58720-3288-4bdf-9c18-4b5e7d0b2708",
"reactive": true
},
"output_type": "execute_result"
}
],
"source": [
"@manipulate for s = \"c'é una bella filosofia\"\n",
" bar(String.(langs), predict(s),\n",
" label=[\"Probability\"], ylims=(0,1))\n",
"end"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Julia 0.6.1-pre",
"language": "julia",
"name": "julia-0.6"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "0.6.2"
},
"widgets": {
"state": {
"16a34112-fcfc-4231-a945-604910a594dc": {
"views": [
{
"cell_index": 6
}
]
}
},
"version": "1.2.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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