<?php
/*
dobu {
file:id(`example-00002520`),name(`taihandler.conv1d`) {
ascoos {
logo {`
__ _ ___ ___ ___ ___ ___ ___ ___
/ _' |/ / / __/ _ \ / _ \ / / / _ \ / /
| (_| |\ \| (_| (_) | (_) |\ \ | (_) |\ \
\__,_|/__/ \___\___/ \___/ /__/ \___/ /__/
`},
name {`ASCOOS OS`},
version {`1.0.0`}
},
example {
class {`TAIHandler`},
methods {`conv1D()`},
source {`kernel/ai/taihandler/taihandler.conv1d.php`},
category:langs {
en {`Convolution Layers`},
el {`??????????? ????????`}
},
subcategory:langs {
en {`1D Convolution`},
el {`1D ????????`}
},
summary:langs {
en {`1D convolution with padding, stride, bias and activation`},
el {`1D ???????? ?? padding, stride, bias ??? ????????????`}
},
desc:langs {
en {`Demonstrates conv1D on sequential numeric data using SAME padding and ReLU activation.`},
el {`??????????? conv1D ?? ???????? ?????????? ???????? ?? SAME padding ??? ???????????? ReLU.`}
},
author {`Drogidis Christos`},
since {`1.0.0`},
sincePHP {`8.4.0`}
},
results:langs {
all {`Input: [1,2,3,4]
Kernel: [1,0,-1]
Output (conv1D SAME + ReLU): [0,0,0,3,4,0]
Execution statistics
Execution Time 0.177 ms
Memory Delta 3.92 KB
Peak Memory 18.00 MB
PHP Version 8.4.24
Ascoos OS`}
}
}
}
*/
declare(strict_types=1);
use ASCOOS\OS\Kernel\AI\TAIHandler;
$startTime = microtime(true);
$startMem = memory_get_usage();
$ai = new TAIHandler([], []);
$input = [1, 2, 3, 4];
$kernel = [1, 0, -1];
$output = $ai->conv1D($input, $kernel, 1, 'same', 0.0, fn($x) => max(0, $x));
echo "<pre>";
echo "Input: " . json_encode($input) . "\n";
echo "Kernel: " . json_encode($kernel) . "\n";
echo "Output (conv1D SAME + ReLU): " . json_encode($output) . "\n";
echo "</pre>";
$ai->Free();
print_stats($startTime, $startMem);
?>
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