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import numpy as np | |
import torch | |
import torch.nn.functional as F | |
from pytorch_metric_learning.utils import common_functions as c_f | |
from pytorch_metric_learning.losses.large_margin_softmax_loss import LargeMarginSoftmaxLoss | |
class MagFaceLoss(LargeMarginSoftmaxLoss): | |
""" | |
Implementation of MagFace: https://arxiv.org/pdf/1801.07698.pdf (extension to ArcFace) | |
""" |
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#include <ogg/ogg.h> | |
#include <stdio.h> | |
#include <stdlib.h> | |
#include <stdint.h> | |
#include <string.h> | |
// get_opus_raw関数のプロトタイプ | |
// この関数は外部で定義され、Opusエンコードされたraw binaryを提供します。 | |
int16_t get_opus_raw(uint8_t *buffer); |
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import SwiftUI | |
@_spi(Advanced) import SwiftUIIntrospect | |
struct DelegateEnabledScrollView<Content: View>: View { | |
@State private var scrollViewDelegate: DelegateEnabledScrollViewDelegate? | |
@State private var scrollView: UIScrollView? = nil | |
let content: (UIScrollView?) -> Content | |
var onDidZoom: ((UIScrollView) -> Void)? | |
var onWillBeginDragging: ((UIScrollView) -> Void)? |
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/* | |
https://github.com/karpathy/llama2.c/blob/master/run.c | |
GPT-4による解説 | |
このプログラムは、Transformerネットワークを実装し、トークン化されたテキスト入力から次の最も適したトークンを予測します。具体的には以下のようになります: | |
先頭の部分は、TransformerWeightsとRunStateという2つのデータ構造とそれらの関連するメモリの管理を含みます。 | |
Configという構造体は、トランスフォーマーネットワークのパラメータを保持します。 | |
次に、指定されたチェックポイントファイルから重みを初期化する関数があります。この関数は、チェックポイントファイルからトランスフォーマーネットワークの重みを読み込み、適切に配置します。 |
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// https://github.com/pschatzmann/arduino-audio-tools/ settings for M5Stack Core2 | |
// Audio settings | |
const int sample_rate = 44100; | |
const int channels = 1; | |
// Speaker settings | |
I2SStream out; | |
auto config = out.defaultConfig(TX_MODE); | |
config.sample_rate = sample_rate; |
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#/bin/sh | |
# M1 Mac環境でAmazon FreeRTOS on ESP32のビルドを行う | |
# FreeRTOSのソースはAWSコンソールのzipから落とさないで、 | |
# https://github.com/aws/amazon-freertos から持ってくること | |
# 参考: | |
# https://docs.aws.amazon.com/freertos/latest/userguide/getting_started_espressif.html#setup-espressif-idf42 | |
# https://github.com/SeanMollet/esp-idf/tree/esp-2020r3-aarch64 | |
# | |
# ビルドは下記のコマンドで | |
# idf.py -DVENDOR=espressif -DBOARD=esp32_wrover_kit -DCOMPILER=xtensa-esp32 build |
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const functions = require('firebase-functions'); | |
const request = require('request'); | |
const { Translate } = require('@google-cloud/translate'); | |
/* | |
Firebase Functionsの環境変数 | |
slack.bot_user_tokenとgoogle.project_idを適当に設定してください | |
*/ | |
async function postMessage(payload) { |
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#!/bin/sh | |
RUBY_VERSION=2.6.3 | |
NODE_VERSION=12 | |
# install docker | |
sudo apt install -y apt-transport-https ca-certificates curl software-properties-common | |
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add - | |
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable" | |
sudo apt update |
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