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package main | |
import ( | |
"crypto/rand" | |
"crypto/rsa" | |
"crypto/sha256" | |
"fmt" | |
) | |
func main() { |
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package main | |
import ( | |
"crypto/rand" | |
"crypto/rsa" | |
"crypto/x509" | |
"encoding/pem" | |
"fmt" | |
) |
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package main | |
import ( | |
"archive/tar" | |
"compress/gzip" | |
"crypto/aes" | |
"crypto/cipher" | |
"crypto/rand" | |
"io" | |
"log" |
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package main | |
import ( | |
"context" | |
"fmt" | |
"strconv" | |
"github.com/redis/rueidis" | |
) | |
func main() { |
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package main | |
import ( | |
"context" | |
"fmt" | |
"github.com/redis/rueidis" | |
) | |
func main() { | |
client, err := rueidis.NewClient(rueidis.ClientOption{InitAddress: []string{"127.0.0.1:6377"}}) |
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import torch | |
import torch.nn as nn | |
import torch.optim as optim | |
class LSTMModel(nn.Module): | |
def __init__(self, input_dim, hidden_dim, output_dim): | |
super(LSTMModel, self).__init__() | |
self.hidden_dim = hidden_dim | |
self.lstm = nn.LSTM(input_dim, hidden_dim) | |
self.fc = nn.Linear(hidden_dim, output_dim) |
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package main | |
import ( | |
"fmt" | |
"io/ioutil" | |
"log" | |
"net/http" | |
"net/http/httputil" | |
) |
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import { | |
TeamsActivityHandler, | |
CardFactory, | |
TurnContext, | |
} from "botbuilder"; | |
import rawWelcomeCard from "./adaptiveCards/welcome.json"; | |
import rawReplyCard from "./adaptiveCards/reply.json"; | |
import { AdaptiveCards } from "@microsoft/adaptivecards-tools"; | |
import { Configuration, OpenAIApi } from "openai"; |
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import torch | |
from torch import nn | |
from torch.nn import functional as F | |
from torchvision import transforms | |
import pytorch_lightning as pl | |
class Block(nn.Module): | |
def __init__(self, in_ch, out_ch): | |
super().__init__() |
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package allocs | |
import ( | |
"context" | |
"testing" | |
"time" | |
"github.com/go-redis/redis/v9" // v9-rc2 | |
"github.com/rueian/rueidis" // v0.0.90 | |
) |
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