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import torch.nn as nn
class SelfAttention(nn.Module):
def __init__(self, embed_size, heads):
super().__init__()
self.embed_size = embed_size
self.heads = heads
self.head_dim = embed_size // heads
self.values = nn.Linear(self.head_dim, self.head_dim, bias=False)
self.keys = nn.Linear(self.head_dim, self.head_dim, bias=False)
self.queries = nn.Linear(self.head_dim, self.head_dim, bias=False)
self.fc_out = nn.Linear(heads * self.head_dim, embed_size)
def forward(self, values, keys, query):
# 分头计算注意力
N = query.shape[0]
value_len, key_len, query_len = values.shape[1], keys.shape[1], query.shape[1]
values = values.reshape(N, value_len, self.heads, self.head_dim)
keys = keys.reshape(N, key_len, self.heads, self.head_dim)
queries = query.reshape(N, query_len, self.heads, self.head_dim)
energy = torch.einsum("nqhd,nkhd->nhqk", [queries, keys])
attention = torch.softmax(energy / (self.embed_size ** (1/2)), dim=3)
out = torch.einsum("nhql,nlhd->nqhd", [attention, values])
out = out.reshape(N, query_len, self.heads * self.head_dim)
return self.fc_out(out)
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import LSTM, Dense
model = Sequential()
model.add(LSTM(50, activation='relu', input_shape=(n_steps, n_features)))
model.add(Dense(1))
model.compile(optimizer='adam', loss='mse')
from transformers import BertTokenizer, BertForSequenceClassification
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
model = BertForSequenceClassification.from_pretrained('bert-base-uncased')
inputs = tokenizer("I love this product!", return_tensors="pt")
outputs = model(**inputs)
from deap import base, creator, tools
creator.create("FitnessMax", base.Fitness, weights=(1.0,))
creator.create("Individual", list, fitness=creator.FitnessMax)
toolbox = base.Toolbox()
toolbox.register("attr_float", random.uniform, -5, 5)
toolbox.register("individual", tools.initRepeat, creator.Individual, toolbox.attr_float, n=10)
pragma solidity ^0.8.0;
contract SimpleAuction {
address payable public beneficiary;
uint public auctionEndTime;
address public highestBidder;
uint public highestBid;
mapping(address => uint) pendingReturns;
constructor(uint _biddingTime) {
beneficiary = payable(msg.sender);
auctionEndTime = block.timestamp + _biddingTime;
}
function bid() public payable {
require(block.timestamp <= auctionEndTime, "Auction ended");
require(msg.value > highestBid, "Bid too low");
if (highestBid != 0) {
pendingReturns[highestBidder] += highestBid;
}
highestBidder = msg.sender;
highestBid = msg.value;
}
}
from Crypto.PublicKey import RSA
key = RSA.generate(2048)
private_key = key.export_key()
public_key = key.publickey().export_key()