Ortiqcha moslashish

import torch
import torch.nn as nn
from torch.utils.data import TensorDataset, DataLoader

def malumot(n_oquv=60, n_valid=400, shovqin=0.25, urug=42):
    g = torch.Generator().manual_seed(urug)
    X = torch.randn(n_oquv + n_valid, 8, generator=g)
    mantiq = (X[:, 0] * 1.5 - X[:, 1] + X[:, 2] * 0.5)
    mantiq = mantiq + torch.randn(len(X), generator=g) * shovqin
    y = (mantiq > 0).long()
    return (TensorDataset(X[:n_oquv], y[:n_oquv]),
            TensorDataset(X[n_oquv:], y[n_oquv:]))

def tarmoq(yashirin=256, dropout=0.0):
    torch.manual_seed(0)
    qatlamlar = [nn.Linear(8, yashirin), nn.ReLU()]
    if dropout: qatlamlar.append(nn.Dropout(dropout))
    qatlamlar += [nn.Linear(yashirin, yashirin), nn.ReLU()]
    if dropout: qatlamlar.append(nn.Dropout(dropout))
    qatlamlar.append(nn.Linear(yashirin, 2))
    return nn.Sequential(*qatlamlar)

kriteriya = nn.CrossEntropyLoss()

def baholash(model, dl):
    model.eval(); j = t = 0; yo = 0.0
    with torch.no_grad():
        for xb, yb in dl:
            o = model(xb)
            yo += kriteriya(o, yb).item() * len(yb)
            t += (o.argmax(1) == yb).sum().item()
            j += len(yb)
    return yo / j, t / j

def oqit(model, oquv_dl, valid_dl, davrlar=200, wd=0.0, chop=None):
    opt = torch.optim.Adam(model.parameters(), lr=0.01, weight_decay=wd)
    tarix = []
    for davr in range(1, davrlar + 1):
        model.train(); s = 0.0; n = 0
        for xb, yb in oquv_dl:
            opt.zero_grad()
            l = kriteriya(model(xb), yb)
            l.backward(); opt.step()
            s += l.item() * len(yb); n += len(yb)
        vy, va = baholash(model, valid_dl)
        tarix.append((davr, s / n, vy, va))
        if chop and davr in chop:
            print(f"{davr:5d} | {s/n:10.4f} | {vy:12.4f} | {va:13.2%}")
    return tarix

oquv, valid = malumot()
torch.manual_seed(7)
oquv_dl = DataLoader(oquv, batch_size=16, shuffle=True)
valid_dl = DataLoader(valid, batch_size=64)

print("Davr | O'quv yo'q. | Valid. yo'q. | Valid. aniqlik")
print("------|------------|--------------|---------------")
tarix = oqit(tarmoq(), oquv_dl, valid_dl, 200, chop=[1,5,10,25,50,100,150,200])

eng = min(tarix, key=lambda r: r[2])
print(f"eng past validatsiya yo'qotishi: {eng[2]:.4f} ({eng[0]}-davrda)")
print(f"200-davrda: {tarix[-1][2]:.4f}  -> {tarix[-1][2]/eng[2]:.1f} barobar yomon")