print(“n### SECTION D: end-to-end Transformer (vanilla fp32 vs Apex fused + AMP) ###”) VOCAB, D, NHEAD, LAYERS, SEQ, BATCH, STEPS = 2000, 256, 4, 4, 128, 32, 60 class Block(torch.nn.Module): def __init__(self, d, nhead, norm_cls): tremendous().__init__() self.attn = torch.nn.MultiheadAttention(d, nhead, batch_first=True) self.ff = torch.nn.Sequential(torch.nn.Linear(d, 4 * d), torch.nn.GELU(), torch.nn.Linear(4 * d, d)) self.n1, self.n2 =…