{"record":{"id":"3ad1836f6e6715cb","repo":"rohitg00/ai-engineering-from-scratch","slug":"text-length-nt-exceeds-max-self-cfg-max-text-le","errorCode":null,"errorMessage":"text length {nt} exceeds max {self.cfg.max_text_len}","messagePattern":"text length (.+?) exceeds max (.+?)","errorType":"validation","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"phases/19-capstone-projects/61-cross-attention-fusion/code/main.py","lineNumber":189,"sourceCode":"        self.pos_emb = nn.Embedding(cfg.max_text_len, cfg.hidden)\n        self.blocks = nn.ModuleList([DecoderBlock(cfg) for _ in range(cfg.depth)])\n        self.norm = nn.LayerNorm(cfg.hidden, eps=1e-6)\n        self.head = nn.Linear(cfg.hidden, cfg.text_vocab, bias=False)\n\n    def build_kv_cache(self, memory: torch.Tensor) -> list[tuple[torch.Tensor, torch.Tensor]]:\n        cache = []\n        for block in self.blocks:\n            k, v = block.cross_attn.project_memory(memory)\n            cache.append((k, v))\n        return cache\n\n    def forward(self, text_ids: torch.Tensor, memory: torch.Tensor,\n                use_cache: bool = False) -> torch.Tensor:\n        if text_ids.dim() != 2:\n            raise ValueError(f\"expected (B, Nt) ids, got {tuple(text_ids.shape)}\")\n        b, nt = text_ids.shape\n        if nt > self.cfg.max_text_len:\n            raise ValueError(f\"text length {nt} exceeds max {self.cfg.max_text_len}\")\n\n        positions = torch.arange(nt, device=text_ids.device)\n        x = self.tok_emb(text_ids) + self.pos_emb(positions).unsqueeze(0)\n\n        mask = causal_mask(nt).to(text_ids.device)\n\n        cache = self.build_kv_cache(memory) if use_cache else [None] * len(self.blocks)\n\n        for block, kv in zip(self.blocks, cache):\n            x = block(x, memory=memory, text_mask=mask, kv_cache=kv)\n\n        x = self.norm(x)\n        return self.head(x)\n\n\ndef synth_memory(batch: int, n_tokens: int, dim: int, seed: int) -> torch.Tensor:\n    gen = torch.Generator().manual_seed(seed)\n    return torch.randn(batch, n_tokens, dim, generator=gen)","sourceCodeStart":171,"sourceCodeEnd":207,"githubUrl":"https://github.com/rohitg00/ai-engineering-from-scratch/blob/39ea8a1c6d0b61f071226eff7ede4d4105fed820/phases/19-capstone-projects/61-cross-attention-fusion/code/main.py#L171-L207","documentation":"Error \"text length {nt} exceeds max {self.cfg.max_text_len}\" thrown in rohitg00/ai-engineering-from-scratch.","triggerScenarios":"Thrown at phases/19-capstone-projects/61-cross-attention-fusion/code/main.py:189 when the library encounters an invalid state.","commonSituations":"See trigger scenarios.","solutions":[],"exampleFix":null,"handlingStrategy":null,"validationCode":null,"typeGuard":null,"tryCatchPattern":null,"preventionTips":[],"tags":[],"backgroundTag":null,"analyzedSha":"39ea8a1c6d0b61f071226eff7ede4d4105fed820","analyzedAt":"2026-08-26T03:13:46.626Z","schemaVersion":2},"datasetVersion":"2026-08-26T07:17:17.940Z"}