{"record":{"id":"9fb4567bc488e872","repo":"rohitg00/ai-engineering-from-scratch","slug":"sequence-length-seq-exceeds-context-length-self-9fb456","errorCode":null,"errorMessage":"sequence length {seq} exceeds context_length={self.cfg.context_length}","messagePattern":"sequence length (.+?) exceeds context_length=(.+?)","errorType":"validation","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"phases/19-capstone-projects/37-loading-pretrained-weights/code/main.py","lineNumber":145,"sourceCode":"        self.cfg = cfg\n        self.tok_embed = nn.Embedding(cfg.vocab_size, cfg.d_model)\n        self.pos_embed = nn.Embedding(cfg.context_length, cfg.d_model)\n        self.embed_dropout = nn.Dropout(cfg.dropout)\n        self.blocks = nn.ModuleList([TransformerBlock(cfg) for _ in range(cfg.num_layers)])\n        self.final_ln = LayerNorm(cfg.d_model)\n        self.lm_head = nn.Linear(cfg.d_model, cfg.vocab_size, bias=False)\n        if cfg.weight_tying:\n            self.lm_head.weight = self.tok_embed.weight\n        self.register_buffer(\n            \"position_ids\",\n            torch.arange(cfg.context_length, dtype=torch.long),\n            persistent=False,\n        )\n\n    def forward(self, tokens: torch.Tensor) -> torch.Tensor:\n        batch, seq = tokens.shape\n        if seq > self.cfg.context_length:\n            raise ValueError(\n                f\"sequence length {seq} exceeds context_length={self.cfg.context_length}\"\n            )\n        tok = self.tok_embed(tokens)\n        pos = self.pos_embed(self.position_ids[:seq])\n        x = self.embed_dropout(tok + pos)\n        for block in self.blocks:\n            x = block(x)\n        return self.lm_head(self.final_ln(x))\n\n\n@dataclass\nclass LoadReport:\n    \"\"\"Outcome of a load. Print this; it tells you whether the load succeeded.\"\"\"\n\n    loaded: list[tuple[str, str, tuple[int, ...]]] = field(default_factory=list)\n    missing: list[str] = field(default_factory=list)\n    unexpected: list[str] = field(default_factory=list)\n    shape_mismatch: list[tuple[str, tuple[int, ...], tuple[int, ...]]] = field(default_factory=list)","sourceCodeStart":127,"sourceCodeEnd":163,"githubUrl":"https://github.com/rohitg00/ai-engineering-from-scratch/blob/39ea8a1c6d0b61f071226eff7ede4d4105fed820/phases/19-capstone-projects/37-loading-pretrained-weights/code/main.py#L127-L163","documentation":"Error \"sequence length {seq} exceeds context_length={self.cfg.context_length}\" thrown in rohitg00/ai-engineering-from-scratch.","triggerScenarios":"Thrown at phases/19-capstone-projects/37-loading-pretrained-weights/code/main.py:145 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"}