rohitg00/ai-engineering-from-scratch · error · ValueError
token and positional embeddings must share d_model
Error message
token and positional embeddings must share d_model
What it means
Error "token and positional embeddings must share d_model" thrown in rohitg00/ai-engineering-from-scratch.
Source
Thrown at phases/19-capstone-projects/32-token-positional-embeddings/code/main.py:148
"""
def __init__(
self,
token_embedding: TokenEmbedding,
positional_embedding: nn.Module,
) -> None:
super().__init__()
if not isinstance(token_embedding, TokenEmbedding):
raise TypeError("token_embedding must be a TokenEmbedding")
if not isinstance(
positional_embedding,
(LearnedPositionalEmbedding, SinusoidalPositionalEmbedding),
):
raise TypeError(
"positional_embedding must be Learned or Sinusoidal Positional Embedding"
)
if token_embedding.d_model != getattr(positional_embedding, "d_model", None):
raise ValueError("token and positional embeddings must share d_model")
self.token_embedding = token_embedding
self.positional_embedding = positional_embedding
@property
def d_model(self) -> int:
return self.token_embedding.d_model
def forward(self, ids: torch.Tensor) -> torch.Tensor:
if ids.dim() != 2:
raise ValueError(f"ids must be (B, T), got shape {tuple(ids.shape)}")
seq_len = ids.shape[1]
tok = self.token_embedding(ids)
pos = self.positional_embedding(seq_len)
return tok + pos.unsqueeze(0)
def count_parameters(module: nn.Module) -> int:
return sum(p.numel() for p in module.parameters() if p.requires_grad)View on GitHub (pinned to 39ea8a1c6d)
When it happens
Trigger: Thrown at phases/19-capstone-projects/32-token-positional-embeddings/code/main.py:148 when the library encounters an invalid state.
Common situations: See trigger scenarios.
AI-assisted analysis of rohitg00/ai-engineering-from-scratch@39ea8a1c6d (2026-08-26).
Data as JSON: /api/errors/4483d1abb4f117f3.
Report an issue: GitHub.