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Change casing in model.py comments #284

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Change casing in model.py comments #284

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8 changes: 4 additions & 4 deletions llama/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@ class ModelArgs:
n_heads: int = 32
n_kv_heads: Optional[int] = None
vocab_size: int = -1
multiple_of: int = 256 # make SwiGLU hidden layer size multiple of large power of 2
multiple_of: int = 256 # Make SwiGLU hidden layer size multiple of large power of 2
ffn_dim_multiplier: Optional[float] = None
norm_eps: float = 1e-5
rope_theta: float = 500000
Expand All @@ -50,7 +50,7 @@ def precompute_freqs_cis(dim: int, end: int, theta: float = 10000.0):
freqs = 1.0 / (theta ** (torch.arange(0, dim, 2)[: (dim // 2)].float() / dim))
t = torch.arange(end, device=freqs.device, dtype=torch.float32)
freqs = torch.outer(t, freqs)
freqs_cis = torch.polar(torch.ones_like(freqs), freqs) # complex64
freqs_cis = torch.polar(torch.ones_like(freqs), freqs) # Complex64
return freqs_cis


Expand Down Expand Up @@ -168,7 +168,7 @@ def forward(
keys = self.cache_k[:bsz, : start_pos + seqlen]
values = self.cache_v[:bsz, : start_pos + seqlen]

# repeat k/v heads if n_kv_heads < n_heads
# Repeat k/v heads if n_kv_heads < n_heads
keys = repeat_kv(
keys, self.n_rep
) # (bs, cache_len + seqlen, n_local_heads, head_dim)
Expand Down Expand Up @@ -200,7 +200,7 @@ def __init__(
):
super().__init__()
hidden_dim = int(2 * hidden_dim / 3)
# custom dim factor multiplier
# Custom dim factor multiplier
if ffn_dim_multiplier is not None:
hidden_dim = int(ffn_dim_multiplier * hidden_dim)
hidden_dim = multiple_of * ((hidden_dim + multiple_of - 1) // multiple_of)
Expand Down