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remove pca toggle #3

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remove pca toggle #3

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23 changes: 3 additions & 20 deletions circuit_sparsity/viz.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1485,13 +1485,8 @@ def _maybe_item(x):
cols = st.columns([1, 1])
model_config = viz_data["importances"]["beeg_model_config"]
with cols[0]:
cols2 = st.columns([1, 2, 1])
cols2 = st.columns([2, 1])
with cols2[0]:
use_pca = st.toggle(
"PCA components",
value=False,
)
with cols2[1]:
chidx = st.selectbox(
"res channel index",
options=[
Expand All @@ -1502,14 +1497,10 @@ def _maybe_item(x):
)
chidx = int(chidx.split(" ")[0])

with cols2[2]:
with cols2[1]:
st.text(f"encname: {model_config.tokenizer_name}")

if use_pca:
U, S, V = get_embed_weights_pca(model_path, q=100)
embsort = U[:, chidx].cpu().sort(descending=True)
else:
embsort = embed_weight[:, chidx].sort(descending=True)
embsort = embed_weight[:, chidx].sort(descending=True)

def _filter_embsort(xs):
return [
Expand Down Expand Up @@ -1588,12 +1579,6 @@ def _filter_embsort(xs):
status_placeholder.html("<pre>ready<br>&nbsp;</pre>")


@cache("get_embed_weights_pca_v1")
def get_embed_weights_pca(model_path, q):
wte = get_embed_weights(model_path).float()
return torch.pca_lowrank(wte, niter=10, q=q)


@cache("get_embed_weights_v1")
def get_embed_weights(model_path):
return get_model_weights(model_path, lambda x: x["transformer.wte.weight"]).half()
Expand Down Expand Up @@ -1714,5 +1699,3 @@ def treemap(f, x):
st.set_page_config(page_title="Circuit viz", layout="wide")

main()