projects
/
picoclvr.git
/ blobdiff
commit
grep
author
committer
pickaxe
?
search:
re
summary
|
shortlog
|
log
|
commit
|
commitdiff
|
tree
raw
|
inline
| side by side
Update.
[picoclvr.git]
/
graph.py
diff --git
a/graph.py
b/graph.py
index
6db9ed7
..
07e376a
100755
(executable)
--- a/
graph.py
+++ b/
graph.py
@@
-14,10
+14,12
@@
import cairo
def save_attention_image(
def save_attention_image(
- filename, # image to save
+ # image to save
+ filename,
tokens_input,
tokens_output,
tokens_input,
tokens_output,
- attention_matrices, # list of 2d tensors T1xT2, T2xT3, ..., Tk-1xTk
+ # list of 2d tensors T2xT1, T3xT2, ..., TkxTk-1
+ attention_matrices,
# do not draw links with a lesser attention
min_link_attention=0,
# draw only the strongest links necessary so that their summed
# do not draw links with a lesser attention
min_link_attention=0,
# draw only the strongest links necessary so that their summed
@@
-25,6
+27,7
@@
def save_attention_image(
min_total_attention=None,
# draw only the top k links
k_top=None,
min_total_attention=None,
# draw only the top k links
k_top=None,
+ # the purely graphical settings
curved=True,
pixel_scale=8,
token_gap=15,
curved=True,
pixel_scale=8,
token_gap=15,
@@
-170,8
+173,7
@@
if __name__ == "__main__":
attention_matrices = [m[0, 0] for m in model.retrieve_attention()]
attention_matrices = [m[0, 0] for m in model.retrieve_attention()]
- # attention_matrices = [ torch.rand(3,5), torch.rand(8,3), torch.rand(5,8) ]
- # for a in attention_matrices: a=a/a.sum(-1,keepdim=True)
+ # attention_matrices = [torch.rand(*s) for s in [ (4,5),(3,4),(8,3),(5,8) ]]
save_attention_image(
"attention.pdf",
save_attention_image(
"attention.pdf",