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fixed various syntax errors keeping the code from functioning: #1

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fixed various syntax errors keeping the code from functioning: #1

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7c0a9b6
fixed various syntax errors keeping the code from functioning: missin…
scottvr Mar 20, 2023
5a60dca
fixed a fatfinger-on-exit issue I didn't notice before I pushed
scottvr Mar 20, 2023
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6 changes: 3 additions & 3 deletions scripts/embedding_inspector.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@
import torch, os
from modules.textual_inversion.textual_inversion import Embedding
import math, random
from embedding_solver import EmbeddingGroupFinder
from scripts.embedding_solver import EmbeddingGroupFinder

MAX_TABS = 20 # max number of tokens to save per embedding.
MAX_NUM_MIX = 100 # number of tokens that can be mixed to make a new token.
Expand Down Expand Up @@ -608,14 +608,14 @@ def add_tab():
mix_inputs.append(gr.Textbox(label="Name "+str(n), lines=1, placeholder="Enter name of token/embedding or ID"))
with gr.Column():
mix_sliders.append(gr.Slider(label="Multiplier",value=1.0,minimum=-1.0, maximum=1.0, step=0.1))
if MAX_NUM_MIX>SHOW_NUM_MIX:
if MAX_NUM_MIX>SHOW_NUM_MIX:
with gr.Accordion('',open=False):
for n in range(SHOW_NUM_MIX,MAX_NUM_MIX):
tab.add_row(gr.Row())
with tab.rows[-1]:
with gr.Column():
mix_inputs.append(gr.Textbox(label="Name "+str(n), lines=1, placeholder="Enter name of token/embedding or ID"))
with gr.Column():
with gr.Column():
mix_sliders.append(gr.Slider(label="Multiplier",value=1.0,minimum=-1.0, maximum=1.0, step=0.1))

with gr.Row():
Expand Down
12 changes: 6 additions & 6 deletions scripts/embedding_solver.py
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Original file line number Diff line number Diff line change
Expand Up @@ -242,7 +242,7 @@ def print_best(self, best_emb_groups_list, partial=False):
for best_emb_groups, iterations in best_emb_groups_list:
if best_emb_groups is None:
continue
self.textbox += f"\n\n%0.1f :: Iteration: {iterations}\n" % (time.time() - self.start_time))
self.textbox += f"\n\n%0.1f :: Iteration: {iterations}\n" % (time.time() - self.start_time)
for subset_id in [len(best_emb_groups) - 1]:
subset = best_emb_groups[subset_id]
if len(subset) == 0:
Expand All @@ -256,7 +256,7 @@ def print_best(self, best_emb_groups_list, partial=False):
self.mix_sliders.append(weight)
self.textbox += f" {weight} * {mapped_emb_id}: {emb_id_to_name(int(mapped_emb_id), self.tokenizer)}\n\n"
if partial == True:
return self.textbox += "---------------------------------\n\n"
return self.textbox + "---------------------------------\n\n"
s = sorted(self.target_emb)
rel_diff = s[int(0.75 * len(self.target_emb))] - s[int(0.25 * len(self.target_emb) )]
self.textbox += f"this_emb: {group_vec.detach().numpy()}\n"
Expand Down Expand Up @@ -325,7 +325,7 @@ def encode_token(self, t):
t = t.lower()
try:
if t[-1] == "*":
return self.orig_to_sorted[text_to_emb_ids([t[:-1]]]
return self.orig_to_sorted[text_to_emb_ids([t[:-1]])]
else:
return self.orig_to_sorted[text_to_emb_ids(t + "</w>", self.tokenizer)]
except KeyError:
Expand Down Expand Up @@ -442,7 +442,7 @@ def evaluate_optimization_methodology(self, last_time, score_improvement):
best_optimization_records = [ (self.optimization_records[key], key) for key in self.optimization_records ]
best_optimization_records.sort()
for rec, key in best_optimization_records:
self.textbox += "*/t=%0.7f (%s), #=%d, t=%0.1f\n" % (rec[0], key, rec[1], rec[2]))
self.textbox += "*/t=%0.7f (%s), #=%d, t=%0.1f\n" % (rec[0], key, rec[1], rec[2])
self.textbox += "\n"
self.last_printed_optimization_time = cur_time

Expand Down Expand Up @@ -483,7 +483,7 @@ def solve(self):

while self.emb_id < len(self.target_embs):
t = self.target_embs[self.emb_id]
self.textbox += f"\n === Embedding # {self.emb_id+1} / {len(self.target_embs)} === \n\n")
self.textbox += f"\n === Embedding # {self.emb_id+1} / {len(self.target_embs)} === \n\n"

# if not self.do_resume:
self.set_target(t)
Expand Down Expand Up @@ -596,7 +596,7 @@ def solve_one(self):
self.save_near_emb_cache()

if len(to_precache) > 0:
self.textbox += self.time_str() + f"<Finding neighbors to {to_precache[0]} -> {emb_id_to_name(to_precache[0, self.tokenizer)]}> \r"
self.textbox += self.time_str() + f"<Finding neighbors to {to_precache[0]} -> {emb_id_to_name(to_precache[0, self.tokenizer])}> \r"
self.near_emb_cache[to_precache[0]] = self.find_near_embs(self.orig_all_embs[to_precache[0]])
to_precache = to_precache[1:]
if len(to_precache) == 0:
Expand Down