def display_cp(self) -> None:
display_df(
pd.DataFrame.from_records([
dict(
name=self.name,
iteration=self.cp["iteration"],
loss=self.new_loss,
patience=self.patience,
max_patience=self.cp["max_patience"],
num_left=self.num_epochs - self.epoch,
min_loss=self.cp["min_loss"],
)
]))
display_df(
pd.DataFrame.from_records([
dict(
val_correct=f"{self.val_correct}/{self.val_total}",
val_acc=round(self.cp["val_acc_history"][-1], 3),
max_val_acc=round(self.cp["max_val_acc"], 3),
correct=f"{self.correct}/{self.total}",
acc=round(self.cp["acc_history"][-1], 3),
max_acc=round(self.cp["max_acc"], 3),
trans_correct=f"{self.trans_correct}/{self.trans_total}",
trans_acc=round(self.cp["trans_acc_history"][-1], 3),
max_trans_acc=round(self.cp["max_trans_acc"], 3),
)
]))
def print_num_memes_in_folders():
display_df(
pd.DataFrame.from_records(
list({
"name": name,
"num": len(list(os.listdir(MEMES_REPO + name + "/")))
} for name in MEMES_TO_USE)).sort_values("num"))
def stonks_to_aws() -> None:
names = [
os.path.splitext(filename)[0]
for filename in os.listdir(LOAD_STONK_REPO.format("jit"))
]
stats: Dict[str, int] = dict(num_names=len(names), success=0, failed=0)
for name in names:
success = upload_to_aws(LOAD_STONK_REPO.format("jit") + f"{name}.pt")
stats["success" if success else "failed"] += 1
clear_output()
display_df(pd.DataFrame.from_records([stats]))
def histo(self):
df = pd.DataFrame(list(self.smd["name_acc"].items()),
columns=["name", "acc"]).sort_values(by="acc",
ascending=True)
_ = plt.figure(figsize=(20, 6))
_ = plt.hist(df["acc"], range=(0.7, 1), bins=3 * 40)
plt.grid()
plt.title("Market Accuracy Histogram")
plt.show()
df["acc"] = df["acc"].apply(round_3)
display_df(df[:25])
def miss_match() -> None:
downloaded_blanks = [
os.path.splitext(filename)[0] for filename in os.listdir(BLANKS_REPO)
]
display_df(
pd.read_sql(
cast(
str,
training_db.query(Template).filter(
cast(ClauseElement,
~Template.name.in_(downloaded_blanks))).statement,
),
training_db.bind,
))
def evaluated():
num_filled = (
site_db.query(RedditMeme)
.filter(
and_(
cast(ClauseElement, RedditMeme.version == LOAD_MEME_CLF_VERSION),
cast(ClauseElement, RedditMeme.is_a_template_official != None),
)
)
.count()
)
total_official = (
site_db.query(RedditMeme)
.filter(cast(ClauseElement, RedditMeme.is_a_template_official != None))
.count()
)
num_stonks = (
site_db.query(RedditMeme)
.filter(cast(ClauseElement, RedditMeme.stonk_official != None))
.count()
)
num_not_template = (
site_db.query(RedditMeme)
.filter(cast(ClauseElement, RedditMeme.is_a_template_official == False))
.count()
)
num_not_template_wrong = (
site_db.query(RedditMeme)
.filter(
and_(
cast(ClauseElement, RedditMeme.version == LOAD_MEME_CLF_VERSION),
cast(ClauseElement, RedditMeme.stonk == True),
cast(ClauseElement, RedditMeme.is_a_template_official == False),
)
)
.count()
)
tp = (
site_db.query(RedditMeme)
.filter(
and_(
cast(ClauseElement, RedditMeme.meme_clf == RedditMeme.stonk_official),
cast(ClauseElement, RedditMeme.stonk == True),
cast(ClauseElement, RedditMeme.stonk_official != None),
cast(ClauseElement, RedditMeme.version == LOAD_MEME_CLF_VERSION),
)
)
.count()
)
fn = (
site_db.query(RedditMeme)
.filter(
and_(
cast(ClauseElement, RedditMeme.meme_clf == RedditMeme.stonk_official),
cast(ClauseElement, RedditMeme.stonk == False),
cast(ClauseElement, RedditMeme.stonk_official != None),
cast(ClauseElement, RedditMeme.version == LOAD_MEME_CLF_VERSION),
)
)
.count()
)
meme_clf_wrong = (
site_db.query(RedditMeme)
.filter(
and_(
cast(ClauseElement, RedditMeme.meme_clf != RedditMeme.stonk_official),
cast(ClauseElement, RedditMeme.stonk_official != None),
cast(ClauseElement, RedditMeme.version == LOAD_MEME_CLF_VERSION),
)
)
.count()
)
meme_clf_wrong_stonk_right = (
site_db.query(RedditMeme)
.filter(
and_(
cast(ClauseElement, RedditMeme.meme_clf != RedditMeme.stonk_official),
cast(ClauseElement, RedditMeme.stonk == False),
cast(ClauseElement, RedditMeme.stonk_official != None),
cast(ClauseElement, RedditMeme.version == LOAD_MEME_CLF_VERSION),
)
)
.count()
)
meme_clf_wrong_stonk_wrong = (
site_db.query(RedditMeme)
.filter(
and_(
cast(ClauseElement, RedditMeme.meme_clf != RedditMeme.stonk_official),
cast(ClauseElement, RedditMeme.stonk == True),
cast(ClauseElement, RedditMeme.stonk_official != None),
cast(ClauseElement, RedditMeme.version == LOAD_MEME_CLF_VERSION),
)
)
.count()
)
display_df(
pd.DataFrame.from_records(
[
dict(
num_stonks=num_stonks,
num_not_template=num_not_template,
total_official=total_official,
num_filled=num_filled,
percent_done=round(num_filled / total_official, 3),
)
]
)
)
display_df(
pd.DataFrame.from_records(
[
dict(
num_not_template_wrong=num_not_template_wrong,
num_nt_wrong_percent=round(
num_not_template_wrong / num_not_template, 3
),
true_positives=tp,
tp_percent=round(tp / num_stonks, 3),
false_negatives=fn,
fn_percent=round(fn / num_stonks, 3),
)
]
)
)
display_df(
pd.DataFrame.from_records(
[
dict(
meme_clf_wrong=meme_clf_wrong,
wrong_right=meme_clf_wrong_stonk_right,
wr_percent=round(fn / meme_clf_wrong, 3),
wrong_wrong=meme_clf_wrong_stonk_wrong,
ww_percent=round(fn / meme_clf_wrong, 3),
)
]
)
)
def print_worst(self) -> None:
display_df(
pd.DataFrame(list(self.smd["name_acc"].items()),
columns=["name", "acc"]).sort_values("acc",
ascending=True))
def print_stats(name: str = ""):
if name:
correct_stonk = (site_db.query(RedditMeme).filter(
and_(
cast(ClauseElement,
RedditMeme.version == LOAD_MEME_CLF_VERSION),
cast(ClauseElement, RedditMeme.stonk_correct == True),
cast(ClauseElement, RedditMeme.meme_clf == name),
)).count())
wrong_stonk = (site_db.query(RedditMeme).filter(
and_(
cast(ClauseElement,
RedditMeme.version == LOAD_MEME_CLF_VERSION),
cast(ClauseElement, RedditMeme.stonk_correct == False),
cast(ClauseElement, RedditMeme.meme_clf == name),
)).count())
num_posts = (site_db.query(RedditMeme).filter(
and_(
cast(ClauseElement,
RedditMeme.version == LOAD_MEME_CLF_VERSION),
cast(ClauseElement, RedditMeme.meme_clf == name),
cast(ClauseElement, RedditMeme.stonk == True),
)).count())
else:
correct_stonk = 0
wrong_stonk = 0
num_posts = 0
correct_stonks = (site_db.query(RedditMeme).filter(
and_(
cast(ClauseElement, RedditMeme.version == LOAD_MEME_CLF_VERSION),
cast(ClauseElement, RedditMeme.stonk_correct == True),
)).count())
wrong_stonks = (site_db.query(RedditMeme).filter(
and_(
cast(ClauseElement, RedditMeme.version == LOAD_MEME_CLF_VERSION),
cast(ClauseElement, RedditMeme.stonk_correct == False),
)).count())
correct_meme_clf = (site_db.query(RedditMeme).filter(
and_(
cast(ClauseElement, RedditMeme.version == LOAD_MEME_CLF_VERSION),
cast(ClauseElement, RedditMeme.meme_clf_correct == True),
)).count())
wrong_meme_clf = (site_db.query(RedditMeme).filter(
and_(
cast(ClauseElement, RedditMeme.version == LOAD_MEME_CLF_VERSION),
cast(ClauseElement, RedditMeme.meme_clf_correct == False),
)).count())
memes_classified = (site_db.query(RedditMeme).filter(
cast(ClauseElement,
RedditMeme.version == LOAD_MEME_CLF_VERSION)).count())
memes_unclassified = (site_db.query(RedditMeme).filter(
cast(ClauseElement, RedditMeme.version == None)).count())
perc_correct = correct_stonk / (correct_stonk + wrong_stonk) if (
correct_stonk + wrong_stonk) != 0 else 0
percent_correct = correct_stonks / (correct_stonks + wrong_stonks) if (
correct_stonks + wrong_stonks) != 0 else 0
display_df(
pd.DataFrame.from_records([
dict(
num_posts=num_posts,
correct_stonk=correct_stonk,
wrong_stonk=wrong_stonk,
perc_correct=perc_correct,
memes_classified=memes_classified,
memes_unclassified=memes_unclassified,
correct_stonks=correct_stonks,
wrong_stonks=wrong_stonks,
percent_correct=percent_correct,
correct_meme_clf=correct_meme_clf,
wrong_meme_clf=wrong_meme_clf,
)
]))