Hello Everybody, I am looking for some help with the deployment of a tabular model, particularly with the service.py file My load_save.py file to test my loading and saving of the model looks like below

import numpy as np

from numpy import random

from tqdm import tqdm

import fastbook

fastbook.setup_book()

from fastbook import *

from fastai.tabular.all import *

import pandas as pd

import matplotlib.pyplot as plt

from fastai.imports import *

np.set_printoptions(linewidth=130)

from sklearn.ensemble import RandomForestClassifier

from sklearn.metrics import accuracy_score

from pathlib import Path

import os

import xgboost as xgb

from xgboost import plot_importance

from xgboost import XGBClassifier

import warnings

import gc

import pickle

from joblib import dump, load

import typing as t

import bentoml

torch.manual_seed(42)

path = Path('data/')

train_df = pd.read_csv(path/'train.csv',index_col='id')

test_df = pd.read_csv(path/'test.csv',index_col='id')

sub_df = pd.read_csv(path/'sample_submission.csv')

cont_names,cat_names = cont_cat_split(train_df, dep_var='Depression')

splits = RandomSplitter(valid_pct=0.2)(range_of(train_df))

to = TabularPandas(train_df, procs=[Categorify, FillMissing,Normalize],

#to = TabularPandas(train_df, procs=[Categorify,Normalize],

cat_names = cat_names,

cont_names = cont_names,

y_names='Depression',

y_block=CategoryBlock(),

splits=splits)

dls = to.dataloaders(bs=64)

#dls = to.dataloaders(bs=1024)

test_dl = dls.test_dl(test_df)

X_train, y_train = to.train.xs, to.train.ys.values.ravel()

X_test, y_test = to.valid.xs, to.valid.ys.values.ravel()

xgb_model = xgb.XGBClassifier()

xgb_model = xgb_model.fit(X_train, y_train)

#xgb_preds = tensor(xgb_model.predict(test_dl.xs))

#xgb_preds_x = tensor(xgb_model.predict(X_test))

bentoml.xgboost.save_model("mental_health_v1", xgb_model)

My test.py file which returns tensor([0, 0, 0, ..., 0, 1, 0]) when i run python test.py on my terminal Looks like below

import bentoml

import xgboost as xgb

import pandas as pd

from pathlib import Path

import fastbook

fastbook.setup_book()

from fastbook import *

from fastai.tabular.all import *

# Load the model by setting the model tag

booster = bentoml.xgboost.load_model("mental_health_v1:hsohdawgwkno6aav")

path = Path('data/')

test_df = pd.read_csv(path/'test.csv',index_col='id')

train_df = pd.read_csv(path/'train.csv',index_col='id')

cont_names,cat_names = cont_cat_split(train_df, dep_var='Depression')

splits = RandomSplitter(valid_pct=0.2)(range_of(train_df))

to = TabularPandas(train_df, procs=[Categorify, FillMissing,Normalize],

#to = TabularPandas(train_df, procs=[Categorify,Normalize],

cat_names = cat_names,

cont_names = cont_names,

y_names='Depression',

y_block=CategoryBlock(),

splits=splits)

dls = to.dataloaders(bs=64)

test_dl = dls.test_dl(test_df)

res = tensor(booster.predict(test_dl.xs))

print(res)

I have tried various ways of building my predict method in my service.py file with the simplest version being something like

import os

import numpy as np

import bentoml

import fastbook

fastbook.setup_book()

from fastbook import *

from fastai.tabular.all import *

from typing import Annotated  # Python 3.9 or above

from typing_extensions import Annotated  # Older than 3.9

import pandas as pd

from bentoml.validators import DataframeSchema

from fastai.tabular.all import *

import xgboost as xgb

@bentoml.service(

resources={"cpu": "8"},

traffic={"timeout": 10},

)

class MentalHealthClassifier:

#retrieve the latest version of the model from the BentoML model store

bento_model = bentoml.models.get("mental_health_v1:latest")

#bento_model = BentoModel('mental_health_v1:q5kcqtf5ys3qoaav')

def __init__(self):

self.model = bentoml.xgboost.load_model(self.bento_model)

@bentoml.api

def predict(self, data:pd.DataFrame):

return bento_model.predict(data)

but nothing seems to work when i pass in some data for example { "Name": "Shivam", "Gender": "Male", "Age": 53, "City": "Visakhapatnam", "Working Professional or Student": "Working Professional", "Profession": "Judge", "Academic Pressure": 5, "Work Pressure": 4, "CGPA": 7.34, "Study Satisfaction": 3, "Job Satisfaction": 2, "Sleep Duration": "Less than 5 hours", "Dietary Habits": "Moderate", "Degree": "LLB", "Have you ever had suicidal thoughts ?": "Yes", "Work/Study Hours": 93, "Financial Stress": 4, "Family History of Mental Illness": "No" } Any ideas on how to help with this would be highly appreciated.