request: How to deploy a logistic regression model writen in PyTorch?

[IonBoleac]

How can i deploy a logistic regression model written in PyTorch? The model's arch is:

import torch
import torch.nn as nn
import torch.nn.functional as F

class LogisticRegression(nn.Module):
    def __init__(self, input_len_data=55):
        super(LogisticRegression,self).__init__()
        self.f1 = nn.Linear(input_len_data, 1000)
        self.f2 = nn.Linear(1000, 1)

    def forward(self,x):
        x = self.f1(x)
        x = F.leaky_relu(x)
        x = F.dropout(x, p = 0.2)
        x = self.f2(x)
        return  F.sigmoid(x)
    
    def predict(self, inp):
        """predict digit for input"""
        self.eval()
        with torch.inference_mode():
            raw_output = self(inp)
            pred = torch.round(raw_output)
            return pred

I trained the model with this script:

device = "cuda" if torch.cuda.is_available() else "cpu"
model = LogisticRegression(input_len_data=55).to(device=device)
learning_rate = 0.0001
criterion = torch.nn.BCELoss() 
optimizer = torch.optim.SGD(model.parameters(), lr=learning_rate)

# Calculate accuracy (a classification metric)
def accuracy_fn(y_true, y_pred):
    correct = torch.eq(y_true, y_pred).sum().item() # torch.eq() calculates where two tensors are equal
    acc = (correct / len(y_pred)) * 100 
    return acc

# Fit the model
torch.manual_seed(42)
epochs = 1000

for epoch in range(epochs):
    ### Training
    model.train()
    # 1. Forward pass
    y_pred_train = model(X_train).squeeze() # squeeze removes dimensions of size 1

    # 2. Calculate loss/accuracy
    loss = criterion(y_pred_train, y_train)
    acc = (torch.eq(torch.round(y_pred_train), y_train).sum().item() / len(y_train)) * 100

    # 3. Optimizer zero grad
    optimizer.zero_grad()

    # 4. Loss backwards
    loss.backward()

    # 5. Optimizer step
    optimizer.step()

    ### Testing
    model.eval()
    with torch.inference_mode():
        # 1. Forward pass
        y_pred_test = torch.round(model(X_test).squeeze()) 
        # 2. Caculate loss/accuracy
        test_loss = criterion(y_pred_test,
                            y_test)
        test_acc = (torch.eq(torch.round(y_pred_test), y_test).sum().item() / len(y_test)) * 100

    # Print out what's happening every 10 epochs
    if epoch % 100 == 0:
        print(f"Epoch: {epoch} | Loss: {loss:.5f}, Accuracy: {acc:.2f}% | Test loss: {test_loss:.5f}, Test acc: {test_acc:.2f}%")
        #print(f"Predictions: {y_pred_test}/n")

And saved the model in a bento with this command:

bentoml.pytorch.save_model('logits_V1_1_bento', model)

To serve the bento i used this service script:

import numpy as np
import bentoml
from bentoml.io import NumpyNdarray
import torch

model_runner = bentoml.pytorch.get("logits_v1_1_bento:gbrwqwwm2oqhx3p3").to_runner()

svc = bentoml.Service(name="test_service", runners=[model_runner])

def to_numpy(tensor):
    return tensor.detach().cpu().numpy()


@svc.api(
    input=NumpyNdarray(), 
    output=NumpyNdarray()
)
async def classify(input_series) -> np.ndarray:
    #assert input_series.shape == (1, 53)
    input_tensor = torch.from_numpy(input_series)
    #result = model_runner.predict.run(input_tensor)
    result = await model_runner.async_run(input_tensor)
    return to_numpy(result)
# bentoml serve service:svc

The serving is working but when i make a request with a csv file

curl -X POST "http://127.0.0.1:3000/classify" -T ./torchserve_test.csv -H "Content-type: text/csv"

I receive this error:

2024-02-16T15:44:09+0100 [ERROR] [api_server:test_service:1] Exception on /classify [POST] (trace=93a4137933ba4675dd3440887dc79c71,span=e9615789d9823f39,sampled=0,service.name=test_service)
Traceback (most recent call last):
  File "/home/ion/.local/lib/python3.10/site-packages/bentoml/_internal/server/http_app.py", line 328, in api_func
    input_data = await api.input.from_http_request(request)
  File "/home/ion/.local/lib/python3.10/site-packages/bentoml/_internal/io_descriptors/numpy.py", line 401, in from_http_request
    obj = await request.json()
  File "/home/ion/.local/lib/python3.10/site-packages/starlette/requests.py", line 252, in json
    self._json = json.loads(body)
  File "/usr/lib/python3.10/json/__init__.py", line 346, in loads
    return _default_decoder.decode(s)
  File "/usr/lib/python3.10/json/decoder.py", line 337, in decode
    obj, end = self.raw_decode(s, idx=_w(s, 0).end())
  File "/usr/lib/python3.10/json/decoder.py", line 355, in raw_decode
    raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
2024-02-16T15:44:09+0100 [INFO] [api_server:test_service:1] 127.0.0.1:58520 (scheme=http,method=POST,path=/classify,type=csv/file,length=1272) (status=500,type=application/json,length=110) 1.761ms (trace=93a4137933ba4675dd3440887dc79c71,span=e9615789d9823f39,sampled=0,service.name=test_service)

How can i resolve this error?

[IonBoleac]

The problem is resolved. I fixed adding the data that is send in json format. The solution is arrived meanwhile i take a shower ahahah