import os
import sys
import unittest
import torch
from torch import Tensor
from typing import List, Tuple

PROJECT_ROOT = os.path.realpath(os.path.join(os.path.dirname(__file__), "..", ".."))
MODULE_ROOT = os.path.join(PROJECT_ROOT, "modules")
sys.path.append(MODULE_ROOT)

from pytorch_wrapper.pt_compute_loss import PtComputeLoss 
from pytorch_wrapper.ptn_l1_loss import PtnL1Loss 


class TestComputeLoss(unittest.TestCase):
    def setUp(self) -> None:
        """
        Set up the test instance by initializing the loss functions and test cases.
        """
        self.compute_node = PtComputeLoss()
        self.loss_node = PtnL1Loss()
        self.loss_fun_none = self.loss_node.f("none")[0]
        self.loss_fun_mean = self.loss_node.f("mean")[0]
        self.loss_fun_sum = self.loss_node.f("sum")[0]

        # Test cases: (predicted values y_hat, ground truth y)
        self.test_cases: List[Tuple[Tensor, Tensor]] = [
            (
                torch.tensor([0.1, -1.0, 10, -100, 1000], dtype=torch.float32),
                torch.tensor([0.09, -1.1, 9, -101, 999], dtype=torch.float32),
            )
        ]

    def unreduced_loss(self, y_hat: Tensor, y: Tensor) -> Tensor:
        """
        Compute the unreduced L1 loss.

        Args:
            y_hat (Tensor): Predicted values.
            y (Tensor): Ground truth values.

        Returns:
            Tensor: Unreduced element-wise L1 loss.
        """
        return torch.abs(y_hat - y)

    def test_none(self) -> None:
        """
        Test L1 loss with reduction='none'.
        """
        for y_hat, y in self.test_cases:
            with self.subTest(y_hat=y_hat):
                actual = self.compute_node.f(y_hat, y, self.loss_fun_none)[0]
                expected = self.unreduced_loss(y_hat, y)
                actual = self.loss_fun_none(y_hat, y)
                self.assertTrue(torch.allclose(actual, expected, atol=1e-6),
                                f"Expected {expected}, got {actual}")

    def test_mean(self) -> None:
        """
        Test L1 loss with reduction='mean'.
        """
        for y_hat, y in self.test_cases:
            with self.subTest(y_hat=y_hat):
                loss = self.unreduced_loss(y_hat, y)
                expected = loss.mean(dim=0)
                actual = self.compute_node.f(y_hat, y, self.loss_fun_mean)[0]
                self.assertTrue(torch.equal(actual, expected),
                                f"Expected {expected}, got {actual}")

    def test_sum(self) -> None:
        """
        Test L1 loss with reduction='sum'.
        """
        for y_hat, y in self.test_cases:
            with self.subTest(y_hat=y_hat):
                loss = self.unreduced_loss(y_hat, y)
                expected = loss.sum(dim=0)
                actual = self.compute_node.f(y_hat, y, self.loss_fun_sum)[0]
                self.assertTrue(torch.equal(actual, expected),
                                f"Expected {expected}, got {actual}")


if __name__ == "__main__":
    unittest.main()