import torch
import pytest
from pina.data.dataset import PinaDatasetFactory, PinaTensorDataset

input_tensor = torch.rand((100, 10))
output_tensor = torch.rand((100, 2))

input_tensor_2 = torch.rand((50, 10))
output_tensor_2 = torch.rand((50, 2))

conditions_dict_single = {
    "data": {
        "input": input_tensor,
        "target": output_tensor,
    }
}

conditions_dict_single_multi = {
    "data_1": {
        "input": input_tensor,
        "target": output_tensor,
    },
    "data_2": {
        "input": input_tensor_2,
        "target": output_tensor_2,
    },
}

max_conditions_lengths_single = {"data": 100}

max_conditions_lengths_multi = {"data_1": 100, "data_2": 50}


@pytest.mark.parametrize(
    "conditions_dict, max_conditions_lengths",
    [
        (conditions_dict_single, max_conditions_lengths_single),
        (conditions_dict_single_multi, max_conditions_lengths_multi),
    ],
)
def test_constructor_tensor(conditions_dict, max_conditions_lengths):
    dataset = PinaDatasetFactory(
        conditions_dict,
        max_conditions_lengths=max_conditions_lengths,
        automatic_batching=True,
    )
    assert isinstance(dataset, PinaTensorDataset)


def test_getitem_single():
    dataset = PinaDatasetFactory(
        conditions_dict_single,
        max_conditions_lengths=max_conditions_lengths_single,
        automatic_batching=False,
    )

    tensors = dataset.fetch_from_idx_list([i for i in range(70)])
    assert isinstance(tensors, dict)
    assert list(tensors.keys()) == ["data"]
    assert sorted(list(tensors["data"].keys())) == ["input", "target"]
    assert isinstance(tensors["data"]["input"], torch.Tensor)
    assert tensors["data"]["input"].shape == torch.Size((70, 10))
    assert isinstance(tensors["data"]["target"], torch.Tensor)
    assert tensors["data"]["target"].shape == torch.Size((70, 2))


def test_getitem_multi():
    dataset = PinaDatasetFactory(
        conditions_dict_single_multi,
        max_conditions_lengths=max_conditions_lengths_multi,
        automatic_batching=False,
    )
    tensors = dataset.fetch_from_idx_list([i for i in range(70)])
    assert isinstance(tensors, dict)
    assert list(tensors.keys()) == ["data_1", "data_2"]
    assert sorted(list(tensors["data_1"].keys())) == ["input", "target"]
    assert isinstance(tensors["data_1"]["input"], torch.Tensor)
    assert tensors["data_1"]["input"].shape == torch.Size((70, 10))
    assert isinstance(tensors["data_1"]["target"], torch.Tensor)
    assert tensors["data_1"]["target"].shape == torch.Size((70, 2))

    assert sorted(list(tensors["data_2"].keys())) == ["input", "target"]
    assert isinstance(tensors["data_2"]["input"], torch.Tensor)
    assert tensors["data_2"]["input"].shape == torch.Size((50, 10))
    assert isinstance(tensors["data_2"]["target"], torch.Tensor)
    assert tensors["data_2"]["target"].shape == torch.Size((50, 2))