Module neuralops.tests.data.test_dataset_loader

Tests for neuralops.data.dataset_loader module.

Classes

class TestExperimentConfig

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class TestExperimentConfig:
    """Test ExperimentConfig fields and initialization."""

    def test_default_values(self):
        cfg = ExperimentConfig(dataset_name="sst2")
        assert cfg.dataset_name == "sst2"
        assert cfg.task_type == "single"
        assert cfg.max_seq_length == 128
        assert cfg.num_labels == 2
        assert cfg.metric == "accuracy"
        assert cfg.split_ratio == 0.1

    def test_custom_values(self):
        cfg = ExperimentConfig(
            dataset_name="custom.csv",
            dataset_path="/tmp/custom.csv",
            task_type="pair",
            max_seq_length=256,
            num_labels=3,
            metric="f1",
        )
        assert cfg.dataset_name == "custom.csv"
        assert cfg.dataset_path == "/tmp/custom.csv"
        assert cfg.task_type == "pair"
        assert cfg.max_seq_length == 256
        assert cfg.num_labels == 3
        assert cfg.metric == "f1"

Test ExperimentConfig fields and initialization.

Methods

def test_custom_values(self)

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def test_custom_values(self):
    cfg = ExperimentConfig(
        dataset_name="custom.csv",
        dataset_path="/tmp/custom.csv",
        task_type="pair",
        max_seq_length=256,
        num_labels=3,
        metric="f1",
    )
    assert cfg.dataset_name == "custom.csv"
    assert cfg.dataset_path == "/tmp/custom.csv"
    assert cfg.task_type == "pair"
    assert cfg.max_seq_length == 256
    assert cfg.num_labels == 3
    assert cfg.metric == "f1"

def test_default_values(self)

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def test_default_values(self):
    cfg = ExperimentConfig(dataset_name="sst2")
    assert cfg.dataset_name == "sst2"
    assert cfg.task_type == "single"
    assert cfg.max_seq_length == 128
    assert cfg.num_labels == 2
    assert cfg.metric == "accuracy"
    assert cfg.split_ratio == 0.1

class TestLoadDataset

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class TestLoadDataset:
    """Test load_dataset routing across formats."""

    @patch("neuralops.data.dataset_loader._load_glue")
    def test_load_glue_routing(self, mock_glue):
        mock_glue.return_value = {"train": [], "validation": []}
        cfg = ExperimentConfig(dataset_name="sst2")
        result = load_dataset(cfg)
        mock_glue.assert_called_once_with(cfg)
        assert "train" in result

    @patch("neuralops.data.dataset_loader._load_synthetic")
    def test_load_synthetic_routing(self, mock_synth):
        mock_synth.return_value = {"train": [], "validation": []}
        cfg = ExperimentConfig(dataset_name="synthetic")
        result = load_dataset(cfg)
        mock_synth.assert_called_once_with(cfg)
        assert "train" in result

    @patch("neuralops.data.dataset_loader._load_custom")
    def test_load_custom_routing(self, mock_custom):
        mock_custom.return_value = {"train": []}
        cfg = ExperimentConfig(dataset_name="data.parquet")
        result = load_dataset(cfg)
        mock_custom.assert_called_once_with(cfg)
        assert "train" in result

Test load_dataset routing across formats.

Methods

def test_load_custom_routing(self, mock_custom)

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@patch("neuralops.data.dataset_loader._load_custom")
def test_load_custom_routing(self, mock_custom):
    mock_custom.return_value = {"train": []}
    cfg = ExperimentConfig(dataset_name="data.parquet")
    result = load_dataset(cfg)
    mock_custom.assert_called_once_with(cfg)
    assert "train" in result

def test_load_glue_routing(self, mock_glue)

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@patch("neuralops.data.dataset_loader._load_glue")
def test_load_glue_routing(self, mock_glue):
    mock_glue.return_value = {"train": [], "validation": []}
    cfg = ExperimentConfig(dataset_name="sst2")
    result = load_dataset(cfg)
    mock_glue.assert_called_once_with(cfg)
    assert "train" in result

def test_load_synthetic_routing(self, mock_synth)

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@patch("neuralops.data.dataset_loader._load_synthetic")
def test_load_synthetic_routing(self, mock_synth):
    mock_synth.return_value = {"train": [], "validation": []}
    cfg = ExperimentConfig(dataset_name="synthetic")
    result = load_dataset(cfg)
    mock_synth.assert_called_once_with(cfg)
    assert "train" in result