def test_hilbert_freq_shape_forward_fourier_true():
    """
    Test that hilbert_freq returns the correct shape when forward_fourier=True.
    Input shape: (batch, channels, seq_len)
    Output shape: (batch, channels, seq_len, 2)
    """
    batch, channels, seq_len = 2, 3, 100
    input_tensor = torch.randn(batch, channels, seq_len)
    output = hilbert_freq(input_tensor, forward_fourier=True)
    expected_shape = (batch, channels, seq_len, 2)
    assert output.shape == expected_shape, f"Expected shape {expected_shape}, got {output.shape}"

    Test that hilbert_freq returns the correct shape when forward_fourier=True.
    Input shape: (batch, channels, seq_len)
    Output shape: (batch, channels, seq_len, 2)
    
test/unit_tests/models/test_functional.py