Function test_tensorbatch_wrap_buffers

tests/cvcuda/python/test_tensor_batch.py:155–200

()

def test_tensorbatch_wrap_buffers():
    # from cuda buffer, without layout
    buffers = [
        util.to_cuda_buffer(np.ones(rand_shape(3), dtype=np.int32)) for _ in range(10)
    ]
    batch = cvcuda.as_tensors(buffers)
    assert batch.capacity == len(buffers)
    assert len(batch) == len(buffers)
    assert batch.dtype == np.int32
    assert batch.layout is None
    assert batch.ndim == 3

    # from torch tensor, with layout
    buffers = [rand_torch_tensor(np.int16, 4) for i in range(5)]
    batch = cvcuda.as_tensors(buffers, layout="NHWC")
    assert batch.capacity == len(buffers)
    assert len(batch) == len(buffers)
    assert batch.dtype == np.int16
    assert batch.layout == "NHWC"
    assert batch.ndim == 4

    # mismatching rank
    with t.raises(
        RuntimeError,
        match="NVCV_ERROR_INVALID_ARGUMENT: "
        "Trying to add a tensor to a tensor batch with an inconsistent rank.",
    ):
        buffers = [rand_torch_tensor(np.int16, 3), rand_torch_tensor(np.int16, 4)]
        cvcuda.as_tensors(buffers)

    # mismatching dtype
    with t.raises(
        RuntimeError,
        match="NVCV_ERROR_INVALID_ARGUMENT: "
        "Trying to add a tensor to a tensor batch with an inconsistent type.",
    ):
        buffers = [rand_torch_tensor(np.int16, 3), rand_torch_tensor(np.int32, 3)]
        cvcuda.as_tensors(buffers)

    # invalid types
    with t.raises(
        RuntimeError,
        match="Input buffer doesn't provide cuda_array_interface or DLPack interfaces.",
    ):
        buffers = [[1, 2, 3]]
        cvcuda.as_tensors(buffers)


def test_tensorbatch_errors():