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"""Basic runtime enablement test."""

import tvm
from tvm import te
import numpy as np
import tvm.testing


@tvm.testing.uses_gpu
def test_nd_create():
    for target, ctx in tvm.testing.enabled_targets():
        for dtype in ["uint8", "int8", "uint16", "int16", "uint32", "int32", "float32"]:
            x = np.random.randint(0, 10, size=(3, 4))
            x = np.array(x, dtype=dtype)
            y = tvm.nd.array(x, ctx=ctx)
            z = y.copyto(ctx)
            assert y.dtype == x.dtype
            assert y.shape == x.shape
            assert isinstance(y, tvm.nd.NDArray)
            np.testing.assert_equal(x, y.asnumpy())
            np.testing.assert_equal(x, z.asnumpy())
        # no need here, just to test usablity
        ctx.sync()


def test_fp16_conversion():
    n = 100

    for (src, dst) in [("float32", "float16"), ("float16", "float32")]:
        A = te.placeholder((n,), dtype=src)
        B = te.compute((n,), lambda i: A[i].astype(dst))

        s = te.create_schedule([B.op])
        func = tvm.build(s, [A, B], "llvm")

        x_tvm = tvm.nd.array(100 * np.random.randn(n).astype(src) - 50)
        y_tvm = tvm.nd.array(100 * np.random.randn(n).astype(dst) - 50)

        func(x_tvm, y_tvm)

        expected = x_tvm.asnumpy().astype(dst)
        real = y_tvm.asnumpy()

        tvm.testing.assert_allclose(expected, real)


def test_dtype():
    dtype = tvm.DataType("handle")
    assert dtype.type_code == tvm.DataTypeCode.HANDLE


if __name__ == "__main__":
    test_nd_create()
    test_fp16_conversion()
    test_dtype()
