from typing import Optional

import pytest

from docarray import BaseDoc, DocList
from docarray.utils._internal.misc import is_jax_available

if is_jax_available():
    import jax.numpy as jnp
    from jax import jit

    from docarray.typing import JaxArray


@pytest.mark.jax
def test_basic_jax_operation():
    def basic_jax_fn(x):
        return jnp.sum(x)

    def abstract_JaxArray(array: 'JaxArray') -> jnp.ndarray:
        return array.tensor

    class Mmdoc(BaseDoc):
        tensor: Optional[JaxArray[3, 224, 224]] = None

    N = 10

    batch = DocList[Mmdoc](Mmdoc() for _ in range(N))
    batch.tensor = jnp.zeros((N, 3, 224, 224))

    batch = batch.to_doc_vec()

    jax_fn = jit(basic_jax_fn)
    result = jax_fn(abstract_JaxArray(batch.tensor))

    assert (
        result == 0.0
    )  # checking if the sum of the tensor data is zero as initialized

from typing import Optional

import pytest

from docarray import BaseDoc, DocList
from docarray.utils._internal.misc import is_jax_available

if is_jax_available():
    import jax.numpy as jnp
    from jax import jit

    from docarray.typing import JaxArray


@pytest.mark.jax
def test_basic_jax_operation():
    def basic_jax_fn(x):
        return jnp.sum(x)

    def abstract_JaxArray(array: 'JaxArray') -> jnp.ndarray:
        return array.tensor

    class Mmdoc(BaseDoc):
        tensor: Optional[JaxArray[3, 224, 224]]

    N = 10

    batch = DocList[Mmdoc](Mmdoc() for _ in range(N))
    batch.tensor = jnp.zeros((N, 3, 224, 224))

    batch = batch.to_doc_vec()

    jax_fn = jit(basic_jax_fn)
    result = jax_fn(abstract_JaxArray(batch.tensor))

    assert (
        result == 0.0
    )  # checking if the sum of the tensor data is zero as initialized
