# Path: jaxopt/tree_util.py

# 
# Path: jaxopt/_src/test_util.py
# def ridge_solver(X, y, lam):
# def ridge_solver_jac(X, y, lam, eps=1e-4):
# def lasso_skl(X, y, lam, tol=1e-5, fit_intercept=False):
# def lasso_skl_jac(X, y, lam, tol=1e-5, fit_intercept=False, eps=1e-4):
# def enet_skl(X, y, params_prox, tol=1e-5, fit_intercept=False):
# def enet_skl_jac(X, y, params_prox, tol=1e-5, fit_intercept=False, eps=1e-5):
# def multitask_lasso_skl(X, Y, lam, tol=1e-5):
# def logreg_skl(X, y, lam, tol=1e-5, fit_intercept=False,
#                penalty="l2", multiclass=True):
#   def _reshape_coef(coef):
# def logreg_skl_jac(X, y, lam, tol=1e-5, fit_intercept=False, penalty="l2",
#                    multiclass=True, eps=1e-5):
# def multiclass_linear_svm_skl(X, y, lam, tol=1e-5):
# def multiclass_linear_svm_skl_jac(X, y, lam, tol=1e-5, eps=1e-5):
# def lsq_linear_osp(X, y, bounds, tol=1e-10, max_iter=None):
# def lsq_linear_cube_osp(X, y, l, tol=1e-10, max_iter=None):
# def lsq_linear_cube_osp_jac(X, y, l, eps=1e-5, tol=1e-10, max_iter=None):
# def check_states_have_same_types(state1, state2):
# def _canonicalize_dtype(x64_enabled, dtype):
# def canonicalize_dtype(dtype):
# def _dtype(x):
# def default_tolerance():
# def tolerance(dtype, tol=None):
# def device_under_test():
# def _assert_numpy_allclose(a, b, atol=None, rtol=None, err_msg=''):
# def is_sequence(x):
#   def assertArraysEqual(self, x, y, *, check_dtypes=True, err_msg=''):
#   def assertArraysAllClose(self, x, y, *, check_dtypes=True, atol=None,
#                            rtol=None, err_msg=''):
#   def assertDtypesMatch(self, x, y, *, canonicalize_dtypes=True):
#   def assertAllClose(self, x, y, *, check_dtypes=True, atol=None, rtol=None,
#                      canonicalize_dtypes=True, err_msg=''):
#   XX = jnp.dot(X.T, X)
#   I = jnp.eye(X.shape[1])
# class JaxoptTestCase(parameterized.TestCase):


from absl.testing import absltest
from jaxopt import tree_util
from jaxopt._src import test_util
import jax.numpy as jnp
import jax.tree_util as jtu
import numpy as onp
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.






class TreeUtilTest(test_util.JaxoptTestCase):

  def setUp(self):
    super().setUp()
    rng = onp.random.RandomState(0)

    self.tree_A = (rng.randn(20, 10), rng.randn(20))
    self.tree_B = (rng.randn(20, 10), rng.randn(20))

    self.tree_A_dict = (1.0, {"k1": 1.0, "k2": (1.0, 1.0)}, 1.0)
    self.tree_B_dict = (1.0, {"k1": 2.0, "k2": (3.0, 4.0)}, 5.0)

    self.array_A = rng.randn(20)
    self.array_B = rng.randn(20)

  def _assertTreesAllClose(self, tree_A, tree_B):
    self.assertArraysAllClose(tree_A[0], tree_B[0])
    self.assertArraysAllClose(tree_A[1], tree_B[1])

  def test_tree_add(self):
    expected = self.array_A + self.array_B

# Path: jaxopt/tree_util.py

# 
# Path: jaxopt/_src/test_util.py
# def ridge_solver(X, y, lam):
# def ridge_solver_jac(X, y, lam, eps=1e-4):
# def lasso_skl(X, y, lam, tol=1e-5, fit_intercept=False):
# def lasso_skl_jac(X, y, lam, tol=1e-5, fit_intercept=False, eps=1e-4):
# def enet_skl(X, y, params_prox, tol=1e-5, fit_intercept=False):
# def enet_skl_jac(X, y, params_prox, tol=1e-5, fit_intercept=False, eps=1e-5):
# def multitask_lasso_skl(X, Y, lam, tol=1e-5):
# def logreg_skl(X, y, lam, tol=1e-5, fit_intercept=False,
#                penalty="l2", multiclass=True):
#   def _reshape_coef(coef):
# def logreg_skl_jac(X, y, lam, tol=1e-5, fit_intercept=False, penalty="l2",
#                    multiclass=True, eps=1e-5):
# def multiclass_linear_svm_skl(X, y, lam, tol=1e-5):
# def multiclass_linear_svm_skl_jac(X, y, lam, tol=1e-5, eps=1e-5):
# def lsq_linear_osp(X, y, bounds, tol=1e-10, max_iter=None):
# def lsq_linear_cube_osp(X, y, l, tol=1e-10, max_iter=None):
# def lsq_linear_cube_osp_jac(X, y, l, eps=1e-5, tol=1e-10, max_iter=None):
# def check_states_have_same_types(state1, state2):
# def _canonicalize_dtype(x64_enabled, dtype):
# def canonicalize_dtype(dtype):
# def _dtype(x):
# def default_tolerance():
# def tolerance(dtype, tol=None):
# def device_under_test():
# def _assert_numpy_allclose(a, b, atol=None, rtol=None, err_msg=''):
# def is_sequence(x):
#   def assertArraysEqual(self, x, y, *, check_dtypes=True, err_msg=''):
#   def assertArraysAllClose(self, x, y, *, check_dtypes=True, atol=None,
#                            rtol=None, err_msg=''):
#   def assertDtypesMatch(self, x, y, *, canonicalize_dtypes=True):
#   def assertAllClose(self, x, y, *, check_dtypes=True, atol=None, rtol=None,
#                      canonicalize_dtypes=True, err_msg=''):
#   XX = jnp.dot(X.T, X)
#   I = jnp.eye(X.shape[1])
# class JaxoptTestCase(parameterized.TestCase):


# Path: tests/tree_util_test.py
from absl.testing import absltest
from jaxopt import tree_util
from jaxopt._src import test_util
import jax.numpy as jnp
import jax.tree_util as jtu
import numpy as onp

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.






class TreeUtilTest(test_util.JaxoptTestCase):

  def setUp(self):
    super().setUp()
    rng = onp.random.RandomState(0)

    self.tree_A = (rng.randn(20, 10), rng.randn(20))
    self.tree_B = (rng.randn(20, 10), rng.randn(20))

    self.tree_A_dict = (1.0, {"k1": 1.0, "k2": (1.0, 1.0)}, 1.0)
    self.tree_B_dict = (1.0, {"k1": 2.0, "k2": (3.0, 4.0)}, 5.0)

    self.array_A = rng.randn(20)
    self.array_B = rng.randn(20)

  def _assertTreesAllClose(self, tree_A, tree_B):
    self.assertArraysAllClose(tree_A[0], tree_B[0])
    self.assertArraysAllClose(tree_A[1], tree_B[1])

  def test_tree_add(self):
    expected = self.array_A + self.array_B

    got = tree_util.tree_add(self.array_A, self.array_B)