Remove unused imports

benchmarks/lbfgs_benchmark.py

@@ -14,14 +14,12 @@
 
 """Benchmark LBFGS implementation."""
 
-import time
 
 from absl import app
 from absl import flags
 
 from sklearn import datasets
 
-import jax
 import jax.numpy as jnp
 import jaxopt
 

benchmarks/proximal_gradient_benchmark.py

@@ -16,7 +16,6 @@
 
 import time
 
-from typing import NamedTuple
 from typing import Sequence
 
 from absl import app

examples/deep_learning/plot_sgd_solvers.py

@@ -38,7 +38,6 @@
 
 from absl import flags
 
-import logging
 import sys
 from timeit import default_timer as timer
 
@@ -49,7 +48,6 @@
 from jaxopt import ArmijoSGD
 from jaxopt import PolyakSGD
 from jaxopt import OptaxSolver
-from jaxopt.tree_util import tree_l2_norm, tree_sub
 
 import optax
 from flax import linen as nn

examples/fixed_point/deep_equilibrium_model.py

@@ -34,19 +34,16 @@
 """
 
 from functools import partial
-from typing import Any, Mapping, Tuple, Callable
+from typing import Any, Tuple, Callable
 
 from absl import app
 from absl import flags
 
-import flax
 from flax import linen as nn
 
 import jax
 import jax.numpy as jnp
-from jax.tree_util import tree_structure
 
-import jaxopt
 from jaxopt import loss
 from jaxopt import OptaxSolver
 from jaxopt import FixedPointIteration
@@ -58,7 +55,6 @@
 
 import tensorflow_datasets as tfds
 import tensorflow as tf
-from collections import namedtuple
 
 
 dataset_names = [

examples/fixed_point/plot_picard_ode.py

@@ -58,12 +58,9 @@
 
 from jaxopt import AndersonAcceleration
 
-from jaxopt import objective
-from jaxopt.tree_util import tree_scalar_mul, tree_sub
 
 import numpy as np
 import matplotlib.pyplot as plt
-from sklearn import datasets
 from matplotlib.pyplot import cm
 import scipy.integrate
 

examples/implicit_diff/lasso_implicit_diff.py

@@ -20,7 +20,6 @@
 from absl import app
 from absl import flags
 
-import jax
 import jax.numpy as jnp
 
 from jaxopt import BlockCoordinateDescent

jaxopt/_src/anderson.py

@@ -17,7 +17,6 @@
 from typing import Any
 from typing import Callable
 from typing import NamedTuple
-from typing import List
 from typing import Union
 
 from typing import Optional
@@ -27,12 +26,10 @@
 import jax.numpy as jnp
 
 from jaxopt._src import base
-from jaxopt._src import linear_solve
-from jaxopt._src.tree_util import tree_l2_norm, tree_sub
-from jaxopt._src.tree_util import tree_vdot, tree_add
-from jaxopt._src.tree_util import tree_mul, tree_scalar_mul
+from jaxopt._src.tree_util import tree_sub
+from jaxopt._src.tree_util import tree_vdot
 from jaxopt._src.tree_util import tree_average, tree_add_scalar_mul
-from jaxopt._src.tree_util import tree_map, tree_gram
+from jaxopt._src.tree_util import tree_map
 
 
 def minimize_residuals(residual_gram, ridge):

jaxopt/_src/anderson_wrapper.py

@@ -18,16 +18,14 @@
 from typing import Callable
 from typing import Optional
 from typing import NamedTuple
-from typing import Union
 
 from dataclasses import dataclass
 
 import jax
 import jax.numpy as jnp
 
 from jaxopt._src import base
-from jaxopt._src.tree_util import tree_l2_norm, tree_sub, tree_map
-from jaxopt._src.anderson import AndersonAcceleration
+from jaxopt._src.tree_util import tree_sub, tree_map
 from jaxopt._src.anderson import anderson_step, update_history
 
 

jaxopt/_src/backtracking_linesearch.py

@@ -22,7 +22,6 @@
 
 from dataclasses import dataclass
 
-import jax
 import jax.numpy as jnp
 
 from jaxopt._src import base

jaxopt/_src/base.py

@@ -35,7 +35,6 @@
 # jaxopt._src.linear_solve instead.
 # This allows to define linear solver with base.Solver interface,
 # and then exporting them in jaxopt.linear_solve.
-from jaxopt._src import linear_solve
 
 from jaxopt import loop
 from jaxopt import tree_util

jaxopt/_src/bisection.py

@@ -25,8 +25,6 @@
 import jax.numpy as jnp
 
 from jaxopt._src import base
-from jaxopt._src import implicit_diff as idf
-from jaxopt._src import loop
 
 
 class BisectionState(NamedTuple):

jaxopt/_src/block_cd.py

@@ -20,18 +20,14 @@
 from typing import Callable
 from typing import NamedTuple
 from typing import Optional
-from typing import Union
 
 from dataclasses import dataclass
 
 import jax
 import jax.numpy as jnp
 
 from jaxopt._src import base
-from jaxopt._src import implicit_diff as idf
-from jaxopt._src import loop
 from jaxopt._src import objective
-from jaxopt._src import tree_util
 
 
 class BlockCDState(NamedTuple):

jaxopt/_src/cd_qp.py

@@ -26,7 +26,6 @@
 
 from jaxopt._src import base
 from jaxopt._src import projection
-from jaxopt._src import tree_util
 
 
 class BoxCDQPState(NamedTuple):

jaxopt/_src/cvxpy_wrapper.py

@@ -13,18 +13,14 @@
 # limitations under the License.
 """CVXPY wrappers."""
 
-from typing import Any
 from typing import Callable
 from typing import Optional
-from typing import Tuple
 
 from dataclasses import dataclass
 
-import jax
 import jax.numpy as jnp 
 from jaxopt._src import base
 from jaxopt._src import implicit_diff as idf
-from jaxopt._src import linear_solve
 from jaxopt._src import tree_util
 
 

jaxopt/_src/fixed_point_iteration.py

@@ -23,7 +23,6 @@
 from dataclasses import dataclass
 
 import jax.numpy as jnp
-from jax.tree_util import tree_leaves, tree_structure
 
 from jaxopt._src import base
 from jaxopt._src.tree_util import tree_l2_norm, tree_sub

jaxopt/_src/gradient_descent.py

@@ -15,9 +15,7 @@
 """Implementation of gradient descent in JAX."""
 
 from typing import Any
-from typing import Callable
 from typing import NamedTuple
-from typing import Union
 
 from dataclasses import dataclass
 

jaxopt/_src/iterative_refinement.py

@@ -23,20 +23,15 @@
 from typing import Callable
 from typing import NamedTuple
 from typing import Optional
-from typing import Union
 
 from dataclasses import dataclass
 from functools import partial
 
-import jax
 import jax.numpy as jnp
 
-from jaxopt._src import loop
 from jaxopt._src import base
-from jaxopt._src import implicit_diff as idf
 from jaxopt._src.tree_util import tree_zeros_like, tree_add, tree_sub
-from jaxopt._src.tree_util import tree_add_scalar_mul, tree_scalar_mul
-from jaxopt._src.tree_util import tree_vdot, tree_negative, tree_l2_norm
+from jaxopt._src.tree_util import tree_l2_norm
 from jaxopt._src.linear_operator import _make_linear_operator
 import jaxopt._src.linear_solve as linear_solve
 

jaxopt/_src/lbfgs.py

@@ -17,7 +17,6 @@
 import warnings
 
 from dataclasses import dataclass
-from functools import partial
 from typing import Any, Callable, NamedTuple, Optional, Union
 
 import jax

jaxopt/_src/levenberg_marquardt.py

@@ -14,7 +14,6 @@
 
 """Levenberg-Marquardt algorithm in JAX."""
 
-import math
 from typing import Any
 from typing import Callable
 from typing import Literal
@@ -35,7 +34,7 @@
 from jaxopt._src.linear_solve import solve_inv
 from jaxopt._src.linear_solve import solve_lu
 from jaxopt._src.linear_solve import solve_qr
-from jaxopt._src.tree_util import tree_l2_norm, tree_inf_norm, tree_sub, tree_add, tree_mul
+from jaxopt._src.tree_util import tree_l2_norm, tree_inf_norm
 
 
 class LevenbergMarquardtState(NamedTuple):

jaxopt/_src/linear_operator.py

@@ -16,9 +16,8 @@
 import functools
 import jax
 import jax.numpy as jnp
-import numpy as onp
 
-from jaxopt.tree_util import tree_map, tree_sum, tree_mul
+from jaxopt.tree_util import tree_map
 
 
 class DenseLinearOperator:

jaxopt/_src/nonlinear_cg.py

@@ -25,7 +25,6 @@
 from jaxopt._src.linesearch_util import _setup_linesearch
 from jaxopt._src.tree_util import tree_single_dtype, get_real_dtype
 from jaxopt.tree_util import tree_add_scalar_mul
-from jaxopt.tree_util import tree_div
 from jaxopt.tree_util import tree_l2_norm
 from jaxopt.tree_util import tree_scalar_mul
 from jaxopt.tree_util import tree_sub

jaxopt/_src/osqp.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """GPU-friendly implementation of OSQP."""
-from abc import ABC, abstractmethod
+from abc import abstractmethod
 from dataclasses import dataclass
 from functools import partial
 
@@ -24,7 +24,6 @@
 from typing import Union
 
 import jax
-import jax.nn as nn
 import jax.numpy as jnp
 from jax.tree_util import tree_reduce
 

jaxopt/_src/scipy_wrappers.py

@@ -21,8 +21,6 @@
 #   currently only ScipyMinimize exposes this option.
 """
 
-import abc
-import dataclasses
 from dataclasses import dataclass
 from typing import Any
 from typing import Callable

jaxopt/_src/test_util.py

@@ -14,16 +14,13 @@
 
 """Test utilities."""
 
-from absl.testing import absltest
 from absl.testing import parameterized
 
 import functools
 
 import jax
 import jax.numpy as jnp
 
-from jaxopt._src import base
-from jaxopt._src import loss
 
 import numpy as onp
 import scipy as osp

jaxopt/_src/zoom_linesearch.py

@@ -34,7 +34,6 @@
 from jaxopt.tree_util import tree_scalar_mul
 from jaxopt.tree_util import tree_vdot_real
 from jaxopt.tree_util import tree_conj
-from jaxopt.tree_util import tree_l2_norm
 
 # pylint: disable=g-bare-generic
 # pylint: disable=invalid-name

tests/anderson_test.py

@@ -19,18 +19,14 @@
 import jax
 import jax.numpy as jnp
 from jax import scipy as jsp
-from jax.tree_util import tree_map, tree_all
 from jax.test_util import check_grads
 
 import jaxopt
-from jaxopt.tree_util import tree_l2_norm, tree_scalar_mul
-from jaxopt._src.tree_util import tree_average, tree_sub
-from jaxopt import objective
+from jaxopt.tree_util import tree_l2_norm
 from jaxopt import AndersonAcceleration
 from jaxopt._src import test_util
 
 import numpy as onp
-from sklearn import datasets
 
 
 class AndersonAccelerationTest(test_util.JaxoptTestCase):

tests/anderson_wrapper_test.py

@@ -14,31 +14,22 @@
 
 
 from absl.testing import absltest
-from absl.testing import parameterized
 
-import jax
 import jax.numpy as jnp
-from jax import config
-from jax.tree_util import tree_map, tree_all
 from jax.test_util import check_grads
 import optax
 
-from jaxopt.tree_util import tree_l2_norm, tree_scalar_mul, tree_sub
 from jaxopt import objective
 
-from jaxopt import projection
 from jaxopt import prox
 from jaxopt._src import test_util
 
 from jaxopt import AndersonWrapper
 from jaxopt import BlockCoordinateDescent
-from jaxopt import GradientDescent
 from jaxopt import OptaxSolver
 from jaxopt import PolyakSGD
 from jaxopt import ProximalGradient
 
-import numpy as onp
-import scipy
 from sklearn import datasets