Bump min JAX version to 0.4.16 + minor no-op linter fixes.

PiperOrigin-RevId: 589663637

Author: romanngg

neural_tangents/_src/batching.py

@@ -46,16 +46,20 @@
 import warnings
 
 import jax
+
 from jax import device_put
 from jax import devices
 from jax import jit
 from jax import pmap
 from jax import random
+
 import jax.numpy as jnp
+
 from jax.tree_util import tree_all
 from jax.tree_util import tree_flatten
 from jax.tree_util import tree_map
 from jax.tree_util import tree_unflatten
+
 import numpy as np
 
 from .utils import utils

neural_tangents/_src/empirical.py

@@ -116,16 +116,22 @@
 from jax import linear_transpose
 from jax import vjp
 from jax import vmap
+
 from jax.core import Jaxpr
 from jax.core import JaxprEqn
 from jax.core import Literal
 from jax.core import ShapedArray
 from jax.core import Value
 from jax.core import Var
+
+from jax.extend import linear_util as lu
+
 from jax.interpreters import ad
 from jax.interpreters.ad import UndefinedPrimal
 from jax.interpreters.ad import Zero
+
 import jax.numpy as jnp
+
 from jax.tree_util import tree_flatten
 from jax.tree_util import tree_map
 from jax.tree_util import tree_reduce
@@ -134,6 +140,7 @@
 from jax.tree_util import tree_unflatten
 from jax.util import safe_map as map
 from jax.util import safe_zip as zip
+
 import numpy as np
 
 from .utils import rules
@@ -146,12 +153,6 @@
 from .utils.typing import VMapAxes
 from .utils.typing import VMapAxisTriple
 
-try:
-  # jax >=0.4.16
-  from jax.extend import linear_util as lu
-except ImportError:
-  from jax import linear_util as lu
-
 
 # LINEARIZATION AND TAYLOR EXPANSION
 

neural_tangents/_src/monte_carlo.py

@@ -26,19 +26,34 @@
 kernel function is JITted internally.
 """
 
-
 from functools import partial
 import operator
 from typing import Generator, Iterable, Optional, Union
 
-from .batching import batch
-from .empirical import empirical_kernel_fn, NtkImplementation, DEFAULT_NTK_IMPLEMENTATION, _DEFAULT_NTK_FWD, _DEFAULT_NTK_S_RULES, _DEFAULT_NTK_J_RULES
 import jax
 from jax import random
 import jax.numpy as jnp
 from jax.tree_util import tree_map
+
+from .batching import batch
+
+from .empirical import _DEFAULT_NTK_FWD
+from .empirical import _DEFAULT_NTK_J_RULES
+from .empirical import _DEFAULT_NTK_S_RULES
+from .empirical import DEFAULT_NTK_IMPLEMENTATION
+from .empirical import empirical_kernel_fn
+from .empirical import NtkImplementation
+
 from .utils import utils
-from .utils.typing import ApplyFn, Axes, EmpiricalGetKernelFn, Get, InitFn, MonteCarloKernelFn, NTTree, PyTree, VMapAxes
+from .utils.typing import ApplyFn
+from .utils.typing import Axes
+from .utils.typing import EmpiricalGetKernelFn
+from .utils.typing import Get
+from .utils.typing import InitFn
+from .utils.typing import MonteCarloKernelFn
+from .utils.typing import NTTree
+from .utils.typing import PyTree
+from .utils.typing import VMapAxes
 
 
 def _sample_once_kernel_fn(

neural_tangents/_src/predict.py

@@ -27,21 +27,25 @@
   note that closed-form kernels currently only support a single `channel_axis`).
 """
 
-
 import collections
 from functools import lru_cache
-from typing import Callable, Generator, Iterable, NamedTuple, Optional, Any, Union, Protocol
+from typing import Any, Callable, Generator, Iterable, NamedTuple, Optional, Protocol, Union
 
 import jax
 from jax import grad
 from jax.experimental import ode
 import jax.numpy as jnp
 import jax.scipy as jsp
-from jax.tree_util import tree_all, tree_map
+from jax.tree_util import tree_all
+from jax.tree_util import tree_map
 import numpy as np
 import scipy as sp
-from .utils import dataclasses, utils
-from .utils.typing import Axes, Get, KernelFn
+
+from .utils import dataclasses
+from .utils import utils
+from .utils.typing import Axes
+from .utils.typing import Get
+from .utils.typing import KernelFn
 
 
 PyTree = Any

neural_tangents/_src/stax/branching.py

@@ -18,16 +18,19 @@
 several branches into one.
 """
 
-
 import functools
 from typing import Callable, Iterable, Optional, Sequence
 import warnings
 
 from jax import numpy as jnp
 import jax.example_libraries.stax as ostax
-from .requirements import layer, supports_masking
+
 from ..utils.kernel import Kernel
-from ..utils.typing import InternalLayer, InternalLayerMasked, Kernels
+from ..utils.typing import InternalLayer
+from ..utils.typing import InternalLayerMasked
+from ..utils.typing import Kernels
+from .requirements import layer
+from .requirements import supports_masking
 
 
 @layer

neural_tangents/_src/stax/combinators.py

@@ -20,11 +20,21 @@
 
 import frozendict
 import jax
-from jax import random, lax
+from jax import lax
+from jax import random
 import jax.example_libraries.stax as ostax
-from .requirements import Diagonal, get_req, layer, requires
+
 from ..utils.kernel import Kernel
-from ..utils.typing import InternalLayer, Layer, LayerKernelFn, NTTree, NTTrees, Shapes
+from ..utils.typing import InternalLayer
+from ..utils.typing import Layer
+from ..utils.typing import LayerKernelFn
+from ..utils.typing import NTTree
+from ..utils.typing import NTTrees
+from ..utils.typing import Shapes
+from .requirements import Diagonal
+from .requirements import get_req
+from .requirements import layer
+from .requirements import requires
 
 
 @layer

neural_tangents/_src/stax/elementwise.py

@@ -24,15 +24,24 @@
 import warnings
 
 import jax
-from jax import custom_jvp, grad, vmap
+from jax import custom_jvp
+from jax import grad
 from jax import numpy as jnp
+from jax import vmap
 from jax.scipy.special import erf
 import numpy as np
-from .requirements import Diagonal, get_diagonal, get_diagonal_outer_prods, layer, requires, supports_masking
 import scipy as sp
+
 from ..utils import utils
 from ..utils.kernel import Kernel
-from ..utils.typing import InternalLayer, LayerKernelFn
+from ..utils.typing import InternalLayer
+from ..utils.typing import LayerKernelFn
+from .requirements import Diagonal
+from .requirements import get_diagonal
+from .requirements import get_diagonal_outer_prods
+from .requirements import layer
+from .requirements import requires
+from .requirements import supports_masking
 
 
 @layer

neural_tangents/_src/stax/linear.py

@@ -22,18 +22,30 @@
 import warnings
 
 import jax
+from jax import eval_shape
 from jax import lax
 from jax import numpy as jnp
 from jax import ops
 from jax import random
-from jax import ShapeDtypeStruct, eval_shape, vmap
+from jax import ShapeDtypeStruct
+from jax import vmap
 from jax.core import ShapedArray
 import jax.example_libraries.stax as ostax
 import numpy as np
-from .requirements import Bool, Diagonal, get_diagonal_outer_prods, layer, mean_and_var, requires, supports_masking
+
 from ..utils import utils
 from ..utils.kernel import Kernel
-from ..utils.typing import Axes, InternalLayer, InternalLayerMasked, PyTree
+from ..utils.typing import Axes
+from ..utils.typing import InternalLayer
+from ..utils.typing import InternalLayerMasked
+from ..utils.typing import PyTree
+from .requirements import Bool
+from .requirements import Diagonal
+from .requirements import get_diagonal_outer_prods
+from .requirements import layer
+from .requirements import mean_and_var
+from .requirements import requires
+from .requirements import supports_masking
 
 
 # Enums

neural_tangents/_src/stax/requirements.py

@@ -14,23 +14,34 @@
 
 """Requirement management for :obj:`~neural_tangents.stax` layers."""
 
+import dataclasses
 import enum
 from typing import Callable, Optional, Sequence, Union
 import warnings
 
 import frozendict
 import jax
+from jax import eval_shape
 from jax import lax
 from jax import numpy as jnp
-from jax import eval_shape
 from jax.core import ShapedArray
-from jax.tree_util import tree_map, tree_all
-from ..utils import utils
-import dataclasses
+from jax.tree_util import tree_all
+from jax.tree_util import tree_map
+import numpy as np
+
 from ..utils import dataclasses as nt_dataclasses
+from ..utils import utils
 from ..utils.kernel import Kernel
-from ..utils.typing import AnalyticKernelFn, Axes, Get, InitFn, ApplyFn, InternalLayer, Layer, LayerKernelFn, NTTree, PyTree
-import numpy as np
+from ..utils.typing import AnalyticKernelFn
+from ..utils.typing import ApplyFn
+from ..utils.typing import Axes
+from ..utils.typing import Get
+from ..utils.typing import InitFn
+from ..utils.typing import InternalLayer
+from ..utils.typing import Layer
+from ..utils.typing import LayerKernelFn
+from ..utils.typing import NTTree
+from ..utils.typing import PyTree
 
 
 # Public decorators

neural_tangents/_src/utils/rules.py

@@ -14,18 +14,26 @@
 
 """Structured derivatives rules."""
 
-from .dataclasses import dataclass, field
 import functools
-from typing import Callable, Optional, Any, Union
+from typing import Any, Callable, Optional, Union
 
-from . import utils
 import jax
 from jax import lax
-from jax.core import JaxprEqn, ShapedArray, Primitive, Jaxpr, Var, AbstractValue, Literal
+from jax.core import AbstractValue
+from jax.core import Jaxpr
+from jax.core import JaxprEqn
+from jax.core import Literal
+from jax.core import Primitive
+from jax.core import ShapedArray
+from jax.core import Var
 from jax.interpreters import ad
 import jax.numpy as jnp
 import numpy as np
 
+from . import utils
+from .dataclasses import dataclass
+from .dataclasses import field
+
 
 # pytype: disable=wrong-keyword-args