metaopt · XuehaiPan · Nov 19, 2022 · Nov 18, 2022 · Nov 18, 2022 · Nov 18, 2022
diff --git a/.github/workflows/set_release.py b/.github/workflows/set_release.py
@@ -6,7 +6,7 @@
 
 VERSION_FILE = ROOT / 'torchopt' / 'version.py'
 
-VERSION_CONTENT = VERSION_FILE.read_text()
+VERSION_CONTENT = VERSION_FILE.read_text(encoding='UTF-8')
 
 VERSION_FILE.write_text(
     data=re.sub(

diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -13,6 +13,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- Add `nan_to_num` hook and gradient transformation by [@XuehaiPan](https://github.com/XuehaiPan) in [#119](https://github.com/metaopt/torchopt/pull/119).
 - Add matrix inversion linear solver with neumann series approximation by [@Benjamin-eecs](https://github.com/Benjamin-eecs) and [@XuehaiPan](https://github.com/XuehaiPan) in [#98](https://github.com/metaopt/torchopt/pull/98).
 - Add if condition of number of threads for CPU OPs by [@JieRen98](https://github.com/JieRen98) in [#105](https://github.com/metaopt/torchopt/pull/105).
 - Add implicit MAML omniglot few-shot classification example with OOP APIs by [@XuehaiPan](https://github.com/XuehaiPan) in [#107](https://github.com/metaopt/torchopt/pull/107).

diff --git a/docs/source/api/api.rst b/docs/source/api/api.rst
@@ -186,28 +186,32 @@ Optimizer Hooks
 
     register_hook
     zero_nan_hook
+    nan_to_num_hook
 
 Hook
 ~~~~
 
 .. autofunction:: register_hook
 .. autofunction:: zero_nan_hook
+.. autofunction:: nan_to_num_hook
 
 ------
 
 Gradient Transformation
 =======================
 
-.. currentmodule:: torchopt.clip
+.. currentmodule:: torchopt
 
 .. autosummary::
 
     clip_grad_norm
+    nan_to_num
 
 Transforms
 ~~~~~~~~~~
 
 .. autofunction:: clip_grad_norm
+.. autofunction:: nan_to_num
 
 Optimizer Schedules
 ===================

diff --git a/docs/source/spelling_wordlist.txt b/docs/source/spelling_wordlist.txt
@@ -93,3 +93,6 @@ Karush
 Kuhn
 Tucker
 Neumann
+num
+posinf
+neginf
diff --git a/torchopt/__init__.py b/torchopt/__init__.py
@@ -31,6 +31,7 @@
 from torchopt.alias import adam, adamw, rmsprop, sgd
 from torchopt.clip import clip_grad_norm
 from torchopt.combine import chain
+from torchopt.hook import register_hook
 from torchopt.optim import SGD, Adam, AdamW, Optimizer, RMSProp, RMSprop, meta
 from torchopt.optim.func import FuncOptimizer
 from torchopt.optim.meta import (
@@ -41,6 +42,7 @@
     MetaRMSprop,
     MetaSGD,
 )
+from torchopt.transform import nan_to_num
 from torchopt.update import apply_updates
 from torchopt.utils import (
     extract_state_dict,
@@ -60,6 +62,8 @@
     'rmsprop',
     'sgd',
     'clip_grad_norm',
+    'nan_to_num',
+    'register_hook',
     'chain',
     'Optimizer',
     'SGD',

diff --git a/torchopt/hook.py b/torchopt/hook.py
@@ -14,18 +14,32 @@
 # ==============================================================================
 """Hook utilities."""
 
+from typing import Callable, Optional
+
 import torch
 
 from torchopt import pytree
 from torchopt.base import EmptyState, GradientTransformation
 
 
-__all__ = ['zero_nan_hook', 'register_hook']
+__all__ = ['zero_nan_hook', 'nan_to_num_hook', 'register_hook']
 
 
 def zero_nan_hook(g: torch.Tensor) -> torch.Tensor:
-    """Registers a zero nan hook to replace nan with zero."""
-    return torch.where(torch.isnan(g), torch.zeros_like(g), g)
+    """A zero ``nan`` hook to replace ``nan`` with zero."""
+    return g.nan_to_num(nan=0.0)
+
+
+def nan_to_num_hook(
+    nan: float = 0.0, posinf: Optional[float] = None, neginf: Optional[float] = None
+) -> Callable[[torch.Tensor], torch.Tensor]:
+    """Returns a ``nan`` to num hook to replace ``nan`` / ``+inf`` / ``-inf`` with the given numbers."""
+
+    def hook(g: torch.Tensor) -> torch.Tensor:
+        """A hook to replace ``nan`` / ``+inf`` / ``-inf`` with the given numbers."""
+        return g.nan_to_num(nan=nan, posinf=posinf, neginf=neginf)
+
+    return hook
 
 
 def register_hook(hook) -> GradientTransformation:

diff --git a/torchopt/transform/__init__.py b/torchopt/transform/__init__.py
@@ -32,6 +32,7 @@
 """Preset transformations."""
 
 from torchopt.transform.add_decayed_weights import add_decayed_weights
+from torchopt.transform.nan_to_num import nan_to_num
 from torchopt.transform.scale import scale
 from torchopt.transform.scale_by_adam import scale_by_accelerated_adam, scale_by_adam
 from torchopt.transform.scale_by_rms import scale_by_rms
@@ -49,4 +50,5 @@
     'scale_by_accelerated_adam',
     'scale_by_rms',
     'scale_by_stddev',
+    'nan_to_num',
 ]
diff --git a/torchopt/transform/nan_to_num.py b/torchopt/transform/nan_to_num.py
@@ -0,0 +1,49 @@
+# Copyright 2022 MetaOPT Team. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# 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.
+# ==============================================================================
+"""Preset transformations that replaces updates with non-finite values to the given numbers."""
+
+from typing import Optional
+
+from torchopt import pytree
+from torchopt.base import EmptyState, GradientTransformation
+
+
+def nan_to_num(
+    nan: float = 0.0, posinf: Optional[float] = None, neginf: Optional[float] = None
+) -> GradientTransformation:
+    """Replaces updates with values ``nan`` / ``+inf`` / ``-inf`` to the given numbers.
+
+    Returns:
+        An ``(init_fn, update_fn)`` tuple.
+    """
+
+    def init_fn(params):  # pylint: disable=unused-argument
+        return EmptyState()
+
+    def update_fn(updates, state, *, params=None, inplace=True):  # pylint: disable=unused-argument
+        if inplace:
+
+            def f(g):
+                return g.nan_to_num_(nan=nan, posinf=posinf, neginf=neginf)
+
+        else:
+
+            def f(g):
+                return g.nan_to_num(nan=nan, posinf=posinf, neginf=neginf)
+
+        new_updates = pytree.tree_map(f, updates)
+        return new_updates, state
+
+    return GradientTransformation(init_fn, update_fn)
-Original file line number
+Diff line change
@@ Expand Up / @@ -93,3 +93,6 @@ Karush @@
     Kuhn
     Tucker
     Neumann
+    num
+    posinf
+    neginf