[FIX | FMT] RTD build, apply latest black and isort, remove cover…

…alls (#323)

* [DOC] Fix RTD build

* [FMT] Apply `black==24.2.0`

* [DEL] Remove coveralls upload

.github/workflows/test.yaml

@@ -46,10 +46,3 @@ jobs:
       if: contains('refs/heads/master refs/heads/development refs/heads/release', github.ref) != 1
       run: |
         make test-light
-
-    - name: Test coveralls - python ${{ matrix.python-version }}
-      run: coveralls --service=github
-      env:
-        GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        flag-name: run-${{ matrix.python-version }}
-        parallel: true

.readthedocs.yml

@@ -6,10 +6,14 @@ version: 2
 sphinx:
   configuration: docs_src/rtd/conf.py
 
+build:
+  os: ubuntu-22.04
+  tools:
+    python: "3.8"
+
 python:
-  version: "3.8"
   install:
-    - method: pip
-      path: .
-      extra_requirements:
-        - docs
+  - method: pip
+    path: .
+    extra_requirements:
+      - docs

backpack/__init__.py

@@ -1,4 +1,5 @@
 """BackPACK."""
+
 from inspect import isclass
 from types import TracebackType
 from typing import Callable, Optional, Tuple, Type, Union

backpack/context.py

@@ -1,4 +1,5 @@
 """Context class for BackPACK."""
+
 from typing import Callable, Iterable, List, Tuple, Type
 
 from torch.nn import Module

backpack/core/derivatives/adaptive_avg_pool_nd.py

@@ -1,4 +1,5 @@
 """Implements the derivatives for AdaptiveAvgPool."""
+
 from typing import List, Tuple, Union
 from warnings import warn
 

backpack/core/derivatives/avgpoolnd.py

@@ -3,6 +3,7 @@
 Average pooling can be expressed as convolution over grouped channels with a constant
 kernel.
 """
+
 from typing import Any, List, Tuple
 
 from einops import rearrange

backpack/core/derivatives/basederivatives.py

@@ -1,4 +1,5 @@
 """Base classes for more flexible Jacobians and second-order information."""
+
 import warnings
 from abc import ABC
 from typing import Callable, List, Tuple

backpack/core/derivatives/batchnorm_nd.py

@@ -1,4 +1,5 @@
 """Contains derivatives for BatchNorm."""
+
 from typing import List, Tuple, Union
 
 from torch import Size, Tensor, einsum

backpack/core/derivatives/conv_transposend.py

@@ -1,4 +1,5 @@
 """Partial derivatives for ``torch.nn.ConvTranspose{1,2,3}d``."""
+
 from typing import List, Tuple, Union
 
 from einops import rearrange

backpack/core/derivatives/crossentropyloss.py

@@ -1,4 +1,5 @@
 """Partial derivatives for cross-entropy loss."""
+
 from math import sqrt
 from typing import Callable, Dict, List, Tuple
 

backpack/core/derivatives/dropout.py

@@ -1,4 +1,5 @@
 """Partial derivatives for the dropout layer."""
+
 from typing import List, Tuple
 
 from torch import Tensor, eq, ones_like

backpack/core/derivatives/elu.py

@@ -1,4 +1,5 @@
 """Partial derivatives for the ELU activation function."""
+
 from typing import List, Tuple
 
 from torch import Tensor, exp, le, ones_like, zeros_like

backpack/core/derivatives/embedding.py

@@ -1,4 +1,5 @@
 """Derivatives for Embedding."""
+
 from typing import List, Tuple
 
 from torch import Tensor, einsum, zeros

backpack/core/derivatives/flatten.py

@@ -1,4 +1,5 @@
 """Partial derivatives of the flatten layer."""
+
 from typing import List, Tuple
 
 from torch import Tensor

backpack/core/derivatives/leakyrelu.py

@@ -1,4 +1,5 @@
 """Partial derivatives for the leaky ReLU layer."""
+
 from typing import List, Tuple
 
 from torch import Tensor, gt

backpack/core/derivatives/linear.py

@@ -1,4 +1,5 @@
 """Contains partial derivatives for the ``torch.nn.Linear`` layer."""
+
 from typing import List, Tuple
 
 from torch import Size, Tensor, einsum

backpack/core/derivatives/logsigmoid.py

@@ -1,4 +1,5 @@
 """Contains partial derivatives for the ``torch.nn.LogSigmoid`` layer."""
+
 from typing import List, Tuple
 
 from torch import Tensor, exp

backpack/core/derivatives/lstm.py

@@ -1,4 +1,5 @@
 """Partial derivatives for nn.LSTM."""
+
 from typing import List, Tuple
 
 from torch import Tensor, cat, einsum, sigmoid, tanh, zeros

backpack/core/derivatives/nll_base.py

@@ -1,4 +1,5 @@
 """Partial derivative bases for NLL losses."""
+
 from math import sqrt
 from typing import List, Tuple
 

backpack/core/derivatives/permute.py

@@ -1,4 +1,5 @@
 """Module containing derivatives of Permute."""
+
 from typing import List, Tuple
 
 from torch import Tensor, argsort

backpack/core/derivatives/relu.py

@@ -1,4 +1,5 @@
 """Partial derivatives for the ReLU activation function."""
+
 from typing import List, Tuple
 
 from torch import Tensor, gt

backpack/core/derivatives/rnn.py

@@ -1,4 +1,5 @@
 """Partial derivatives for the torch.nn.RNN layer."""
+
 from typing import List, Tuple
 
 from torch import Tensor, cat, einsum, zeros

backpack/core/derivatives/scale_module.py

@@ -1,4 +1,5 @@
 """Derivatives of ScaleModule (implies Identity)."""
+
 from typing import List, Tuple, Union
 
 from torch import Tensor

backpack/core/derivatives/selu.py

@@ -1,4 +1,5 @@
 """Partial derivatives for the SELU activation function."""
+
 from typing import List, Tuple
 
 from torch import Tensor, exp, le, ones_like, zeros_like

backpack/core/derivatives/shape_check.py

@@ -2,6 +2,7 @@
 
 Helpers to check input and output sizes of Jacobian-matrix products.
 """
+
 import functools
 from typing import Any, Callable
 

backpack/core/derivatives/sigmoid.py

@@ -1,4 +1,5 @@
 """Partial derivatives for the Sigmoid activation function."""
+
 from typing import List, Tuple
 
 from torch import Tensor

backpack/core/derivatives/slicing.py

@@ -1,4 +1,5 @@
 """Contains derivatives of slicing operation."""
+
 from typing import List, Tuple
 
 from torch import Tensor, zeros

backpack/core/derivatives/sum_module.py

@@ -1,4 +1,5 @@
 """Contains derivatives for SumModule."""
+
 from typing import List, Tuple
 
 from torch import Tensor

backpack/core/derivatives/tanh.py

@@ -1,4 +1,5 @@
 """Partial derivatives for the Tanh activation function."""
+
 from typing import List, Tuple
 
 from torch import Tensor

backpack/core/derivatives/zeropad2d.py

@@ -1,4 +1,5 @@
 """Partial derivatives for the ZeroPad2d function."""
+
 from typing import List, Tuple
 
 from einops import rearrange

backpack/custom_module/branching.py

@@ -1,4 +1,5 @@
 """Emulating branching with modules."""
+
 from typing import Any, OrderedDict, Tuple, Union
 
 from torch import Tensor

backpack/custom_module/graph_utils.py

@@ -1,4 +1,5 @@
 """Transformation tools to make graph BackPACK compatible."""
+
 from copy import deepcopy
 from typing import Tuple, Union
 from warnings import warn

backpack/custom_module/permute.py

@@ -1,4 +1,5 @@
 """Module containing Permute module."""
+
 from typing import Any
 
 from torch import Tensor

backpack/custom_module/reduce_tuple.py

@@ -1,4 +1,5 @@
 """Module containing ReduceTuple module."""
+
 from typing import Union
 
 from torch import Tensor

backpack/custom_module/scale_module.py

@@ -1,4 +1,5 @@
 """Contains ScaleModule."""
+
 from torch import Tensor
 from torch.nn import Module
 

backpack/extensions/backprop_extension.py

@@ -1,4 +1,5 @@
 """Implements the backpropagation mechanism."""
+
 from __future__ import annotations
 
 import abc

backpack/extensions/curvmatprod/__init__.py

@@ -20,7 +20,6 @@
   by Felix Dangel, Stefan Harmeling, Philipp Hennig, 2020.
 """
 
-
 from .ggnmp import GGNMP
 from .hmp import HMP
 from .pchmp import PCHMP

backpack/extensions/firstorder/base.py

@@ -1,4 +1,5 @@
 """Base class for first order extensions."""
+
 from typing import Dict, List, Type
 
 from torch.nn import Module

backpack/extensions/firstorder/batch_grad/__init__.py

@@ -2,6 +2,7 @@
 
 It defines the module extension for each module.
 """
+
 from typing import List
 
 from torch.nn import (

backpack/extensions/firstorder/batch_grad/batch_grad_base.py

@@ -1,4 +1,5 @@
 """Calculates the batch_grad derivative."""
+
 from __future__ import annotations
 
 from typing import TYPE_CHECKING, Callable, List, Tuple

backpack/extensions/firstorder/batch_grad/batchnorm_nd.py

@@ -1,4 +1,5 @@
 """Contains grad_batch extension for BatchNorm."""
+
 from typing import Tuple, Union
 
 from torch import Tensor

backpack/extensions/firstorder/batch_grad/embedding.py

@@ -1,4 +1,5 @@
 """BatchGrad extension for Embedding."""
+
 from backpack.core.derivatives.embedding import EmbeddingDerivatives
 from backpack.extensions.firstorder.batch_grad.batch_grad_base import BatchGradBase
 

backpack/extensions/firstorder/batch_grad/rnn.py

@@ -1,4 +1,5 @@
 """Contains BatchGradRNN."""
+
 from backpack.core.derivatives.lstm import LSTMDerivatives
 from backpack.core.derivatives.rnn import RNNDerivatives
 from backpack.extensions.firstorder.batch_grad.batch_grad_base import BatchGradBase

backpack/extensions/firstorder/batch_l2_grad/__init__.py

@@ -3,6 +3,7 @@
 Defines the backpropagation extension.
 Within it, define the extension for each module.
 """
+
 from torch.nn import (
     LSTM,
     RNN,

backpack/extensions/firstorder/batch_l2_grad/batch_l2_base.py

@@ -1,4 +1,5 @@
 """Contains Base class for batch_l2_grad."""
+
 from __future__ import annotations
 
 from typing import TYPE_CHECKING, Callable, List, Tuple

backpack/extensions/firstorder/batch_l2_grad/batchnorm_nd.py

@@ -1,4 +1,5 @@
 """Contains batch_l2 extension for BatchNorm."""
+
 from typing import Tuple, Union
 
 from torch import Tensor

backpack/extensions/firstorder/batch_l2_grad/convnd.py

@@ -1,4 +1,5 @@
 """batch_l2 extension for Conv."""
+
 from torch import einsum
 
 from backpack.core.derivatives.conv1d import Conv1DDerivatives

backpack/extensions/firstorder/batch_l2_grad/convtransposend.py

@@ -1,4 +1,5 @@
 """batch_l2 extension for ConvTranspose."""
+
 from torch import einsum
 
 from backpack.core.derivatives.conv_transpose1d import ConvTranspose1DDerivatives

backpack/extensions/firstorder/batch_l2_grad/embedding.py

@@ -1,4 +1,5 @@
 """BatchL2 extension for Embedding."""
+
 from backpack.core.derivatives.embedding import EmbeddingDerivatives
 from backpack.extensions.firstorder.batch_l2_grad.batch_l2_base import BatchL2Base
 

backpack/extensions/firstorder/batch_l2_grad/linear.py

@@ -1,4 +1,5 @@
 """Contains batch_l2 extension for Linear."""
+
 from __future__ import annotations
 
 from typing import TYPE_CHECKING, Tuple

backpack/extensions/firstorder/batch_l2_grad/rnn.py

@@ -1,4 +1,5 @@
 """Contains BatchL2RNN."""
+
 from backpack.core.derivatives.lstm import LSTMDerivatives
 from backpack.core.derivatives.rnn import RNNDerivatives
 from backpack.extensions.firstorder.batch_l2_grad.batch_l2_base import BatchL2Base

backpack/extensions/firstorder/gradient/__init__.py

@@ -2,4 +2,5 @@
 
 It calculates the same result as torch backward().
 """
+
 # TODO: Rewrite variance to not need this extension

backpack/extensions/firstorder/gradient/base.py

@@ -1,4 +1,5 @@
 """Calculates the gradient."""
+
 from backpack.extensions.firstorder.base import FirstOrderModuleExtension
 
 

backpack/extensions/firstorder/gradient/batchnorm_nd.py

@@ -1,4 +1,5 @@
 """Gradient extension for BatchNorm."""
+
 from typing import Tuple, Union
 
 from torch import Tensor

backpack/extensions/firstorder/gradient/embedding.py

@@ -1,4 +1,5 @@
 """Gradient extension for Embedding."""
+
 from backpack.core.derivatives.embedding import EmbeddingDerivatives
 from backpack.extensions.firstorder.gradient.base import GradBaseModule
 

backpack/extensions/firstorder/gradient/rnn.py

@@ -1,4 +1,5 @@
 """Contains GradRNN."""
+
 from backpack.core.derivatives.lstm import LSTMDerivatives
 from backpack.core.derivatives.rnn import RNNDerivatives
 from backpack.extensions.firstorder.gradient.base import GradBaseModule

backpack/extensions/firstorder/sum_grad_squared/__init__.py

@@ -2,6 +2,7 @@
 
 Defines module extension for each module.
 """
+
 from torch.nn import (
     LSTM,
     RNN,

backpack/extensions/firstorder/sum_grad_squared/batchnorm_nd.py

@@ -1,4 +1,5 @@
 """SGS extension for BatchNorm."""
+
 from typing import Tuple, Union
 
 from torch import Tensor

backpack/extensions/firstorder/sum_grad_squared/embedding.py

@@ -1,4 +1,5 @@
 """SGS extension for Embedding."""
+
 from backpack.core.derivatives.embedding import EmbeddingDerivatives
 from backpack.extensions.firstorder.sum_grad_squared.sgs_base import SGSBase
 

backpack/extensions/firstorder/sum_grad_squared/rnn.py

@@ -1,4 +1,5 @@
 """Contains SGSRNN module."""
+
 from backpack.core.derivatives.lstm import LSTMDerivatives
 from backpack.core.derivatives.rnn import RNNDerivatives
 from backpack.extensions.firstorder.sum_grad_squared.sgs_base import SGSBase

backpack/extensions/firstorder/sum_grad_squared/sgs_base.py

@@ -1,4 +1,5 @@
 """Contains SGSBase, the base module for sum_grad_squared extension."""
+
 from __future__ import annotations
 
 from typing import TYPE_CHECKING, Callable, List, Tuple