[pre-commit.ci] pre-commit autoupdate (#118)

* [pre-commit.ci] pre-commit autoupdate

updates:
- [github.com/pre-commit/pre-commit-hooks: v4.1.0 → v4.3.0](pre-commit/pre-commit-hooks@v4.1.0...v4.3.0)
- [github.com/PyCQA/flake8: 4.0.1 → 5.0.4](PyCQA/flake8@4.0.1...5.0.4)
- [github.com/psf/black: 21.12b0 → 22.6.0](psf/black@21.12b0...22.6.0)
- [github.com/pre-commit/mirrors-prettier: v2.5.1 → v2.7.1](pre-commit/mirrors-prettier@v2.5.1...v2.7.1)

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: pre-commit-ci[bot]

.pre-commit-config.yaml

@@ -3,7 +3,7 @@ default_language_version:
 
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.1.0
+    rev: v4.3.0
     hooks:
       # list of supported hooks: https://pre-commit.com/hooks.html
       - id: trailing-whitespace
@@ -24,7 +24,7 @@ repos:
             "satflow",
           ]
   - repo: https://github.com/PyCQA/flake8
-    rev: 4.0.1
+    rev: 5.0.4
     hooks:
       - id: flake8
         args:
@@ -42,14 +42,14 @@ repos:
       - id: isort
         args: [--profile, black, --line-length, "100", "satflow"]
   - repo: https://github.com/psf/black
-    rev: 21.12b0
+    rev: 22.6.0
     hooks:
       - id: black
         args: [--line-length, "100"]
 
   # yaml formatting
   - repo: https://github.com/pre-commit/mirrors-prettier
-    rev: v2.5.1
+    rev: v2.7.1
     hooks:
       - id: prettier
         types: [yaml]

satflow/models/gan/discriminators.py

@@ -170,7 +170,7 @@ def __init__(
         nf_mult_prev = 1
         for n in range(1, n_layers):  # gradually increase the number of filters
             nf_mult_prev = nf_mult
-            nf_mult = min(2 ** n, 8)
+            nf_mult = min(2**n, 8)
             if conv_type == "antialiased":
                 block = [
                     conv2d(
@@ -201,7 +201,7 @@ def __init__(
             sequence += block
 
         nf_mult_prev = nf_mult
-        nf_mult = min(2 ** n_layers, 8)
+        nf_mult = min(2**n_layers, 8)
         sequence += [
             conv2d(
                 ndf * nf_mult_prev,

satflow/models/gan/generators.py

@@ -113,7 +113,7 @@ def __init__(
 
         n_downsampling = 2
         for i in range(n_downsampling):  # add downsampling layers
-            mult = 2 ** i
+            mult = 2**i
             if conv_type == "antialiased":
                 block = [
                     conv2d(
@@ -144,7 +144,7 @@ def __init__(
 
             model += block
 
-        mult = 2 ** n_downsampling
+        mult = 2**n_downsampling
         for i in range(n_blocks):  # add ResNet blocks
 
             model += [

satflow/models/layers/Attention.py

@@ -122,7 +122,7 @@ def __init__(self, in_dim, activation=F.relu, pooling_factor=2):  # TODO for bet
         self.value_conv = nn.Conv3d(in_channels=in_dim, out_channels=in_dim, kernel_size=1)
 
         self.pooling = nn.MaxPool3d(kernel_size=2, stride=pooling_factor)
-        self.pooling_factor = pooling_factor ** 3
+        self.pooling_factor = pooling_factor**3
 
         self.gamma = nn.Parameter(torch.zeros(1))
 

satflow/models/layers/Discriminator.py

@@ -168,7 +168,7 @@ def __init__(
     ):
         super().__init__()
 
-        gain = 2 ** 0.5
+        gain = 2**0.5
 
         self.conv0 = SpectralNorm(
             nn.Conv2d(
@@ -329,7 +329,7 @@ def __init__(
     ):
         super().__init__()
 
-        gain = 2 ** 0.5
+        gain = 2**0.5
 
         self.conv0 = SpectralNorm(
             nn.Conv3d(
@@ -393,7 +393,7 @@ class TemporalDiscriminator(nn.Module):
     def __init__(self, chn=128, n_class=4):
         super().__init__()
 
-        gain = 2 ** 0.5
+        gain = 2**0.5
 
         self.pre_conv = nn.Sequential(
             SpectralNorm(nn.Conv3d(3, 2 * chn, 3, padding=1)),