Drop pylint for flake8 + fixes

Author: jbegaint

.flake8

@@ -0,0 +1,18 @@
+[flake8]
+ignore =
+    E203, # black and flake8 disagree on whitespace before ':'
+    E501, # line too long (> 79 characters)
+    W503, # black and flake8 disagree on how to place operators
+    F403, # 'from module import *' used; unable to detect undefined names
+
+per-file-ignores =
+	# imported but unused
+	__init__.py: F401
+
+max-line-length = 88
+
+# maximum McCabe complexity 
+max-complexity = 12
+
+exclude =
+	build

.gitlab-ci.yml

@@ -53,9 +53,9 @@ pylint:
   before_script:
     - python --version
     - pip install compressai --find-links=dist/
-    - pip install pylint
+    - pip install flake8 flake8-bugbear flake8-comprehensions
   script:
-    - pylint compressai examples
+    - make check-flake8
   tags:
     - docker
 

Makefile

@@ -15,7 +15,7 @@ help: ## Show this message
 
 
 # Check style and linting
-.PHONY: check-black check-isort check-mypy static-analysis
+.PHONY: check-black check-isort check-flake8 check-mypy static-analysis
 
 check-black: ## Run black checks
 	@echo "--> Running black checks"
@@ -25,11 +25,15 @@ check-isort: ## Run isort checks
 	@echo "--> Running isort checks"
 	@isort --check-only $(src_dirs)
 
+check-flake8: ## Run flake8 checks
+	@echo "--> Running flake8 checks"
+	@flake8 $(src_dirs)
+
 check-mypy: ## Run mypy checks
 	@echo "--> Running mypy checks"
 	@mypy
 
-static-analysis: check-black check-isort check-mypy ## Run all static checks
+static-analysis: check-black check-isort check-flake8 check-mypy ## Run all static checks
 
 
 # Apply styling

compressai/__init__.py

@@ -39,7 +39,7 @@ def set_entropy_coder(entropy_coder):
     Args:
         entropy_coder (string): Name of the entropy coder
     """
-    global _entropy_coder  # pylint: disable=W0603
+    global _entropy_coder
     if entropy_coder not in _available_entropy_coders:
         raise ValueError(
             f'Invalid entropy coder "{entropy_coder}", choose from'

compressai/entropy_models/entropy_models.py

@@ -10,12 +10,9 @@
 
 from torch import Tensor
 
-# isort: off; pylint: disable=E0611,E0401
 from compressai._CXX import pmf_to_quantized_cdf as _pmf_to_quantized_cdf
 from compressai.ops import LowerBound
 
-# isort: on; pylint: enable=E0611,E0401
-
 
 class _EntropyCoder:
     """Proxy class to an actual entropy coder class."""
@@ -33,12 +30,12 @@ def __init__(self, method):
             )
 
         if method == "ans":
-            from compressai import ans  # pylint: disable=E0611
+            from compressai import ans
 
             encoder = ans.RansEncoder()
             decoder = ans.RansDecoder()
         elif method == "rangecoder":
-            import range_coder  # pylint: disable=E0401
+            import range_coder
 
             encoder = range_coder.RangeEncoder()
             decoder = range_coder.RangeDecoder()
@@ -354,7 +351,7 @@ def _get_medians(self) -> Tensor:
     def update(self, force: bool = False) -> bool:
         # Check if we need to update the bottleneck parameters, the offsets are
         # only computed and stored when the conditonal model is update()'d.
-        if self._offset.numel() > 0 and not force:  # pylint: disable=E0203
+        if self._offset.numel() > 0 and not force:
             return False
 
         medians = self.quantiles[:, 0, 1]
@@ -580,7 +577,7 @@ def update_scale_table(self, scale_table, force=False):
         # updated.
         if self._offset.numel() > 0 and not force:
             return False
-        device = self.scale_table.device  # pylint: disable=E0203
+        device = self.scale_table.device
         self.scale_table = self._prepare_scale_table(scale_table).to(device)
         self.update()
         return True

compressai/layers/__init__.py

@@ -14,15 +14,3 @@
 
 from .gdn import *
 from .layers import *
-
-__all__ = [
-    "GDN",
-    "GDN1",
-    "AttentionBlock",
-    "MaskedConv2d",
-    "ResidualBlock",
-    "ResidualBlockUpsample",
-    "ResidualBlockWithStride",
-    "conv3x3",
-    "subpel_conv3x3",
-]

compressai/layers/gdn.py

@@ -20,6 +20,8 @@
 
 from compressai.ops.parametrizers import NonNegativeParametrizer
 
+__all__ = ["GDN", "GDN1"]
+
 
 class GDN(nn.Module):
     r"""Generalized Divisive Normalization layer.

compressai/layers/layers.py

@@ -21,6 +21,16 @@
 
 from .gdn import GDN
 
+__all__ = [
+    "AttentionBlock",
+    "MaskedConv2d",
+    "ResidualBlock",
+    "ResidualBlockUpsample",
+    "ResidualBlockWithStride",
+    "conv3x3",
+    "subpel_conv3x3",
+]
+
 
 class MaskedConv2d(nn.Conv2d):
     r"""Masked 2D convolution implementation, mask future "unseen" pixels.

compressai/models/priors.py

@@ -19,16 +19,12 @@
 import torch.nn as nn
 import torch.nn.functional as F
 
-# pylint: disable=E0611,E0401
 from compressai.ans import BufferedRansEncoder, RansDecoder
 from compressai.entropy_models import EntropyBottleneck, GaussianConditional
 from compressai.layers import GDN, MaskedConv2d
 
 from .utils import conv, deconv, update_registered_buffers
 
-# pylint: enable=E0611,E0401
-
-
 __all__ = [
     "CompressionModel",
     "FactorizedPrior",
@@ -186,9 +182,7 @@ def decompress(self, strings, shape):
 SCALES_LEVELS = 64
 
 
-def get_scale_table(
-    min=SCALES_MIN, max=SCALES_MAX, levels=SCALES_LEVELS
-):  # pylint: disable=W0622
+def get_scale_table(min=SCALES_MIN, max=SCALES_MAX, levels=SCALES_LEVELS):
     return torch.exp(torch.linspace(math.log(min), math.log(max), levels))
 
 

compressai/utils/find_close/__main__.py

@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# pylint: disable=line-too-long
 """
 Find the closest codec quality parameter to reach a given metric (bpp, ms-ssim,
 or psnr).
@@ -21,7 +20,6 @@
     * :code:`python -m compressai.utils.find_close webp ~/picture.png 0.5 --metric bpp`
     * :code:`python -m compressai.utils.find_close jpeg ~/picture.png 35 --metric psnr --save`
 """
-# pylint: enable=line-too-long
 
 import argparse
 import sys
@@ -47,7 +45,7 @@ def get_codec_q_bounds(codec: Codec) -> Tuple[bool, int, int]:
         upper = 64
         rev = True
     else:
-        assert False, codec
+        raise ValueError(f"Invalid codec {codec}")
     return rev, lower, upper
 
 

compressai/utils/update_model/__main__.py

@@ -63,7 +63,7 @@ def load_checkpoint(filepath: Path) -> Dict[str, torch.Tensor]:
 
 
 description = """
-Export a trained model to a new checkpoint with an updated CDFs parameters and a 
+Export a trained model to a new checkpoint with an updated CDFs parameters and a
 hash prefix, so that it can be loaded later via `load_state_dict_from_url`.
 """.strip()
 

compressai/zoo/__init__.py

@@ -12,7 +12,14 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from .image import *
+from .image import (
+    bmshj2018_factorized,
+    bmshj2018_hyperprior,
+    cheng2020_anchor,
+    cheng2020_attn,
+    mbt2018,
+    mbt2018_mean,
+)
 from .pretrained import load_pretrained as load_state_dict
 
 models = {

examples/train.py

@@ -82,16 +82,16 @@ def configure_optimizers(net, args):
     """Separate parameters for the main optimizer and the auxiliary optimizer.
     Return two optimizers"""
 
-    parameters = set(
+    parameters = {
         n
         for n, p in net.named_parameters()
         if not n.endswith(".quantiles") and p.requires_grad
-    )
-    aux_parameters = set(
+    }
+    aux_parameters = {
         n
         for n, p in net.named_parameters()
         if n.endswith(".quantiles") and p.requires_grad
-    )
+    }
 
     # Make sure we don't have an intersection of parameters
     params_dict = dict(net.named_parameters())
@@ -102,11 +102,11 @@ def configure_optimizers(net, args):
     assert len(union_params) - len(params_dict.keys()) == 0
 
     optimizer = optim.Adam(
-        (params_dict[n] for n in sorted(list(parameters))),
+        (params_dict[n] for n in sorted(parameters)),
         lr=args.learning_rate,
     )
     aux_optimizer = optim.Adam(
-        (params_dict[n] for n in sorted(list(aux_parameters))),
+        (params_dict[n] for n in sorted(aux_parameters)),
         lr=args.aux_learning_rate,
     )
     return optimizer, aux_optimizer

mypy.ini

@@ -29,3 +29,6 @@ ignore_missing_imports = True
 
 [mypy-scipy.*]
 ignore_missing_imports = True
+
+[mypy-numpy.*]
+ignore_missing_imports = True

pyproject.toml

@@ -29,16 +29,6 @@ line_length = 88
 known_third_party = "PIL,pytorch_msssim,torchvision,torch"
 skip_gitignore = true
 
-[tool.pylint.messages_control]
-disable = "C0330,C0326,bad-continuation,C0103,C0304,W0221,R0902,R0914,C0114,W0511,C0116,W0201,C0415,R0401,R0201,R0913,R0903,R0801"
-
-[tool.pylint.format]
-max-line-length = "88"
-
-[tool.pylint.typecheck]
-ignored-modules = "torch"
-extension-pkg-whitelist = "compressai.ans,compressai._cxx,range_coder"
-
 [tool.pytest.ini_options]
 markers = [
     "pretrained: download and check pretrained models (slow, deselect with '-m \"not pretrained\"')",

setup.py

@@ -84,7 +84,9 @@ def get_extensions():
 
 TEST_REQUIRES = ["pytest", "pytest-cov"]
 DEV_REQUIRES = TEST_REQUIRES + [
-    "pylint",
+    "flake8",
+    "flake8-bugbear",
+    "flake8-comprehensions",
     "black",
     "isort",
 ]

tests/test_bench_codec.py

@@ -61,7 +61,7 @@ def test_bench_codec(capsys, codec):
     assert expected["name"] == output["name"]
 
     for key in ("psnr", "ms-ssim", "bpp"):
-        if not key in expected["results"]:
+        if key not in expected["results"]:
             continue
         assert np.allclose(
             expected["results"][key], output["results"][key], rtol=1e-5, atol=1e-5

tests/test_entropy_models.py

@@ -22,7 +22,6 @@
     EntropyModel,
     GaussianConditional,
 )
-from compressai.models.priors import FactorizedPrior
 from compressai.zoo import bmshj2018_factorized, bmshj2018_hyperprior
 
 
@@ -90,10 +89,10 @@ def test_forward(self, entropy_model):
 
     def test_invalid_coder(self):
         with pytest.raises(ValueError):
-            entropy_model = EntropyModel(entropy_coder="huffman")
+            EntropyModel(entropy_coder="huffman")
 
         with pytest.raises(ValueError):
-            entropy_model = EntropyModel(entropy_coder=0xFF)
+            EntropyModel(entropy_coder=0xFF)
 
     def test_invalid_inputs(self, entropy_model):
         with pytest.raises(TypeError):

tests/test_eval_model.py

@@ -101,7 +101,7 @@ def test_eval_model_pretrained(capsys, model, quality, metric, entropy_estimatio
         assert expected[key] == output[key]
 
     for key in ("psnr", "ms-ssim", "bpp"):
-        if not key in expected["results"]:
+        if key not in expected["results"]:
             continue
         assert np.allclose(
             expected["results"][key], output["results"][key], rtol=1e-5, atol=1e-5

tests/test_init.py

@@ -16,6 +16,8 @@
 def test_import_errors():
     import compressai
 
+    del compressai
+
 
 def test_version():
     from compressai.version import __version__

tests/test_scripting.py

@@ -43,4 +43,4 @@ def test_masked_conv_A(self):
         conv = MaskedConv2d(3, 3, 3, padding=1)
 
         with pytest.raises(RuntimeError):
-            m = torch.jit.script(conv)
+            torch.jit.script(conv)

tests/test_update_model.py

@@ -83,7 +83,7 @@ def test_valid_name(tmpdir):
     assert len(stdout) == 0
     assert len(stderr) == 0
 
-    files = sorted(list(Path(tmpdir).glob("*.pth.tar")))
+    files = sorted(Path(tmpdir).glob("*.pth.tar"))
     assert len(files) == 2
 
     assert files[0].name == "model.pth.tar"

tests/test_waseda.py

@@ -12,9 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pytest
-import torch
-
 from compressai.models.waseda import Cheng2020Anchor
 from compressai.zoo import cheng2020_anchor