Merge branch 'main' into fix-tree

.github/workflows/test.yml

@@ -11,25 +11,14 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.7", "3.8", "3.9", "3.10"]
+        python-version: ["3.8", "3.9", "3.10"]
         pytorch-version: ["1.4.0", "1.5.1", "1.6.0", "1.7.1", "1.8", "1.9", "1.10", "1.11", "1.12", "1.13", "2.0", "2.1"]
         include:
           - python-version: 3.11
             pytorch-version: 2.0
           - python-version: 3.11
             pytorch-version: 2.1
         exclude:
-          - python-version: 3.7
-            pytorch-version: 1.11
-          - python-version: 3.7
-            pytorch-version: 1.12
-          - python-version: 3.7
-            pytorch-version: 1.13
-          - python-version: 3.7
-            pytorch-version: 2.0
-          - python-version: 3.7
-            pytorch-version: 2.1
-
           - python-version: 3.9
             pytorch-version: 1.4.0
           - python-version: 3.9
@@ -63,12 +52,13 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        python -m pip install mypy pytest pytest-cov
+        python -m pip install pytest pytest-cov
         pip install torch==${{ matrix.pytorch-version }} torchvision transformers
         pip install compressai
     - name: mypy
       if: ${{ matrix.pytorch-version == '2.1' }}
       run: |
+        python -m pip install mypy==1.7.1
         mypy --install-types --non-interactive .
     - name: pytest
       if: ${{ matrix.pytorch-version == '2.1' }}
@@ -77,6 +67,6 @@ jobs:
     - name: pytest
       if: ${{ matrix.pytorch-version != '2.1' }}
       run: |
-        pytest --no-output -k "not test_eval_order_doesnt_matter and not test_google and not test_uninitialized_tensor and not test_input_size_half_precision and not test_recursive_with_missing_layers"
+        pytest --no-output -k "not test_eval_order_doesnt_matter and not test_google and not test_uninitialized_tensor and not test_input_size_half_precision and not test_recursive_with_missing_layers and not test_flan_t5_small"
     - name: codecov
       uses: codecov/codecov-action@v1

.pre-commit-config.yaml

@@ -1,45 +1,12 @@
 ci:
   skip: [mypy, pytest]
 repos:
-  - repo: https://github.com/asottile/pyupgrade
-    rev: v3.15.0
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.1.9
     hooks:
-    - id: pyupgrade
-      args: [--py38-plus]
-
-  - repo: https://github.com/hadialqattan/pycln
-    rev: v2.2.2
-    hooks:
-      - id: pycln
-        args: [--all]
-
-  - repo: https://github.com/PyCQA/isort
-    rev: 5.12.0
-    hooks:
-      - id: isort
-
-  - repo: https://github.com/psf/black-pre-commit-mirror
-    rev: 23.9.1
-    hooks:
-      - id: black
-        args: [-C]
-
-  - repo: https://github.com/PyCQA/flake8
-    rev: 6.1.0
-    hooks:
-      - id: flake8
-        additional_dependencies:
-          [
-            flake8-future-annotations,
-            flake8-bugbear,
-            flake8-comprehensions,
-          ]
-
-  - repo: https://github.com/PyCQA/pylint
-    rev: v3.0.1
-    hooks:
-      - id: pylint
-        args: ["--disable=import-error"]
+      - id: ruff
+        args: [ --fix ]
+      - id: ruff-format
 
   - repo: local
     hooks:

README.md

@@ -1,6 +1,6 @@
 # torchinfo
 
-[![Python 3.7+](https://img.shields.io/badge/python-3.7+-blue.svg)](https://www.python.org/downloads/release/python-370/)
+[![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/release/python-380/)
 [![PyPI version](https://badge.fury.io/py/torchinfo.svg)](https://badge.fury.io/py/torchinfo)
 [![Conda version](https://img.shields.io/conda/vn/conda-forge/torchinfo)](https://anaconda.org/conda-forge/torchinfo)
 [![Build Status](https://github.com/TylerYep/torchinfo/actions/workflows/test.yml/badge.svg)](https://github.com/TylerYep/torchinfo/actions/workflows/test.yml)
@@ -470,7 +470,7 @@ Estimated Total Size (MB): 0.00
 All issues and pull requests are much appreciated! If you are wondering how to build the project:
 
 - torchinfo is actively developed using the lastest version of Python.
-  - Changes should be backward compatible to Python 3.7, and will follow Python's End-of-Life guidance for old versions.
+  - Changes should be backward compatible to Python 3.8, and will follow Python's End-of-Life guidance for old versions.
   - Run `pip install -r requirements-dev.txt`. We use the latest versions of all dev packages.
   - Run `pre-commit install`.
   - To use auto-formatting tools, use `pre-commit run -a`.

profiler.py

@@ -2,10 +2,10 @@
 import pstats
 import random
 
-import torchvision  # type: ignore[import-untyped]  # pylint: disable=unused-import  # noqa: F401, E501
-from tqdm import trange  # pylint: disable=unused-import  # noqa: F401
+import torchvision  # type: ignore[import-untyped]  # noqa: F401
+from tqdm import trange  # noqa: F401
 
-from torchinfo import summary  # pylint: disable=unused-import  # noqa: F401
+from torchinfo import summary  # noqa: F401
 
 
 def profile() -> None:

requirements-dev.txt

@@ -1,10 +1,5 @@
-black
 codecov
-flake8
-isort
 mypy
-pycln
-pylint
 pytest
 pytest-cov
 pre-commit

ruff.toml

@@ -1,3 +1,4 @@
+target-version = "py38"
 select = ["ALL"]
 ignore = [
     "ANN101",  # Missing type annotation for `self` in method
@@ -12,17 +13,22 @@ ignore = [
 	"FBT001",  # Boolean positional arg in function definition
 	"FBT002",  # Boolean default value in function definition
 	"FBT003",  # Boolean positional value in function call
+	"FIX002",  # Line contains TODO
+	"ISC001",  # Isort
     "PLR0911", # Too many return statements (11 > 6)
 	"PLR2004", # Magic value used in comparison, consider replacing 2 with a constant variable
     "PLR0912", # Too many branches
 	"PLR0913", # Too many arguments to function call
 	"PLR0915", # Too many statements
-	"PTH123",  # `open()` should be replaced by `Path.open()`
 	"S101",    # Use of `assert` detected
 	"S311",    # Standard pseudo-random generators are not suitable for cryptographic purposes
 	"T201",    # print() found
+	"T203",    # pprint() found
 	"TCH001",  # Move application import into a type-checking block
     "TCH003",  # Move standard library import into a type-checking block
+	"TD002",   # Missing author in TODO; try: `# TODO(<author_name>): ...`
+	"TD003",   # Missing issue link on the line following this TODO
+	"TD005",   # Missing issue description after `TODO`
 	"TRY003",  # Avoid specifying long messages outside the exception class
 
 	# torchinfo-specific ignores
@@ -38,8 +44,7 @@ ignore = [
     "TRY004",  # Prefer `TypeError` exception for invalid type
     "TRY301",  # Abstract `raise` to an inner function
 ]
-target-version = "py37"
-exclude = ["tests"]
+exclude = ["tests"]  # TODO: check tests too
 
 [flake8-pytest-style]
 fixture-parentheses = false

setup.cfg

@@ -25,45 +25,15 @@ keywords = torch pytorch torchsummary torch-summary summary keras deep-learning
 
 [options]
 packages = torchinfo
-python_requires = >=3.7
+python_requires = >=3.8
 include_package_data = True
 
 [options.package_data]
 torchinfo = py.typed
 
 [mypy]
 strict = True
-implicit_reexport = True
+warn_unreachable = True
+disallow_any_unimported = True
+extra_checks = True
 enable_error_code = ignore-without-code
-
-[pylint.main]
-evaluation = 10.0 - ((float(5 * error + warning + refactor + convention + info) / statement) * 10)
-
-[pylint.MESSAGES CONTROL]
-extension-pkg-whitelist = torch
-enable =
-    useless-suppression,
-    deprecated-pragma,
-    use-symbolic-message-instead,
-disable =
-    missing-module-docstring,
-    missing-function-docstring,
-    too-many-instance-attributes,
-    too-many-arguments,
-    too-many-branches,
-    too-many-locals,
-    invalid-name,
-    line-too-long,  # Covered by flake8
-    no-member,
-    fixme,
-    duplicate-code,
-
-[isort]
-profile = black
-
-[flake8]
-max-line-length = 88
-extend-ignore = E203,F401
-
-[tool:pytest]
-python_files = *_test.py

tests/conftest.py

@@ -6,7 +6,8 @@
 import pytest
 
 from torchinfo import ModelStatistics
-from torchinfo.formatting import HEADER_TITLES, ColumnSettings
+from torchinfo.enums import ColumnSettings
+from torchinfo.formatting import HEADER_TITLES
 from torchinfo.torchinfo import clear_cached_forward_pass
 
 

tests/fixtures/genotype.py

@@ -1,5 +1,4 @@
 # type: ignore
-# pylint: skip-file
 from collections import namedtuple
 
 import torch

tests/fixtures/models.py

@@ -1,4 +1,3 @@
-# pylint: disable=too-few-public-methods
 from __future__ import annotations
 
 import math
@@ -180,7 +179,7 @@ def __init__(self) -> None:
         self.weights = torch.nn.ParameterList(
             [
                 torch.nn.Parameter(weight)
-                for weight in torch.Tensor(100, 300).split([100, 200], dim=1)  # type: ignore[no-untyped-call] # noqa: E501
+                for weight in torch.Tensor(100, 300).split([100, 200], dim=1)  # type: ignore[no-untyped-call]
             ]
         )
 
@@ -303,7 +302,7 @@ def __init__(self) -> None:
         self.constant = 5
 
     def forward(self, x: dict[int, torch.Tensor], scale_factor: int) -> torch.Tensor:
-        return scale_factor * (x[256] + x[512][0]) * self.constant
+        return cast(torch.Tensor, scale_factor * (x[256] + x[512][0]) * self.constant)
 
 
 class ModuleDictModel(nn.Module):
@@ -359,7 +358,7 @@ def __int__(self) -> IntWithGetitem:
         return self
 
     def __getitem__(self, val: int) -> torch.Tensor:
-        return self.tensor * val
+        return cast(torch.Tensor, self.tensor * val)
 
 
 class EdgecaseInputOutputModel(nn.Module):
@@ -576,7 +575,7 @@ def __init__(self) -> None:
         self.b = nn.Parameter(torch.empty(10), requires_grad=False)
 
     def forward(self, x: torch.Tensor) -> torch.Tensor:
-        return self.w * x + self.b
+        return cast(torch.Tensor, self.w * x + self.b)
 
 
 class MixedTrainable(nn.Module):
@@ -718,7 +717,7 @@ def __init__(
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         h = torch.mm(x, self.a) + self.b
         if self.output_dim is None:
-            return h
+            return cast(torch.Tensor, h)
         return cast(torch.Tensor, self.fc2(h))
 
 

tests/fixtures/tmva_net.py

@@ -1,8 +1,7 @@
 # type: ignore
-# pylint: skip-file
 import torch
-import torch.nn as nn
 import torch.nn.functional as F
+from torch import nn
 
 
 class DoubleConvBlock(nn.Module):

tests/torchinfo_test.py

@@ -558,14 +558,14 @@ def test_empty_module_list() -> None:
 
 
 def test_single_parameter_model() -> None:
-    class ParameterA(nn.Module):  # pylint: disable=too-few-public-methods
+    class ParameterA(nn.Module):
         """A model with one parameter."""
 
         def __init__(self) -> None:
             super().__init__()
             self.w = nn.Parameter(torch.zeros(1024))
 
-    class ParameterB(nn.Module):  # pylint: disable=too-few-public-methods
+    class ParameterB(nn.Module):
         """A model with one parameter and one Conv2d layer."""
 
         def __init__(self) -> None:

torchinfo/enums.py

@@ -7,6 +7,8 @@
 class Mode(str, Enum):
     """Enum containing all model modes."""
 
+    __slots__ = ()
+
     TRAIN = "train"
     EVAL = "eval"
 
@@ -15,6 +17,8 @@ class Mode(str, Enum):
 class RowSettings(str, Enum):
     """Enum containing all available row settings."""
 
+    __slots__ = ()
+
     DEPTH = "depth"
     VAR_NAMES = "var_names"
     ASCII_ONLY = "ascii_only"
@@ -25,6 +29,8 @@ class RowSettings(str, Enum):
 class ColumnSettings(str, Enum):
     """Enum containing all available column settings."""
 
+    __slots__ = ()
+
     KERNEL_SIZE = "kernel_size"
     INPUT_SIZE = "input_size"
     OUTPUT_SIZE = "output_size"
@@ -38,6 +44,8 @@ class ColumnSettings(str, Enum):
 class Units(str, Enum):
     """Enum containing all available bytes units."""
 
+    __slots__ = ()
+
     AUTO = "auto"
     MEGABYTES = "M"
     GIGABYTES = "G"

torchinfo/layer_info.py

@@ -86,7 +86,7 @@ def trainable(self) -> str:
 
     @staticmethod
     def calculate_size(
-        inputs: DETECTED_INPUT_OUTPUT_TYPES, batch_dim: int | None
+        inputs: DETECTED_INPUT_OUTPUT_TYPES | None, batch_dim: int | None
     ) -> tuple[list[int], int]:
         """
         Set input_size or output_size using the model's inputs.