mirror of
https://github.com/tinygrad/tinygrad.git
synced 2026-01-08 22:48:25 -05:00
remove pylint from pre-commit and CI (#12658)
* remove pylint from pre-commit and CI * multidevice test is fast * faster pre-commit * 8 is faster than 4 * better name * how did that typecheck?
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2
.github/workflows/test.yml
vendored
2
.github/workflows/test.yml
vendored
@@ -238,8 +238,6 @@ jobs:
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pip3 install --upgrade --force-reinstall ruff==0.11.0
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python3 -m ruff check .
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python3 -m ruff check examples/mlperf/ --ignore E501
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- name: Lint tinygrad with pylint
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run: python -m pylint tinygrad/
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- name: Run mypy
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run: |
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python -m mypy --strict-equality --lineprecision-report .
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@@ -20,21 +20,15 @@ repos:
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language: system
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always_run: true
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pass_filenames: false
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- id: tests
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name: subset of tests
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entry: env PYTHONPATH="." python3 -m pytest -n=4 test/test_ops.py test/test_dtype.py test/test_schedule.py test/test_assign.py
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language: system
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always_run: true
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pass_filenames: false
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- id: example
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name: multi device tests
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name: test all devices
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entry: python3 test/external/external_test_example.py
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language: system
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always_run: true
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pass_filenames: false
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- id: pylint
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name: pylint
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entry: python3 -m pylint tinygrad/
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- id: tests
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name: subset of tests
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entry: env PYTHONPATH="." python3 -m pytest -n=8 test/test_ops.py test/test_dtype.py test/test_schedule.py test/test_assign.py
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language: system
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always_run: true
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pass_filenames: false
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4
test/external/external_test_example.py
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4
test/external/external_test_example.py
vendored
@@ -58,8 +58,8 @@ class TestExample(unittest.TestCase):
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print(f"WARNING: {device} test isn't running")
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return
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x = Tensor.eye(64, device=device, requires_grad=True)
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y = Tensor.eye(64, device=device, requires_grad=True)
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x = Tensor.eye(8, device=device, requires_grad=True)
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y = Tensor.eye(8, device=device, requires_grad=True)
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z = y.matmul(x).sum()
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z.backward()
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@@ -134,8 +134,8 @@ class TestTiny(unittest.TestCase):
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def test_mnist_backward(self):
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# NOTE: we don't have the whole model here for speed
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layers = [
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nn.Conv2d(1, 32, 5), Tensor.relu,
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nn.Conv2d(32, 32, 5), Tensor.relu]
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nn.Conv2d(1, 8, 5), Tensor.relu,
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nn.Conv2d(8, 8, 5), Tensor.relu]
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# replace random weights with ones
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# TODO: there's a bug here where it's tying two of the biases together. we need UNIQUE const
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@@ -144,7 +144,7 @@ class TestTiny(unittest.TestCase):
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# realize gradients
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for x in nn.state.get_parameters(layers): x.requires_grad_()
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Tensor.empty(4, 1, 28, 28).sequential(layers).sum().backward()
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Tensor.empty(4, 1, 14, 14).sequential(layers).sum().backward()
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Tensor.realize(*[x.grad for x in nn.state.get_parameters(layers) if x.grad is not None])
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# *** image ***
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@@ -7,7 +7,7 @@ from tinygrad.uop.ops import Ops, UOp, sym_infer, sint, Variable, ssimplify, Gro
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from tinygrad.dtype import AddrSpace, PtrDType
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if TYPE_CHECKING:
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from tinygrad.codegen.opt.tc import TensorCore
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from tinygrad.codegen.opt.kernel import Opt
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from tinygrad.codegen.opt import Opt
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@dataclass(frozen=True)
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class Estimates:
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