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33 lines
1.0 KiB
Python
33 lines
1.0 KiB
Python
import unittest
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from tinygrad.tensor import Tensor
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# stuff needed to unpack a kernel
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from tinygrad.ops import LazyOp, TernaryOps, BinaryOps, UnaryOps, ReduceOps, BufferOps, MemBuffer, ConstBuffer
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from tinygrad.lazy import LazyBuffer
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from tinygrad.helpers import dtypes
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from tinygrad.shape.shapetracker import ShapeTracker
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from tinygrad.shape.view import View
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from tinygrad.shape.symbolic import Variable
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import numpy as np
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import time
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inf, nan = float('inf'), float('nan')
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class TestLazyOp(unittest.TestCase):
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def test_lazyop_str(self):
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t = Tensor.rand(10) + Tensor.rand(10)
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s = t.lazydata.schedule()
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ast = s[-1].ast
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ast_remade = eval(str(ast))
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self.assertEqual(ast, ast_remade)
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def test_selfreferential_speed(self):
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st = time.monotonic()
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for i in range(25):
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p = LazyBuffer.fromCPU(np.array([1]))
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for _ in range(i): p = p.e(BinaryOps.ADD, p)
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# sanity check if caching works this should be way faster
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assert time.monotonic() -st < 0.5, f"{i}"
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if __name__ == '__main__':
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unittest.main()
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