mirror of https://github.com/commaai/tinygrad.git
93 lines
2.8 KiB
Python
93 lines
2.8 KiB
Python
import unittest, pickle
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import numpy as np
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from tinygrad import Tensor, TinyJit, Variable
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from tinygrad.engine.schedule import create_schedule
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class TestPickle(unittest.TestCase):
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def test_pickle_realized_tensor(self):
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t = Tensor.rand(10, 10).realize()
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st = pickle.dumps(t)
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t2:Tensor = pickle.loads(st)
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np.testing.assert_equal(t.numpy(), t2.numpy())
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def test_pickle_unrealized_tensor(self):
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t = Tensor.ones(10, 10)
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st = pickle.dumps(t)
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t2:Tensor = pickle.loads(st)
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np.testing.assert_equal(t.numpy(), t2.numpy())
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def test_pickle_variable(self):
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v = Variable("i", 1, 20).bind(10)
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t1 = Tensor.ones(10, v).contiguous()
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t2 = Tensor.ones(10, v).contiguous()
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ret = (t1+t2).sum(1)
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st = pickle.dumps(ret)
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del ret
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vt2 = pickle.loads(st)
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np.testing.assert_equal(vt2.numpy(), 20)
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def test_pickle_buffer_view(self):
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t = Tensor.arange(10, device="CLANG").contiguous().realize()
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vt = t[3:5].contiguous().realize()
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assert hasattr(vt.lazydata.buffer, 'base')
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ref_value = vt.tolist()
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st = pickle.dumps(vt)
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del t, vt
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vt2 = pickle.loads(st)
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assert hasattr(vt2.lazydata.buffer, 'base')
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assert ref_value == vt2.tolist()
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def test_pickle_numpy(self):
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t = Tensor(np.array([1,2,3,4.]))
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st = pickle.dumps(t)
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t2:Tensor = pickle.loads(st)
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np.testing.assert_equal(t.numpy(), t2.numpy())
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def test_pickle_jit(self):
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@TinyJit
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def add(a, b): return a.sum()+b+1
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for _ in range(3): add(Tensor.rand(10, 10), Tensor.rand(10, 10))
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st = pickle.dumps(add)
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del add
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add_fxn = pickle.loads(st)
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x = Tensor.ones(10, 10).contiguous().realize()
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y = Tensor.ones(10, 10).contiguous().realize()
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print("post jit")
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out = add_fxn(x, y)
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np.testing.assert_equal(out.numpy(), 102)
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def test_pickle_schedule(self):
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a = Tensor([1,2])
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out = a + 2
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sched = create_schedule([out.lazydata])
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pk = pickle.dumps(sched)
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sched_pk = pickle.loads(pk)
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assert sched_pk[-1].ast == sched[-1].ast
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class TestPickleJIT(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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@TinyJit
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def add(a, b): return a.sum()+b+1
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for _ in range(3): add(Tensor.rand(1000, 1000), Tensor.rand(1000, 1000))
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cls.st = pickle.dumps(add)
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del add
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def test_inspect(self):
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import io
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class FakeClass:
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def __init__(self, *args, **kwargs):
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print(self.module, self.name)
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class InspectUnpickler(pickle.Unpickler):
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def find_class(self, module, name): return type("SpecializedFakeClass", (FakeClass,), {"name": name, "module": module})
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InspectUnpickler(io.BytesIO(self.st)).load()
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@unittest.skip("we are still saving intermediate buffers")
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def test_size(self):
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# confirm no intermediate buffers are saved
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self.assertLess(len(self.st), 1_000_000)
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if __name__ == '__main__':
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unittest.main()
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