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https://github.com/firestar5683/StarPilot.git
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firestar5683
22a8575199
Keep official openpilot ancestry and dependency licenses. Store resources directly in Git, remove LFS setup requirements, and leave the downloadable big model outside the source tree.
49 lines
1.8 KiB
Python
49 lines
1.8 KiB
Python
import unittest
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from tinygrad import Tensor, Device, Variable
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from examples.gpt2 import Transformer
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from tinygrad.nn.state import get_state_dict
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class TestMethodCache(unittest.TestCase):
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def setUp(self):
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self.backup_compiler = Device[Device.DEFAULT].compiler.compile_cached
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def tearDown(self):
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Device[Device.DEFAULT].compiler.compile_cached = self.backup_compiler
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def test_simple_methodcache(self):
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a = Tensor([1])
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b = Tensor([2])
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c = Tensor([3])
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d = Tensor([4])
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(a+b).realize()
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Device[Device.DEFAULT].compiler.compile_cached = None
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(c+d).realize()
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def test_nested_methodcache(self):
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a,b,c,d = Tensor([1]), Tensor([2]), Tensor([3]), Tensor([4])
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((a+b)+(a+b)).realize()
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Device[Device.DEFAULT].compiler.compile_cached = None
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((c+d)+(c+d)).realize()
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def test_nested_methodcache_swap(self):
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a,b,c,d = Tensor([1]), Tensor([2]), Tensor([3]), Tensor([4])
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((a+b)+(c+d)).realize()
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Device[Device.DEFAULT].compiler.compile_cached = None
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((c+d)+(a+b)).realize()
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@unittest.skip("incorrect use of transformer")
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def test_small_transformer(self):
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args_tiny = {"dim": 16, "n_heads": 8, "n_layers": 8, "norm_eps": 1e-05, "vocab_size": 10}
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model = Transformer(**args_tiny)
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for v in get_state_dict(model).values(): v.assign(Tensor.empty(*v.shape, dtype=v.dtype).realize())
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# NOTE: you have to do this twice due to the k-v cache
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for i in range(3): model(Tensor([[1,2,3,4]]), Variable("start_pos", 0, 10).bind(i)).realize()
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for i in range(3): model(Tensor([[1,2,3,4]]), Variable("start_pos", 0, 10).bind(i)).realize()
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Device[Device.DEFAULT].compiler.compile_cached = None
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for i in range(3): model(Tensor([[1,2,3,4]]), Variable("start_pos", 0, 10).bind(i)).realize()
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if __name__ == '__main__':
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unittest.main()
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