a425f24d54
Added an additional `repr` argument to the cache hook, which represents a human-readable string representation of the signature and argument attributes associated with the compiled binary.
92 lines
2.2 KiB
Python
92 lines
2.2 KiB
Python
import torch
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import triton
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from triton.code_gen import JITFunction
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import triton.language as tl
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import os
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import shutil
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import pytest
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tmpdir = ".tmp"
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@triton.jit
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def function_1(i):
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i = i + 1
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i = function_2(i)
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return i
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@triton.jit
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def function_2(i):
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i = i + 1
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return i
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@triton.jit
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def kernel(X, i, BLOCK: tl.constexpr):
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i = i + 1
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i = function_1(i)
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tl.store(X, i)
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@triton.jit(do_not_specialize=["i"])
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def kernel_nospec(X, i, BLOCK: tl.constexpr):
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i = i + 1
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i = function_1(i)
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tl.store(X, i)
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def apply_src_change(target, old, new):
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delattr(kernel.fn, 'hash')
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delattr(function_1.fn, 'hash')
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delattr(function_2.fn, 'hash')
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function_1.src = function_1.src.replace(old, new)
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target.src = target.src.replace(old, new)
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ret = target.cache_key
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target.src = target.src.replace(new, old)
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return ret
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def test_nochange():
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baseline = kernel.cache_key
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updated = apply_src_change(kernel, 'i + 1', 'i + 1')
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assert baseline == updated
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def test_toplevel_change():
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baseline = kernel.cache_key
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updated = apply_src_change(kernel, 'i + 1', 'i + 2')
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assert baseline != updated
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def test_nested1_change():
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baseline = kernel.cache_key
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updated = apply_src_change(function_1, 'i + 1', 'i + 2')
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assert baseline != updated
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def reset_tmp_dir():
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os.environ["TRITON_CACHE_DIR"] = tmpdir
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if os.path.exists(tmpdir):
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shutil.rmtree(tmpdir)
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def test_reuse():
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counter = 0
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def inc_counter(key, binary, repr):
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nonlocal counter
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counter += 1
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JITFunction.cache_hook = inc_counter
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reset_tmp_dir()
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x = torch.empty(1, dtype=torch.int32, device='cuda')
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for i in range(10):
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kernel[(1,)](x, 1, BLOCK=1024)
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assert counter == 1
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@pytest.mark.parametrize('mode', ['enable', 'disable'])
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def test_specialize(mode):
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counter = 0
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def inc_counter(key, binary, repr):
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nonlocal counter
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counter += 1
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JITFunction.cache_hook = inc_counter
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reset_tmp_dir()
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x = torch.empty(1, dtype=torch.int32, device='cuda')
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function = {'enable': kernel, 'disable': kernel_nospec}[mode]
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target = {'enable': 5, 'disable': 1}[mode]
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for i in [1, 2, 4, 8, 16, 32]:
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function[(1,)](x, i, BLOCK=512)
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assert counter == target
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