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https://github.com/tinygrad/tinygrad.git
synced 2026-02-03 11:14:56 -05:00
85d26ddc36
* remove the loop * cleanups * tests failing still * global_loop_ctx wasn't needed * replace_op is cleaner * minor opt * cast opt was wrong * uop_num * uop num was dumb * tuplize_uops * torch tests * fix test_uops
108 lines
3.2 KiB
Python
108 lines
3.2 KiB
Python
import random, traceback
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import numpy as np
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from collections import Counter, defaultdict
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from extra.optimization.helpers import load_worlds, ast_str_to_lin
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from tinygrad.codegen.linearizer import Linearizer
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from tinygrad.features.search import get_linearizer_actions, bufs_from_lin, tuplize_uops
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from tinygrad.graph import print_tree
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from tinygrad.helpers import ImageDType, prod, getenv
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from tinygrad.ops import Device, Compiled, Interpreted
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from tinygrad.lazy import vars_from_ast
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device = Device[Device.DEFAULT]
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class LB:
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# placeholder LazyBuffer
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def __init__(self, rawbuf, dtype):
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self.realized = rawbuf
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self.output_buffer = rawbuf
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self.dtype = dtype
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def fuzz_linearizer(lin: Linearizer):
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random.seed(42)
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np.random.seed(42)
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print_tree(lin.ast)
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print(lin.colored_shape())
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rawbufs = bufs_from_lin(lin)
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seen_uops = {}
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ground_truth = None
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while 1:
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if len(seen_uops) >= 20: break # enough for this kernel
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actions = get_linearizer_actions(lin, include_0=False)
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if not actions: break
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lin = random.choice(list(actions.values()))
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if lin.applied_opts: print(f"applied action: {lin.applied_opts[-1]}")
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# stop if kernel uops repeat
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tuops = tuplize_uops(lin.linearize().uops)
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if tuops in seen_uops: break
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seen_uops[tuops] = tuple(lin.applied_opts)
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print(lin.colored_shape())
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# get a new output buffer
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rawbufs[0] = type(rawbufs[0])(rawbufs[0].size, rawbufs[0].dtype)
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var_vals = {v: random.randint(v.min, v.max) for v in vars_from_ast(lin.ast)}
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# TODO: images needs required_optimization
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if isinstance(device, Compiled):
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try:
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prg = device.to_program(lin)
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except:
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print(lin.ast)
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traceback.print_exc()
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print("COMPILE FAILED!!")
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return "COMPILE_ERROR"
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try:
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prg.exec(rawbufs, var_vals, force_wait=True)
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except:
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print(lin.ast)
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traceback.print_exc()
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print("EXEC FAILED!!")
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return "EXEC_ERROR"
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else:
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try:
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device.exec_ast(lin.ast, output=LB(rawbufs[0], rawbufs[0].dtype), inputs=[LB(buf, buf.dtype) for buf in rawbufs[1:]])
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except Exception as e:
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print(lin.ast)
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traceback.print_exc()
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return e
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result = rawbufs[0].toCPU()
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if ground_truth is None:
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ground_truth = result
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else:
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try:
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np.testing.assert_allclose(result, ground_truth, rtol=1e-2, atol=1e-2)
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except AssertionError:
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print(lin.ast)
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traceback.print_exc()
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return "NOT_ALLCLOSE"
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except Exception as e:
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print(lin.ast)
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traceback.print_exc()
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return e
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return "PASS"
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if __name__ == "__main__":
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ast_strs = load_worlds()
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print(f"{len(ast_strs)=}")
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tested = 0
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c = Counter()
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failed = []
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for i, ast in enumerate(ast_strs[:getenv("FUZZ_N", len(ast_strs))]):
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if "Variable" in ast and isinstance(device, Interpreted): continue # no symbolic shape for Interpreted
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if "dtypes.image" in ast and Device.DEFAULT != "GPU": continue # IMAGE is only for GPU
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print(f"testing ast {i}")
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tested += 1
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lin = ast_str_to_lin(ast)
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fuzz = str(fuzz_linearizer(lin))
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c[fuzz] += 1
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if fuzz != "PASS":
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failed.append(i)
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print(f"{tested=}")
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print(c.most_common())
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print(f"{failed=}") |