Files
tinygrad/test/test_uops.py
George Hotz 7b8d06c9f1 test uops (#1444)
* test uops

* tests should pass

* improve uops

* precision
2023-08-05 12:35:56 -07:00

78 lines
3.8 KiB
Python

import unittest, math
import numpy as np
from tinygrad.helpers import dtypes
from tinygrad.tensor import Device
from tinygrad.ops import UnaryOps, BinaryOps, TernaryOps, ASTRunner, Compiled
from tinygrad.codegen.linearizer import UOps, Token, ConstOp, MemOp
from tinygrad.shape.symbolic import Variable
def _uops_to_prg(uops):
src, global_size, local_size = Device[Device.DEFAULT].renderer("test", uops)
return ASTRunner("test", src, global_size, local_size).build(Device[Device.DEFAULT].runtime)
def _test_single_value(tc, tt, vals, op):
uops = [
[UOps.DEFINE_GLOBAL, None, [], ('data0', tc.dtype)],
*[[UOps.DEFINE_GLOBAL, None, [], (f'data{i+1}', ta.dtype)] for i,ta in enumerate(tt)],
*[[UOps.LOAD, ta, [], MemOp(f'data{i+1}', Variable.num(0), False, ta.dtype, Variable.ands([]))] for i,ta in enumerate(tt)],
[UOps.ALU, tc, tt, op],
[UOps.STORE, None, [tc], MemOp('data0', Variable.num(0), False, tc.dtype, Variable.ands([]))]
]
buf = Device[Device.DEFAULT].buffer(1, tc.dtype)
buf2 = [Device[Device.DEFAULT].buffer.fromCPU(np.array([a], dtype=ta.dtype.np)) for a,ta in zip(vals, tt)]
prg = _uops_to_prg(uops)
prg([buf]+buf2)
return buf.toCPU()[0]
def _test_single_value_const(tc, tt, vals, op):
uops = [
[UOps.DEFINE_GLOBAL, None, [], ('data0', tc.dtype)],
*[[UOps.LOAD, ta, [], ConstOp(a, Variable.ands([]))] for ta,a in zip(tt, vals)],
[UOps.ALU, tc, tt, op],
[UOps.STORE, None, [tc], MemOp('data0', Variable.num(0), False, tc.dtype, Variable.ands([]))]
]
buf = Device[Device.DEFAULT].buffer(1, tc.dtype)
prg = _uops_to_prg(uops)
prg([buf])
return buf.toCPU()[0]
@unittest.skipIf(not isinstance(Device[Device.DEFAULT], Compiled), "only test for compiled backends")
class TestUOps(unittest.TestCase):
def _equal(self, v1, v2):
if not (math.isnan(v1) and math.isnan(v2)): self.assertAlmostEqual(v1, v2, places=5)
def _test_uop_fxn(self, bop, fxn, dt=dtypes.float32):
for f in [_test_single_value, _test_single_value_const]:
for a in [-2.0, 2.0]:
self._equal(f(Token('c', dt), [Token('a', dt)], [a], bop), fxn(a))
def test_exp2(self): self._test_uop_fxn(UnaryOps.EXP2, lambda a: np.exp2(a))
def test_log2(self): self._test_uop_fxn(UnaryOps.LOG2, lambda a: math.log2(a) if a > 0 else float('nan'))
def test_sin(self): self._test_uop_fxn(UnaryOps.SIN, lambda a: math.sin(a))
def test_sqrt(self): self._test_uop_fxn(UnaryOps.SQRT, lambda a: math.sqrt(a) if a >= 0 else float('nan'))
#def test_recip(self): self._test_uop_fxn(UnaryOps.RECIP, lambda a: 1.0/a)
def _test_bop_fxn(self, bop, fxn, dt=dtypes.float32):
for f in [_test_single_value, _test_single_value_const]:
for a in [-2.0, 2.0]:
for b in [-3.0, 3.0]:
self._equal(f(Token('c', dt), [Token('a', dt), Token('b', dt)], [a,b], bop), fxn(a,b))
def test_add(self): self._test_bop_fxn(BinaryOps.ADD, lambda a,b: a+b)
def test_sub(self): self._test_bop_fxn(BinaryOps.SUB, lambda a,b: a-b)
def test_mul(self): self._test_bop_fxn(BinaryOps.MUL, lambda a,b: a*b)
def test_div(self): self._test_bop_fxn(BinaryOps.DIV, lambda a,b: a/b)
def test_max(self): self._test_bop_fxn(BinaryOps.MAX, lambda a,b: max(a,b))
def test_cmpeq(self): self._test_bop_fxn(BinaryOps.CMPEQ, lambda a,b: float(a==b))
# CMPLT and MOD aren't tested
def _test_top_fxn(self, bop, fxn, dt=dtypes.float32):
for f in [_test_single_value, _test_single_value_const]:
for a in [-2.0, 0, 1, 2.0]:
for b in [-3.0, 3.0]:
for c in [-4.0, 4.0]:
self._equal(f(Token('d', dt), [Token('a', dt), Token('b', dt), Token('c', dt)], [a,b,c], bop), fxn(a,b,c))
def test_mulacc(self): self._test_top_fxn(TernaryOps.MULACC, lambda a,b,c: (a*b)+c)
def test_where(self): self._test_top_fxn(TernaryOps.WHERE, lambda a,b,c: b if a!=0 else c)
if __name__ == '__main__':
unittest.main(verbosity=2)