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121 lines
6.4 KiB
121 lines
6.4 KiB
import unittest
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from typing import List, cast
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import numpy as np
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from tinygrad.device import Buffer, Device, is_dtype_supported
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from tinygrad.dtype import dtypes, ConstType
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from tinygrad.engine.realize import CompiledRunner
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from tinygrad.helpers import dedup, flatten, prod
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from tinygrad.renderer.cstyle import CStyleLanguage
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from tinygrad.renderer.ptx import PTXRenderer
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from tinygrad.renderer.wgsl import WGSLRenderer
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from tinygrad.runtime.ops_python import PythonRenderer
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from tinygrad.uop.ops import UOp, Ops, python_alu
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from tinygrad.renderer import ProgramSpec
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from tinygrad.tensor import Tensor, _to_np_dtype
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from tinygrad.codegen import full_rewrite
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from tinygrad.engine.realize import lower_schedule_item
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def _test_uop_result(inputs:List[Tensor], stores:List[UOp], local_size=None):
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for x in inputs: x.realize()
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# NOTE: we only toposort the stores
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uops: List[UOp] = []
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def _recursive_add(uop:UOp) -> List[UOp]: return flatten([_recursive_add(x) for x in uop.src])+[uop]
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uops = dedup(flatten(_recursive_add(st) for st in stores))
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outbufs = [Buffer(Device.DEFAULT, sz:=(1 if local_size is None else prod(local_size)), (dtype:=u.src[1].dtype), \
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initial_value=np.zeros(sz, dtype=_to_np_dtype(dtype)).data) for u in uops if u.op is Ops.STORE]
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inbufs = [cast(UOp,x.uop).base.buffer for x in inputs]
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src = Device[Device.DEFAULT].renderer.render(uops)
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ei = CompiledRunner(ProgramSpec("test", src, Device.DEFAULT, uops[-1], uops=uops, local_size=local_size))
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ei.exec(outbufs+inbufs)
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return [np.frombuffer(x.as_buffer(), _to_np_dtype(x.dtype)) for x in outbufs]
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def _setup_and_test_alu(alu_op:Ops, input_val:ConstType, *alu_src_uops:UOp):
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dtype = alu_src_uops[0].dtype
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a = UOp(Ops.DEFINE_GLOBAL, dtype.ptr(), (), 0)
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b = UOp(Ops.DEFINE_GLOBAL, dtype.ptr(), (), 1)
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idx = UOp.const(dtypes.int, 0)
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ld = UOp(Ops.LOAD, dtype, (b.index(idx),))
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alu = ld.alu(alu_op, *alu_src_uops)
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store = UOp.store(a.index(idx), alu)
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sink = UOp(Ops.SINK, dtypes.void, (store,))
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uops = full_rewrite(sink, Device[Device.DEFAULT].renderer)
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return _test_uop_result([Tensor([input_val])], uops)[0]
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class TestRendererFailures(unittest.TestCase):
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@unittest.skipIf(not isinstance(Device[Device.DEFAULT].renderer, (PTXRenderer, PythonRenderer)), "test is for ptx or python renderer")
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def test_gated_store_with_alu(self):
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a = UOp(Ops.DEFINE_GLOBAL, dtypes.int.ptr(), (), 0)
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gate_alu = (lidx0:=UOp(Ops.SPECIAL, dtypes.int, (), ('lidx0', 4))).ne(0)
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gated_alu_store = UOp(Ops.STORE, dtypes.void, (a.index(lidx0, gate_alu), UOp.const(dtypes.int, 1)))
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sink = UOp(Ops.SINK, dtypes.void, (gated_alu_store,))
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uops = full_rewrite(sink, Device[Device.DEFAULT].renderer)
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ret = _test_uop_result([], uops, local_size=[4, 1, 1])[0]
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np.testing.assert_equal(ret, [0, 1, 1, 1])
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@unittest.skipIf(not isinstance(Device[Device.DEFAULT].renderer, (PTXRenderer, PythonRenderer)), "test is for ptx or python renderer")
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def test_gated_store_with_alu_2d(self):
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a = UOp(Ops.DEFINE_GLOBAL, dtypes.int.ptr(), (), 0)
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gate_alu_0 = (lidx0:=UOp(Ops.SPECIAL, dtypes.int, (), ('lidx0', 4))).ne(0)
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gate_alu_1 = (lidx1:=UOp(Ops.SPECIAL, dtypes.int, (), ('lidx1', 2))).ne(0)
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gated_alu_store = UOp(Ops.STORE, dtypes.void, (a.index(lidx0+lidx1*4, gate_alu_0&gate_alu_1), UOp.const(dtypes.int, 1)))
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sink = UOp(Ops.SINK, dtypes.void, (gated_alu_store,))
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uops = full_rewrite(sink, Device[Device.DEFAULT].renderer)
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ret = _test_uop_result([], uops, local_size=[4, 2, 1])[0]
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np.testing.assert_equal(ret, [0, 0, 0, 0, 0, 1, 1, 1])
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@unittest.skipIf(not isinstance(Device[Device.DEFAULT].renderer, CStyleLanguage), "uops are for cstyle")
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class TestCStyleFailures(unittest.TestCase):
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def test_inline_const_alu(self):
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# CPU doesn't use the max function
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ret = _setup_and_test_alu(Ops.MAX, 1, UOp.const(dtypes.int, dtypes.min(dtypes.int)+1))
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self.assertEqual(ret[0], 1)
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def _test_src_strip_paren(self, op: Ops, should_strip_paren:bool=True):
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dtype = "bool" if op in (Ops.OR, Ops.XOR, Ops.AND) else None
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ret = Tensor.empty(1, dtype=dtype)
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for _ in range(5): ret = python_alu[op](ret, Tensor.empty(1, dtype=dtype))
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schedule = ret.schedule()
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assert len(schedule) == 1
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ei = lower_schedule_item(schedule[0])
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src = ei.prg.p.src
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self.assertEqual("("*5 not in src, should_strip_paren)
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def test_repeat_add(self): self._test_src_strip_paren(Ops.ADD)
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def test_repeat_mul(self): self._test_src_strip_paren(Ops.MUL)
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def test_repeat_xor(self): self._test_src_strip_paren(Ops.XOR)
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def test_repeat_or(self): self._test_src_strip_paren(Ops.OR)
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def test_repeat_and(self): self._test_src_strip_paren(Ops.AND)
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def test_repeat_sub(self): self._test_src_strip_paren(Ops.SUB, should_strip_paren=False)
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@unittest.skipUnless(isinstance(Device[Device.DEFAULT].renderer, WGSLRenderer), "tests for wgsl renderer")
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class TestWGSLFailures(unittest.TestCase):
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def test_multiply_infinity(self):
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# multiplying a positive constant by infinity should return infinity
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# WGSL pipelines do not handle this reliably, some of which return zero, unless infinity always comes from a read on a dynamic buffer
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ret = _setup_and_test_alu(Ops.MUL, 5.0, UOp.const(dtypes.float32, float("inf")))
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self.assertEqual(ret[0], float("inf"))
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@unittest.skipIf(not isinstance(Device[Device.DEFAULT].renderer, PTXRenderer), "tests for ptx renderer")
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class TestPTXFailures(unittest.TestCase):
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@unittest.skip("INDEX can only have a gate ALU parent, not an IF")
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def test_gated_store_with_if(self):
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a = UOp(Ops.DEFINE_GLOBAL, dtypes.int.ptr(), (), 0)
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gate_alu = (lidx0:=UOp(Ops.SPECIAL, dtypes.int, (), ('lidx0', 4))).ne(0)
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val = UOp.const(dtypes.int, 1)
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if_uop = UOp(Ops.IF, dtypes.void, (gate_alu,))
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gated_alu_store = UOp(Ops.STORE, dtypes.void, (a.index(lidx0, if_uop), val))
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sink = UOp(Ops.SINK, dtypes.void, (gated_alu_store,))
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uops = full_rewrite(sink, Device[Device.DEFAULT].renderer)
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ret = _test_uop_result([], uops, local_size=[4, 1, 1])[0]
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np.testing.assert_equal(ret, [0, 1, 1, 1])
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@unittest.skipUnless(is_dtype_supported(dtypes.half), "need half")
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def test_gated_define_acc_with_half_dtype(self):
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a = Tensor.randn(32, 32, dtype=dtypes.half).realize()
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b = Tensor.randn(34, 32, dtype=dtypes.half).realize()
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result = a.pad((1,1)).matmul(b, dtype=dtypes.half).numpy()
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reference = a.pad((1,1)).matmul(b, dtype=dtypes.float).numpy()
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np.testing.assert_allclose(result, reference, atol=1e-2, rtol=1e-2)
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if __name__ == '__main__':
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unittest.main()
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