filter fake buffers in search

test/test_search.py

@@ -3,12 +3,15 @@
 from tinygrad.codegen.kernel import Opt, OptOps
 from tinygrad.codegen.linearizer import Linearizer
 from tinygrad.engine.schedule import create_schedule
-from tinygrad.engine.search import time_linearizer, bufs_from_lin, actions
+from tinygrad.engine.search import time_linearizer, bufs_from_lin, actions, beam_search
 from tinygrad.device import Device, Buffer
-from tinygrad.ops import LoadOps, BufferOps
+from tinygrad.ops import LazyOp, LoadOps, BufferOps, ReduceOps, BinaryOps, MemBuffer, ConstBuffer
 from tinygrad.tensor import Tensor
+from tinygrad.dtype import dtypes
 from tinygrad.helpers import Context
 from tinygrad.engine.realize import capturing
+from tinygrad.shape.shapetracker import ShapeTracker
+from tinygrad.shape.view import View
 
 class TestTimeLinearizer(unittest.TestCase):
   @unittest.skipIf(Device.DEFAULT in {"AMD", "NV"}, "Tries to open HSA/CUDA. #4607")
@@ -66,5 +69,14 @@ def test_get_linearizer_actions(self):
     if Opt(OptOps.GROUPTOP, 0, 0) in actions:
       assert len([x for x in lins if x.applied_opts[0] == Opt(OptOps.GROUPTOP, axis=0, amt=3)]) == 0, "did not de-dup GROUPTOP"
 
+  def test_filter_global_buffer(self):
+    # taken from https://github.com/tinygrad/tinygrad/issues/4612
+    ast = LazyOp(op=BufferOps.STORE, src=(LazyOp(op=ReduceOps.MAX, src=(LazyOp(op=BinaryOps.MUL, src=(LazyOp(op=BinaryOps.ADD, src=(LazyOp(op=BinaryOps.ADD, src=(LazyOp(op=BinaryOps.ADD, src=(LazyOp(op=BinaryOps.ADD, src=(LazyOp(op=BinaryOps.ADD, src=(LazyOp(op=BufferOps.LOAD, src=(), arg=MemBuffer(idx=1, dtype=dtypes.float, st=ShapeTracker(views=(View(shape=(384768,), strides=(1,), offset=0, mask=((0, 64128),), contiguous=False), View(shape=(1, 501, 256), strides=(0, 1, 501), offset=256512, mask=None, contiguous=False))))), LazyOp(op=BufferOps.LOAD, src=(), arg=MemBuffer(idx=2, dtype=dtypes.float, st=ShapeTracker(views=(View(shape=(384768,), strides=(1,), offset=-64128, mask=((64128, 128256),), contiguous=False), View(shape=(1, 501, 256), strides=(0, 1, 501), offset=256512, mask=None, contiguous=False)))))), arg=None), LazyOp(op=BufferOps.LOAD, src=(), arg=MemBuffer(idx=3, dtype=dtypes.float, st=ShapeTracker(views=(View(shape=(384768,), strides=(1,), offset=-128256, mask=((128256, 192384),), contiguous=False), View(shape=(1, 501, 256), strides=(0, 1, 501), offset=256512, mask=None, contiguous=False)))))), arg=None), LazyOp(op=BufferOps.LOAD, src=(), arg=MemBuffer(idx=4, dtype=dtypes.float, st=ShapeTracker(views=(View(shape=(384768,), strides=(1,), offset=-192384, mask=((192384, 256512),), contiguous=False), View(shape=(1, 501, 256), strides=(0, 1, 501), offset=256512, mask=None, contiguous=False)))))), arg=None), LazyOp(op=BufferOps.LOAD, src=(), arg=MemBuffer(idx=5, dtype=dtypes.float, st=ShapeTracker(views=(View(shape=(384768,), strides=(1,), offset=-256512, mask=((256512, 320640),), contiguous=False), View(shape=(1, 501, 256), strides=(0, 1, 501), offset=256512, mask=None, contiguous=False)))))), arg=None), LazyOp(op=BufferOps.LOAD, src=(), arg=MemBuffer(idx=6, dtype=dtypes.float, st=ShapeTracker(views=(View(shape=(384768,), strides=(1,), offset=-320640, mask=((320640, 384768),), contiguous=False), View(shape=(1, 501, 256), strides=(0, 1, 501), offset=256512, mask=None, contiguous=False)))))), arg=None), LazyOp(op=BufferOps.CONST, src=(), arg=ConstBuffer(val=1.4285714285714286, dtype=dtypes.float, st=ShapeTracker(views=(View(shape=(1, 501, 256), strides=(0, 0, 0), offset=0, mask=None, contiguous=False),))))), arg=None),), arg=(1,)),), arg=MemBuffer(idx=0, dtype=dtypes.float, st=ShapeTracker(views=(View(shape=(1, 1, 256), strides=(0, 0, 1), offset=0, mask=None, contiguous=True),))))  # noqa: E501
+    lin = Linearizer(ast)
+
+    bufs = bufs_from_lin(lin)
+    best_lin = beam_search(lin, bufs, 3)
+    assert best_lin
+
 if __name__ == '__main__':
   unittest.main()

tinygrad/engine/search.py

@@ -42,10 +42,11 @@ def _time_program(p:Program, lib:bytes, var_vals, rawbufs, early_stop=None, max_
   try: car = CompiledRunner(p, precompiled=lib)
   except AssertionError: return [math.inf] * cnt
   tms = []
+  input_bufs = [rawbufs[i] for i,_ in car.p.globals]
   for _ in range(cnt):
     if clear_l2:
       with Context(DEBUG=0, BEAM=0, CACHECOLLECTING=0): Tensor.ones(1024,1024).contiguous().realize()
-    tms.append(cast(float, car(rawbufs, var_vals, wait=True))*factor)
+    tms.append(cast(float, car(input_bufs, var_vals, wait=True))*factor)
     if early_stop is not None and early_stop < tms[-1]: break
   return tms