try pad Invalid

test/test_tiny.py

@@ -31,9 +31,13 @@ class TestTiny(unittest.TestCase):
     out = Tensor.ones(16).contiguous() + Tensor.ones(16).contiguous()
     self.assertListEqual(out.tolist(), [2]*16)
 
+  def test_stack(self):
+    out = Tensor.stack(Tensor.ones(8).contiguous(), Tensor.zeros(8).contiguous())
+    self.assertListEqual(out.flatten().tolist(), [1]*8+[0]*8)
+
   def test_cat(self):
-    out = Tensor.cat(Tensor.ones(8).contiguous(), Tensor.zeros(8).contiguous())
-    self.assertListEqual(out.tolist(), [1]*8+[0]*8)
+    out = Tensor.cat(Tensor.ones(8).contiguous(), Tensor.zeros(5).contiguous())
+    self.assertListEqual(out.tolist(), [1]*8+[0]*5)
 
   def test_sum(self, N=getenv("SUM_N", 256)):
     out = Tensor.ones(N).contiguous().sum()

tinygrad/mixin/op.py

@@ -286,7 +286,7 @@ class OpMixin(ElementwiseMixin, ReduceMixin):
     X = self.shrink(tuple((-smin(pB,0),smin(pA+s,s)) for (pB,pA),s in zip(pX, self.shape))) if has_neg else self
     pads = tuple((smax(pB,0), smax(pA,0)) for pB,pA in pX) if has_neg else pX
     base = MovementMixin.pad(X, pads)
-    if value == 0: return base
+    if value == Invalid: return base
     return MovementMixin.pad(X.const_like(1).cast(dtypes.bool), pads).where(base, value)
 
   def _pad_circular(self, pX:tuple[tuple[sint, sint], ...]) -> Self:

tinygrad/schedule/indexing.py

@@ -3,7 +3,7 @@ import functools, itertools
 from dataclasses import dataclass, field, replace
 from tinygrad.dtype import dtypes, AddrSpace
 from tinygrad.uop.ops import PatternMatcher, UPat, Ops, UOp, resolve, GroupOp, graph_rewrite, sint, AxisType, profile_matches, broadcast_axes
-from tinygrad.uop.ops import gate_kernel_sink
+from tinygrad.uop.ops import gate_kernel_sink, Invalid
 from tinygrad.uop.symbolic import symbolic, pm_simplify_valid, pm_drop_and_clauses
 from tinygrad.helpers import argsort, all_same, cpu_profile, PCONTIG, colored, Context, SPEC
 
@@ -101,7 +101,7 @@ def convert_pad_to_where_to_keep_behavior_local(ctx:IndexingContext, x:UOp):
   if x not in ctx.range_map: return None
   bx = create_bufferize_and_index_based_on_ranges(ctx, x)
   valid: UOp = UOp.const(dtypes.bool, True).uprod([r.get_valid() for r in ctx.range_map[x][0]])
-  return valid.where(bx.src[0], UOp.const(x.dtype, 0))
+  return valid.where(bx.src[0], UOp.const(x.dtype, Invalid))
 
 def convert_reduce_to_reduce_with_ranges(ctx:IndexingContext, x:UOp):
   if x.arg[1] == 0: return None