support symbolic reshape with non-contiguous (#4844)

* support symbolic reshape with non-contiguous

pre-requisite for symbolic arange (make symbolic ones that can be folded).

* test cases

* typo

* shorter

test/test_symbolic_jit.py

@@ -182,8 +182,7 @@ class TestSymbolicJit(unittest.TestCase):
     jf = TinyJit(f)
     for i in range(1, 5):
       vi = Variable("i", 1, 10).bind(i)
-      # TODO: without contiguous, the CONST shape are different in jit
+      t = Tensor.ones(i)
-      t = Tensor.ones(i).contiguous()
       symbolic = jf(t.reshape(vi)).item()
       expected = f(t).item()
       np.testing.assert_equal(symbolic, expected)

test/test_symbolic_shapetracker.py

@@ -102,7 +102,7 @@ class TestShapeTrackerUnbind(unittest.TestCase):
     assert unbound_st == ShapeTracker((View.create(shape=(1, 4), offset=4*v),))
     assert var_val == {v: 2}
 
-class TestSymbolicReshape(unittest.TestCase):
+class TestSymbolicReshapeFromContiguous(unittest.TestCase):
   def test_reshape_into_symbols_simple(self):
     for i in range(1, 6):
       vi = Variable("i", 1, 5).bind(i)
@@ -151,6 +151,41 @@ class TestSymbolicReshape(unittest.TestCase):
     new_shape = (2, (NumNode(1)+Variable('start_pos', 1, 128)), 16, 64)
     assert view.reshape(new_shape) is None
 
+class TestSymbolicReshapeFromNonContiguous(unittest.TestCase):
+  def test_reshape_from_const(self):
+    vi = Variable("i", 1, 5).bind(4)
+    t = Tensor.ones(3, 4).reshape(3, vi)
+    assert t.shape == (3, vi)
+    assert not t.lazydata.st.contiguous
+    assert len(t.lazydata.st.views) == 1
+
+  def test_reshape_not_allowed(self):
+    vi = Variable("i", 1, 5).bind(4)
+    with self.assertRaises(ValueError):
+      # different shape length  # TODO: cases where contractions matched might be fine
+      Tensor.ones(3, 4, 1).reshape(3, vi)
+    with self.assertRaises(ValueError):
+      # size matched, but dimensions do not match
+      Tensor.ones(4, 3).reshape(3, vi)
+
+  def test_reshape_from_padded(self):
+    vi = Variable("i", 1, 5).bind(4)
+    t = Tensor.ones(3, 4).contiguous().expand(2, 3, 4).pad(((1, 1), None, None)).shrink((None, None, (1, 3)))
+    st = t.lazydata.st
+    assert len(st.views) == 1
+    view = st.views[0]
+    assert view.shape == (4, 3, 2)
+    t = t.reshape(vi, 3, 2)
+    st2 = t.lazydata.st
+    assert len(st2.views) == 1
+    view2 = st2.views[0]
+    # check only shape changed. strides, offset, mask, contiguous remained the same
+    assert view2.shape == (vi, 3, 2)
+    assert view.strides == view2.strides == (0, 4, 1)
+    assert view.offset == view2.offset == 1
+    assert view.mask == view2.mask == ((1, 3), (0, 3), (0, 2))
+    assert not view.contiguous and not view2.contiguous
+
 class TestSymbolicExpand(unittest.TestCase):
   def test_expand_into_symbols(self):
     vi = Variable("i", 1, 5).bind(3)

tinygrad/shape/view.py

@@ -3,7 +3,7 @@ import functools, operator, itertools, math
 from dataclasses import dataclass
 from typing import Tuple, List, Optional, Dict, Set, cast
 from tinygrad.helpers import prod, all_int, argsort
-from tinygrad.shape.symbolic import Node, NumNode, Variable, sint
+from tinygrad.shape.symbolic import Node, NumNode, Variable, sint, sym_infer
 
 @functools.lru_cache(maxsize=None)
 def canonicalize_strides(shape:Tuple[sint, ...], strides:Tuple[sint, ...]) -> Tuple[sint, ...]:
@@ -268,7 +268,7 @@ class View:
       assert 0 in new_shape, f"cannot reshape 0 size to {new_shape}"
       return View.create(new_shape)
     # check for the same size
-    if all_int(self.shape):
+    if (self_all_int := all_int(self.shape)):
       assert all(isinstance(s, (int, Variable)) for s in new_shape), f"{self.shape=} -> {new_shape=} contains non (int, Variable) dim"
       if prod(self.shape) != prod([s if isinstance(s, int) else cast(Variable,s).val for s in new_shape]):
         raise ValueError(f"size mismatched, can't reshape {self.shape=} -> {new_shape=}")
@@ -278,6 +278,18 @@ class View:
     # after the asserts, it's okay to check contiguous
     if self.contiguous: return View.create(new_shape)
 
+    # if it's not contiguous and new shape is symbolic, check if it's directly replaceable
+    if self_all_int and not all_int(new_shape):
+      if len(self.shape) != len(new_shape): raise ValueError(f"cannot symbolic reshape non-contiguous {self} -> {new_shape}")
+      for si, so in zip(self.shape, new_shape):
+        if isinstance(so, int):
+          if si != so: raise ValueError(f"cannot symbolic reshape non-contiguous {self} -> {new_shape}")
+        else:
+          var_vals = {v: v.unbind()[1] for v in so.vars()}
+          if si != sym_infer(so, var_vals): raise ValueError(f"cannot symbolic reshape non-contiguous {self} -> {new_shape}")
+      # all dimensions matched, return the new view directly
+      return View(new_shape, self.strides, self.offset, self.mask, self.contiguous)
+
     strides, r_new_shape = [], reversed(new_shape)
     for merged_dim, new_stride, real_dim in reversed(_merge_dims(self.shape, self.strides, self.mask)):
       acc = 1