Lunderberg commented on PR #14095:
URL: https://github.com/apache/tvm/pull/14095#issuecomment-1441044009
It looks like this would also allow index maps that reduce the number of
elements in a buffer. For example, if I use the transform `lambda i, j: [i %
2, j]`, I'd expect to receive an error, because I've reduced the buffer size
from `[N, M]` to `[2, M]`. I put together a quick unit test (below), and
```python
class TestNonInjectiveTransform(BasePaddingCompare):
"""Each location must map to a unique transformed location"""
index_map = tvm.testing.parameter(lambda i, j: [i % 2, j])
def before():
A = T.alloc_buffer((4, 4), "int32")
for i, j in T.grid(4, 4):
with T.block("block"):
vi, vj = T.axis.remap("SS", [i, j])
A[vi, vj] = 0
expected = tvm.tir.schedule.schedule.ScheduleError
```
No error is thrown, and I instead get the following output.
```python
@T.prim_func
def after():
A = T.alloc_buffer((2, 4), "int32")
for i, j in T.grid(4, 4):
with T.block("block"):
vi, vj = T.axis.remap("SS", [i, j])
T.reads()
T.writes(A[vi % 2, vj])
A[vi % 2, vj] = 0
```
This could be useful, as several other primitives could then be expressed in
terms of a buffer transform, which may reduce complexity (e.g. This `lambda
i,j: [i%2, j]` transformation could be used to implement double-buffering), but
it could also have a large effect on any of the consumers of `A`.
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