learning-chip opened a new issue #8413:
URL: https://github.com/apache/tvm/issues/8413
## Problem description
`tvm.contrib.sparse.placeholder` is intended to be an input type for
`topi.sparse.csrmv` (#1289, #1291). However, passing `sparse.placeholder` to
`tvm.build` leads to `ValueError: don't know how to convert type <class
'tvm.contrib.sparse.CSRPlaceholderOp'> to object`.
This is because `tvm.contrib.sparse.CSRPlaceholderOp` cannot pass the check
inside `tvm.runtime.object_generic.convert_to_object`:
https://github.com/apache/tvm/blob/26281792e92ae24ec7a14b11e8df8fbacf9c4882/python/tvm/runtime/object_generic.py#L57
where `ObjectTypes` is defined as :
https://github.com/apache/tvm/blob/26281792e92ae24ec7a14b11e8df8fbacf9c4882/python/tvm/runtime/object_generic.py#L38
## Steps to reproduce
Build TVM `0.8.dev` from the latest master branch, and then run:
```python
# Adapted from
https://github.com/apache/tvm/blob/main/tests/python/topi/python/test_topi_sparse.py
import tvm
from tvm import te
from tvm import topi
import tvm.contrib.sparse as tvmsp
def build_csrmv(use_sparse=False, dtype='float32', target='llvm'):
nr, nc, nnz = te.var("nr"), te.var("nc"), te.var("nnz")
A = tvmsp.placeholder(shape=(nr, nc), nonzeros=nnz, dtype=dtype,
name="A")
B = te.placeholder((nc, 1), dtype=dtype, name="B")
OUT = topi.sparse.csrmv(A, B)
s = te.create_schedule(OUT.op)
if use_sparse:
f = tvm.build(
s, [nr, A, B, OUT],
target=target, name="csrmv"
)
else:
f = tvm.build(
s, [nr, A.data, A.indices, A.indptr, B, OUT],
target=target, name="csrmv"
)
return f
csrmv = build_csrmv() # works, when passing separate components insides CSR
matrix
csrmv_sp = build_csrmv(use_sparse=True) # failed, when passing the CSR
matrix as a whole
```
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