csullivan commented on code in PR #16498:
URL: https://github.com/apache/tvm/pull/16498#discussion_r1520310371
##########
tests/python/relax/test_frontend_nn_op.py:
##########
@@ -619,6 +619,111 @@ def test(qkv: R.Tensor((1, 1, 24, 16), dtype="float16"),
offset: R.Shape(["offse
tvm.ir.assert_structural_equal(irmodule, Expected)
+def test_tensor_ir_inplace_op():
+ hidden_size = 4096
+ dtype = "float16"
+
+ @T.prim_func
+ def inplace_take(
+ var_weight: T.handle, var_pos: T.handle, var_embeddings: T.handle,
offset: T.int64
+ ):
+ T.func_attr({"tir.noalias": T.bool(True)})
+ vocab_size = T.int64()
+ weight = T.match_buffer(var_weight, (vocab_size, hidden_size), dtype)
+ seq_len = T.int64()
+ total_seq_len = T.int64()
+ pos = T.match_buffer(var_pos, (seq_len,), "int32")
+ embeddings = T.match_buffer(var_embeddings, (total_seq_len,
hidden_size), dtype)
+ for ax0, ax1 in T.grid(seq_len, hidden_size):
+ with T.block("T_take"):
+ v0, v1 = T.axis.remap("SS", [ax0, ax1])
+ T.reads(weight[pos[v0], v1], pos[v0])
+ T.writes(embeddings[v0, v1])
+ embeddings[v0 + offset, v1] = weight[pos[v0], v1]
+
+ class Model(Module):
+ def test(
+ self, embedding_table: Tensor, input_ids: Tensor, embedding_dst:
Tensor, offset: int
+ ):
+ tensor_expr_op_out = op.tensor_ir_op(
Review Comment:
No worries, I was just hoping to use this PR to guide my use of
`nn.op.tensor_ir_inplace_op` but then became nervous about using the feature
when I saw it wasn't tested. I haven't made any change to update the test and
would appreciate the update whenever you have cycles to come back to this. It's
not blocking me though, so low priority is fine. Thanks @MasterJH5574
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