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Update argument order for relax.op.pad to make it round-trippable #17657

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Merged
Hzfengsy merged 5 commits into from
Feb 17, 2025
Merged

Update argument order for relax.op.pad to make it round-trippable #17657

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71145a8
Update argument order for relax.op.pad to make it round-trippable
yongwww Feb 16, 2025
49e6e30
fix lint
yongwww Feb 16, 2025
b8d6c7c
Fix inconsistent IR when printing R.nn.pad operator
parsifal-47 Jan 26, 2025
5e5df02
Change value to be the last arg
yongwww Feb 16, 2025
94fc661
Fix lint
yongwww Feb 17, 2025
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Fix lint
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@yongwww
yongwww committed Feb 17, 2025
commit 94fc6619e8456ba4bc61784cb1149a96201cb7fe
2 changes: 1 addition & 1 deletion python/tvm/relax/frontend/nn/op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1567,7 +1567,7 @@ def get_timestep_embedding(

# Zero pad
if embedding_dim % 2 == 1:
emb = _op.nn.pad(emb, 0, (0, 1, 0, 0))
emb = _op.nn.pad(emb, (0, 1, 0, 0))

# Cast to proper output type
emb = _op.astype(emb, dtype)
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2 changes: 1 addition & 1 deletion python/tvm/relax/op/nn/nn.py
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Expand Up @@ -20,7 +20,7 @@
from tvm import DataType
from tvm.tir import FloatImm

from ...expr import Expr, const
from ...expr import Expr
from . import _ffi_api


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10 changes: 6 additions & 4 deletions tests/python/relax/test_frontend_nn_op.py
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Expand Up @@ -293,7 +293,9 @@ def test(self, x: Tensor):
return chunk

@R.function
def test(x: R.Tensor((8,), dtype="float32"), _io: R.Object) -> R.Tuple(
def test(
x: R.Tensor((8,), dtype="float32"), _io: R.Object
) -> R.Tuple(
R.Tuple(
R.Tensor((2,), dtype="float32"),
R.Tensor((2,), dtype="float32"),
Expand Down Expand Up @@ -488,9 +490,9 @@ def test(
) -> R.Tuple(R.Tensor((1, 32, 32, 32), dtype="float32"), R.Tuple(R.Object)):
R.func_attr({"num_input": 4})
with R.dataflow():
scaled_dot_product_attention: R.Tensor((1, 32, 32, 32), dtype="float32") = (
R.nn.attention(query, key, value, scale=None, causal_mask=None)
)
scaled_dot_product_attention: R.Tensor(
(1, 32, 32, 32), dtype="float32"
) = R.nn.attention(query, key, value, scale=None, causal_mask=None)
gv1: R.Tuple(R.Tensor((1, 32, 32, 32), dtype="float32"), R.Tuple(R.Object)) = (
scaled_dot_product_attention,
(_io,),
Expand Down