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Fix lint
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echuraev committed Jun 8, 2022
1 parent edd94cb commit 3d468cf
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Showing 3 changed files with 12 additions and 8 deletions.
4 changes: 3 additions & 1 deletion python/tvm/topi/adreno/conv2d_nchw_winograd.py
Original file line number Diff line number Diff line change
Expand Up @@ -137,4 +137,6 @@ def conv2d_nchw_winograd_comp(
output: tvm.te.Tensor
4-D or 5-D with shape NCHW or NCHW4c
"""
return conv2d_winograd_comp(cfg, data, kernel, strides, padding, dilation, out_dtype, args, pre_computed, "NCHW")
return conv2d_winograd_comp(
cfg, data, kernel, strides, padding, dilation, out_dtype, args, pre_computed, "NCHW"
)
4 changes: 3 additions & 1 deletion python/tvm/topi/adreno/conv2d_nhwc_winograd.py
Original file line number Diff line number Diff line change
Expand Up @@ -137,4 +137,6 @@ def conv2d_nhwc_winograd_comp(
output: tvm.te.Tensor
4-D or 5-D with shape NCHW or NCHW4c
"""
return conv2d_winograd_comp(cfg, data, kernel, strides, padding, dilation, out_dtype, args, pre_computed, "NHWC")
return conv2d_winograd_comp(
cfg, data, kernel, strides, padding, dilation, out_dtype, args, pre_computed, "NHWC"
)
12 changes: 6 additions & 6 deletions python/tvm/topi/adreno/conv2d_winograd_common.py
Original file line number Diff line number Diff line change
Expand Up @@ -301,9 +301,9 @@ def conv2d_winograd_comp(
else:
output = te.compute(
(N, CO, H, W, COB),
lambda n, co, h, w, cob: inverse[co][n * nH * nW + idxdiv(h, m) * nW + idxdiv(w, m)][
idxmod(h, m)
][idxmod(w, m)][cob].astype(out_dtype),
lambda n, co, h, w, cob: inverse[co][
n * nH * nW + idxdiv(h, m) * nW + idxdiv(w, m)
][idxmod(h, m)][idxmod(w, m)][cob].astype(out_dtype),
name="output",
tag="cast_from_acc" + args["accumulator"][-2:],
)
Expand All @@ -320,9 +320,9 @@ def conv2d_winograd_comp(
else:
output = te.compute(
(N, H, W, CO, COB),
lambda n, h, w, co, cob: inverse[co][n * nH * nW + idxdiv(h, m) * nW + idxdiv(w, m)][
idxmod(h, m)
][idxmod(w, m)][cob].astype(out_dtype),
lambda n, h, w, co, cob: inverse[co][
n * nH * nW + idxdiv(h, m) * nW + idxdiv(w, m)
][idxmod(h, m)][idxmod(w, m)][cob].astype(out_dtype),
name="output",
tag="cast_from_acc" + args["accumulator"][-2:],
)
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