lhutton1 commented on code in PR #15648:
URL: https://github.com/apache/tvm/pull/15648#discussion_r1315667771
##########
python/tvm/topi/arm_cpu/conv2d_gemm.py:
##########
@@ -428,12 +435,29 @@ def schedule_conv2d_gemm_native(cfg, s, out, final_out):
b, m, n = data_im2col.op.axis
if data_im2col.op.name == "data_im2col":
- n_outer, n_inner = s[data_im2col].split(n, 16)
+ if A.op.name == "A_padded_K":
+ s[data_im2col].compute_at(s[A], A.op.axis[1])
+ s[A].parallel(A.op.axis[1])
+ elif A.op.name == "A_padded_M":
+ s[data_im2col].parallel(m)
+ s[A].parallel(A.op.axis[1])
+ else:
+ s[data_im2col].parallel(m)
+
+ split_factor = 16
+ n_size = data_im2col.shape[2]
+ if n_size % split_factor != 0:
+ # Split by kernel area (KH * KW) to ensure proper vectorization
+ ic = data_im2col.op.input_tensors[0].shape[3]
+ split_factor = n_size // ic
+
+ n_outer, n_inner = s[data_im2col].split(n, split_factor)
s[data_im2col].unroll(n_outer)
s[data_im2col].vectorize(n_inner)
- s[data_im2col].parallel(m)
elif padding_A:
s[data_im2col].compute_inline()
+ _, n_inner = s[A].split(A.op.axis[2], 16)
Review Comment:
For the 16 here, let's make it a variable to maintain the link to
https://github.com/apache/tvm/pull/15648/files#diff-42b1313a1be464c7f2c94f75d656be725f1ccb54b9391cd5b27c33009ac0e2d5R421
##########
python/tvm/topi/arm_cpu/conv2d_gemm.py:
##########
@@ -326,7 +328,12 @@ def schedule_conv2d_gemm_interleaved(cfg, s, out,
final_out):
b, m, n = data_im2col.op.axis
if data_im2col.op.name == "data_im2col":
- n_outer, n_inner = s[data_im2col].split(n, 16)
+ n_size = data_im2col.shape[2]
+ if n_size % 16 == 0:
+ split_factor = 16
+ else:
+ split_factor = 8
+ n_outer, n_inner = s[data_im2col].split(n, split_factor)
Review Comment:
nit: as its a separate change, could it be split into a new PR?
##########
python/tvm/topi/arm_cpu/conv2d_gemm.py:
##########
@@ -428,12 +435,29 @@ def schedule_conv2d_gemm_native(cfg, s, out, final_out):
b, m, n = data_im2col.op.axis
if data_im2col.op.name == "data_im2col":
- n_outer, n_inner = s[data_im2col].split(n, 16)
+ if A.op.name == "A_padded_K":
Review Comment:
would be good to add a comment here stating that if there are both
"padding_K" and "padding_M" ops, this path will be selected
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