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[TOPI] Setting workload correctly for Depthwise Spatial conv ARM. #5182

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Mar 31, 2020
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[TOPI] Setting workload correctly for Depthwise Spatial conv ARM. #5182

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4 changes: 2 additions & 2 deletions topi/python/topi/arm_cpu/conv2d_alter_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -154,14 +154,14 @@ def _alter_conv2d_layout(attrs, inputs, tinfos, out_type):
if topi_tmpl == "depthwise_conv2d_nchw_spatial_pack.arm_cpu":
assert data_layout == "NCHW" and kernel_layout == "OIHW"
N, CI, H, W = get_const_tuple(data.shape)
CO, _, KH, KW = get_const_tuple(kernel.shape)
CO, M, KH, KW = get_const_tuple(kernel.shape)
VC = cfg['tile_co'].size[-1]

new_attrs['kernel_layout'] = 'OIHW%do' % (cfg['tile_co'].size[-1])

# Store the same config for the altered operator (workload)
new_data = data
new_kernel = te.placeholder((idxd(CO, VC), CI, KH, KW, VC), dtype=kernel.dtype)
new_kernel = te.placeholder((idxd(CO, VC), M, KH, KW, VC), dtype=kernel.dtype)
new_workload = autotvm.task.args_to_workload(
[new_data, new_kernel, strides, padding, dilation, out_dtype],
"depthwise_conv2d_nchw_spatial_pack.arm_cpu")
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