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[Topi, ARM] Disbale Winograd for quantized tensors. #5363

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merged 2 commits into from Apr 21, 2020
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[Topi, ARM] Disbale Winograd for quantized tensors. #5363

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[Topi, ARM] Disbale Winograd for quantized tensors.
anijain2305 Apr 17, 2020
cae36cd
Relaxing float
anijain2305 Apr 20, 2020
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9 changes: 7 additions & 2 deletions python/tvm/relay/op/strategy/arm_cpu.py
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Expand Up @@ -59,16 +59,21 @@ def conv2d_strategy_arm_cpu(attrs, inputs, out_type, target):
wrap_compute_conv2d(topi.arm_cpu.conv2d_nchw_spatial_pack),
wrap_topi_schedule(topi.arm_cpu.schedule_conv2d_nchw_spatial_pack),
name="conv2d_nchw_spatial_pack.arm_cpu")

# Intel x86 conv2d schedule.
strategy.add_implementation(
wrap_compute_conv2d(topi.x86.conv2d_nchw),
wrap_topi_schedule(topi.x86.schedule_conv2d_nchw),
name="conv2d_nchw.x86")

# check if winograd algorithm is applicable
_, _, kh, kw = get_const_tuple(kernel.shape)
pt, pl, pb, pr = topi.nn.get_pad_tuple(padding, (kh, kw))
if kh == 3 and kw == 3 and stride_h == 1 and stride_w == 1 and \
dilation_h == 1 and dilation_w == 1:
is_dtype_fp32 = data.dtype == "float32" and kernel.dtype == "float32"
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Float16 Too ? (perhaps double aka float64 too)
I get good results with it (e.g yolov3-tiny on mali).
Wouldn't be better to deny int8/int16/int32 ?

is_winograd_applicable = kh == 3 and kw == 3 and \
stride_h == 1 and stride_w == 1 and \
dilation_h == 1 and dilation_w == 1
if is_dtype_fp32 and is_winograd_applicable:
strategy.add_implementation(
wrap_compute_conv2d(topi.arm_cpu.conv2d_nchw_winograd),
wrap_topi_schedule(topi.arm_cpu.schedule_conv2d_nchw_winograd),
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