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New TensorFlow TFCrossConv() module (#7827)

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* New TensorFlow `TFCrossConv()` module

* Move from experimental to common

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* Add C3x

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* Add to C3x to yolo.py

* Add to C3x to tf.py

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* TFC3x bug fix

* TFC3x bug fix

* TFC3x bug fix

* Add TFDWConv g==c1==c2 check

* Add comment

* Update tf.py

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Glenn Jocherandpre-commit-ci[bot] authored and GitHub committed 2022-05-16 17:02:16 +02:00
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commit fb7fa5be8b
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+64 -28
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models/yolo.py
+2 -2
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@@ -266,13 +266,13 @@ def parse_model(d, ch): # model_dict, input_channels(3)
n = n_ = max(round(n * gd), 1) if n > 1 else n # depth gain
if m in (Conv, GhostConv, Bottleneck, GhostBottleneck, SPP, SPPF, DWConv, MixConv2d, Focus, CrossConv,
BottleneckCSP, C3, C3TR, C3SPP, C3Ghost):
BottleneckCSP, C3, C3TR, C3SPP, C3Ghost, C3x):
c1, c2 = ch[f], args[0]
if c2 != no: # if not output
c2 = make_divisible(c2 * gw, 8)
args = [c1, c2, *args[1:]]
if m in [BottleneckCSP, C3, C3TR, C3Ghost]:
if m in [BottleneckCSP, C3, C3TR, C3Ghost, C3x]:
args.insert(2, n) # number of repeats
n = 1
elif m is nn.BatchNorm2d: