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Searched refs:style_loss (Results 1 – 8 of 8) sorted by relevance

/dports/misc/mxnet/incubator-mxnet-1.9.0/example/gluon/style_transfer/
H A Dmain.py91 style_loss = 0.
96 style_loss = style_loss + 2 * args.style_weight * \
99 total_loss = content_loss + style_loss
106 agg_style_loss += style_loss[0]
190 style_loss = 0.
194 style_loss = style_loss + 2 * args.style_weight * mse_loss(gram_y, gram_s)
195 total_loss = content_loss + style_loss
/dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/gluon/style_transfer/
H A Dmain.py91 style_loss = 0.
96 style_loss = style_loss + 2 * args.style_weight * \
99 total_loss = content_loss + style_loss
106 agg_style_loss += style_loss[0]
190 style_loss = 0.
194 style_loss = style_loss + 2 * args.style_weight * mse_loss(gram_y, gram_s)
195 total_loss = content_loss + style_loss
/dports/math/py-keras/Keras-2.4.3/examples/
H A Dneural_style_transfer.py171 def style_loss(style, combination): function
222 sl = style_loss(style_reference_features, combination_features)
H A Dneural_doodle.py258 def style_loss(style_image, target_image, style_masks, target_masks): function
311 sl = style_loss(style_feat, target_feat, style_masks, target_masks)
/dports/misc/mxnet/incubator-mxnet-1.9.0/example/neural-style/end_to_end/
H A Dbasic.py97 style_loss, content_loss = get_loss(gram, content)
98 sym = mx.sym.Group([style_loss, content_loss])
/dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/neural-style/end_to_end/
H A Dbasic.py97 style_loss, content_loss = get_loss(gram, content)
98 sym = mx.sym.Group([style_loss, content_loss])
/dports/misc/mxnet/incubator-mxnet-1.9.0/example/neural-style/
H A Dnstyle.py198 style_loss, content_loss = get_loss(gram, content)
200 style_loss, content_loss, size, dev)
/dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/neural-style/
H A Dnstyle.py198 style_loss, content_loss = get_loss(gram, content)
200 style_loss, content_loss, size, dev)