@@ -15945,3 +15945,17 @@ paddle.nn.functional.binary_cross_entropy_with_logits(logit=Tensor([256],"float3
1594515945paddle.nn.functional.binary_cross_entropy_with_logits(logit=Tensor([512],"float32"), label=Tensor([512],"float32"), reduction="sum", )
1594615946paddle.nn.functional.binary_cross_entropy_with_logits(logit=Tensor([64, 19],"float32"), label=Tensor([64, 19],"float32"), reduction="none", )
1594715947paddle.nn.functional.binary_cross_entropy_with_logits(logit=Tensor([64, 26],"float32"), label=Tensor([64, 26],"float32"), reduction="none", )
15948+ paddle.nn.functional.kl_div(Tensor([40, 20, 50],"float32"), Tensor([40, 20, 50],"float32"), "batchmean", False, )
15949+ paddle.nn.functional.kl_div(Tensor([40, 20, 50],"float32"), Tensor([40, 20, 50],"float32"), "batchmean", True, )
15950+ paddle.nn.functional.kl_div(Tensor([40, 20, 50],"float32"), Tensor([40, 20, 50],"float32"), "none", False, )
15951+ paddle.nn.functional.kl_div(Tensor([5, 20],"float32"), Tensor([5, 20],"float64"), "mean", False, )
15952+ paddle.nn.functional.kl_div(Tensor([5, 20],"float64"), Tensor([5, 20],"float32"), )
15953+ paddle.nn.functional.kl_div(Tensor([5, 20],"float64"), Tensor([5, 20],"float64"), "batchmean", False, )
15954+ paddle.nn.functional.kl_div(Tensor([5, 20],"float64"), Tensor([5, 20],"float64"), "mean", False, )
15955+ paddle.nn.functional.kl_div(Tensor([5, 20],"float64"), Tensor([5, 20],"float64"), "mean", True, )
15956+ paddle.nn.functional.kl_div(Tensor([5, 20],"float64"), Tensor([5, 20],"float64"), "none", False, )
15957+ paddle.nn.functional.kl_div(Tensor([5, 20],"float64"), Tensor([5, 20],"float64"), "sum", False, )
15958+ paddle.nn.functional.kl_div(Tensor([5, 2],"float32"), label=Tensor([5, 2],"float32"), reduction="mean", name=None, )
15959+ paddle.nn.functional.kl_div(Tensor([5, 2],"float64"), Tensor([5, 2],"float64"), "mean", False, )
15960+ paddle.nn.functional.kl_div(Tensor([],"float64"), Tensor([],"float64"), "batchmean", False, )
15961+ paddle.nn.functional.kl_div(input=Tensor([32, 128, 128],"float32"), label=Tensor([32, 128, 128],"float32"), reduction="batchmean", )
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