From 000b16c8c3fa90f5c10e36bfbcf63a9a8a98d067 Mon Sep 17 00:00:00 2001 From: co63oc Date: Wed, 18 Jun 2025 13:25:48 +0800 Subject: [PATCH] Fix --- .../5_accuracy/accuracy_gpu_error_grads_diff.txt | 14 ++++++++++++++ 1 file changed, 14 insertions(+) diff --git a/tester/api_config/5_accuracy/accuracy_gpu_error_grads_diff.txt b/tester/api_config/5_accuracy/accuracy_gpu_error_grads_diff.txt index af3b5af23..35009e91a 100644 --- a/tester/api_config/5_accuracy/accuracy_gpu_error_grads_diff.txt +++ b/tester/api_config/5_accuracy/accuracy_gpu_error_grads_diff.txt @@ -15945,3 +15945,17 @@ paddle.nn.functional.binary_cross_entropy_with_logits(logit=Tensor([256],"float3 paddle.nn.functional.binary_cross_entropy_with_logits(logit=Tensor([512],"float32"), label=Tensor([512],"float32"), reduction="sum", ) paddle.nn.functional.binary_cross_entropy_with_logits(logit=Tensor([64, 19],"float32"), label=Tensor([64, 19],"float32"), reduction="none", ) paddle.nn.functional.binary_cross_entropy_with_logits(logit=Tensor([64, 26],"float32"), label=Tensor([64, 26],"float32"), reduction="none", ) +paddle.nn.functional.kl_div(Tensor([40, 20, 50],"float32"), Tensor([40, 20, 50],"float32"), "batchmean", False, ) +paddle.nn.functional.kl_div(Tensor([40, 20, 50],"float32"), Tensor([40, 20, 50],"float32"), "batchmean", True, ) +paddle.nn.functional.kl_div(Tensor([40, 20, 50],"float32"), Tensor([40, 20, 50],"float32"), "none", False, ) +paddle.nn.functional.kl_div(Tensor([5, 20],"float32"), Tensor([5, 20],"float64"), "mean", False, ) +paddle.nn.functional.kl_div(Tensor([5, 20],"float64"), Tensor([5, 20],"float32"), ) +paddle.nn.functional.kl_div(Tensor([5, 20],"float64"), Tensor([5, 20],"float64"), "batchmean", False, ) +paddle.nn.functional.kl_div(Tensor([5, 20],"float64"), Tensor([5, 20],"float64"), "mean", False, ) +paddle.nn.functional.kl_div(Tensor([5, 20],"float64"), Tensor([5, 20],"float64"), "mean", True, ) +paddle.nn.functional.kl_div(Tensor([5, 20],"float64"), Tensor([5, 20],"float64"), "none", False, ) +paddle.nn.functional.kl_div(Tensor([5, 20],"float64"), Tensor([5, 20],"float64"), "sum", False, ) +paddle.nn.functional.kl_div(Tensor([5, 2],"float32"), label=Tensor([5, 2],"float32"), reduction="mean", name=None, ) +paddle.nn.functional.kl_div(Tensor([5, 2],"float64"), Tensor([5, 2],"float64"), "mean", False, ) +paddle.nn.functional.kl_div(Tensor([],"float64"), Tensor([],"float64"), "batchmean", False, ) +paddle.nn.functional.kl_div(input=Tensor([32, 128, 128],"float32"), label=Tensor([32, 128, 128],"float32"), reduction="batchmean", )