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fix big tensor gpu monitor config #599

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Merged
Zeref996 merged 1 commit into from
Dec 24, 2025
Merged

fix big tensor gpu monitor config #599

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13 changes: 0 additions & 13 deletions tester/api_config/monitor_config/big_tensor/GPU/monitoring_configs.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -708,7 +708,6 @@ paddle.Tensor.nansum(Tensor([477218589, 3, 3],"float16"), axis=-1, )
paddle.Tensor.nansum(Tensor([477218589, 3, 3],"float16"), axis=0, keepdim=True, )
paddle.Tensor.neg(Tensor([2281701379],"float32"), )
paddle.Tensor.nonzero(Tensor([2281701379],"bool"), )
paddle.Tensor.nonzero(Tensor([253522376, 9],"bool"), )
paddle.Tensor.nonzero(Tensor([380283564, 6],"bool"), )
paddle.Tensor.nonzero(Tensor([429496730, 10],"bool"), )
paddle.Tensor.nonzero(Tensor([456340276, 5],"bool"), )
Expand Down Expand Up @@ -1251,7 +1250,6 @@ paddle.broadcast_tensors(input=list[Tensor([63380594, 6, 6],"bool"),Tensor([6338
paddle.broadcast_tensors(list[Tensor([12, 35791395, 10, 1],"float16"),Tensor([12, 1, 10, 1],"float16"),], )
paddle.bucketize(Tensor([1073741825, 4],"float16"), Tensor([4],"float16"), out_int32=True, )
paddle.bucketize(Tensor([1073741825, 4],"float16"), Tensor([4],"float16"), right=True, )
paddle.bucketize(Tensor([2, 2147483649],"float16"), Tensor([2147483649],"float16"), )
paddle.bucketize(Tensor([2, 2147483649],"float16"), Tensor([2147483649],"float16"), right=True, )
paddle.bucketize(Tensor([2, 2147483649],"float16"), Tensor([4],"float16"), )
paddle.bucketize(Tensor([2, 2147483649],"float16"), Tensor([4],"float16"), out_int32=True, )
Expand Down Expand Up @@ -1631,7 +1629,6 @@ paddle.geometric.send_uv(Tensor([214748365, 20],"float16"), Tensor([214748365, 2
paddle.greater_equal(Tensor([380283564, 3, 2],"float16"), Tensor([380283564, 3, 2],"float32"), )
paddle.greater_equal(Tensor([380283564, 3, 2],"float32"), Tensor([380283564, 3, 2],"float64"), )
paddle.greater_equal(Tensor([4, 3, 357913942],"float32"), Tensor([4, 3, 357913942],"float16"), )
paddle.greater_equal(Tensor([715827883, 3, 2],"float16"), Tensor([715827883, 3, 2],"float64"), )
paddle.greater_equal(Tensor([715827883, 3, 2],"float32"), Tensor([715827883, 3, 2],"float16"), )
paddle.greater_equal(Tensor([715827883, 3, 2],"float64"), Tensor([715827883, 3, 2],"float16"), )
paddle.greater_than(Tensor([4, 285212673, 2],"float16"), Tensor([4, 285212673, 2],"float32"), )
Expand Down Expand Up @@ -1661,7 +1658,6 @@ paddle.histogram(input=Tensor([570425345, 4],"int32"), )
paddle.hsplit(Tensor([126761188, 6, 3],"int64"), 2, )
paddle.hsplit(Tensor([126761188, 6, 3],"int64"), 3, )
paddle.hsplit(Tensor([380283564, 6],"int64"), 2, )
paddle.hsplit(Tensor([380283564, 6],"int64"), 3, )
paddle.hsplit(Tensor([4, 190141782, 3],"int64"), 2, )
paddle.hsplit(Tensor([4, 190141782, 3],"int64"), 3, )
paddle.hsplit(Tensor([4, 6, 95070891],"int64"), 2, )
Expand Down Expand Up @@ -1764,7 +1760,6 @@ paddle.index_sample(Tensor([2, 2147483649],"float16"), Tensor([2, 1],"int64"), )
paddle.index_sample(Tensor([2, 250880],"float16"), Tensor([2, 1140850690],"int64"), )
paddle.index_sample(Tensor([2, 99],"float16"), Tensor([2, 1140850690],"int64"), )
paddle.index_sample(Tensor([5460096, 20],"float16"), Tensor([5460096, 418],"int64"), )
paddle.index_sample(Tensor([831232, 5167],"float16"), Tensor([831232, 2745],"int64"), )
paddle.index_sample(Tensor([932832, 4605],"float16"), Tensor([932832, 2446],"int64"), )
paddle.index_select(Tensor([1431655766, 3],"float16"), Tensor([2401],"int64"), )
paddle.index_select(Tensor([357913942, 12],"float16"), Tensor([2401],"int64"), )
Expand Down Expand Up @@ -2112,7 +2107,6 @@ paddle.median(x=Tensor([142606337, 4, 4],"float32"), axis=1, keepdim=False, )
paddle.meshgrid(list[Tensor([1],"float32"),Tensor([1],"float32"),Tensor([2281701379],"float32"),], )
paddle.meshgrid(list[Tensor([1],"float32"),Tensor([2281701379],"float32"),Tensor([1],"float32"),], )
paddle.meshgrid(list[Tensor([2281701379],"float32"),Tensor([1],"float32"),Tensor([1],"float32"),], )
paddle.min(Tensor([10, 5, 9544372, 9],"float16"), Tensor([2],"int64"), )
paddle.min(Tensor([10, 5302429, 9, 9],"float16"), Tensor([2],"int64"), )
paddle.min(Tensor([1073741825, 4],"float16"), None, False, )
paddle.min(Tensor([1073741825, 4],"float16"), axis=0, )
Expand Down Expand Up @@ -2324,10 +2318,8 @@ paddle.nn.functional.conv3d_transpose(Tensor([4, 8, 8, 8, 4],"float32"), Tensor(
paddle.nn.functional.conv3d_transpose(Tensor([4, 8, 8, 8, 4],"float32"), Tensor([4, 3, 3, 3, 21126865],"float32"), None, output_size=None, padding="same", stride=1, dilation=1, groups=2, data_format="NDHWC", )
paddle.nn.functional.conv3d_transpose(x=Tensor([2, 2, 2, 2, 3],"float32"), weight=Tensor([3, 1, 3, 84507459, 3],"float32"), bias=Tensor([3],"float32"), stride=1, padding=list[1,0,1,], groups=3, data_format="NDHWC", dilation=1, )
paddle.nn.functional.conv3d_transpose(x=Tensor([2, 3, 2, 2, 2],"float32"), weight=Tensor([3, 1, 3, 84507459, 3],"float32"), bias=Tensor([3],"float32"), stride=1, padding=list[1,0,1,], groups=3, dilation=1, )
paddle.nn.functional.cosine_similarity(Tensor([1, 5, 508993460],"float32"), Tensor([1, 5, 508993460],"float32"), axis=-1, eps=1e-08, )
paddle.nn.functional.cosine_similarity(Tensor([10, 12, 19014179],"float32"), Tensor([10, 1, 19014179],"float32"), axis=2, eps=1e-06, )
paddle.nn.functional.cosine_similarity(Tensor([175515491, 13],"float32"), Tensor([175515491, 13],"float32"), axis=0, eps=1e-06, )
paddle.nn.functional.cosine_similarity(Tensor([230496730, 5, 2],"float32"), Tensor([1, 5, 2],"float32"), axis=-2, eps=1e-08, )
paddle.nn.functional.cosine_similarity(Tensor([230496730, 5, 2],"float32"), Tensor([230496730, 5, 2],"float32"), axis=0, eps=1e-08, )
paddle.nn.functional.cross_entropy(Tensor([102, 22369622],"float32"), Tensor([102, 1],"int64"), weight=None, ignore_index=-1, reduction="sum", soft_label=False, axis=-1, use_softmax=True, label_smoothing=0.0, name=None, )
paddle.nn.functional.cross_entropy(Tensor([102, 42107523],"float16"), Tensor([102, 1],"int64"), weight=None, ignore_index=-1, reduction="none", soft_label=False, axis=-1, use_softmax=True, label_smoothing=0.0, name=None, )
Expand Down Expand Up @@ -2599,8 +2591,6 @@ paddle.nn.functional.normalize(Tensor([224, 19173962],"float16"), )
paddle.nn.functional.npair_loss(Tensor([18, 126761188],"float32"), positive=Tensor([18, 126761188],"float32"), labels=Tensor([18],"float32"), l2_reg=0.002, )
paddle.nn.functional.one_hot(Tensor([1, 2281701379],"int64"), 3, )
paddle.nn.functional.one_hot(Tensor([1140850690, 2],"int64"), num_classes=2, )
paddle.nn.functional.one_hot(Tensor([130, 17551550],"int64"), num_classes=2, )
paddle.nn.functional.one_hot(Tensor([14, 2, 40744668, 2],"int64"), 3, )
paddle.nn.functional.one_hot(Tensor([14, 20372334, 4, 2],"int64"), 3, )
paddle.nn.functional.one_hot(Tensor([2281701379, 1],"int64"), 2, )
paddle.nn.functional.one_hot(Tensor([2281701379],"int64"), num_classes=2, )
Expand Down Expand Up @@ -2822,9 +2812,7 @@ paddle.nn.utils.vector_to_parameters(Tensor([2281701379],"float32"), list[Tensor
paddle.nn.utils.vector_to_parameters(Tensor([2281701379],"float32"), list[Tensor([3, 2, 4],"float32"),Tensor([3],"float32"),], )
paddle.nn.utils.vector_to_parameters(Tensor([2281701379],"float32"), list[Tensor([48, 8],"float32"),Tensor([48, 16],"float32"),Tensor([48],"float32"),Tensor([48],"float32"),Tensor([48, 16],"float32"),Tensor([48, 16],"float32"),Tensor([48],"float32"),Tensor([48],"float32"),], )
paddle.nn.utils.vector_to_parameters(Tensor([2281701379],"float32"), list[Tensor([64, 8],"float32"),Tensor([64, 16],"float32"),Tensor([64],"float32"),Tensor([64],"float32"),Tensor([64, 16],"float32"),Tensor([64, 16],"float32"),Tensor([64],"float32"),Tensor([64],"float32"),], )
paddle.nonzero(Tensor([10, 228170138],"bool"), )
paddle.nonzero(Tensor([11641334, 196],"float32"), )
paddle.nonzero(Tensor([1455167, 2, 28, 28],"float32"), )
paddle.nonzero(Tensor([145517, 80, 14, 14],"float32"), )
paddle.nonzero(Tensor([22817014, 100],"float32"), )
paddle.nonzero(x=Tensor([81489335, 4, 7],"float32"), )
Expand Down Expand Up @@ -3140,7 +3128,6 @@ paddle.tile(Tensor([216, 248, 1, 21298, 2],"float32"), list[1,1,1,1,1,], )
paddle.tile(Tensor([216, 5281717, 1, 1, 2],"float32"), list[1,1,1,1,1,], )
paddle.tile(Tensor([8388609, 8, 1, 1, 64],"float16"), list[1,1,1,1,1,], )
paddle.tolist(Tensor([2, 1140850690],"float32"), )
paddle.tolist(Tensor([2, 1140850690],"int64"), )
paddle.topk(Tensor([100, 22817014],"float32"), 10, axis=0, )
paddle.topk(Tensor([13091, 174296],"float32"), 2, axis=-1, )
paddle.topk(Tensor([2, 1140850690],"float32"), 2, axis=-1, )
Expand Down