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[0-size Tensor No.203] Add 0-size Tensor support for paddle.nn.functional.multi_margin_loss #341

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Merged
cangtianhuang merged 2 commits into from
Jun 30, 2025
Merged

[0-size Tensor No.203] Add 0-size Tensor support for paddle.nn.functional.multi_margin_loss #341

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10cd7e4
Fix
co63oc Jun 30, 2025
5c25c4c
Fix
co63oc Jun 30, 2025
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1 change: 0 additions & 1 deletion report/0size_tensor_cpu/error_api.txt
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Expand Up @@ -148,7 +148,6 @@ paddle.nn.functional.margin_cross_entropy
paddle.nn.functional.max_pool1d
paddle.nn.functional.max_pool3d
paddle.nn.functional.max_unpool2d
paddle.nn.functional.multi_margin_loss
paddle.nn.functional.nll_loss
paddle.nn.functional.pad
paddle.nn.functional.pixel_shuffle
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4 changes: 0 additions & 4 deletions report/0size_tensor_cpu/error_config.txt
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Expand Up @@ -8043,10 +8043,6 @@ paddle.nn.functional.max_unpool2d(Tensor([2, 4, 11, 0],"float64"), Tensor([2, 4,
paddle.nn.functional.max_unpool2d(Tensor([2, 4, 11, 0],"float64"), Tensor([2, 4, 11, 11],"int32"), kernel_size=4, stride=None, padding=2, data_format="NCHW", output_size=None, name=None, )
paddle.nn.functional.max_unpool2d(Tensor([2, 4, 21, 0],"float32"), Tensor([2, 4, 21, 0],"int32"), kernel_size=4, stride=2, padding=2, data_format="NCHW", output_size=None, name=None, )
paddle.nn.functional.max_unpool2d(Tensor([2, 4, 21, 0],"float32"), Tensor([2, 4, 21, 21],"int32"), kernel_size=4, stride=2, padding=2, data_format="NCHW", output_size=None, name=None, )
paddle.nn.functional.multi_margin_loss(Tensor([5, 0],"float64"), Tensor([5],"int64"), p=1, margin=1.0, weight=Tensor([2],"float64"), reduction="mean", name=None, )
paddle.nn.functional.multi_margin_loss(Tensor([5, 0],"float64"), Tensor([5],"int64"), p=2, margin=1.0, weight=None, reduction="mean", name=None, )
paddle.nn.functional.multi_margin_loss(input=Tensor([5, 0],"float64"), label=Tensor([5],"int64"), p=1, margin=1.0, weight=Tensor([2],"float64"), reduction="mean", )
paddle.nn.functional.multi_margin_loss(input=Tensor([5, 0],"float64"), label=Tensor([5],"int64"), p=2, margin=1.0, weight=None, reduction="mean", )
paddle.nn.functional.nll_loss(Tensor([10, 0],"float64"), Tensor([10],"int64"), weight=None, ignore_index=-100, reduction="mean", name=None, )
paddle.nn.functional.nll_loss(Tensor([10, 0],"float64"), Tensor([10],"int64"), weight=None, ignore_index=-100, reduction="sum", name=None, )
paddle.nn.functional.nll_loss(Tensor([10, 0],"float64"), Tensor([10],"int64"), weight=Tensor([10],"float64"), ignore_index=-100, reduction="mean", name=None, )
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1 change: 0 additions & 1 deletion report/0size_tensor_gpu/error_api.txt
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Expand Up @@ -223,7 +223,6 @@ paddle.nn.functional.max_unpool2d
paddle.nn.functional.max_unpool3d
paddle.nn.functional.maxout
paddle.nn.functional.mse_loss
paddle.nn.functional.multi_margin_loss
paddle.nn.functional.nll_loss
paddle.nn.functional.normalize
paddle.nn.functional.one_hot
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1 change: 0 additions & 1 deletion report/0size_tensor_gpu/error_api_paddleonly.txt
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Expand Up @@ -75,7 +75,6 @@ paddle.nn.functional.max_unpool2d
paddle.nn.functional.max_unpool3d
paddle.nn.functional.maxout
paddle.nn.functional.mse_loss
paddle.nn.functional.multi_margin_loss
paddle.nn.functional.pad
paddle.nn.functional.pixel_shuffle
paddle.nn.functional.pixel_unshuffle
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4 changes: 0 additions & 4 deletions report/0size_tensor_gpu/error_config.txt
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Expand Up @@ -11530,10 +11530,6 @@ paddle.nn.functional.mse_loss(Tensor([8, 32, 0, 256],"float16"), Tensor([8, 32,
paddle.nn.functional.mse_loss(Tensor([8, 32, 256, 0],"float16"), Tensor([8, 32, 256, 0],"float16"), reduction="sum", )
paddle.nn.functional.mse_loss(Tensor([8, 64, 0, 128],"float16"), Tensor([8, 64, 0, 128],"float16"), reduction="sum", )
paddle.nn.functional.mse_loss(Tensor([8, 64, 128, 0],"float16"), Tensor([8, 64, 128, 0],"float16"), reduction="sum", )
paddle.nn.functional.multi_margin_loss(Tensor([5, 0],"float64"), Tensor([5],"int64"), p=1, margin=1.0, weight=Tensor([2],"float64"), reduction="mean", name=None, )
paddle.nn.functional.multi_margin_loss(Tensor([5, 0],"float64"), Tensor([5],"int64"), p=2, margin=1.0, weight=None, reduction="mean", name=None, )
paddle.nn.functional.multi_margin_loss(input=Tensor([5, 0],"float64"), label=Tensor([5],"int64"), p=1, margin=1.0, weight=Tensor([2],"float64"), reduction="mean", )
paddle.nn.functional.multi_margin_loss(input=Tensor([5, 0],"float64"), label=Tensor([5],"int64"), p=2, margin=1.0, weight=None, reduction="mean", )
paddle.nn.functional.nll_loss(Tensor([10, 0],"float64"), Tensor([10],"int64"), weight=None, ignore_index=-100, reduction="mean", name=None, )
paddle.nn.functional.nll_loss(Tensor([10, 0],"float64"), Tensor([10],"int64"), weight=None, ignore_index=-100, reduction="sum", name=None, )
paddle.nn.functional.nll_loss(Tensor([10, 0],"float64"), Tensor([10],"int64"), weight=Tensor([10],"float64"), ignore_index=-100, reduction="mean", name=None, )
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6 changes: 0 additions & 6 deletions report/0size_tensor_gpu/error_config_paddleonly.txt
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Expand Up @@ -4579,12 +4579,6 @@ paddle.nn.functional.mse_loss(Tensor([3, 3, 0, 10],"float32"), Tensor([3, 3, 0,
paddle.nn.functional.mse_loss(Tensor([3, 3, 0, 10],"float32"), Tensor([3, 3, 0, 10],"float32"), "sum", )
paddle.nn.functional.mse_loss(Tensor([3, 3, 10, 0],"float32"), Tensor([3, 3, 10, 0],"float32"), "none", )
paddle.nn.functional.mse_loss(Tensor([3, 3, 10, 0],"float32"), Tensor([3, 3, 10, 0],"float32"), "sum", )
paddle.nn.functional.multi_margin_loss(Tensor([5, 0],"float64"), Tensor([5],"int64"), p=1, margin=1.0, weight=None, reduction="mean", name=None, )
paddle.nn.functional.multi_margin_loss(Tensor([5, 0],"float64"), Tensor([5],"int64"), p=1, margin=1.0, weight=None, reduction="none", name=None, )
paddle.nn.functional.multi_margin_loss(Tensor([5, 0],"float64"), Tensor([5],"int64"), p=1, margin=1.0, weight=None, reduction="sum", name=None, )
paddle.nn.functional.multi_margin_loss(input=Tensor([5, 0],"float64"), label=Tensor([5],"int64"), p=1, margin=1.0, weight=None, reduction="mean", )
paddle.nn.functional.multi_margin_loss(input=Tensor([5, 0],"float64"), label=Tensor([5],"int64"), p=1, margin=1.0, weight=None, reduction="none", )
paddle.nn.functional.multi_margin_loss(input=Tensor([5, 0],"float64"), label=Tensor([5],"int64"), p=1, margin=1.0, weight=None, reduction="sum", )
paddle.nn.functional.pad(Tensor([0, 1, 1, 13],"float32"), pad=list[0,0,0,1,], mode="replicate", value=0.0, data_format="NCHW", name=None, )
paddle.nn.functional.pad(Tensor([0, 1, 1, 1],"float16"), pad=list[0,0,0,1,], mode="replicate", value=0.0, data_format="NCHW", name=None, )
paddle.nn.functional.pad(Tensor([0, 1, 1, 1],"float32"), list[0,0,0,0,], )
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