Merge branch 'main' of https://github.com/PFCCLab/PaddleAPITest into main

Author: wanghuancoder

report/0size_tensor_cpu/error_api.txt

@@ -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.nll_loss
 paddle.nn.functional.pad
 paddle.nn.functional.pixel_shuffle
 paddle.nn.functional.pixel_unshuffle

report/0size_tensor_cpu/error_config.txt

@@ -8043,22 +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.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, )
-paddle.nn.functional.nll_loss(Tensor([10, 0],"float64"), Tensor([10],"int64"), weight=Tensor([10],"float64"), ignore_index=-100, reduction="none", name=None, )
-paddle.nn.functional.nll_loss(Tensor([10, 0],"float64"), Tensor([10],"int64"), weight=Tensor([10],"float64"), ignore_index=-100, reduction="sum", name=None, )
-paddle.nn.functional.nll_loss(Tensor([4, 0],"float32"), Tensor([4],"int64"), )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 2, 4],"float32"), Tensor([5, 2, 4],"int64"), )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"int64"), weight=None, ignore_index=-100, reduction="mean", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"int64"), weight=Tensor([3],"float64"), ignore_index=-100, reduction="mean", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"int64"), weight=Tensor([3],"float64"), ignore_index=-100, reduction="none", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"int64"), weight=Tensor([3],"float64"), ignore_index=-100, reduction="sum", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5],"float64"), Tensor([5, 5, 5],"int64"), weight=None, ignore_index=-100, reduction="mean", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5],"float64"), Tensor([5, 5, 5],"int64"), weight=None, ignore_index=-100, reduction="sum", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5],"float64"), Tensor([5, 5, 5],"int64"), weight=Tensor([3],"float64"), ignore_index=-100, reduction="mean", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5],"float64"), Tensor([5, 5, 5],"int64"), weight=Tensor([3],"float64"), ignore_index=-100, reduction="sum", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0],"float32"), Tensor([5],"int64"), )
 paddle.nn.functional.pad(Tensor([0, 1, 1, 1],"int32"), Tensor([4],"int32"), value=False, )
 paddle.nn.functional.pad(Tensor([0, 1, 10, 10],"int32"), Tensor([4],"int32"), value=False, )
 paddle.nn.functional.pad(Tensor([0, 1, 100, 100],"int32"), Tensor([4],"int32"), value=False, )

report/0size_tensor_gpu/error_api.txt

@@ -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.nll_loss
 paddle.nn.functional.normalize
 paddle.nn.functional.one_hot
 paddle.nn.functional.pad

report/0size_tensor_gpu/error_config.txt

@@ -11530,22 +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.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, )
-paddle.nn.functional.nll_loss(Tensor([10, 0],"float64"), Tensor([10],"int64"), weight=Tensor([10],"float64"), ignore_index=-100, reduction="none", name=None, )
-paddle.nn.functional.nll_loss(Tensor([10, 0],"float64"), Tensor([10],"int64"), weight=Tensor([10],"float64"), ignore_index=-100, reduction="sum", name=None, )
-paddle.nn.functional.nll_loss(Tensor([4, 0],"float32"), Tensor([4],"int64"), )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 2, 4],"float32"), Tensor([5, 2, 4],"int64"), )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"int64"), weight=None, ignore_index=-100, reduction="mean", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"int64"), weight=Tensor([3],"float64"), ignore_index=-100, reduction="mean", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"int64"), weight=Tensor([3],"float64"), ignore_index=-100, reduction="none", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"int64"), weight=Tensor([3],"float64"), ignore_index=-100, reduction="sum", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5],"float64"), Tensor([5, 5, 5],"int64"), weight=None, ignore_index=-100, reduction="mean", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5],"float64"), Tensor([5, 5, 5],"int64"), weight=None, ignore_index=-100, reduction="sum", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5],"float64"), Tensor([5, 5, 5],"int64"), weight=Tensor([3],"float64"), ignore_index=-100, reduction="mean", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0, 5, 5],"float64"), Tensor([5, 5, 5],"int64"), weight=Tensor([3],"float64"), ignore_index=-100, reduction="sum", name=None, )
-paddle.nn.functional.nll_loss(Tensor([5, 0],"float32"), Tensor([5],"int64"), )
 paddle.nn.functional.normalize(Tensor([0, 10],"float32"), axis=0, )
 paddle.nn.functional.normalize(Tensor([0, 3],"float32"), axis=0, )
 paddle.nn.functional.normalize(Tensor([0, 4],"float32"), axis=0, )

report/big_tensor_gpu/error_api.txt

@@ -12,7 +12,6 @@ paddle.Tensor.all
 paddle.Tensor.any
 paddle.Tensor.argmax
 paddle.Tensor.astype
-paddle.Tensor.chunk
 paddle.Tensor.clip
 paddle.Tensor.cumsum
 paddle.Tensor.diff
@@ -57,7 +56,6 @@ paddle.atan2
 paddle.bincount
 paddle.bmm
 paddle.broadcast_tensors
-paddle.chunk
 paddle.clip
 paddle.combinations
 paddle.complex

report/big_tensor_gpu/error_config.txt

@@ -480,55 +480,6 @@ paddle.Tensor.argmax(Tensor([75245, 1, 30324],"float32"), axis=-2, )
 paddle.Tensor.argmax(Tensor([83837, 1, 27216],"float32"), axis=-2, )
 paddle.Tensor.argmax(Tensor([93991, 1, 24276],"float32"), axis=-2, )
 paddle.Tensor.astype(Tensor([1, 3, 1431655765],"float32"), Dtype(int32), )
-paddle.Tensor.chunk(Tensor([1, 1, 1, 2281701379],"float32"), 4, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 1, 10164, 224489],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 1, 11109, 205393],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 1, 12096, 188633],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 1, 2100, 1086525],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 1, 2281701379],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 1, 24276, 93991],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 1, 2541, 897955],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 1, 27216, 83837],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 1, 3024, 754531],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 1, 30324, 75245],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 10, 1, 228170138],"float32"), 4, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 101, 1, 22591103],"float32"), 4, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 101, 22591103],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 102, 1, 22369622],"float32"), 4, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 103, 1, 22152441],"float32"), 4, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 103, 22152441],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 104, 21939437],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 105, 1, 21730490],"float32"), 4, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 106, 1, 21525485],"float32"), 4, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 106, 21525485],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 108, 1, 21126865],"float32"), 4, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 108, 21126865],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 109, 1, 20933041],"float32"), 4, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 109, 20933041],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 11, 1, 207427399],"float32"), 4, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 11, 207427399],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 111, 20555869],"float32"), 2, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 112, 1, 20372334],"float32"), 4, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 117, 1, 19501722],"float32"), 4, axis=-1, )
-paddle.Tensor.chunk(Tensor([1, 2281701379],"float32"), 2, axis=1, )
-paddle.Tensor.chunk(Tensor([13, 5484860, 32],"float32"), 8, axis=1, )
-paddle.Tensor.chunk(Tensor([1901418, 300, 4],"float32"), 4, )
-paddle.Tensor.chunk(Tensor([227, 1116839, 3, 3],"float32"), chunks=2, axis=1, )
-paddle.Tensor.chunk(Tensor([227, 9, 1116839],"float32"), chunks=2, axis=-1, )
-paddle.Tensor.chunk(Tensor([256, 2228225, 2, 2],"float32"), chunks=2, axis=1, )
-paddle.Tensor.chunk(Tensor([475355, 300, 16],"float32"), 2, )
-paddle.Tensor.chunk(Tensor([512, 1451, 64, 48],"float32"), 2, axis=1, )
-paddle.Tensor.chunk(Tensor([512, 174763, 8, 6],"float16"), 2, axis=1, )
-paddle.Tensor.chunk(Tensor([512, 2731, 64, 48],"float16"), 2, axis=1, )
-paddle.Tensor.chunk(Tensor([512, 699051, 4, 3],"float16"), 2, axis=1, )
-paddle.Tensor.chunk(Tensor([512, 92843, 8, 6],"float32"), 2, axis=1, )
-paddle.Tensor.chunk(Tensor([56, 10186167, 2, 2],"float32"), chunks=2, axis=1, )
-paddle.Tensor.chunk(Tensor([56, 38, 1072229],"float32"), chunks=2, axis=-1, )
-paddle.Tensor.chunk(Tensor([5704254, 100, 4],"float32"), 4, )
-paddle.Tensor.chunk(Tensor([75304, 300, 101],"float32"), 16, )
-paddle.Tensor.chunk(Tensor([82, 3091737, 3, 3],"float32"), chunks=2, axis=1, )
-paddle.Tensor.chunk(Tensor([82, 9, 3091737],"float32"), chunks=2, axis=-1, )
-paddle.Tensor.chunk(Tensor([950709, 300, 8],"float32"), 8, )
 paddle.Tensor.clip(Tensor([1, 2, 1073741825, 2],"float16"), min=1, )
 paddle.Tensor.clip(Tensor([1, 2, 300, 7158279],"float16"), min=1, )
 paddle.Tensor.clip(Tensor([1, 7158279, 300, 2],"float16"), min=1, )
@@ -1728,37 +1679,6 @@ paddle.broadcast_tensors(tuple(Tensor([2, 1],"float16"),Tensor([2, 2147483649],"
 paddle.broadcast_tensors(tuple(Tensor([2, 2147483649],"float16"),Tensor([2, 1],"float16"),Tensor([2, 1],"float16"),), )
 paddle.broadcast_tensors(tuple(Tensor([2, 2147483649],"float16"),Tensor([2, 2147483649],"float16"),Tensor([2, 2147483649],"float16"),), )
 paddle.broadcast_tensors(tuple(Tensor([4294967297, 1],"float16"),Tensor([4294967297, 1],"float16"),Tensor([4294967297, 1],"float16"),), )
-paddle.chunk(Tensor([1, 1, 1, 4294967297],"float16"), 2, axis=-1, )
-paddle.chunk(Tensor([1, 1, 64, 67108865],"float16"), 2, axis=-1, )
-paddle.chunk(Tensor([1, 11, 207427399],"float32"), chunks=2, axis=-1, )
-paddle.chunk(Tensor([1, 4, 20, 28521268],"float32"), 3, axis=-1, )
-paddle.chunk(Tensor([13, 16, 10969719],"float32"), chunks=2, axis=-1, )
-paddle.chunk(Tensor([13, 175515491, 1],"float32"), 4, axis=1, )
-paddle.chunk(Tensor([13, 4, 7, 6268411],"float32"), 3, axis=-1, )
-paddle.chunk(Tensor([13, 5484860, 32],"float32"), 3, axis=1, )
-paddle.chunk(Tensor([13, 56, 3134206],"float32"), 3, axis=-1, )
-paddle.chunk(Tensor([16, 5593, 25500],"float32"), 2, axis=1, )
-paddle.chunk(Tensor([2048, 1114113],"float32"), 2, axis=-1, )
-paddle.chunk(Tensor([4, 139265, 64, 64],"float32"), 3, axis=1, )
-paddle.chunk(Tensor([4, 262145, 64, 64],"float16"), 3, axis=1, )
-paddle.chunk(Tensor([4, 6, 6],"int32"), chunks=3, axis=Tensor([2281701379],"int32"), )
-paddle.chunk(Tensor([52, 4, 7, 1567103],"float32"), 3, axis=-1, )
-paddle.chunk(Tensor([52, 5484860, 8],"float32"), 3, axis=1, )
-paddle.chunk(Tensor([8192, 278529],"float32"), 2, axis=-1, )
-paddle.chunk(x=Tensor([1431655766, 3],"float16"), chunks=3, axis=0, )
-paddle.chunk(x=Tensor([2281701379],"bool"), chunks=3, axis=0, )
-paddle.chunk(x=Tensor([3, 1431655766],"float16"), chunks=3, axis=-1, )
-paddle.chunk(x=Tensor([3, 3],"float16"), chunks=3, axis=Tensor([2281701379],"int64"), )
-paddle.chunk(x=Tensor([3, 3],"float32"), chunks=3, axis=Tensor([2281701379],"int64"), )
-paddle.chunk(x=Tensor([3, 3],"float64"), chunks=3, axis=Tensor([2281701379],"int64"), )
-paddle.chunk(x=Tensor([3, 3],"int32"), chunks=3, axis=Tensor([2281701379],"int64"), )
-paddle.chunk(x=Tensor([3, 3],"int64"), chunks=3, axis=Tensor([2281701379],"int64"), )
-paddle.chunk(x=Tensor([3, 760567127],"float32"), chunks=3, axis=-1, )
-paddle.chunk(x=Tensor([3, 760567127],"int32"), chunks=3, axis=-1, )
-paddle.chunk(x=Tensor([3, 760567127],"int64"), chunks=3, axis=-1, )
-paddle.chunk(x=Tensor([760567127, 3],"float32"), chunks=3, axis=0, )
-paddle.chunk(x=Tensor([760567127, 3],"int32"), chunks=3, axis=0, )
-paddle.chunk(x=Tensor([760567127, 3],"int64"), chunks=3, axis=0, )
 paddle.clip(Tensor([103884, 1, 152, 272],"float16"), 0, 1, )
 paddle.clip(Tensor([20, 1, 152, 1412819],"float16"), 0, 1, )
 paddle.clip(Tensor([20, 1, 789517, 272],"float16"), 0, 1, )

report/ci_ce_cpu/error_api.txt

@@ -43,7 +43,6 @@ paddle.linalg.lstsq
 paddle.linalg.matrix_rank
 paddle.linalg.norm
 paddle.linalg.pinv
-paddle.linalg.svd_lowrank
 paddle.logit
 paddle.max
 paddle.maximum

report/ci_ce_cpu/error_config.txt

@@ -1618,46 +1618,6 @@ paddle.linalg.pinv(x=Tensor([2, 2],"complex64"), hermitian=True, )
 paddle.linalg.pinv(x=Tensor([2, 2],"float32"), hermitian=True, )
 paddle.linalg.pinv(x=Tensor([2, 2],"float64"), hermitian=True, )
 paddle.linalg.pinv(x=Tensor([4, 2, 2],"float64"), hermitian=True, )
-paddle.linalg.svd_lowrank(Tensor([1, 100, 40],"float64"), q=12, )
-paddle.linalg.svd_lowrank(Tensor([1, 100, 40],"float64"), q=6, )
-paddle.linalg.svd_lowrank(Tensor([1, 100, 40],"float64"), q=8, )
-paddle.linalg.svd_lowrank(Tensor([1, 17, 4],"float64"), q=2, )
-paddle.linalg.svd_lowrank(Tensor([1, 17, 4],"float64"), q=4, )
-paddle.linalg.svd_lowrank(Tensor([1, 4, 17],"float64"), q=2, )
-paddle.linalg.svd_lowrank(Tensor([1, 40, 100],"float64"), q=12, )
-paddle.linalg.svd_lowrank(Tensor([1, 40, 100],"float64"), q=6, )
-paddle.linalg.svd_lowrank(Tensor([1, 40, 100],"float64"), q=8, )
-paddle.linalg.svd_lowrank(Tensor([100, 40],"float64"), q=12, )
-paddle.linalg.svd_lowrank(Tensor([100, 40],"float64"), q=6, )
-paddle.linalg.svd_lowrank(Tensor([100, 40],"float64"), q=8, )
-paddle.linalg.svd_lowrank(Tensor([17, 4],"float64"), q=2, )
-paddle.linalg.svd_lowrank(Tensor([17, 4],"float64"), q=4, )
-paddle.linalg.svd_lowrank(Tensor([2, 3, 100, 40],"float64"), q=12, )
-paddle.linalg.svd_lowrank(Tensor([2, 3, 100, 40],"float64"), q=6, )
-paddle.linalg.svd_lowrank(Tensor([2, 3, 100, 40],"float64"), q=8, )
-paddle.linalg.svd_lowrank(Tensor([2, 3, 17, 4],"float64"), q=2, )
-paddle.linalg.svd_lowrank(Tensor([2, 3, 17, 4],"float64"), q=4, )
-paddle.linalg.svd_lowrank(Tensor([2, 3, 4, 17],"float64"), q=2, )
-paddle.linalg.svd_lowrank(Tensor([2, 3, 4, 17],"float64"), q=4, )
-paddle.linalg.svd_lowrank(Tensor([2, 3, 40, 100],"float64"), q=12, )
-paddle.linalg.svd_lowrank(Tensor([2, 3, 40, 100],"float64"), q=6, )
-paddle.linalg.svd_lowrank(Tensor([2, 3, 40, 100],"float64"), q=8, )
-paddle.linalg.svd_lowrank(Tensor([3, 100, 40],"float64"), q=12, )
-paddle.linalg.svd_lowrank(Tensor([3, 100, 40],"float64"), q=6, )
-paddle.linalg.svd_lowrank(Tensor([3, 100, 40],"float64"), q=8, )
-paddle.linalg.svd_lowrank(Tensor([3, 17, 4],"float64"), q=2, )
-paddle.linalg.svd_lowrank(Tensor([3, 17, 4],"float64"), q=4, )
-paddle.linalg.svd_lowrank(Tensor([3, 4, 17],"float64"), q=2, )
-paddle.linalg.svd_lowrank(Tensor([3, 4, 17],"float64"), q=4, )
-paddle.linalg.svd_lowrank(Tensor([3, 40, 100],"float64"), q=12, )
-paddle.linalg.svd_lowrank(Tensor([3, 40, 100],"float64"), q=6, )
-paddle.linalg.svd_lowrank(Tensor([3, 40, 100],"float64"), q=8, )
-paddle.linalg.svd_lowrank(Tensor([4, 17],"float64"), q=2, )
-paddle.linalg.svd_lowrank(Tensor([4, 17],"float64"), q=4, )
-paddle.linalg.svd_lowrank(Tensor([40, 100],"float64"), q=12, )
-paddle.linalg.svd_lowrank(Tensor([40, 100],"float64"), q=6, )
-paddle.linalg.svd_lowrank(Tensor([40, 100],"float64"), q=8, )
-paddle.linalg.svd_lowrank(Tensor([5, 5],"float64"), None, )
 paddle.logit(Tensor([],"float32"), )
 paddle.logit(x=Tensor([4, 2],"float64"), )
 paddle.logit(x=Tensor([4, 3, 2, 5],"float64"), )

report/ci_ce_gpu/error_api.txt

@@ -88,7 +88,6 @@ paddle.broadcast_to
 paddle.dot
 paddle.linalg.norm
 paddle.linalg.pinv
-paddle.linalg.svd_lowrank
 paddle.logit
 paddle.maximum
 paddle.minimum