Merge pull request #249 from cangtianhuang/report

[BIT] Fix cpu 0607 report

Author: wanghuancoder

report/ci_ce_cpu/20250607/cpu_error/error_api.txt

@@ -2,15 +2,12 @@ paddle.Tensor.__mul__
 paddle.Tensor.astype
 paddle.Tensor.cast
 paddle.Tensor.expand
-paddle.Tensor.topk
 paddle.add_n
 paddle.broadcast_to
 paddle.cast
 paddle.cumulative_trapezoid
 paddle.expand
 paddle.geometric.send_ue_recv
-paddle.geometric.send_uv
-paddle.heaviside
 paddle.incubate.nn.functional.fused_layer_norm
 paddle.kron
 paddle.linalg.cond

report/ci_ce_cpu/20250607/cpu_error/error_config.txt

@@ -20,8 +20,6 @@ paddle.Tensor.expand(Tensor([1, 50, 1, 1],"float16"), list[2,50,1,64,], )
 paddle.Tensor.expand(Tensor([1, 51, 1, 1],"float16"), list[2,51,1,64,], )
 paddle.Tensor.expand(Tensor([1, 52, 1, 1],"float16"), list[2,52,1,64,], )
 paddle.Tensor.expand(Tensor([1, 57, 1, 1],"float16"), list[2,57,1,64,], )
-paddle.Tensor.topk(Tensor([3276800],"float32"), 98148, )
-paddle.Tensor.topk(Tensor([3276800],"float32"), 98760, )
 paddle.add_n(list[Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),], )
 paddle.add_n(list[Tensor([16, 256],"float32"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),Tensor([16, 256],"float16"),], )
 paddle.broadcast_to(Tensor([1],"float16"), list[300,40,], )
@@ -38,24 +36,16 @@ paddle.cumulative_trapezoid(y=Tensor([2, 3],"float64"), x=None, dx=None, axis=-1
 paddle.cumulative_trapezoid(y=Tensor([2, 3],"float64"), x=Tensor([2, 3],"float64"), dx=None, axis=-1, )
 paddle.cumulative_trapezoid(y=Tensor([3, 3, 4],"float32"), x=Tensor([3],"float32"), dx=None, axis=1, )
 paddle.expand(Tensor([3, 2],"float16"), shape=list[512,3,2,], )
-paddle.geometric.send_ue_recv(Tensor([10, 20],"float64"), Tensor([15, 20],"float64"), Tensor([15],"int64"), Tensor([15],"int64"), "mul", "mean", None, None, )
 paddle.geometric.send_ue_recv(Tensor([10, 20],"float64"), Tensor([150, 1],"float64"), Tensor([150],"int64"), Tensor([150],"int64"), "add", "max", None, None, )
 paddle.geometric.send_ue_recv(Tensor([10, 20],"float64"), Tensor([150, 1],"float64"), Tensor([150],"int64"), Tensor([150],"int64"), "add", "mean", None, None, )
 paddle.geometric.send_ue_recv(Tensor([10, 20],"float64"), Tensor([150, 1],"float64"), Tensor([150],"int64"), Tensor([150],"int64"), "add", "min", None, None, )
 paddle.geometric.send_ue_recv(Tensor([10, 20],"float64"), Tensor([150, 1],"float64"), Tensor([150],"int64"), Tensor([150],"int64"), "add", "sum", None, None, )
 paddle.geometric.send_ue_recv(Tensor([10, 20],"float64"), Tensor([150, 1],"float64"), Tensor([150],"int64"), Tensor([150],"int64"), "mul", "mean", None, None, )
 paddle.geometric.send_ue_recv(Tensor([10, 20],"float64"), Tensor([150, 1],"float64"), Tensor([150],"int64"), Tensor([150],"int64"), "mul", "min", None, None, )
-paddle.geometric.send_ue_recv(Tensor([10, 20],"float64"), Tensor([150, 1],"float64"), Tensor([150],"int64"), Tensor([150],"int64"), "mul", "sum", None, None, )
 paddle.geometric.send_ue_recv(Tensor([10, 8, 5],"float64"), Tensor([15, 8, 1],"float64"), Tensor([15],"int64"), Tensor([15],"int64"), "add", "mean", None, None, )
 paddle.geometric.send_ue_recv(Tensor([10, 8, 5],"float64"), Tensor([15, 8, 1],"float64"), Tensor([15],"int64"), Tensor([15],"int64"), "add", "sum", None, None, )
 paddle.geometric.send_ue_recv(Tensor([10, 8, 5],"float64"), Tensor([15, 8, 1],"float64"), Tensor([15],"int64"), Tensor([15],"int64"), "mul", "min", None, None, )
-paddle.geometric.send_ue_recv(Tensor([3, 3],"float32"), Tensor([4, 1],"float32"), Tensor([4],"int32"), Tensor([4],"int32"), "div", "sum", )
 paddle.geometric.send_ue_recv(Tensor([3, 3],"float32"), Tensor([4, 1],"float32"), Tensor([4],"int32"), Tensor([4],"int32"), "sub", "mean", )
-paddle.geometric.send_ue_recv(Tensor([3, 3],"float32"), Tensor([4, 1],"float32"), Tensor([4],"int32"), Tensor([4],"int32"), "sub", "sum", )
-paddle.geometric.send_uv(Tensor([10, 10, 1],"float64"), Tensor([10, 10, 10],"float64"), Tensor([15],"int64"), Tensor([15],"int64"), "add", )
-paddle.heaviside(Tensor([1],"float32"), Tensor([300, 2048],"float32"), )
-paddle.heaviside(Tensor([2048],"float32"), Tensor([300, 2048],"float32"), )
-paddle.heaviside(Tensor([],"float32"), Tensor([2, 3, 4],"float32"), )
 paddle.incubate.nn.functional.fused_layer_norm(Tensor([16, 256],"float32"), Tensor([256],"float32"), Tensor([256],"float32"), 1e-05, begin_norm_axis=1, bias=Tensor([256],"float32"), residual=Tensor([16, 256],"float32"), residual_alpha=0.69204696, )
 paddle.kron(Tensor([12, 8],"float16"), Tensor([16, 8],"float16"), )
 paddle.kron(Tensor([16, 16],"float16"), Tensor([32, 20],"float16"), )