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jinyouzhijinyouzhi
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fix dilation param mismatch for F.max_pool1d (#615)
1 parent 66787a2 commit 979589e

20 files changed

+371
-371
lines changed

‎tester/api_config/10_performance/case_little.txt‎

Lines changed: 11 additions & 11 deletions
Original file line numberDiff line numberDiff line change
@@ -14671,27 +14671,27 @@ paddle.nn.functional.avg_pool1d(x=Tensor([2, 3, 8],"float64"), kernel_size=1, st
1467114671
paddle.nn.functional.avg_pool1d(x=Tensor([2, 3, 8],"float32"), kernel_size=2, stride=2, padding=0, )
1467214672
paddle.nn.functional.max_pool1d(Tensor([2, 3, 32],"float32"), kernel_size=2, stride=2, padding=0, )
1467314673
paddle.nn.functional.max_pool1d(Tensor([2, 3, 32],"float32"), kernel_size=2, stride=2, padding="SAME", )
14674-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 32],"float32"), 2, None, 0, False, False, None, )
14675-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 1, 1, 0, False, False, None, )
14676-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 2, list[1,], 1, False, False, None, )
14677-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 2, 2, 0, False, False, None, )
14674+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 32],"float32"), 2, None, 0, False, False, )
14675+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 1, 1, 0, False, False, )
14676+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 2, list[1,], 1, False, False, )
14677+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 2, 2, 0, False, False, )
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paddle.nn.functional.max_pool1d(x=Tensor([2, 3, 8],"float64"), kernel_size=2, stride=1, padding=list[1,], )
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paddle.nn.functional.max_pool1d(x=Tensor([2, 3, 8],"float64"), kernel_size=2, stride=1, padding=0, ceil_mode=True, )
14680-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), list[3,], 1, 1, False, False, None, )
14681-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 3, 4, 0, False, False, None, )
14680+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), list[3,], 1, 1, False, False, )
14681+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 3, 4, 0, False, False, )
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paddle.nn.functional.max_pool1d(x=Tensor([2, 3, 8],"float64"), kernel_size=2, stride=1, padding=1, )
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paddle.nn.functional.max_pool1d(x=Tensor([2, 3, 8],"float64"), kernel_size=2, stride=2, padding=0, )
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paddle.nn.functional.max_pool1d(x=Tensor([2, 3, 8],"float64"), kernel_size=list[3,], stride=1, padding=1, )
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paddle.nn.functional.max_pool1d(x=Tensor([2, 3, 8],"float32"), kernel_size=2, stride=2, padding=0, )
14686-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 2, 1, 0, False, True, None, )
14686+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 2, 1, 0, False, True, )
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paddle.nn.functional.max_pool1d(x=Tensor([2, 3, 8],"float64"), kernel_size=2, stride=2, padding=1, )
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paddle.nn.functional.max_pool1d(x=Tensor([2, 3, 8],"float64"), kernel_size=2, stride=list[1,], padding=1, )
14689-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 2, 1, 1, False, False, None, )
14689+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 2, 1, 1, False, False, )
1469014690
paddle.nn.functional.max_pool1d(x=Tensor([2, 3, 8],"float64"), kernel_size=1, stride=1, padding=0, )
14691-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 2, 2, 1, False, False, None, )
14691+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 2, 2, 1, False, False, )
1469214692
paddle.nn.functional.max_pool1d(x=Tensor([2, 3, 8],"float64"), kernel_size=3, stride=4, padding=0, )
14693-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 2, 1, list[1,], False, False, None, )
14694-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float32"), 2, 2, 0, False, False, None, )
14693+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float64"), 2, 1, list[1,], False, False, )
14694+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 8],"float32"), 2, 2, 0, False, False, )
1469514695
paddle.empty(list[8192,16384,], dtype="float8_e4m3fn", )
1469614696
paddle.empty(list[37,7168,], dtype="float32", )
1469714697
paddle.empty(list[249,7168,], dtype="float32", )

‎tester/api_config/10_performance/top_three_case.txt‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1715,7 +1715,7 @@ paddle.nn.functional.avg_pool1d(Tensor([16, 2, 120],"float32"), 25, 1, 0, True,
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paddle.nn.functional.avg_pool1d(Tensor([16, 1, 120],"float32"), 25, 1, 0, True, False, None, )
17161716
paddle.nn.functional.avg_pool1d(Tensor([13, 1, 120],"float32"), 25, 1, 0, True, False, None, )
17171717
paddle.nn.functional.max_pool1d(Tensor([91, 32, 7],"float32"), 7, )
1718-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 32],"float32"), 2, None, 0, False, False, None, )
1718+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 32],"float32"), 2, None, 0, False, False, )
17191719
paddle.nn.functional.max_pool1d(Tensor([2, 3, 32],"float32"), kernel_size=2, stride=2, padding="SAME", )
17201720
paddle.Tensor.__getitem__(Tensor([8168, 8, 1280],"bfloat16"), slice(None,-6,None), )
17211721
paddle.Tensor.__getitem__(Tensor([7712, 8, 1280],"bfloat16"), slice(None,-2,None), )

‎tester/api_config/7_0_size/0_size_tensor_1_8_1.txt‎

Lines changed: 15 additions & 15 deletions
Original file line numberDiff line numberDiff line change
@@ -76392,28 +76392,28 @@ paddle.nn.functional.lp_pool1d(Tensor([2, 3, 0],"float32"), norm_type=7, kernel_
7639276392
paddle.nn.functional.lp_pool2d(Tensor([0, 3, 32, 32],"float16"), 2, kernel_size=3, stride=2, ceil_mode=False, )
7639376393
paddle.nn.functional.lp_pool2d(Tensor([0, 3, 32, 32],"float16"), norm_type=2.0, kernel_size=3, stride=2, padding=0, ceil_mode=False, data_format="NCHW", name=None, )
7639476394
paddle.nn.functional.margin_ranking_loss(Tensor([0],"float16"), Tensor([0],"float16"), Tensor([0],"float16"), 0.5, "mean", None, )
76395-
paddle.nn.functional.max_pool1d(Tensor([0, 1, 2],"float64"), 2, 2, 0, True, False, None, )
76395+
paddle.nn.functional.max_pool1d(Tensor([0, 1, 2],"float64"), 2, 2, 0, True, False, )
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paddle.nn.functional.max_pool1d(Tensor([0, 3, 16],"float32"), kernel_size=2, stride=2, return_mask=True, )
76397-
paddle.nn.functional.max_pool1d(Tensor([0, 3, 16],"float64"), 2, 2, 0, True, False, None, )
76397+
paddle.nn.functional.max_pool1d(Tensor([0, 3, 16],"float64"), 2, 2, 0, True, False, )
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paddle.nn.functional.max_pool1d(Tensor([0, 3, 16],"float64"), kernel_size=2, stride=2, return_mask=True, )
76399-
paddle.nn.functional.max_pool1d(Tensor([0, 3, 32],"float32"), 2, None, 0, False, False, None, )
76399+
paddle.nn.functional.max_pool1d(Tensor([0, 3, 32],"float32"), 2, None, 0, False, False, )
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paddle.nn.functional.max_pool1d(Tensor([0, 3, 32],"float32"), kernel_size=2, stride=2, padding="SAME", )
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paddle.nn.functional.max_pool1d(Tensor([0, 3, 32],"float32"), kernel_size=2, stride=2, padding=0, )
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paddle.nn.functional.max_pool1d(Tensor([0, 3, 32],"float32"), kernel_size=2, stride=2, padding=0, return_mask=True, )
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paddle.nn.functional.max_pool1d(Tensor([0, 3, 6],"float32"), kernel_size=5, stride=5, padding=0, ceil_mode=True, return_mask=True, )
76404-
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float32"), 2, 2, 0, False, False, None, )
76405-
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 1, 1, 0, False, False, None, )
76406-
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 2, 1, 0, False, True, None, )
76407-
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 2, 1, 1, False, False, None, )
76408-
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 2, 1, list[1,1,], False, False, None, )
76409-
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 2, 1, list[1,], False, False, None, )
76410-
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 2, 2, 0, False, False, None, )
76411-
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 2, 2, 1, False, False, None, )
76412-
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 2, list[1,], 1, False, False, None, )
76413-
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 3, 4, 0, False, False, None, )
76414-
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), list[3,], 1, 1, False, False, None, )
76404+
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float32"), 2, 2, 0, False, False, )
76405+
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 1, 1, 0, False, False, )
76406+
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 2, 1, 0, False, True, )
76407+
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 2, 1, 1, False, False, )
76408+
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 2, 1, list[1,1,], False, False, )
76409+
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 2, 1, list[1,], False, False, )
76410+
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 2, 2, 0, False, False, )
76411+
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 2, 2, 1, False, False, )
76412+
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 2, list[1,], 1, False, False, )
76413+
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), 3, 4, 0, False, False, )
76414+
paddle.nn.functional.max_pool1d(Tensor([0, 3, 8],"float64"), list[3,], 1, 1, False, False, )
7641576415
paddle.nn.functional.max_pool1d(Tensor([0, 32, 7],"float32"), 7, )
76416-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 2, 1, list[1,1,], False, False, None, )
76416+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 2, 1, list[1,1,], False, False, )
7641776417
paddle.nn.functional.max_pool1d(x=Tensor([0, 1, 2],"float64"), kernel_size=2, stride=2, padding=0, return_mask=True, )
7641876418
paddle.nn.functional.max_pool1d(x=Tensor([0, 3, 8],"float32"), kernel_size=2, stride=2, padding=0, )
7641976419
paddle.nn.functional.max_pool1d(x=Tensor([0, 3, 8],"float64"), kernel_size=1, stride=1, padding=0, )

‎tester/api_config/7_0_size/0_size_tensor_1_8_invalid_1.txt‎

Lines changed: 27 additions & 27 deletions
Original file line numberDiff line numberDiff line change
@@ -21099,44 +21099,44 @@ paddle.nn.functional.margin_ranking_loss(Tensor([0],"float16"), Tensor([128],"fl
2109921099
paddle.nn.functional.margin_ranking_loss(Tensor([128],"float16"), Tensor([0],"float16"), Tensor([128],"float16"), 0.5, "mean", None, )
2110021100
paddle.nn.functional.margin_ranking_loss(Tensor([128],"float16"), Tensor([128],"float16"), Tensor([0],"float16"), 0.5, "mean", None, )
2110121101
paddle.nn.functional.max_pool1d(Tensor([1, 0, 16],"float32"), kernel_size=2, stride=2, return_mask=True, )
21102-
paddle.nn.functional.max_pool1d(Tensor([1, 0, 16],"float64"), 2, 2, 0, True, False, None, )
21102+
paddle.nn.functional.max_pool1d(Tensor([1, 0, 16],"float64"), 2, 2, 0, True, False, )
2110321103
paddle.nn.functional.max_pool1d(Tensor([1, 0, 16],"float64"), kernel_size=2, stride=2, return_mask=True, )
21104-
paddle.nn.functional.max_pool1d(Tensor([1, 0, 2],"float64"), 2, 2, 0, True, False, None, )
21104+
paddle.nn.functional.max_pool1d(Tensor([1, 0, 2],"float64"), 2, 2, 0, True, False, )
2110521105
paddle.nn.functional.max_pool1d(Tensor([1, 0, 6],"float32"), kernel_size=5, stride=5, padding=0, ceil_mode=True, return_mask=True, )
21106-
paddle.nn.functional.max_pool1d(Tensor([1, 1, 0],"float64"), 2, 2, 0, True, False, None, )
21106+
paddle.nn.functional.max_pool1d(Tensor([1, 1, 0],"float64"), 2, 2, 0, True, False, )
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paddle.nn.functional.max_pool1d(Tensor([1, 3, 0],"float32"), kernel_size=2, stride=2, return_mask=True, )
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paddle.nn.functional.max_pool1d(Tensor([1, 3, 0],"float32"), kernel_size=5, stride=5, padding=0, ceil_mode=True, return_mask=True, )
21109-
paddle.nn.functional.max_pool1d(Tensor([1, 3, 0],"float64"), 2, 2, 0, True, False, None, )
21109+
paddle.nn.functional.max_pool1d(Tensor([1, 3, 0],"float64"), 2, 2, 0, True, False, )
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paddle.nn.functional.max_pool1d(Tensor([1, 3, 0],"float64"), kernel_size=2, stride=2, return_mask=True, )
21111-
paddle.nn.functional.max_pool1d(Tensor([2, 0, 32],"float32"), 2, None, 0, False, False, None, )
21111+
paddle.nn.functional.max_pool1d(Tensor([2, 0, 32],"float32"), 2, None, 0, False, False, )
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paddle.nn.functional.max_pool1d(Tensor([2, 0, 32],"float32"), kernel_size=2, stride=2, padding="SAME", )
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paddle.nn.functional.max_pool1d(Tensor([2, 0, 32],"float32"), kernel_size=2, stride=2, padding=0, )
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paddle.nn.functional.max_pool1d(Tensor([2, 0, 32],"float32"), kernel_size=2, stride=2, padding=0, return_mask=True, )
21115-
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float32"), 2, 2, 0, False, False, None, )
21116-
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 1, 1, 0, False, False, None, )
21117-
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 2, 1, 0, False, True, None, )
21118-
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 2, 1, 1, False, False, None, )
21119-
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 2, 1, list[1,1,], False, False, None, )
21120-
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 2, 1, list[1,], False, False, None, )
21121-
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 2, 2, 0, False, False, None, )
21122-
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 2, 2, 1, False, False, None, )
21123-
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 2, list[1,], 1, False, False, None, )
21124-
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 3, 4, 0, False, False, None, )
21125-
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), list[3,], 1, 1, False, False, None, )
21126-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float32"), 2, 2, 0, False, False, None, )
21127-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float32"), 2, None, 0, False, False, None, )
21115+
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float32"), 2, 2, 0, False, False, )
21116+
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 1, 1, 0, False, False, )
21117+
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 2, 1, 0, False, True, )
21118+
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 2, 1, 1, False, False, )
21119+
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 2, 1, list[1,1,], False, False, )
21120+
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 2, 1, list[1,], False, False, )
21121+
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 2, 2, 0, False, False, )
21122+
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 2, 2, 1, False, False, )
21123+
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 2, list[1,], 1, False, False, )
21124+
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), 3, 4, 0, False, False, )
21125+
paddle.nn.functional.max_pool1d(Tensor([2, 0, 8],"float64"), list[3,], 1, 1, False, False, )
21126+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float32"), 2, 2, 0, False, False, )
21127+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float32"), 2, None, 0, False, False, )
2112821128
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float32"), kernel_size=2, stride=2, padding="SAME", )
2112921129
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float32"), kernel_size=2, stride=2, padding=0, )
2113021130
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float32"), kernel_size=2, stride=2, padding=0, return_mask=True, )
21131-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 1, 1, 0, False, False, None, )
21132-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 2, 1, 0, False, True, None, )
21133-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 2, 1, 1, False, False, None, )
21134-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 2, 1, list[1,], False, False, None, )
21135-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 2, 2, 0, False, False, None, )
21136-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 2, 2, 1, False, False, None, )
21137-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 2, list[1,], 1, False, False, None, )
21138-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 3, 4, 0, False, False, None, )
21139-
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), list[3,], 1, 1, False, False, None, )
21131+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 1, 1, 0, False, False, )
21132+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 2, 1, 0, False, True, )
21133+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 2, 1, 1, False, False, )
21134+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 2, 1, list[1,], False, False, )
21135+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 2, 2, 0, False, False, )
21136+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 2, 2, 1, False, False, )
21137+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 2, list[1,], 1, False, False, )
21138+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), 3, 4, 0, False, False, )
21139+
paddle.nn.functional.max_pool1d(Tensor([2, 3, 0],"float64"), list[3,], 1, 1, False, False, )
2114021140
paddle.nn.functional.max_pool1d(Tensor([91, 0, 7],"float32"), 7, )
2114121141
paddle.nn.functional.max_pool1d(Tensor([91, 32, 0],"float32"), 7, )
2114221142
paddle.nn.functional.max_pool1d(x=Tensor([1, 0, 2],"float64"), kernel_size=2, stride=2, padding=0, return_mask=True, )

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