patrickvonplaten commited on
Commit
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1 Parent(s): f0d385b
after_fix_log.txt ADDED
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+ Check hf-internal-testing/tiny-random-roberta ...
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+ --------------------------Checking logits match--------------------------
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+ Flax logits shape: (2, 64, 1000), PyTorch logits shape: torch.Size([2, 64, 1000])
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+ βœ… Difference between Flax and PyTorch is 1.7881393432617188e-07 (< 0.01)
5
+ --------------------------Checking losses match--------------------------
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+ Flax loss: 6.887884140014648, PyTorch loss: 6.887884616851807
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+ βœ… Difference between Flax and PyTorch is 4.76837158203125e-07 (< 0.01)
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+ --------------------------Checking gradients match--------------------------
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+ βœ… All grads pass
10
+ --------------------------Checking rel gradients match--------------------------
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+ ❌ Layer ('roberta', 'encoder', 'layer', '0', 'attention', 'self', 'key', 'bias') has PT grad norm 7.584575871001642e-13 and flax grad norm 6.388195094436666e-13.
12
+ ❌ Layer ('roberta', 'encoder', 'layer', '1', 'attention', 'self', 'key', 'bias') has PT grad norm 7.811836030477415e-13 and flax grad norm 6.42668156105447e-13.
13
+ ❌ Layer ('roberta', 'encoder', 'layer', '2', 'attention', 'self', 'key', 'bias') has PT grad norm 8.422985074175993e-13 and flax grad norm 6.414080963405844e-13.
14
+ ❌ Layer ('roberta', 'encoder', 'layer', '3', 'attention', 'self', 'key', 'bias') has PT grad norm 8.625919531608794e-13 and flax grad norm 7.699825477734679e-13.
15
+ ❌ Layer ('roberta', 'encoder', 'layer', '4', 'attention', 'self', 'key', 'bias') has PT grad norm 1.0383360837806777e-12 and flax grad norm 6.049140680551568e-13.
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+ =========================================
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+ Check hf-internal-testing/tiny-random-bert ...
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+ --------------------------Checking logits match--------------------------
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+ Flax logits shape: (2, 64, 1124), PyTorch logits shape: torch.Size([2, 64, 1124])
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+ βœ… Difference between Flax and PyTorch is 1.7881393432617188e-07 (< 0.01)
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+ --------------------------Checking losses match--------------------------
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+ Flax loss: 7.036032199859619, PyTorch loss: 7.036032676696777
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+ βœ… Difference between Flax and PyTorch is 4.76837158203125e-07 (< 0.01)
24
+ --------------------------Checking gradients match--------------------------
25
+ βœ… All grads pass
26
+ --------------------------Checking rel gradients match--------------------------
27
+ ❌ Layer ('bert', 'encoder', 'layer', '0', 'attention', 'self', 'key', 'bias') has PT grad norm 5.234438642080785e-13 and flax grad norm 4.935363641205004e-13.
28
+ ❌ Layer ('bert', 'encoder', 'layer', '1', 'attention', 'self', 'key', 'bias') has PT grad norm 9.028551018787356e-13 and flax grad norm 6.16219206737989e-13.
29
+ ❌ Layer ('bert', 'encoder', 'layer', '2', 'attention', 'self', 'key', 'bias') has PT grad norm 8.728350616056535e-13 and flax grad norm 6.037235598596591e-13.
30
+ ❌ Layer ('bert', 'encoder', 'layer', '3', 'attention', 'self', 'key', 'bias') has PT grad norm 8.327751465850297e-13 and flax grad norm 7.390156737431541e-13.
31
+ ❌ Layer ('bert', 'encoder', 'layer', '4', 'attention', 'self', 'key', 'bias') has PT grad norm 7.404479048130075e-13 and flax grad norm 7.178592030705755e-13.
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+ =========================================
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+ Check hf-internal-testing/tiny-random-t5 ...
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+ --------------------------Checking logits match--------------------------
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+ Flax logits shape: (2, 64, 1103), PyTorch logits shape: torch.Size([2, 64, 1103])
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+ βœ… Difference between Flax and PyTorch is 3.725290298461914e-09 (< 0.01)
37
+ --------------------------Checking losses match--------------------------
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+ Flax loss: 7.006012916564941, PyTorch loss: 7.006012916564941
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+ βœ… Difference between Flax and PyTorch is 0.0 (< 0.01)
40
+ --------------------------Checking gradients match--------------------------
41
+ βœ… All grads pass
42
+ --------------------------Checking rel gradients match--------------------------
43
+ βœ… All rel grads pass
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+ =========================================
45
+ Check hf-internal-testing/tiny-random-bart ...
46
+ --------------------------Checking logits match--------------------------
47
+ Flax logits shape: (2, 64, 1000), PyTorch logits shape: torch.Size([2, 64, 1000])
48
+ βœ… Difference between Flax and PyTorch is 8.940696716308594e-08 (< 0.01)
49
+ --------------------------Checking losses match--------------------------
50
+ Flax loss: 6.919522285461426, PyTorch loss: 6.919522285461426
51
+ βœ… Difference between Flax and PyTorch is 0.0 (< 0.01)
52
+ --------------------------Checking gradients match--------------------------
53
+ βœ… All grads pass
54
+ --------------------------Checking rel gradients match--------------------------
55
+ ❌ Layer ('final_logits_bias',) has PT grad norm 0.0 and flax grad norm 0.0.
56
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 1.1293364247239035e-13 and flax grad norm 7.444291358479557e-14.
57
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'self_attn', 'k_proj', 'bias') has PT grad norm 1.9028742882613858e-13 and flax grad norm 1.0847509820726894e-13.
58
+ ❌ Layer ('model', 'decoder', 'layers', '1', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 1.0747876384459981e-13 and flax grad norm 1.1924105637346055e-13.
59
+ ❌ Layer ('model', 'decoder', 'layers', '1', 'self_attn', 'k_proj', 'bias') has PT grad norm 2.0553104032074165e-13 and flax grad norm 2.416926793251395e-13.
60
+ ❌ Layer ('model', 'encoder', 'layers', '0', 'self_attn', 'k_proj', 'bias') has PT grad norm 1.6505221806215232e-16 and flax grad norm 8.704786207109524e-17.
61
+ ❌ Layer ('model', 'encoder', 'layers', '1', 'self_attn', 'k_proj', 'bias') has PT grad norm 2.145616114665214e-16 and flax grad norm 1.6750639014770325e-16.
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+ =========================================
after_fix_pretrained_log.txt ADDED
@@ -0,0 +1,212 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Check roberta-base ...
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+ --------------------------Checking logits match--------------------------
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+ Flax logits shape: (2, 64, 50265), PyTorch logits shape: torch.Size([2, 64, 50265])
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+ βœ… Difference between Flax and PyTorch is 0.00013017654418945312 (< 0.01)
5
+ --------------------------Checking losses match--------------------------
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+ Flax loss: 14.801228523254395, PyTorch loss: 14.801219940185547
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+ βœ… Difference between Flax and PyTorch is 8.58306884765625e-06 (< 0.01)
8
+ --------------------------Checking gradients match--------------------------
9
+ βœ… All grads pass
10
+ --------------------------Checking rel gradients match--------------------------
11
+ ❌ Layer ('roberta', 'encoder', 'layer', '0', 'attention', 'self', 'key', 'bias') has PT grad norm 6.889232651019483e-08 and flax grad norm 5.7956174970286156e-08.
12
+ ❌ Layer ('roberta', 'encoder', 'layer', '1', 'attention', 'self', 'key', 'bias') has PT grad norm 7.026115156349988e-08 and flax grad norm 6.282134989987753e-08.
13
+ ❌ Layer ('roberta', 'encoder', 'layer', '10', 'attention', 'self', 'key', 'bias') has PT grad norm 2.273949206710313e-08 and flax grad norm 1.8748883334751554e-08.
14
+ ❌ Layer ('roberta', 'encoder', 'layer', '11', 'attention', 'self', 'key', 'bias') has PT grad norm 2.9379741306456708e-08 and flax grad norm 2.6026933497291793e-08.
15
+ ❌ Layer ('roberta', 'encoder', 'layer', '2', 'attention', 'self', 'key', 'bias') has PT grad norm 6.197853963385569e-08 and flax grad norm 5.317058082709991e-08.
16
+ ❌ Layer ('roberta', 'encoder', 'layer', '3', 'attention', 'self', 'key', 'bias') has PT grad norm 7.359258802352997e-08 and flax grad norm 8.573702814373974e-08.
17
+ ❌ Layer ('roberta', 'encoder', 'layer', '4', 'attention', 'self', 'key', 'bias') has PT grad norm 5.1634213349416314e-08 and flax grad norm 5.744939457485998e-08.
18
+ ❌ Layer ('roberta', 'encoder', 'layer', '5', 'attention', 'self', 'key', 'bias') has PT grad norm 4.652720519970899e-08 and flax grad norm 6.121346984855336e-08.
19
+ ❌ Layer ('roberta', 'encoder', 'layer', '6', 'attention', 'self', 'key', 'bias') has PT grad norm 3.8810604507943935e-08 and flax grad norm 4.2490388096894094e-08.
20
+ ❌ Layer ('roberta', 'encoder', 'layer', '7', 'attention', 'self', 'key', 'bias') has PT grad norm 3.7450202938771326e-08 and flax grad norm 3.219445687818734e-08.
21
+ ❌ Layer ('roberta', 'encoder', 'layer', '8', 'attention', 'self', 'key', 'bias') has PT grad norm 3.3088259243641005e-08 and flax grad norm 2.6118801343955056e-08.
22
+ ❌ Layer ('roberta', 'encoder', 'layer', '9', 'attention', 'self', 'key', 'bias') has PT grad norm 2.6417508180998084e-08 and flax grad norm 2.415968225477627e-08.
23
+ =========================================
24
+ Check bert-base-cased ...
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+ --------------------------Checking logits match--------------------------
26
+ Flax logits shape: (2, 64, 28996), PyTorch logits shape: torch.Size([2, 64, 28996])
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+ βœ… Difference between Flax and PyTorch is 5.4836273193359375e-05 (< 0.01)
28
+ --------------------------Checking losses match--------------------------
29
+ Flax loss: 13.967159271240234, PyTorch loss: 13.967162132263184
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+ βœ… Difference between Flax and PyTorch is 2.86102294921875e-06 (< 0.01)
31
+ --------------------------Checking gradients match--------------------------
32
+ βœ… All grads pass
33
+ --------------------------Checking rel gradients match--------------------------
34
+ ❌ Layer ('bert', 'encoder', 'layer', '0', 'attention', 'self', 'key', 'bias') has PT grad norm 8.025740783068613e-08 and flax grad norm 8.381563532111613e-08.
35
+ ❌ Layer ('bert', 'encoder', 'layer', '1', 'attention', 'self', 'key', 'bias') has PT grad norm 7.262840284738559e-08 and flax grad norm 5.0372555904232286e-08.
36
+ ❌ Layer ('bert', 'encoder', 'layer', '10', 'attention', 'self', 'key', 'bias') has PT grad norm 2.6523425233904163e-08 and flax grad norm 2.7082945663892133e-08.
37
+ ❌ Layer ('bert', 'encoder', 'layer', '11', 'attention', 'self', 'key', 'bias') has PT grad norm 2.9038789151059063e-08 and flax grad norm 3.3138192634396546e-08.
38
+ ❌ Layer ('bert', 'encoder', 'layer', '2', 'attention', 'self', 'key', 'bias') has PT grad norm 5.880680831182872e-08 and flax grad norm 5.04786008548308e-08.
39
+ ❌ Layer ('bert', 'encoder', 'layer', '3', 'attention', 'self', 'key', 'bias') has PT grad norm 4.705585965325554e-08 and flax grad norm 4.983893475696277e-08.
40
+ ❌ Layer ('bert', 'encoder', 'layer', '4', 'attention', 'self', 'key', 'bias') has PT grad norm 6.595875134962625e-08 and flax grad norm 5.823812543326312e-08.
41
+ ❌ Layer ('bert', 'encoder', 'layer', '5', 'attention', 'self', 'key', 'bias') has PT grad norm 4.716540402682767e-08 and flax grad norm 6.053270595884896e-08.
42
+ ❌ Layer ('bert', 'encoder', 'layer', '6', 'attention', 'self', 'key', 'bias') has PT grad norm 5.4432636176215965e-08 and flax grad norm 4.0700697923057305e-08.
43
+ ❌ Layer ('bert', 'encoder', 'layer', '8', 'attention', 'self', 'key', 'bias') has PT grad norm 4.059621971919114e-08 and flax grad norm 4.575255374561493e-08.
44
+ ❌ Layer ('bert', 'encoder', 'layer', '9', 'attention', 'self', 'key', 'bias') has PT grad norm 2.9032529269557017e-08 and flax grad norm 2.659336217902819e-08.
45
+ =========================================
46
+ Check t5-small ...
47
+ --------------------------Checking logits match--------------------------
48
+ Flax logits shape: (2, 64, 32128), PyTorch logits shape: torch.Size([2, 64, 32128])
49
+ βœ… Difference between Flax and PyTorch is 7.62939453125e-05 (< 0.01)
50
+ --------------------------Checking losses match--------------------------
51
+ Flax loss: 20.534835815429688, PyTorch loss: 20.534835815429688
52
+ βœ… Difference between Flax and PyTorch is 0.0 (< 0.01)
53
+ --------------------------Checking gradients match--------------------------
54
+ βœ… All grads pass
55
+ --------------------------Checking rel gradients match--------------------------
56
+ βœ… All rel grads pass
57
+ =========================================
58
+ Check facebook/bart-large ...
59
+ --------------------------Checking logits match--------------------------
60
+ Flax logits shape: (2, 64, 50265), PyTorch logits shape: torch.Size([2, 64, 50265])
61
+ βœ… Difference between Flax and PyTorch is 0.0004191398620605469 (< 0.01)
62
+ --------------------------Checking losses match--------------------------
63
+ Flax loss: 13.993148803710938, PyTorch loss: 13.993138313293457
64
+ βœ… Difference between Flax and PyTorch is 1.049041748046875e-05 (< 0.01)
65
+ --------------------------Checking gradients match--------------------------
66
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'fc1', 'kernel') has PT grad norm 11.655710220336914 and flax grad norm 11.6015625.
67
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'fc2', 'kernel') has PT grad norm 7.740886211395264 and flax grad norm 7.71484375.
68
+ ❌ Layer ('model', 'decoder', 'layers', '1', 'fc1', 'kernel') has PT grad norm 6.798306465148926 and flax grad norm 6.765625.
69
+ ❌ Layer ('model', 'decoder', 'layers', '1', 'fc2', 'kernel') has PT grad norm 7.071859836578369 and flax grad norm 7.05078125.
70
+ ❌ Layer ('model', 'decoder', 'layers', '10', 'fc1', 'kernel') has PT grad norm 16.904926300048828 and flax grad norm 16.859375.
71
+ ❌ Layer ('model', 'decoder', 'layers', '10', 'fc2', 'kernel') has PT grad norm 6.783661842346191 and flax grad norm 6.765625.
72
+ ❌ Layer ('model', 'decoder', 'layers', '10', 'self_attn', 'v_proj', 'kernel') has PT grad norm 6.97633171081543 and flax grad norm 6.96484375.
73
+ ❌ Layer ('model', 'decoder', 'layers', '11', 'fc1', 'kernel') has PT grad norm 13.733073234558105 and flax grad norm 13.6875.
74
+ ❌ Layer ('model', 'decoder', 'layers', '11', 'fc2', 'kernel') has PT grad norm 6.311193466186523 and flax grad norm 6.29296875.
75
+ ❌ Layer ('model', 'decoder', 'layers', '2', 'fc1', 'kernel') has PT grad norm 6.043461322784424 and flax grad norm 6.01171875.
76
+ ❌ Layer ('model', 'decoder', 'layers', '2', 'fc2', 'kernel') has PT grad norm 8.091109275817871 and flax grad norm 8.0703125.
77
+ ❌ Layer ('model', 'decoder', 'layers', '3', 'fc1', 'kernel') has PT grad norm 6.561250686645508 and flax grad norm 6.52734375.
78
+ ❌ Layer ('model', 'decoder', 'layers', '3', 'fc2', 'kernel') has PT grad norm 8.535536766052246 and flax grad norm 8.5.
79
+ ❌ Layer ('model', 'decoder', 'layers', '4', 'fc1', 'kernel') has PT grad norm 5.882389545440674 and flax grad norm 5.859375.
80
+ ❌ Layer ('model', 'decoder', 'layers', '4', 'fc2', 'kernel') has PT grad norm 8.772762298583984 and flax grad norm 8.75.
81
+ ❌ Layer ('model', 'decoder', 'layers', '5', 'fc1', 'kernel') has PT grad norm 4.559173107147217 and flax grad norm 4.5390625.
82
+ ❌ Layer ('model', 'decoder', 'layers', '5', 'fc2', 'kernel') has PT grad norm 7.053295612335205 and flax grad norm 7.03515625.
83
+ ❌ Layer ('model', 'decoder', 'layers', '6', 'fc1', 'kernel') has PT grad norm 4.724750995635986 and flax grad norm 4.703125.
84
+ ❌ Layer ('model', 'decoder', 'layers', '6', 'fc2', 'kernel') has PT grad norm 6.6051740646362305 and flax grad norm 6.5859375.
85
+ ❌ Layer ('model', 'decoder', 'layers', '7', 'fc1', 'kernel') has PT grad norm 3.9028773307800293 and flax grad norm 3.884765625.
86
+ ❌ Layer ('model', 'decoder', 'layers', '7', 'fc2', 'kernel') has PT grad norm 6.16121244430542 and flax grad norm 6.14453125.
87
+ ❌ Layer ('model', 'decoder', 'layers', '8', 'fc1', 'kernel') has PT grad norm 3.8737242221832275 and flax grad norm 3.85546875.
88
+ ❌ Layer ('model', 'decoder', 'layers', '8', 'fc2', 'kernel') has PT grad norm 6.476221084594727 and flax grad norm 6.45703125.
89
+ ❌ Layer ('model', 'decoder', 'layers', '9', 'fc1', 'kernel') has PT grad norm 6.240624904632568 and flax grad norm 6.203125.
90
+ ❌ Layer ('model', 'decoder', 'layers', '9', 'fc2', 'kernel') has PT grad norm 6.872060775756836 and flax grad norm 6.8515625.
91
+ ❌ Layer ('model', 'encoder', 'layers', '0', 'fc1', 'kernel') has PT grad norm 18.140913009643555 and flax grad norm 18.0625.
92
+ ❌ Layer ('model', 'encoder', 'layers', '0', 'fc2', 'kernel') has PT grad norm 13.278300285339355 and flax grad norm 13.2265625.
93
+ ❌ Layer ('model', 'encoder', 'layers', '0', 'self_attn', 'v_proj', 'kernel') has PT grad norm 13.971784591674805 and flax grad norm 13.9609375.
94
+ ❌ Layer ('model', 'encoder', 'layers', '1', 'fc1', 'kernel') has PT grad norm 9.453910827636719 and flax grad norm 9.4140625.
95
+ ❌ Layer ('model', 'encoder', 'layers', '1', 'fc2', 'kernel') has PT grad norm 5.271415710449219 and flax grad norm 5.25.
96
+ ❌ Layer ('model', 'encoder', 'layers', '10', 'fc1', 'kernel') has PT grad norm 13.269391059875488 and flax grad norm 13.2109375.
97
+ ❌ Layer ('model', 'encoder', 'layers', '10', 'fc2', 'kernel') has PT grad norm 15.780173301696777 and flax grad norm 15.734375.
98
+ ❌ Layer ('model', 'encoder', 'layers', '10', 'self_attn', 'v_proj', 'kernel') has PT grad norm 21.07574462890625 and flax grad norm 21.0625.
99
+ ❌ Layer ('model', 'encoder', 'layers', '11', 'fc1', 'kernel') has PT grad norm 16.847095489501953 and flax grad norm 16.765625.
100
+ ❌ Layer ('model', 'encoder', 'layers', '11', 'fc2', 'kernel') has PT grad norm 17.480010986328125 and flax grad norm 17.421875.
101
+ ❌ Layer ('model', 'encoder', 'layers', '11', 'self_attn', 'out_proj', 'kernel') has PT grad norm 26.91538429260254 and flax grad norm 26.890625.
102
+ ❌ Layer ('model', 'encoder', 'layers', '11', 'self_attn', 'v_proj', 'kernel') has PT grad norm 26.706096649169922 and flax grad norm 26.6875.
103
+ ❌ Layer ('model', 'encoder', 'layers', '2', 'fc1', 'kernel') has PT grad norm 6.756587505340576 and flax grad norm 6.7265625.
104
+ ❌ Layer ('model', 'encoder', 'layers', '2', 'fc2', 'kernel') has PT grad norm 5.000077724456787 and flax grad norm 4.98046875.
105
+ ❌ Layer ('model', 'encoder', 'layers', '2', 'self_attn', 'out_proj', 'kernel') has PT grad norm 18.72007942199707 and flax grad norm 18.703125.
106
+ ❌ Layer ('model', 'encoder', 'layers', '3', 'fc1', 'kernel') has PT grad norm 9.560458183288574 and flax grad norm 9.515625.
107
+ ❌ Layer ('model', 'encoder', 'layers', '3', 'fc2', 'kernel') has PT grad norm 8.892805099487305 and flax grad norm 8.859375.
108
+ ❌ Layer ('model', 'encoder', 'layers', '4', 'fc1', 'kernel') has PT grad norm 8.845908164978027 and flax grad norm 8.8046875.
109
+ ❌ Layer ('model', 'encoder', 'layers', '4', 'fc2', 'kernel') has PT grad norm 8.670329093933105 and flax grad norm 8.640625.
110
+ ❌ Layer ('model', 'encoder', 'layers', '4', 'self_attn', 'out_proj', 'kernel') has PT grad norm 18.135663986206055 and flax grad norm 18.125.
111
+ ❌ Layer ('model', 'encoder', 'layers', '5', 'fc1', 'kernel') has PT grad norm 10.071086883544922 and flax grad norm 10.03125.
112
+ ❌ Layer ('model', 'encoder', 'layers', '5', 'fc2', 'kernel') has PT grad norm 9.528592109680176 and flax grad norm 9.5.
113
+ ❌ Layer ('model', 'encoder', 'layers', '5', 'self_attn', 'out_proj', 'kernel') has PT grad norm 16.202266693115234 and flax grad norm 16.1875.
114
+ ❌ Layer ('model', 'encoder', 'layers', '5', 'self_attn', 'v_proj', 'kernel') has PT grad norm 17.79180908203125 and flax grad norm 17.78125.
115
+ ❌ Layer ('model', 'encoder', 'layers', '6', 'fc1', 'kernel') has PT grad norm 12.527167320251465 and flax grad norm 12.46875.
116
+ ❌ Layer ('model', 'encoder', 'layers', '6', 'fc2', 'kernel') has PT grad norm 11.495430946350098 and flax grad norm 11.453125.
117
+ ❌ Layer ('model', 'encoder', 'layers', '6', 'self_attn', 'v_proj', 'kernel') has PT grad norm 18.312782287597656 and flax grad norm 18.296875.
118
+ ❌ Layer ('model', 'encoder', 'layers', '7', 'fc1', 'kernel') has PT grad norm 11.963201522827148 and flax grad norm 11.9140625.
119
+ ❌ Layer ('model', 'encoder', 'layers', '7', 'fc2', 'kernel') has PT grad norm 13.052857398986816 and flax grad norm 13.0078125.
120
+ ❌ Layer ('model', 'encoder', 'layers', '7', 'self_attn', 'out_proj', 'kernel') has PT grad norm 17.2364501953125 and flax grad norm 17.21875.
121
+ ❌ Layer ('model', 'encoder', 'layers', '7', 'self_attn', 'v_proj', 'kernel') has PT grad norm 18.88938331604004 and flax grad norm 18.875.
122
+ ❌ Layer ('model', 'encoder', 'layers', '8', 'fc1', 'kernel') has PT grad norm 11.773221969604492 and flax grad norm 11.71875.
123
+ ❌ Layer ('model', 'encoder', 'layers', '8', 'fc2', 'kernel') has PT grad norm 14.441213607788086 and flax grad norm 14.3984375.
124
+ ❌ Layer ('model', 'encoder', 'layers', '8', 'self_attn', 'out_proj', 'kernel') has PT grad norm 19.045316696166992 and flax grad norm 19.03125.
125
+ ❌ Layer ('model', 'encoder', 'layers', '8', 'self_attn', 'v_proj', 'kernel') has PT grad norm 18.37466049194336 and flax grad norm 18.359375.
126
+ ❌ Layer ('model', 'encoder', 'layers', '9', 'fc1', 'kernel') has PT grad norm 12.223063468933105 and flax grad norm 12.1640625.
127
+ ❌ Layer ('model', 'encoder', 'layers', '9', 'fc2', 'kernel') has PT grad norm 15.896522521972656 and flax grad norm 15.8515625.
128
+ --------------------------Checking rel gradients match--------------------------
129
+ ❌ Layer ('final_logits_bias',) has PT grad norm 0.0 and flax grad norm 0.0.
130
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 8.274865592738934e-08 and flax grad norm 0.0.
131
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'self_attn', 'k_proj', 'bias') has PT grad norm 3.530680814378684e-08 and flax grad norm 0.0.
132
+ ❌ Layer ('model', 'decoder', 'layers', '1', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 9.156278935051887e-08 and flax grad norm 0.0.
133
+ ❌ Layer ('model', 'decoder', 'layers', '1', 'self_attn', 'k_proj', 'bias') has PT grad norm 2.7762926180230352e-08 and flax grad norm 0.0.
134
+ ❌ Layer ('model', 'decoder', 'layers', '10', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 2.314587632668008e-08 and flax grad norm 0.0.
135
+ ❌ Layer ('model', 'decoder', 'layers', '10', 'self_attn', 'k_proj', 'bias') has PT grad norm 1.0350275303494527e-08 and flax grad norm 0.0.
136
+ ❌ Layer ('model', 'decoder', 'layers', '11', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 2.4003222520718737e-08 and flax grad norm 0.0.
137
+ ❌ Layer ('model', 'decoder', 'layers', '11', 'self_attn', 'k_proj', 'bias') has PT grad norm 1.0850777165671843e-08 and flax grad norm 0.0.
138
+ ❌ Layer ('model', 'decoder', 'layers', '2', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 8.753153935003866e-08 and flax grad norm 0.0.
139
+ ❌ Layer ('model', 'decoder', 'layers', '2', 'self_attn', 'k_proj', 'bias') has PT grad norm 3.340263532436438e-08 and flax grad norm 0.0.
140
+ ❌ Layer ('model', 'decoder', 'layers', '3', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 7.864576190286243e-08 and flax grad norm 0.0.
141
+ ❌ Layer ('model', 'decoder', 'layers', '3', 'self_attn', 'k_proj', 'bias') has PT grad norm 3.161582284860742e-08 and flax grad norm 0.0.
142
+ ❌ Layer ('model', 'decoder', 'layers', '4', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 3.1698593971896116e-08 and flax grad norm 0.0.
143
+ ❌ Layer ('model', 'decoder', 'layers', '4', 'self_attn', 'k_proj', 'bias') has PT grad norm 3.397210690536667e-08 and flax grad norm 0.0.
144
+ ❌ Layer ('model', 'decoder', 'layers', '5', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 4.269594100492213e-08 and flax grad norm 0.0.
145
+ ❌ Layer ('model', 'decoder', 'layers', '5', 'self_attn', 'k_proj', 'bias') has PT grad norm 2.3111518032692402e-08 and flax grad norm 0.0.
146
+ ❌ Layer ('model', 'decoder', 'layers', '6', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 3.222339373110117e-08 and flax grad norm 0.0.
147
+ ❌ Layer ('model', 'decoder', 'layers', '6', 'self_attn', 'k_proj', 'bias') has PT grad norm 2.2391466458770992e-08 and flax grad norm 0.0.
148
+ ❌ Layer ('model', 'decoder', 'layers', '7', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 2.4886496419185278e-08 and flax grad norm 0.0.
149
+ ❌ Layer ('model', 'decoder', 'layers', '7', 'self_attn', 'k_proj', 'bias') has PT grad norm 1.1538945798861278e-08 and flax grad norm 0.0.
150
+ ❌ Layer ('model', 'decoder', 'layers', '8', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 2.3322632713984603e-08 and flax grad norm 0.0.
151
+ ❌ Layer ('model', 'decoder', 'layers', '8', 'self_attn', 'k_proj', 'bias') has PT grad norm 1.525707205018989e-08 and flax grad norm 0.0.
152
+ ❌ Layer ('model', 'decoder', 'layers', '9', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 2.3752901867624132e-08 and flax grad norm 0.0.
153
+ ❌ Layer ('model', 'decoder', 'layers', '9', 'self_attn', 'k_proj', 'bias') has PT grad norm 1.4804857784156411e-08 and flax grad norm 0.0.
154
+ ❌ Layer ('model', 'encoder', 'layers', '0', 'self_attn', 'k_proj', 'bias') has PT grad norm 8.215602775862862e-08 and flax grad norm 0.0.
155
+ ❌ Layer ('model', 'encoder', 'layers', '1', 'self_attn', 'k_proj', 'bias') has PT grad norm 1.3884370275718538e-07 and flax grad norm 0.0.
156
+ ❌ Layer ('model', 'encoder', 'layers', '10', 'self_attn', 'k_proj', 'bias') has PT grad norm 6.668184937552724e-08 and flax grad norm 0.0.
157
+ ❌ Layer ('model', 'encoder', 'layers', '11', 'self_attn', 'k_proj', 'bias') has PT grad norm 8.486110658623147e-08 and flax grad norm 0.0.
158
+ ❌ Layer ('model', 'encoder', 'layers', '2', 'self_attn', 'k_proj', 'bias') has PT grad norm 7.912614563565512e-08 and flax grad norm 0.0.
159
+ ❌ Layer ('model', 'encoder', 'layers', '3', 'self_attn', 'k_proj', 'bias') has PT grad norm 7.959246062227976e-08 and flax grad norm 0.0.
160
+ ❌ Layer ('model', 'encoder', 'layers', '4', 'self_attn', 'k_proj', 'bias') has PT grad norm 1.1111747255654336e-07 and flax grad norm 0.0.
161
+ ❌ Layer ('model', 'encoder', 'layers', '5', 'self_attn', 'k_proj', 'bias') has PT grad norm 1.0121711824240265e-07 and flax grad norm 0.0.
162
+ ❌ Layer ('model', 'encoder', 'layers', '6', 'self_attn', 'k_proj', 'bias') has PT grad norm 7.735735607639072e-08 and flax grad norm 0.0.
163
+ ❌ Layer ('model', 'encoder', 'layers', '7', 'self_attn', 'k_proj', 'bias') has PT grad norm 1.0352330548357713e-07 and flax grad norm 0.0.
164
+ ❌ Layer ('model', 'encoder', 'layers', '8', 'self_attn', 'k_proj', 'bias') has PT grad norm 8.3155640595578e-08 and flax grad norm 0.0.
165
+ ❌ Layer ('model', 'encoder', 'layers', '9', 'self_attn', 'k_proj', 'bias') has PT grad norm 6.08824493042448e-08 and flax grad norm 0.0.
166
+ =========================================
167
+ Check facebook/bart-large-cnn ...
168
+ --------------------------Checking logits match--------------------------
169
+ Flax logits shape: (2, 64, 50264), PyTorch logits shape: torch.Size([2, 64, 50264])
170
+ βœ… Difference between Flax and PyTorch is 0.0003502368927001953 (< 0.01)
171
+ --------------------------Checking losses match--------------------------
172
+ Flax loss: 13.418181419372559, PyTorch loss: 13.418176651000977
173
+ βœ… Difference between Flax and PyTorch is 4.76837158203125e-06 (< 0.01)
174
+ --------------------------Checking gradients match--------------------------
175
+ βœ… All grads pass
176
+ --------------------------Checking rel gradients match--------------------------
177
+ ❌ Layer ('final_logits_bias',) has PT grad norm 0.0 and flax grad norm 0.0.
178
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 3.5387660091146245e-07 and flax grad norm 4.874667069998395e-07.
179
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'self_attn', 'k_proj', 'bias') has PT grad norm 6.254911966152576e-08 and flax grad norm 6.927437112835833e-08.
180
+ ❌ Layer ('model', 'decoder', 'layers', '1', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 2.0864062832970376e-07 and flax grad norm 1.8239754240312323e-07.
181
+ ❌ Layer ('model', 'decoder', 'layers', '1', 'self_attn', 'k_proj', 'bias') has PT grad norm 6.265895535761956e-08 and flax grad norm 6.79184637419894e-08.
182
+ ❌ Layer ('model', 'decoder', 'layers', '10', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 2.3348372124587513e-08 and flax grad norm 1.9192864186834413e-08.
183
+ ❌ Layer ('model', 'decoder', 'layers', '10', 'self_attn', 'k_proj', 'bias') has PT grad norm 2.108701835368265e-08 and flax grad norm 1.938536442480654e-08.
184
+ ❌ Layer ('model', 'decoder', 'layers', '11', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 2.4383044916476138e-08 and flax grad norm 1.890670375814807e-08.
185
+ ❌ Layer ('model', 'decoder', 'layers', '11', 'self_attn', 'k_proj', 'bias') has PT grad norm 1.4334801790027996e-08 and flax grad norm 1.3059753278810149e-08.
186
+ ❌ Layer ('model', 'decoder', 'layers', '2', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 2.0973679681901558e-07 and flax grad norm 2.6336286396144715e-07.
187
+ ❌ Layer ('model', 'decoder', 'layers', '2', 'self_attn', 'k_proj', 'bias') has PT grad norm 8.528008521579977e-08 and flax grad norm 1.286241939624233e-07.
188
+ ❌ Layer ('model', 'decoder', 'layers', '3', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 1.4659757141544105e-07 and flax grad norm 1.4895935862568876e-07.
189
+ ❌ Layer ('model', 'decoder', 'layers', '3', 'self_attn', 'k_proj', 'bias') has PT grad norm 1.2112769809391466e-07 and flax grad norm 1.382354497536653e-07.
190
+ ❌ Layer ('model', 'decoder', 'layers', '4', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 6.575358924010288e-08 and flax grad norm 7.240216604031957e-08.
191
+ ❌ Layer ('model', 'decoder', 'layers', '4', 'self_attn', 'k_proj', 'bias') has PT grad norm 5.0567738441031906e-08 and flax grad norm 5.817578241362753e-08.
192
+ ❌ Layer ('model', 'decoder', 'layers', '5', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 2.5854723162410664e-07 and flax grad norm 2.9657505251634575e-07.
193
+ ❌ Layer ('model', 'decoder', 'layers', '5', 'self_attn', 'k_proj', 'bias') has PT grad norm 8.977868048987148e-08 and flax grad norm 8.695727160556999e-08.
194
+ ❌ Layer ('model', 'decoder', 'layers', '6', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 1.271907592581556e-07 and flax grad norm 1.5420768306739774e-07.
195
+ ❌ Layer ('model', 'decoder', 'layers', '6', 'self_attn', 'k_proj', 'bias') has PT grad norm 3.32223777377294e-08 and flax grad norm 2.9034252335691235e-08.
196
+ ❌ Layer ('model', 'decoder', 'layers', '7', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 2.932817011469524e-08 and flax grad norm 2.990202219166349e-08.
197
+ ❌ Layer ('model', 'decoder', 'layers', '7', 'self_attn', 'k_proj', 'bias') has PT grad norm 2.2563149570942187e-08 and flax grad norm 1.903124946522894e-08.
198
+ ❌ Layer ('model', 'decoder', 'layers', '8', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 2.1031839381180362e-08 and flax grad norm 1.922012415889185e-08.
199
+ ❌ Layer ('model', 'decoder', 'layers', '8', 'self_attn', 'k_proj', 'bias') has PT grad norm 1.9617312219111227e-08 and flax grad norm 1.901776514046105e-08.
200
+ ❌ Layer ('model', 'encoder', 'layers', '0', 'self_attn', 'k_proj', 'bias') has PT grad norm 9.498415209918676e-08 and flax grad norm 1.0714285281210323e-07.
201
+ ❌ Layer ('model', 'encoder', 'layers', '1', 'self_attn', 'k_proj', 'bias') has PT grad norm 4.2883741002697207e-08 and flax grad norm 3.708849050099161e-08.
202
+ ❌ Layer ('model', 'encoder', 'layers', '10', 'self_attn', 'k_proj', 'bias') has PT grad norm 6.720534884152585e-08 and flax grad norm 5.363398614122161e-08.
203
+ ❌ Layer ('model', 'encoder', 'layers', '11', 'self_attn', 'k_proj', 'bias') has PT grad norm 7.474503149751399e-08 and flax grad norm 7.271213320336756e-08.
204
+ ❌ Layer ('model', 'encoder', 'layers', '2', 'self_attn', 'k_proj', 'bias') has PT grad norm 2.8607770374833308e-08 and flax grad norm 2.428515344377047e-08.
205
+ ❌ Layer ('model', 'encoder', 'layers', '3', 'self_attn', 'k_proj', 'bias') has PT grad norm 6.400713203902342e-08 and flax grad norm 5.387828849734433e-08.
206
+ ❌ Layer ('model', 'encoder', 'layers', '4', 'self_attn', 'k_proj', 'bias') has PT grad norm 4.873627545975978e-08 and flax grad norm 4.757723104376055e-08.
207
+ ❌ Layer ('model', 'encoder', 'layers', '5', 'self_attn', 'k_proj', 'bias') has PT grad norm 5.0619281211083944e-08 and flax grad norm 4.67279193117065e-08.
208
+ ❌ Layer ('model', 'encoder', 'layers', '6', 'self_attn', 'k_proj', 'bias') has PT grad norm 5.6844903895125753e-08 and flax grad norm 6.739185920423552e-08.
209
+ ❌ Layer ('model', 'encoder', 'layers', '7', 'self_attn', 'k_proj', 'bias') has PT grad norm 5.603576624935158e-08 and flax grad norm 5.457893337279529e-08.
210
+ ❌ Layer ('model', 'encoder', 'layers', '8', 'self_attn', 'k_proj', 'bias') has PT grad norm 5.864935914701164e-08 and flax grad norm 6.345069891722233e-08.
211
+ ❌ Layer ('model', 'encoder', 'layers', '9', 'self_attn', 'k_proj', 'bias') has PT grad norm 6.470781244161117e-08 and flax grad norm 6.696199505995537e-08.
212
+ =========================================
before_fix_log.txt ADDED
@@ -0,0 +1,15 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ =========================================
2
+ Check hf-internal-testing/tiny-random-bart ...
3
+ --------------------------Checking logits match--------------------------
4
+ Flax logits shape: (2, 64, 1000), PyTorch logits shape: torch.Size([2, 64, 1000])
5
+ βœ… Difference between Flax and PyTorch is 8.940696716308594e-08 (< 0.01)
6
+ --------------------------Checking losses match--------------------------
7
+ Flax loss: 6.923163414001465, PyTorch loss: 6.923163414001465
8
+ βœ… Difference between Flax and PyTorch is 0.0 (< 0.01)
9
+ --------------------------Checking gradients match--------------------------
10
+ ❌ Layer ('final_logits_bias',) has PT grad norm 0.0 and flax grad norm 0.09163407981395721.
11
+ --------------------------Checking rel gradients match--------------------------
12
+ ❌ Layer ('final_logits_bias',) has PT grad norm 0.0 and flax grad norm 0.09163407981395721.
13
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 9.3028212357852e-14 and flax grad norm 1.6552796459901042e-13.
14
+ ...
15
+ =========================================
before_fix_pretrained_log.txt ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ =========================================
2
+ Check facebook/bart-large ...
3
+ --------------------------Checking logits match--------------------------
4
+ Flax logits shape: (2, 64, 50265), PyTorch logits shape: torch.Size([2, 64, 50265])
5
+ βœ… Difference between Flax and PyTorch is 0.00039315223693847656 (< 0.01)
6
+ --------------------------Checking losses match--------------------------
7
+ Flax loss: 15.027304649353027, PyTorch loss: 15.027304649353027
8
+ βœ… Difference between Flax and PyTorch is 0.0 (< 0.01)
9
+ --------------------------Checking gradients match--------------------------
10
+ ❌ Layer ('final_logits_bias',) has PT grad norm 0.0 and flax grad norm 0.09944064915180206.
11
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'fc1', 'kernel') has PT grad norm 13.111018180847168 and flax grad norm 13.0546875.
12
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'fc2', 'kernel') has PT grad norm 8.751346588134766 and flax grad norm 8.71875.
13
+ ...
14
+ ❌ Layer ('model', 'encoder', 'layers', '0', 'self_attn', 'k_proj', 'kernel') has PT grad norm 18.60892105102539 and flax grad norm 18.59375.
15
+ ...
16
+ ❌ Layer ('model', 'encoder', 'layers', '0', 'self_attn', 'v_proj', 'kernel') has PT grad norm 96.85579681396484 and flax grad norm 96.8125.
17
+ ...
18
+ ❌ Layer ('model', 'encoder', 'layers', '1', 'self_attn', 'out_proj', 'kernel') has PT grad norm 199.41278076171875 and flax grad norm 199.25.
19
+ ...
20
+ --------------------------Checking rel gradients match--------------------------
21
+ ❌ Layer ('final_logits_bias',) has PT grad norm 0.0 and flax grad norm 0.09944064915180206.
22
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 1.4212106691502413e-07 and flax grad norm 0.0.
23
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'self_attn', 'k_proj', 'bias') has PT grad norm 2.0100719311244575e-08 and flax grad norm 0.0.
24
+ ...
25
+ =========================================
26
+ Check facebook/bart-large-cnn ...
27
+ --------------------------Checking logits match--------------------------
28
+ Flax logits shape: (2, 64, 50264), PyTorch logits shape: torch.Size([2, 64, 50264])
29
+ βœ… Difference between Flax and PyTorch is 0.0001919269561767578 (< 0.01)
30
+ --------------------------Checking losses match--------------------------
31
+ Flax loss: 13.262251853942871, PyTorch loss: 13.262249946594238
32
+ βœ… Difference between Flax and PyTorch is 1.9073486328125e-06 (< 0.01)
33
+ --------------------------Checking gradients match--------------------------
34
+ ❌ Layer ('final_logits_bias',) has PT grad norm 0.0 and flax grad norm 0.09764379262924194.
35
+ --------------------------Checking rel gradients match--------------------------
36
+ ❌ Layer ('final_logits_bias',) has PT grad norm 0.0 and flax grad norm 0.09764379262924194.
37
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 2.1513474735002092e-07 and flax grad norm 1.5481474235912174e-07.
38
+ ❌ Layer ('model', 'decoder', 'layers', '0', 'self_attn', 'k_proj', 'bias') has PT grad norm 3.8047311079481005e-08 and flax grad norm 3.508952062247772e-08.
39
+ ...
40
+ =========================================
check_gradients_pt_flax.py CHANGED
@@ -163,16 +163,12 @@ def compare_grads(model_id, pt_architecture):
163
 
164
  pt_loss.backward()
165
 
166
- pt_grad_dict = {k: v.grad if v.grad is not None else torch.zeros_like(v) for k, v in pt_model.named_parameters()}
 
167
 
168
- for k in pt_model.state_dict():
169
- if k not in pt_grad_dict:
170
- # set any unused parameters to zero in the grad-dict
171
- # these won't be compared to the Flax model, but required for loading the PT model from state-dict
172
- pt_grad_dict[k] = torch.zeros_like(pt_model.state_dict()[k])
173
- pt_model.state_dict()[k] = pt_grad_dict[k]
174
 
175
- pt_model.load_state_dict(pt_grad_dict)
176
 
177
  with tempfile.TemporaryDirectory() as tmpdirname:
178
  pt_model.save_pretrained(tmpdirname)
163
 
164
  pt_loss.backward()
165
 
166
+ pt_grad_dict = {k: v.grad for k, v in pt_model.named_parameters()}
167
+ missing_grads = [k for k in pt_model.state_dict().keys() if k not in pt_grad_dict]
168
 
169
+ missing_keys, unexpected_keys = pt_model.load_state_dict(pt_grad_dict, strict=False)
 
 
 
 
 
170
 
171
+ assert missing_grads == missing_keys, f"Error with either grads {missing_keys} or keys {unexpected_keys}"
172
 
173
  with tempfile.TemporaryDirectory() as tmpdirname:
174
  pt_model.save_pretrained(tmpdirname)
run_models.sh CHANGED
@@ -1,8 +1,8 @@
1
  #!/usr/bin/env bash
2
- #model_ids=("hf-internal-testing/tiny-random-roberta" "hf-internal-testing/tiny-random-bert" "hf-internal-testing/tiny-random-bart" "tf-internal-testing/tiny-random-t5")
3
- #model_architectures=("RobertaForMaskedLM" "BertForMaskedLM" "BartForConditionalGeneration" "T5ForConditionalGeneration")
4
- model_ids=("hf-internal-testing/tiny-random-roberta")
5
- model_architectures=("RobertaForMaskedLM")
6
 
7
  rm -rf log.txt
8
  touch log.txt
1
  #!/usr/bin/env bash
2
+ model_ids=("roberta-base" "bert-base-cased" "t5-small" "facebook/bart-large" "facebook/bart-large-cnn")
3
+ model_architectures=("RobertaForMaskedLM" "BertForMaskedLM" "T5ForConditionalGeneration" "BartForConditionalGeneration" "BartForConditionalGeneration" )
4
+ #model_ids=("hf-internal-testing/tiny-random-roberta" "hf-internal-testing/tiny-random-bert" "hf-internal-testing/tiny-random-t5" "hf-internal-testing/tiny-random-bart")
5
+ #model_architectures=("RobertaForMaskedLM" "BertForMaskedLM" "T5ForConditionalGeneration" "BartForConditionalGeneration")
6
 
7
  rm -rf log.txt
8
  touch log.txt