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Check facebook/bart-large ...
--------------------------Checking logits match--------------------------
Flax logits shape: (2, 64, 50265), PyTorch logits shape: torch.Size([2, 64, 50265])
✅ Difference between Flax and PyTorch is 0.00039315223693847656 (< 0.01)
--------------------------Checking losses match--------------------------
Flax loss: 15.027304649353027, PyTorch loss: 15.027304649353027
✅ Difference between Flax and PyTorch is 0.0 (< 0.01)
--------------------------Checking gradients match--------------------------
❌ Layer ('final_logits_bias',) has PT grad norm 0.0 and flax grad norm 0.09944064915180206.
❌ Layer ('model', 'decoder', 'layers', '0', 'fc1', 'kernel') has PT grad norm 13.111018180847168 and flax grad norm 13.0546875.
❌ Layer ('model', 'decoder', 'layers', '0', 'fc2', 'kernel') has PT grad norm 8.751346588134766 and flax grad norm 8.71875.
...
❌ Layer ('model', 'encoder', 'layers', '0', 'self_attn', 'k_proj', 'kernel') has PT grad norm 18.60892105102539 and flax grad norm 18.59375.
...
❌ Layer ('model', 'encoder', 'layers', '0', 'self_attn', 'v_proj', 'kernel') has PT grad norm 96.85579681396484 and flax grad norm 96.8125.
...
❌ Layer ('model', 'encoder', 'layers', '1', 'self_attn', 'out_proj', 'kernel') has PT grad norm 199.41278076171875 and flax grad norm 199.25.
...
--------------------------Checking rel gradients match--------------------------
❌ Layer ('final_logits_bias',) has PT grad norm 0.0 and flax grad norm 0.09944064915180206.
❌ Layer ('model', 'decoder', 'layers', '0', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 1.4212106691502413e-07 and flax grad norm 0.0.
❌ Layer ('model', 'decoder', 'layers', '0', 'self_attn', 'k_proj', 'bias') has PT grad norm 2.0100719311244575e-08 and flax grad norm 0.0.
...
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Check facebook/bart-large-cnn ...
--------------------------Checking logits match--------------------------
Flax logits shape: (2, 64, 50264), PyTorch logits shape: torch.Size([2, 64, 50264])
✅ Difference between Flax and PyTorch is 0.0001919269561767578 (< 0.01)
--------------------------Checking losses match--------------------------
Flax loss: 13.262251853942871, PyTorch loss: 13.262249946594238
✅ Difference between Flax and PyTorch is 1.9073486328125e-06 (< 0.01)
--------------------------Checking gradients match--------------------------
❌ Layer ('final_logits_bias',) has PT grad norm 0.0 and flax grad norm 0.09764379262924194.
--------------------------Checking rel gradients match--------------------------
❌ Layer ('final_logits_bias',) has PT grad norm 0.0 and flax grad norm 0.09764379262924194.
❌ Layer ('model', 'decoder', 'layers', '0', 'encoder_attn', 'k_proj', 'bias') has PT grad norm 2.1513474735002092e-07 and flax grad norm 1.5481474235912174e-07.
❌ Layer ('model', 'decoder', 'layers', '0', 'self_attn', 'k_proj', 'bias') has PT grad norm 3.8047311079481005e-08 and flax grad norm 3.508952062247772e-08.
...
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