Repository navigation
test(compile-dag): a whole Transformer block against finite differenc… - #1493
Merged
Merged
Conversation
…es (#1384) TransformerBlockBackwardTest builds a pre-norm block from TensorOps — token and position gather, RMSNorm from primitives, two-head causal scaledDotProductAttention, gated GELU feed-forward, class-token head — and checks every one of its 204 parameter entries against central finite differences. With the attention adjoint in place nothing in the block stops the gradient, which is the end-to-end claim of #1384. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
aharakal
approved these changes
Nov 10, 2026
Merged
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
…es (#1384)
TransformerBlockBackwardTest builds a pre-norm block from TensorOps — token and position gather, RMSNorm from primitives, two-head causal scaledDotProductAttention, gated GELU feed-forward, class-token head — and checks every one of its 204 parameter entries against central finite differences. With the attention adjoint in place nothing in the block stops the gradient, which is the end-to-end claim of #1384.