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Fix conversion of unnormalized BF16->BF16 weights (llama/7843)
* add truncate_bf16 * truncate intermediate fp32 if converting bf16 to bf16 * fix masking in __compute_fp32_to_bf16 * np.int16 no longer used * missing cast and additional numpy 2.x fix * ggml-impl : do not flush bf16 subnormals to zero * ggml : add reference fp32 to bf16 conversion The fast version is no longer equivalent for all platforms because of the handling of subnormal values. * gguf-py : remove flush to zero for bf16 subnormals * gguf-py : remove float32 truncation to bf16 Rounding achieves the same thing in the cases where this was used. * missed prototype update in merge * merge cleanup --------- Co-authored-by: Francis Couture-Harpin <git@compilade.net>
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committed by
Georgi Gerganov
parent
9cf14ebcbc
commit
6cb38c3673
@ -349,6 +349,7 @@ extern "C" {
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GGML_API ggml_bf16_t ggml_fp32_to_bf16(float);
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GGML_API float ggml_bf16_to_fp32(ggml_bf16_t); // consider just doing << 16
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GGML_API void ggml_bf16_to_fp32_row(const ggml_bf16_t *, float *, int64_t);
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GGML_API void ggml_fp32_to_bf16_row_ref(const float *, ggml_bf16_t *, int64_t);
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GGML_API void ggml_fp32_to_bf16_row(const float *, ggml_bf16_t *, int64_t);
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struct ggml_object;
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