Refactor data structures to reduce memory usage#142
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copybara-service[bot] merged 3 commits intogoogle:devfrom Apr 10, 2024
Merged
Refactor data structures to reduce memory usage#142copybara-service[bot] merged 3 commits intogoogle:devfrom
copybara-service[bot] merged 3 commits intogoogle:devfrom
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jan-wassenberg
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Apr 10, 2024
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Nice, thanks for resolving this TODO :) Some suggestions:
| static constexpr size_t kGatingEinsumWSize = 2 * kFFHiddenDim * kModelDim; | ||
| static constexpr size_t kConv1dWidth = TConfig::kConv1dWidth; | ||
| static constexpr bool kFFBiases = TConfig::kFFBiases; | ||
| static constexpr size_t kAOBiaseDim = |
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Typo (extra e), maybe instead kAttnBiasDim?
| }; | ||
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| struct { | ||
| ArrayT<float, kGriffinDim * kGriffinDim> griffin_linear_x_w; |
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Consider naming the struct member griffin, so we can remove the griffin_ prefix from its names?
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I agree, your solution should be better.
| static constexpr size_t kGatingEinsumWSize = TLayer::kGatingEinsumWSize; | ||
| static constexpr size_t kConv1dWidth = TLayer::kConv1dWidth; | ||
| static constexpr bool kFFBiases = TLayer::kFFBiases; | ||
| static constexpr size_t kAOBiaseDim = TLayer::kAOBiaseDim; |
jan-wassenberg
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Nice, thanks for making the change :)
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This PR moves the Gemma attention weights and Griffin weights into a union to share memory and reduces the additional overhead when not using the Griffin model.