Remove FloatN & simplify adam/reduce with BF16 LayerNorms #295
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karpathy
reviewed
Apr 29, 2024
| @@ -1871,45 +1851,18 @@ void gpt2_update(GPT2 *model, float learning_rate, float beta1, float beta2, flo | |||
| cudaCheck(cudaMalloc((void**)&model->v_memory, model->num_parameters * sizeof(float))); | |||
| cudaCheck(cudaMemset(model->m_memory, 0, model->num_parameters * sizeof(float))); | |||
| cudaCheck(cudaMemset(model->v_memory, 0, model->num_parameters * sizeof(float))); | |||
| printf0("allocated %d MiB for AdamW optimizer state m\n", (int)round(model->num_parameters * sizeof(float) / (1024 * 1024))); | |||
| printf0("allocated %d MiB for AdamW optimizer state v\n", (int)round(model->num_parameters * sizeof(float) / (1024 * 1024))); | |||
| printf("allocated %zu MiB for AdamW optimizer state m\n", (model->num_parameters * sizeof(float)) >> 20); | |||
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fixing this in my local pr before push, should be print0
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The MULTI_GPU path is untested, but everything else seems to work fine. I kept the per-tensor "param_sizeof" as it's used in test_gpt2.cu for example, it's not much code and may be useful again in the future.
This will create merge conflicts with #289 but hopefully not hard to fix.