Automated PR - 2026-07-07

2026-07-07 16:57:50 +00:00
parent 780984275f
commit 63fd9a4f86
157 changed files with 15976 additions and 5043 deletions
@@ -0,0 +1,114 @@
+/******************************************************************************
+ * Copyright (c) 2023, Tri Dao.
+ ******************************************************************************/
+
+// Host entry point for the fused RMS-norm + RoPE kernel.
+
+#include <ATen/cuda/CUDAContext.h>
+#include <c10/cuda/CUDAGuard.h>
+#include <torch/extension.h>
+#include <vector>
+
+#include "fast_hadamard_transform.h"
+
+#define CHECK_SHAPE(x, ...) TORCH_CHECK(x.sizes() == torch::IntArrayRef({__VA_ARGS__}), #x " must have shape (" #__VA_ARGS__ ")")
+
+template<typename input_t, typename output_t, bool norm_affine>
+void rms_norm_rope_cuda(NormRopeHadamardParamsBase &params, cudaStream_t stream);
+
+void set_norm_rope_hadamard_params(NormRopeHadamardParamsBase &params,
+                         // sizes
+                         const size_t batch,
+                         const size_t dim,
+                         const size_t multiple,
+                         // device pointers
+                         const at::Tensor x,
+                         const at::Tensor cos_freqs,
+                         const at::Tensor sin_freqs,
+                         const at::Tensor weights,
+                         const at::Tensor out,
+
+                         bool norm_affine,
+                         float scale
+                         ) {
+
+    // Reset the parameters
+    memset(&params, 0, sizeof(params));
+
+    params.batch = batch;
+    params.dim = dim;
+    params.log_N = int(ceil(std::log2(dim / multiple)));
+
+    // Set the pointers and strides.
+    params.x_ptr = x.data_ptr();
+    params.out_ptr = out.data_ptr();
+    params.cos_freq_ptr = cos_freqs.data_ptr();
+    params.sin_freq_ptr = sin_freqs.data_ptr();
+    if (norm_affine){
+        params.weights_ptr = weights.data_ptr();
+    } else {
+        params.weights_ptr = nullptr;
+    }
+    // All stride are in elements, not bytes.
+    params.x_batch_stride = x.stride(0);
+    params.out_batch_stride = out.stride(0);
+    params.cos_freq_batch_stride = cos_freqs.stride(0);
+    params.sin_freq_batch_stride = sin_freqs.stride(0);
+
+    params.scale = scale;
+
+}
+
+at::Tensor rms_norm_rope(at::Tensor &x, c10::optional<at::Tensor>& weights_, at::Tensor &cos_freqs, at::Tensor &sin_freqs, bool out_16bit) {
+    auto input_type = x.scalar_type();
+    float scale = 1.0f; // :D
+    TORCH_CHECK(input_type == at::ScalarType::BFloat16);
+    TORCH_CHECK(x.is_cuda());
+    const auto shapes_og = x.sizes();
+    const int dim_og = x.size(-1);
+    x = x.reshape({-1, dim_og});
+    if (x.stride(-1) != 1) { x = x.contiguous(); }
+    const auto sizes = x.sizes();
+    const int batch_size = sizes[0];
+    cos_freqs = cos_freqs.reshape({-1, dim_og});
+    sin_freqs = sin_freqs.reshape({-1, dim_og});
+    at::Tensor weights;
+    bool norm_affine = false;
+    if(weights_.has_value()){
+        weights = weights_.value();
+        norm_affine = true;
+    }
+    CHECK_SHAPE(x, batch_size, dim_og);
+    TORCH_CHECK(x.stride(1) == 1);
+    if (dim_og % 8 != 0) {
+        x = torch::nn::functional::pad(x, torch::nn::functional::PadFuncOptions({0, 8 - dim_og % 8}));
+    }
+    const int dim = x.size(1);
+    at::Tensor out;
+    if (out_16bit){
+        out = torch::empty(x.sizes(), x.options().dtype(torch::kBFloat16));
+    } else {
+        out = torch::empty(x.sizes(), x.options().dtype(torch::kFloat8_e4m3fn));
+    }
+    at::cuda::CUDAGuard device_guard{(char)x.get_device()};
+    auto stream = at::cuda::getCurrentCUDAStream().stream();
+    NormRopeHadamardParamsBase params;
+    set_norm_rope_hadamard_params(params, batch_size, dim, 1, x, cos_freqs, sin_freqs, weights, out, norm_affine, scale);
+    TORCH_CHECK(dim % 8 == 0, "fast_hadamard_transform only supports hidden dimension divisible by 8 for now");
+    TORCH_CHECK(dim <= 32768, "fast_hadamard_transform only supports hidden dimension at most 32768 for now");
+    if (norm_affine){
+        if (out_16bit){
+            rms_norm_rope_cuda<at::BFloat16, at::BFloat16, true>(params, stream);
+        } else {
+            rms_norm_rope_cuda<at::BFloat16, at::Float8_e4m3fn, true>(params, stream);
+        }
+
+    } else {
+        if (out_16bit){
+            rms_norm_rope_cuda<at::BFloat16, at::BFloat16, false>(params, stream);
+        } else {
+            rms_norm_rope_cuda<at::BFloat16, at::Float8_e4m3fn, false>(params, stream);
+        }
+    }
+    return out.reshape(shapes_og);
+}