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Add a cuda kernel for upsampling. (#441)

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* Add a cuda kernel for upsampling.

* Update for the latest tokenizers version.
This commit is contained in:
Laurent Mazare
2023-08-14 13:12:17 +01:00
committed by GitHub
parent a094dc503d
commit c84883ecf2
10 changed files with 119 additions and 26 deletions
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62
candle-kernels/src/conv.cu
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@ -220,6 +220,48 @@ __device__ void max_pool2d(
dst[dst_i] = d;
}
template <typename T>
__device__ void upsample_nearest2d(
const size_t w_out,
const size_t h_out,
const double w_scale,
const double h_scale,
const size_t *info,
const T *src,
T *dst
) {
const size_t dst_i = blockIdx.x * blockDim.x + threadIdx.x;
// src: (b_size, c_in, w_in, h_in)
const size_t *src_dims = info;
const size_t *src_s = info + 4;
const size_t c = src_dims[1];
const size_t w_in = src_dims[2];
const size_t h_in = src_dims[3];
if (dst_i >= src_dims[0] * c * w_out * h_out) {
return;
}
// TODO: Improve this.
const size_t b_idx = dst_i / (w_out * h_out * c);
const size_t c_idx = (dst_i / (w_out * h_out)) % c;
const size_t dst_w = (dst_i / h_out) % w_out;
const size_t dst_h = dst_i % h_out;
size_t src_w = static_cast<size_t>(dst_w * w_scale);
size_t src_h = static_cast<size_t>(dst_h * h_scale);
if (src_w >= w_in) {
src_w = w_in - 1;
}
if (src_h >= h_in) {
src_h = h_in - 1;
}
const size_t src_i = b_idx * src_s[0] + c_idx * src_s[1] + src_w * src_s[2] + src_h * src_s[3];
dst[dst_i] = src[src_i];
}
#define CONV1D_OP(TYPENAME, TYPEACC, FN_NAME) \
extern "C" __global__ void FN_NAME( \
@ -278,11 +320,25 @@ extern "C" __global__ void FN_NAME( \
max_pool2d<TYPENAME>(src_numel, w_k, h_k, w_stride, h_stride, info, src, dst); \
} \
#define UPSAMPLE_NEAREST2D_OP(TYPENAME, FN_NAME) \
extern "C" __global__ void FN_NAME( \
const size_t w_out, \
const size_t h_out, \
const double w_scale, \
const double h_scale, \
const size_t *info, \
const TYPENAME *src, \
TYPENAME *dst \
) { \
upsample_nearest2d<TYPENAME>(w_out, h_out, w_scale, h_scale, info, src, dst); \
} \
#if __CUDA_ARCH__ >= 800
CONV1D_OP(__nv_bfloat16, float, conv1d_bf16)
CONV2D_OP(__nv_bfloat16, float, conv2d_bf16)
AVG_POOL2D_OP(__nv_bfloat16, float, avg_pool2d_bf16)
MAX_POOL2D_OP(__nv_bfloat16, max_pool2d_bf16)
UPSAMPLE_NEAREST2D_OP(__nv_bfloat16, upsample_nearest2d_bf16)
#endif
#if __CUDA_ARCH__ >= 530
@ -290,6 +346,7 @@ CONV1D_OP(__half, float, conv1d_f16)
CONV2D_OP(__half, float, conv2d_f16)
AVG_POOL2D_OP(__half, float, avg_pool2d_f16)
MAX_POOL2D_OP(__half, max_pool2d_f16)
UPSAMPLE_NEAREST2D_OP(__half, upsample_nearest2d_f16)
#endif
CONV1D_OP(float, float, conv1d_f32)
@ -311,3 +368,8 @@ MAX_POOL2D_OP(float, max_pool2d_f32)
MAX_POOL2D_OP(double, max_pool2d_f64)
MAX_POOL2D_OP(uint8_t, max_pool2d_u8)
MAX_POOL2D_OP(uint32_t, max_pool2d_u32)
UPSAMPLE_NEAREST2D_OP(float, upsample_nearest2d_f32)
UPSAMPLE_NEAREST2D_OP(double, upsample_nearest2d_f64)
UPSAMPLE_NEAREST2D_OP(uint8_t, upsample_nearest2d_u8)
UPSAMPLE_NEAREST2D_OP(uint32_t, upsample_nearest2d_u32)