From ceff3bb8093cdea2510890df43165b92aed880d6 Mon Sep 17 00:00:00 2001 From: Atanas Dimitrov Date: Tue, 17 Sep 2024 02:42:51 +0300 Subject: [PATCH] Appease linter --- onnxruntime/core/providers/cpu/math/cumsum.cc | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/onnxruntime/core/providers/cpu/math/cumsum.cc b/onnxruntime/core/providers/cpu/math/cumsum.cc index 8e852eeb5f8e1..8321b81021d19 100644 --- a/onnxruntime/core/providers/cpu/math/cumsum.cc +++ b/onnxruntime/core/providers/cpu/math/cumsum.cc @@ -145,7 +145,7 @@ CumSum::CumSum(const OpKernelInfo& info) : OpKernel(info), exclusive_(), reve template Status CumSum::Compute(OpKernelContext* ctx) const { - const Tensor* input = ctx->Input(0); // input tensor + const Tensor* input = ctx->Input(0); // input tensor size_t rank = input->Shape().NumDimensions(); // the rank of the input/output if (rank == 0) return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "Cannot apply CumSum operator on a scalar"); @@ -172,7 +172,7 @@ Status CumSum::Compute(OpKernelContext* ctx) const { const auto input_shape = input->Shape().GetDims(); const size_t axis = onnxruntime::narrow(axis_input); const int64_t dim = input->Shape()[axis]; // dimension size for the axis - const int64_t upper_dim_count = // number of slices we can walk through iteratively + const int64_t upper_dim_count = // number of slices we can walk through iteratively std::accumulate(input_shape.begin(), input_shape.begin() + axis, static_cast(1), std::multiplies()); const int64_t lower_dim_size = // sizes of the slices we can treat as 1D arrays std::accumulate(input_shape.begin() + axis + 1, input_shape.end(), static_cast(1), std::multiplies());