From 9de5fc92a15f961cd113af90587a243d3efefa02 Mon Sep 17 00:00:00 2001
From: hrouis <houssemeddine.rouis92@gmail.com>
Date: Wed, 25 Sep 2024 15:09:09 +0200
Subject: [PATCH] minor kernel cleanings
---
.../backend/cpu/operator/PowImpl_kernels.hpp | 24 ++++++++-----------
1 file changed, 10 insertions(+), 14 deletions(-)
diff --git a/include/aidge/backend/cpu/operator/PowImpl_kernels.hpp b/include/aidge/backend/cpu/operator/PowImpl_kernels.hpp
index a89dc9ff..ab9b2ccc 100644
--- a/include/aidge/backend/cpu/operator/PowImpl_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/PowImpl_kernels.hpp
@@ -31,14 +31,10 @@ void PowImpl_cpu_forward_kernel(const std::vector<std::size_t>& input1Dims,
const I2* input_2 = static_cast<const I2*>(input2_);
O* output = static_cast<O*>(output_);
- size_t totalElements = 1;
- for (size_t dimSize : outputDims) {
- totalElements *= dimSize;
- }
-
+ std::size_t totalElements = std::accumulate(outputDims.cbegin(), outputDims.cend(), std::size_t(1), std::multiplies<std::size_t>());
for (std::size_t oIndex = 0; oIndex < totalElements; ++oIndex)
{
- std::vector<size_t> indexes = getMultiDimIndices(outputDims, oIndex);
+ std::vector<std::size_t> indexes = getMultiDimIndices(outputDims, oIndex);
std::size_t idx1 = getFlattenedIndex(input1Dims, indexes);
std::size_t idx2 = getFlattenedIndex(input2Dims, indexes);
@@ -63,24 +59,24 @@ void PowImpl_cpu_backward_kernel(const std::vector<std::size_t>& input0Dims,
const O* gradOut = static_cast<const O*>(gradOutput_);
// Fill input grads with zeros
- auto input0Elements = std::accumulate(input0Dims.cbegin(), input0Dims.cend(), std::size_t(1), std::multiplies<std::size_t>());
+ std::size_t input0Elements = std::accumulate(input0Dims.cbegin(), input0Dims.cend(), std::size_t(1), std::multiplies<std::size_t>());
std::fill(grad0, grad0 + input0Elements, I1(0));
- auto input1Elements = std::accumulate(input1Dims.cbegin(), input1Dims.cend(), std::size_t(1), std::multiplies<std::size_t>());
- std::fill(grad1, grad1 + input1Elements, I1(0));
+ std::size_t input1Elements = std::accumulate(input1Dims.cbegin(), input1Dims.cend(), std::size_t(1), std::multiplies<std::size_t>());
+ std::fill(grad1, grad1 + input1Elements, I2(0));
- auto totalElements = std::accumulate(outputDims.cbegin(), outputDims.cend(), std::size_t(1), std::multiplies<std::size_t>());
- for (size_t i = 0; i < totalElements; ++i)
+ std::size_t totalElements = std::accumulate(outputDims.cbegin(), outputDims.cend(), std::size_t(1), std::multiplies<std::size_t>());
+ for (size_t oIndex = 0; oIndex < totalElements; ++oIndex)
{
// Compute indexes in inputs 0 and 1 to support broadcasting
- std::vector<std::size_t> indexes = getMultiDimIndices(outputDims, i);
+ std::vector<std::size_t> indexes = getMultiDimIndices(outputDims, oIndex);
std::size_t idx0 = getFlattenedIndex(input0Dims, indexes);
std::size_t idx1 = getFlattenedIndex(input1Dims, indexes);
// grad0 = grad_output * (input1 * pow(input0, (input1 -1)))
- grad0[idx0] += gradOut[i]*input1[idx1]* std::pow(input0[idx0], input1[idx1]-1);
+ grad0[idx0] += gradOut[oIndex]*input1[idx1]* std::pow(input0[idx0], input1[idx1]-1);
// grad1 = grad_output * (output * ln(input0))
- grad1[idx1] += gradOut[i] * std::pow(input0[idx0], input1[idx1]) * std::log(input0[idx0]);
+ grad1[idx1] += gradOut[oIndex] * std::pow(input0[idx0], input1[idx1]) * std::log(input0[idx0]);
}
}
--
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