/* -------------- Pytorch demystified 3: Implementing the CUDA backend ---------------- */

#pytorch-cpp-cuda-separation,
#pytorch-cpp-cuda-separation-dark {
    width: 85%;
}

#pytorch-benchmark-explained,
#pytorch-benchmark-explained-dark {
    width: 70%;
}

#pytorch-paging-explained,
#pytorch-paging-explained-dark {
    width: 100%;
}

#pytorch-mempool-motivation,
#pytorch-mempool-motivation-dark {
    width: 100%;
}

.pytorch-nsight {
    width: 100%;
    margin-top: 20px;
    margin-bottom: 20px;
}

/* Hover preview for nsight images */
@media (hover: hover) {
    .pytorch-nsight {
        position: relative;
        transition: transform 0.2s ease, box-shadow 0.2s ease;
        cursor: zoom-in;
    }

    .pytorch-nsight:hover {
        transform: scale(1.03);
        z-index: 5;
        box-shadow: 4px 6px 16px var(--color-blog-shadow);
    }
}

@media (hover: none) and (pointer: coarse) and (orientation: portrait) {
    #pytorch-cpp-cuda-separation,
    #pytorch-cpp-cuda-separation-dark {
        width: 85%;
    }

    #pytorch-benchmark-explained,
    #pytorch-benchmark-explained-dark {
        width: 85%;
    }
}