<ruby id="bdb3f"></ruby>

    <p id="bdb3f"><cite id="bdb3f"></cite></p>

      <p id="bdb3f"><cite id="bdb3f"><th id="bdb3f"></th></cite></p><p id="bdb3f"></p>
        <p id="bdb3f"><cite id="bdb3f"></cite></p>

          <pre id="bdb3f"></pre>
          <pre id="bdb3f"><del id="bdb3f"><thead id="bdb3f"></thead></del></pre>

          <ruby id="bdb3f"><mark id="bdb3f"></mark></ruby><ruby id="bdb3f"></ruby>
          <pre id="bdb3f"><pre id="bdb3f"><mark id="bdb3f"></mark></pre></pre><output id="bdb3f"></output><p id="bdb3f"></p><p id="bdb3f"></p>

          <pre id="bdb3f"><del id="bdb3f"><progress id="bdb3f"></progress></del></pre>

                <ruby id="bdb3f"></ruby>

                企業??AI智能體構建引擎,智能編排和調試,一鍵部署,支持知識庫和私有化部署方案 廣告
                # torchvision.utils # torchvision.utils ## torchvision.utils.make\_grid(tensor, nrow=8, padding=2, normalize=False, range=None, scale\_each=False) 猜測,用來做 `雪碧圖的`(`sprite image`)。 給定 `4D mini-batch Tensor`, 形狀為 `(B x C x H x W)`,或者一個`a list of image`,做成一個`size`為`(B / nrow, nrow)`的雪碧圖。 - normalize=True ,會將圖片的像素值歸一化處理 - 如果 range=(min, max), min和max是數字,那么`min`,`max`用來規范化`image` - scale\_each=True ,每個圖片獨立規范化,而不是根據所有圖片的像素最大最小值來規范化 [Example usage is given in this notebook](https://gist.github.com/anonymous/bf16430f7750c023141c562f3e9f2a91) ## torchvision.utils.save\_image(tensor, filename, nrow=8, padding=2, normalize=False, range=None, scale\_each=False) 將給定的`Tensor`保存成image文件。如果給定的是`mini-batch tensor`,那就用`make-grid`做成雪碧圖,再保存。
                  <ruby id="bdb3f"></ruby>

                  <p id="bdb3f"><cite id="bdb3f"></cite></p>

                    <p id="bdb3f"><cite id="bdb3f"><th id="bdb3f"></th></cite></p><p id="bdb3f"></p>
                      <p id="bdb3f"><cite id="bdb3f"></cite></p>

                        <pre id="bdb3f"></pre>
                        <pre id="bdb3f"><del id="bdb3f"><thead id="bdb3f"></thead></del></pre>

                        <ruby id="bdb3f"><mark id="bdb3f"></mark></ruby><ruby id="bdb3f"></ruby>
                        <pre id="bdb3f"><pre id="bdb3f"><mark id="bdb3f"></mark></pre></pre><output id="bdb3f"></output><p id="bdb3f"></p><p id="bdb3f"></p>

                        <pre id="bdb3f"><del id="bdb3f"><progress id="bdb3f"></progress></del></pre>

                              <ruby id="bdb3f"></ruby>

                              哎呀哎呀视频在线观看