MkldnnMaxPool2d
===============

Applies max pooling 2D (MKLDNN).

**Abstract Signature:**

``MkldnnMaxPool2d(input: Tensor, kernel_size: int, stride: int, padding: int = 0, dilation: int = 1, ceil_mode: bool = False)``

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        <div id="PyTorch_0" class="op-tab-pane active"><h4>PyTorch</h4><div class="op-detail-row"><span class="label">API:</span> <code>torch.mkldnn_max_pool2d</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Direct Mapping</span></div><div class="op-detail-row"><a href="https://pytorch.org/docs/stable/generated/torch.mkldnn_max_pool2d.html" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div><div id="JAX (Core)_1" class="op-tab-pane "><h4>JAX (Core)</h4><div class="op-detail-row"><span class="label">API:</span> <code>jax.lax.reduce_window</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Plugin (max_pool_functional)</span></div></div><div id="Keras_2" class="op-tab-pane "><h4>Keras</h4><div class="op-detail-row"><span class="label">API:</span> <code>keras.ops.max_pool</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Direct Mapping</span></div><div class="op-detail-row"><a href="https://keras.io/search.html?q=keras.ops.max_pool" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div><div id="Apple MLX_3" class="op-tab-pane "><h4>Apple MLX</h4><div class="op-detail-row"><span class="label">API:</span> <code>mlx.core.max_pool2d</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Direct Mapping</span></div><div class="op-detail-row"><a href="https://ml-explore.github.io/mlx/build/html/python/_autosummary/mlx.core.max_pool2d.html" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div> 
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