L1
==

Auto-generated from mlx_code_defs

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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.nn.L1Loss</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.nn.L1Loss.html" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div><div id="NumPy_1" class="op-tab-pane "><h4>NumPy</h4><div class="op-detail-row"><span class="label">API:</span> <code>numpy.polynomial.tests.test_legendre.L1</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://numpy.org/doc/stable/reference/generated/numpy.polynomial.tests.test_legendre.L1.html" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div><div id="Apple MLX_2" class="op-tab-pane "><h4>Apple MLX</h4><div class="op-detail-row"><span class="label">API:</span> <code>mlx.nn.losses.l1_loss</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.nn.losses.l1_loss.html" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div> 
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