Diagflat
========

Creates a diagonal matrix with the flattened input as the diagonal.

**Abstract Signature:**

``Diagflat(input: Tensor, offset: int = 0)``

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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.diagflat</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.diagflat.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.numpy.diagflat</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://jax.readthedocs.io/en/latest/_autosummary/jax.numpy.diagflat.html" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div><div id="NumPy_2" class="op-tab-pane "><h4>NumPy</h4><div class="op-detail-row"><span class="label">API:</span> <code>numpy.diagflat</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.diagflat.html" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div><div id="Keras_3" class="op-tab-pane "><h4>Keras</h4><div class="op-detail-row"><span class="label">API:</span> <code>keras.ops.numpy.diagflat</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.numpy.diagflat" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div><div id="TensorFlow_4" class="op-tab-pane "><h4>TensorFlow</h4><div class="op-detail-row"><span class="label">API:</span> <code>tf.linalg.diag</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Macro 'tf.linalg.diag(tf.reshape({v}, [-1]), k={k})'</span></div></div><div id="Apple MLX_5" class="op-tab-pane "><h4>Apple MLX</h4><div class="op-detail-row"><span class="label">API:</span> <code>—</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Custom / Partial</span></div></div><div id="Flax NNX_6" class="op-tab-pane "><h4>Flax NNX</h4><div class="op-detail-row"><span class="label">API:</span> <code>jax.numpy.diagflat</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://flax.readthedocs.io/en/latest/search.html?q=jax.numpy.diagflat" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div><div id="PaxML / Praxis_7" class="op-tab-pane "><h4>PaxML / Praxis</h4><div class="op-detail-row"><span class="label">API:</span> <code>jax.numpy.diagflat</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://github.com/search?q=repo%3Agoogle%2Fpaxml+jax.numpy.diagflat&type=code" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div> 
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