Single
======

Cast to single-precision floating-point number (float32).

**Abstract Signature:**

``Single(value)``

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        <button class="op-tab-btn active" onclick="openOpTab(event, 'PyTorch_0')">PyTorch</button><button class="op-tab-btn " onclick="openOpTab(event, 'JAX (Core)_1')">JAX (Core)</button><button class="op-tab-btn " onclick="openOpTab(event, 'NumPy_2')">NumPy</button><button class="op-tab-btn " onclick="openOpTab(event, 'Keras_3')">Keras</button><button class="op-tab-btn " onclick="openOpTab(event, 'TensorFlow_4')">TensorFlow</button><button class="op-tab-btn " onclick="openOpTab(event, 'Apple MLX_5')">Apple MLX</button><button class="op-tab-btn " onclick="openOpTab(event, 'Flax NNX_6')">Flax NNX</button><button class="op-tab-btn " onclick="openOpTab(event, 'PaxML / Praxis_7')">PaxML / Praxis</button> 
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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.float</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.float.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.float32</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.float32.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.float32</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.float32.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.cast</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.cast" 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.cast</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://www.tensorflow.org/api_docs/python/tf/cast" target="_blank" class="op-doc-link">Official Docs ↗</a></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>mlx.core.array</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.array.html" target="_blank" class="op-doc-link">Official Docs ↗</a></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.float32</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.float32" 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.float32</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.float32&type=code" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div> 
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