VarMean
=======

Returns (var, mean).

**Abstract Signature:**

``VarMean(x: Tensor, axis: int, correction: int = 1, keepdims: bool = False)``

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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.var_mean</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.var_mean.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>—</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Macro '(jax.numpy.var({x}, axis={axis}, ddof={correction}, keepdims={keepdims}), jax.numpy.mean({x}, axis={axis}, keepdims={keepdims}))'</span></div></div><div id="NumPy_2" class="op-tab-pane "><h4>NumPy</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>Macro '(numpy.var({x}, axis={axis}, ddof={correction}, keepdims={keepdims}), numpy.mean({x}, axis={axis}, keepdims={keepdims}))'</span></div></div><div id="Keras_3" class="op-tab-pane "><h4>Keras</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>Macro '(keras.ops.var({x}, axis={axis}, keepdims={keepdims}), keras.ops.mean({x}, axis={axis}, keepdims={keepdims}))'</span></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.nn.moments</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Macro '(tf.math.reduce_variance({x}, axis={axis}, keepdims={keepdims}), tf.math.reduce_mean({x}, axis={axis}, keepdims={keepdims}))'</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>Macro '(mlx.core.var({x}, axis={axis}, ddof={correction}, keepdims={keepdims}), mlx.core.mean({x}, axis={axis}, keepdims={keepdims}))'</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>—</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Macro '(jax.numpy.var({x}, axis={axis}, ddof={correction}, keepdims={keepdims}), jax.numpy.mean({x}, axis={axis}, keepdims={keepdims}))'</span></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>—</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Macro '(jax.numpy.var({x}, axis={axis}, ddof={correction}, keepdims={keepdims}), jax.numpy.mean({x}, axis={axis}, keepdims={keepdims}))'</span></div></div> 
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