Addbmm
======

Performs batch matrix-matrix product of matrices with reduced add step.

**Abstract Signature:**

``Addbmm(input: Tensor, batch1: Tensor, batch2: Tensor, beta: float = 1.0, alpha: float = 1.0)``

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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> 
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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.addbmm</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.addbmm.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.sum</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Macro '{beta} * {input} + {alpha} * jax.numpy.sum(jax.numpy.matmul({batch1}, {batch2}), axis=0)'</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>numpy.matmul</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Macro '{beta} * {input} + {alpha} * numpy.sum(numpy.matmul({batch1}, {batch2}), axis=0)'</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>keras.ops.sum</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Macro '{beta} * {input} + {alpha} * keras.ops.sum(keras.ops.matmul({batch1}, {batch2}), axis=0)'</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.linalg.matmul</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Macro '{beta} * {input} + {alpha} * tf.reduce_sum(tf.linalg.matmul({batch1}, {batch2}), axis=0)'</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>mlx.core.matmul</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Macro '{beta} * {input} + {alpha} * mlx.core.sum(mlx.core.matmul({batch1}, {batch2}), axis=0)'</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.sum</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Macro '{beta} * {input} + {alpha} * jax.numpy.sum(jax.numpy.matmul({batch1}, {batch2}), axis=0)'</span></div></div> 
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