QuantizedRnnTanhCell
====================

Applies a quantized RNN cell with Tanh non-linearity to inputs.

**Abstract Signature:**

``QuantizedRnnTanhCell(input: Tensor, hx: Tensor, w_ih: Tensor, w_hh: Tensor, b_ih: Tensor, b_hh: Tensor, packed_ih: Tensor, packed_hh: Tensor, col_offsets: Tensor, scale: float, zero_point: int)``

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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.quantized_rnn_tanh_cell</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.quantized_rnn_tanh_cell.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>Custom / Partial</span></div></div><div id="Keras_2" 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>Custom / Partial</span></div></div><div id="TensorFlow_3" class="op-tab-pane "><h4>TensorFlow</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="Apple MLX_4" 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_5" 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>Custom / Partial</span></div></div> 
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