Multinomial
===========

Generate a tensor of samples from a multinomial distribution according to the probabilities of each of the possible outcomes.

**Abstract Signature:**

``Multinomial(input, dtype: int, sample_size: int, seed: float)``

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        <div id="NumPy_0" class="op-tab-pane active"><h4>NumPy</h4><div class="op-detail-row"><span class="label">API:</span> <code>numpy.random.mtrand.multinomial</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.random.mtrand.multinomial.html" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div><div id="Flax NNX_1" class="op-tab-pane "><h4>Flax NNX</h4><div class="op-detail-row"><span class="label">API:</span> <code>nnx.rnglib.Rngs.multinomial</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=nnx.rnglib.Rngs.multinomial" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div> 
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