# SOME DESCRIPTIVE TITLE.
# Copyright (C) 1999-2020, The Alibaba Group Holding Ltd.
# This file is distributed under the same license as the mars package.
# FIRST AUTHOR <EMAIL@ADDRESS>, 2020.
#
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"Project-Id-Version: mars 0.5.0a2\n"
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"POT-Creation-Date: 2020-06-16 16:57+0800\n"
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#: ../../source/reference/tensor/generated/mars.tensor.random.multinomial.rst:2
msgid "mars.tensor.random.multinomial"
msgstr ""

#: mars.tensor.random.multinomial:1 of
msgid "Draw samples from a multinomial distribution."
msgstr ""

#: mars.tensor.random.multinomial:3 of
msgid ""
"The multinomial distribution is a multivariate generalisation of the "
"binomial distribution.  Take an experiment with one of ``p`` possible "
"outcomes.  An example of such an experiment is throwing a dice, where the"
" outcome can be 1 through 6.  Each sample drawn from the distribution "
"represents `n` such experiments.  Its values, ``X_i = [X_0, X_1, ..., "
"X_p]``, represent the number of times the outcome was ``i``."
msgstr ""

#: mars.tensor.random.multinomial of
msgid "Parameters"
msgstr ""

#: mars.tensor.random.multinomial:11 of
msgid "Number of experiments."
msgstr ""

#: mars.tensor.random.multinomial:13 of
msgid ""
"Probabilities of each of the ``p`` different outcomes.  These should sum "
"to 1 (however, the last element is always assumed to account for the "
"remaining probability, as long as ``sum(pvals[:-1]) <= 1)``."
msgstr ""

#: mars.tensor.random.multinomial:18 of
msgid ""
"Output shape.  If the given shape is, e.g., ``(m, n, k)``, then ``m * n *"
" k`` samples are drawn.  Default is None, in which case a single value is"
" returned."
msgstr ""

#: mars.tensor.random.multinomial:22 of
msgid "Desired chunk size on each dimension"
msgstr ""

#: mars.tensor.random.multinomial:24 of
msgid "Allocate the tensor on GPU if True, False as default"
msgstr ""

#: mars.tensor.random.multinomial:26 of
msgid "Data-type of the returned tensor."
msgstr ""

#: mars.tensor.random.multinomial of
msgid "Returns"
msgstr ""

#: mars.tensor.random.multinomial:29 of
msgid ""
"**out** -- The drawn samples, of shape *size*, if that was provided.  If "
"not, the shape is ``(N,)``.  In other words, each entry "
"``out[i,j,...,:]`` is an N-dimensional value drawn from the distribution."
msgstr ""

#: mars.tensor.random.multinomial:29 of
msgid ""
"**out** -- The drawn samples, of shape *size*, if that was provided.  If "
"not, the shape is ``(N,)``."
msgstr ""

#: mars.tensor.random.multinomial:32 of
msgid ""
"In other words, each entry ``out[i,j,...,:]`` is an N-dimensional value "
"drawn from the distribution."
msgstr ""

#: mars.tensor.random.multinomial of
msgid "Return type"
msgstr ""

#: mars.tensor.random.multinomial:37 of
msgid "Examples"
msgstr ""

#: mars.tensor.random.multinomial:38 of
msgid "Throw a dice 20 times:"
msgstr ""

#: mars.tensor.random.multinomial:45 of
msgid "It landed 4 times on 1, once on 2, etc."
msgstr ""

#: mars.tensor.random.multinomial:47 of
msgid "Now, throw the dice 20 times, and 20 times again:"
msgstr ""

#: mars.tensor.random.multinomial:53 of
msgid ""
"For the first run, we threw 3 times 1, 4 times 2, etc.  For the second, "
"we threw 2 times 1, 4 times 2, etc."
msgstr ""

#: mars.tensor.random.multinomial:56 of
msgid "A loaded die is more likely to land on number 6:"
msgstr ""

#: mars.tensor.random.multinomial:61 of
msgid ""
"The probability inputs should be normalized. As an implementation detail,"
" the value of the last entry is ignored and assumed to take up any "
"leftover probability mass, but this should not be relied on. A biased "
"coin which has twice as much weight on one side as on the other should be"
" sampled like so:"
msgstr ""

#: mars.tensor.random.multinomial:70 of
msgid "not like:"
msgstr ""

