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fix typos in the developer guide
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docs/source/developer_guide.rst

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@@ -61,7 +61,7 @@ functions. Instead, to access a stateless distribution, you need to call
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https://docs.pymc.io/prob\_dists.html#using-pymc-distributions-without-a-model).
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With this distinction in mind, we can take a closer look at the
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stateless distribution part of pymc3 (see distriution api in `doc
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stateless distribution part of pymc3 (see distribution api in `doc
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<https://docs.pymc.io/api/distributions.html>`__), which divided into:
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- Continuous
@@ -670,7 +670,7 @@ does not edit or rewrite the graph directly.
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def __call__(self, array, grad_out=None, extra_vars=None):
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...
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logp, dlogp = self._theano_function(array)
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return
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return logp, dlogp
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def set_extra_values(self, extra_vars):
@@ -857,7 +857,7 @@ MCMC
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The ability for model instance to generate conditional logp and dlogp
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function enable one of the unique feature of PyMC3 - `CompoundStep
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method <https://docs.pymc.io/notebooks/sampling_compound_step.html>`__.
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It is conceptual level it is a Metropolis-within-Gibbs sampler. User can
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On a conceptual level it is a Metropolis-within-Gibbs sampler. User can
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`specify different sampler of different
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RVs <https://docs.pymc.io/notebooks/sampling_compound_step.html?highlight=compoundstep#Specify-compound-steps>`__.
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Alternatively, it is implemented as yet another interceptor: the

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