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[diderot] Diff of /trunk/doc/report/types.tex
Diff of /trunk/doc/report/types.tex
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\section{Images} |
\section{Images} |
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Images are rectangular arrays of tensor data that are used to represent the data sets |
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that Diderot programs are analysing, as well as other data. |
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The syntax of an image type is |
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\begin{center} |
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\kw{image}\kw{(} $n$ \kw{)} \kw{[} $d_1,\ldots{},d_n$ \kw{]} |
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where $n$ is the dimension of the field (typically 2 or 3) and $d_1,\ldots{},d_n$ is the |
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shape of the tensor data (\ie{}, the elements of the image are tensors |
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of type \kw{tensor[}$d_1,\ldots{},d_n$\kw{]}). |
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\section{Fields} |
\section{Fields} |
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Fields are functions from some $n$-dimensional vector space to some tensor type. |
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The syntax of a field type is |
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\begin{center} |
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\kw{field}\kw{\#} $k$ \kw{(} $n$ \kw{)} \kw{[} $d_1,\ldots{},d_n$ \kw{]} |
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\end{center}% |
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where $k \geq 0$ is the number of levels of differentiation supported by the field, |
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$n$ is the dimension of the field (typically 2 or 3), and $d_1,\ldots{},d_n$ is the shape of the field. |
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Probing the field will produce a tensor of type \kw{tensor[}$d_1,\ldots{},d_n$\kw{]}. |
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\section{Kernels} |
\section{Kernels} |
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Kernels are abstract types that represent the \emph{convolution kernels} used |
Kernels are abstract types that represent the \emph{convolution kernels} used |
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