154 lines
3.7 KiB
Markdown
154 lines
3.7 KiB
Markdown
# Layout API overview {#openvino_docs_OV_UG_Layout_Overview}
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## Introduction
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In few words, with layout `NCHW` it is easier to understand what model's shape `{8, 3, 224, 224}` means. Without layout it is just a 4-dimensional tensor.
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Concept of layout helps you (and your application) to understand what does each particular dimension of input/output tensor mean. For example, if your input has shape `{1, 3, 720, 1280}` and layout "NCHW" - it is clear that `N(batch) = 1`, `C(channels) = 3`, `H(height) = 720` and `W(width) = 1280`. Without layout information `{1, 3, 720, 1280}` doesn't give any idea to your application what these number mean and how to resize input image to fit model's expectations.
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Reasons when you may want to care about input/output layout:
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- Perform model modification:
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- Apply [preprocessing](./preprocessing_overview.md) steps, like subtract means, divide by scales, resize image, convert RGB<->BGR
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- Set/get batch for a model
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- Same operations, used during model conversion phase, see [Model Optimizer Embedding Preprocessing Computation](../MO_DG/prepare_model/Additional_Optimizations.md)
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- Improve readability of a model's input and output
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## Layout syntax
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### Short
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The easiest way is to fully specify each dimension with one alphabetical letter
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@sphinxtabset
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@sphinxtab{C++}
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@snippet docs/snippets/ov_layout.cpp ov:layout:simple
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@endsphinxtab
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@sphinxtab{Python}
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@snippet docs/snippets/ov_layout.py ov:layout:simple
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@endsphinxtab
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@endsphinxtabset
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This assigns 'N' to first dimension, 'C' to second, 'H' to 3rd and 'W' to 4th
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### Advanced
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Advanced syntax allows assigning a word to a dimension. To do this, wrap layout with square brackets `[]` and specify each name separated by comma `,`
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@sphinxtabset
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@sphinxtab{C++}
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@snippet docs/snippets/ov_layout.cpp ov:layout:complex
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@endsphinxtab
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@sphinxtab{Python}
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@snippet docs/snippets/ov_layout.py ov:layout:complex
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@endsphinxtab
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@endsphinxtabset
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### Partially defined layout
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If some dimension is not important, it's name can be set to `?`
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@sphinxtabset
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@sphinxtab{C++}
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@snippet docs/snippets/ov_layout.cpp ov:layout:partially_defined
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@endsphinxtab
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@sphinxtab{Python}
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@snippet docs/snippets/ov_layout.py ov:layout:partially_defined
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@endsphinxtab
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@endsphinxtabset
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### Dynamic layout
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If number of dimensions is not important, ellipsis `...` can be used to specify variadic number of dimensions.
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@sphinxtabset
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@sphinxtab{C++}
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@snippet docs/snippets/ov_layout.cpp ov:layout:dynamic
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@endsphinxtab
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@sphinxtab{Python}
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@snippet docs/snippets/ov_layout.py ov:layout:dynamic
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@endsphinxtab
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@endsphinxtabset
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### Predefined names
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Layout has pre-defined some widely used in computer vision dimension names:
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- N/Batch - batch size
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- C/Channels - channels dimension
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- D/Depth - depth
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- H/Height - height
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- W/Width - width
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These names are used in [PreProcessing API](./preprocessing_overview.md) and there is a set of helper functions to get appropriate dimension index from layout
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@sphinxtabset
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@sphinxtab{C++}
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@snippet docs/snippets/ov_layout.cpp ov:layout:predefined
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@endsphinxtab
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@sphinxtab{Python}
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@snippet docs/snippets/ov_layout.py ov:layout:predefined
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@endsphinxtab
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@endsphinxtabset
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### Equality
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Layout names are case-insensitive, which means that ```Layout("NCHW") == Layout("nChW") == Layout("[N,c,H,w]")```
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### Dump layout
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Layout can be converted to string in advanced syntax format. Can be useful for debugging and serialization purposes
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@sphinxtabset
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@sphinxtab{C++}
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@snippet docs/snippets/ov_layout.cpp ov:layout:dump
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@endsphinxtab
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@sphinxtab{Python}
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@snippet docs/snippets/ov_layout.py ov:layout:dump
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@endsphinxtab
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@endsphinxtabset
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## See also
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* <code>ov::Layout</code> C++ class documentation
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