Layout API Overview

The concept of layout helps you (and your application) to understand what each particular dimension of input/output tensor means. For example, if your input has the {1, 3, 720, 1280} shape and the NCHW layout, it is clear that N(batch) = 1, C(channels) = 3, H(height) = 720, and W(width) = 1280. Without the layout information, the {1, 3, 720, 1280} tuple does not give any idea to your application on what these numbers mean and how to resize the input image to fit the expectations of the model.

With the NCHW layout, it is easier to understand what the {8, 3, 224, 224} model shape means. Without the layout, it is just a 4-dimensional tensor.

Below is a list of cases where input/output layout is important:

• Performing model modification:

  • Applying the preprocessing steps, such as subtracting means, dividing by scales, resizing an image, and converting RGB <-> BGR.

  • Setting/getting a batch for a model.

• Doing the same operations as used during the model conversion phase. For more information, refer to the:

  • Convert to OpenVINO

  • OpenVINO Model Conversion Tutorial

  • [LEGACY] Model Optimizer Embedding Preprocessing Computation guide.

• Improving the readability of a model input and output.

Syntax of Layout

Short Syntax

The easiest way is to fully specify each dimension with one alphabet letter.

Python

from openvino import Layout
layout = Layout('NCHW')

C++

layout = ov::Layout("NHWC");

This assigns N to the first dimension, C to the second, H to the third, and W to the fourth.

Advanced Syntax

The advanced syntax allows assigning a word to a dimension. To do this, wrap a layout with square brackets [] and specify each name separated by a comma ,.

Python

# Each dimension has name separated by comma
# Layout is wrapped with square brackets
layout = Layout('[time,temperature,humidity]')

C++

// Each dimension has name separated by comma, layout is wrapped with square brackets
layout = ov::Layout("[time,temperature,humidity]");

Partially Defined Layout

If a certain dimension is not important, its name can be set to ?.

Python

# First dimension is batch, 4th is 'channels'.
# Others are not important for us
layout = Layout('N??C')

# Or the same using advanced syntax
layout = Layout('[n,?,?,c]')

C++

// First dimension is batch, 4th is 'channels'. Others are not important for us
layout = ov::Layout("N??C");
// Or the same using advanced syntax
layout = ov::Layout("[n,?,?,c]");

Dynamic Layout

If several dimensions are not important, an ellipsis ... can be used to specify those dimensions.

Python

# First dimension is 'batch' others are whatever
layout = Layout('N...')

# Second dimension is 'channels' others are whatever
layout = Layout('?C...')

# Last dimension is 'channels' others are whatever
layout = Layout('...C')

C++

// First dimension is 'batch' others are whatever
layout = ov::Layout("N...");

// Second dimension is 'channels' others are whatever
layout = ov::Layout("?C...");

// Last dimension is 'channels' others are whatever
layout = ov::Layout("...C");

Predefined Names

A layout has some pre-defined dimension names, widely used in computer vision:

• N/Batch - batch size

• C/Channels - channels

• D/Depth - depth

• H/Height - height

• W/Width - width

These names are used in PreProcessing API. There is a set of helper functions to get appropriate dimension index from a layout.

Python

from openvino.runtime import layout_helpers
# returns 0 for batch
layout_helpers.batch_idx(Layout('NCDHW'))

# returns 1 for channels
layout_helpers.channels_idx(Layout('NCDHW'))

# returns 2 for depth
layout_helpers.depth_idx(Layout('NCDHW'))

# returns -2 for height
layout_helpers.height_idx(Layout('...HW'))

# returns -1 for width
layout_helpers.width_idx(Layout('...HW'))

C++

// returns 0 for batch
ov::layout::batch_idx("NCDHW");

// returns 1 for channels
ov::layout::channels_idx("NCDHW");

// returns 2 for depth
ov::layout::depth_idx("NCDHW");

// returns -2 for height
ov::layout::height_idx("...HW");

// returns -1 for width
ov::layout::width_idx("...HW");

Equality

Layout names are case-insensitive, which means that Layout("NCHW") = Layout("nChW") = Layout("[N,c,H,w]").

Dump Layout

A layout can be converted to a string in the advanced syntax format. It can be useful for debugging and serialization purposes.

Python

layout = Layout('NCHW')
print(layout)    # prints [N,C,H,W]

C++

layout = ov::Layout("NCHW");
std::cout << layout.to_string(); // prints [N,C,H,W]

Get layout from Model Input/Output

OpenVINO provides helpers which provide a simple interface to get layout from Model input or output.

Python

# Get layout for model input
layout = layout_helpers.get_layout(model.input("input_tensor_name"))
# Get layout for model with single output
layout = layout_helpers.get_layout(model.output())

C++

// Get layout for model input
layout = ov::layout::get_layout(model->input("input_tensor_name"));
// Get layout for model with single output
layout = ov::layout::get_layout(model->output());

See also

• API Reference: ov::Layout C++ class