ef45b5da8d
* Doc Migration from Gitlab (#1289) * doc migration * fix * Update FakeQuantize_1.md * Update performance_benchmarks.md * Updates graphs for FPGA * Update performance_benchmarks.md * Change DL Workbench structure (#1) * Changed DL Workbench structure * Fixed tags * fixes * Update ie_docs.xml * Update performance_benchmarks_faq.md * Fixes in DL Workbench layout * Fixes for CVS-31290 * [DL Workbench] Minor correction * Fix for CVS-30955 * Added nGraph deprecation notice as requested by Zoe * fix broken links in api doxy layouts * CVS-31131 fixes * Additional fixes * Fixed POT TOC * Update PAC_Configure.md PAC DCP 1.2.1 install guide. * Update inference_engine_intro.md * fix broken link * Update opset.md * fix * added opset4 to layout * added new opsets to layout, set labels for them * Update VisionAcceleratorFPGA_Configure.md Updated from 2020.3 to 2020.4 Co-authored-by: domi2000 <domi2000@users.noreply.github.com>
80 lines
2.2 KiB
Markdown
80 lines
2.2 KiB
Markdown
## MVN <a name="MVN"></a> {#openvino_docs_ops_normalization_MVN_1}
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**Versioned name**: *MVN-1*
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**Category**: *Normalization*
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**Short description**: [Reference](http://caffe.berkeleyvision.org/tutorial/layers/mvn.html)
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**Detailed description**
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*MVN* subtracts mean value from the input blob:
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\f[
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o_{i} = i_{i} - \frac{\sum{i_{k}}}{C * H * W}
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\f]
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If *normalize_variance* is set to 1, the output blob is divided by variance:
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\f[
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o_{i}=\frac{o_{i}}{\sum \sqrt {o_{k}^2}+\epsilon}
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\f]
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**Attributes**
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* *across_channels*
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* **Description**: *across_channels* is a flag that specifies whether mean values are shared across channels. For example, *across_channels* equal to `false` means that mean values are not shared across channels.
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* **Range of values**:
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* `false` - do not share mean values across channels
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* `true` - share mean values across channels
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* **Type**: `boolean`
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* **Default value**: `false`
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* **Required**: *no*
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* *normalize_variance*
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* **Description**: *normalize_variance* is a flag that specifies whether to perform variance normalization.
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* **Range of values**:
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* `false` -- do not normalize variance
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* `true` -- normalize variance
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* **Type**: `boolean`
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* **Default value**: `false`
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* **Required**: *no*
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* *eps*
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* **Description**: *eps* is the number to be added to the variance to avoid division by zero when normalizing the value. For example, *epsilon* equal to 0.001 means that 0.001 is added to the variance.
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* **Range of values**: a positive floating-point number
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* **Type**: `float`
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* **Default value**: None
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* **Required**: *yes*
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**Inputs**
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* **1**: 4D or 5D input tensor of any floating point type. Required.
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**Outputs**
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* **1**: normalized tensor of the same type and shape as input tensor.
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**Example**
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```xml
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<layer ... type="MVN">
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<data across_channels="true" eps="1e-9" normalize_variance="true"/>
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<input>
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<port id="0">
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<dim>6</dim>
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<dim>12</dim>
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<dim>10</dim>
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<dim>24</dim>
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</port>
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</input>
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<output>
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<port id="2">
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<dim>6</dim>
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<dim>12</dim>
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<dim>10</dim>
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<dim>24</dim>
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</port>
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</output>
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</layer>
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``` |