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* 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>
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GELU- Gaussian Error Linear Unit
Versioned name: Gelu-2
Category: Activation
Short description: Reference
Detailed description: Reference
Attributes: Gelu operation has no attributes.
Mathematical Formulation Gelu(x)=x*Φ(x), where Φ(x) is the Cumulative Distribution Function for Gaussian Distribution. The following equivalent combination is recognized and fused into single Gelu op:
\f[ Gelu(x) = 0.5x(1.0 + erf((x) / \sqrt{2}) \f]
Similarly, the following Gelu approximation (typical for the TensorFlow*) is recognized and fused into single Gelu op
\f[ Gelu(x) \approx 0.5x(1.0 + tanh(\sqrt{2.0/pi} * (x + 0.044715 * x ^ 3)) \f]
Inputs:
- 1: Multidimensional input tensor. Required.
Example
<layer ... type="Gelu">
<input>
<port id="0">
<dim>1</dim>
<dim>128</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>128</dim>
</port>
</output>
</layer>