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openvino/docs/ops/convolution/BinaryConvolution_1.md

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## BinaryConvolution<a name="BinaryConvolution"></a> {#openvino_docs_ops_convolution_BinaryConvolution_1}
**Versioned name**: *BinaryConvolution-1*
**Category**: *Convolution*
**Short description**: *BinaryConvolution* convolution with binary weights, binary input and integer output
**Attributes**:
The operation has the same attributes as a regular *Convolution* layer and several unique attributes that are listed below:
* *mode*
* **Description**: *mode* defines how input tensor 0/1 values and weights 0/1 are interpreted as real numbers and how the result is computed.
* **Range of values**:
* *xnor-popcount*
* **Type**: `string`
* **Default value**: None
* **Required**: *yes*
* *pad_value*
* **Description**: *pad_value* is a floating-point value used to fill pad area.
* **Range of values**: a floating-point number
* **Type**: `float`
* **Default value**: None
* **Required**: *yes*
**Inputs**:
* **1**: ND tensor with N >= 3, containing integer, float or binary values; filled with 0/1 values of any appropriate type. 0 means -1, 1 means 1 for `mode="xnor-popcount"`. Required.
* **2**: ND tensor with N >= 3 that represents convolutional kernel filled by integer, float or binary values; filled with 0/1 values. 0 means -1, 1 means 1 for `mode="xnor-popcount"`. Required.
**Outputs**:
* **1**: output tensor containing float values.