BinaryConvolution

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
• 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.