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. Required.