Minimum

Versioned name: Minimum-1

Category: Arithmetic binary operation

Short description: Minimum performs element-wise minimum operation with two given tensors applying multi-directional broadcast rules.

Attributes:

  • auto_broadcast
    • Description: specifies rules used for auto-broadcasting of input tensors.
    • Range of values:
      • none - no auto-broadcasting is allowed, all input shapes should match
      • numpy - numpy broadcasting rules, aligned with ONNX Broadcasting. Description is available in ONNX docs.
    • Type: string
    • Default value: "numpy"
    • Required: no

Inputs

  • 1: First input tensor of type T. Required.
  • 2: Second input tensor of type T. Required.

Outputs

  • 1: The result of element-wise minimum operation. A tensor of type T.

Types

  • T: arbitrary type, which supports less/greater comparison.

Detailed description Before performing arithmetic operation, input tensors a and b are broadcasted if their shapes are different and auto_broadcast attributes is not none. Broadcasting is performed according to auto_broadcast value.

After broadcasting Minimum does the following with the input tensors a and b:

\[ o_{i} = min(a_{i}, b_{i}) \]

Examples

Example 1

<layer ... type="Minimum">
<input>
<port id="0">
<dim>256</dim>
<dim>56</dim>
</port>
<port id="1">
<dim>256</dim>
<dim>56</dim>
</port>
</input>
<output>
<port id="2">
<dim>256</dim>
<dim>56</dim>
</port>
</output>
</layer>

Example 2: broadcast

<layer ... type="Minimum">
<input>
<port id="0">
<dim>8</dim>
<dim>1</dim>
<dim>6</dim>
<dim>1</dim>
</port>
<port id="1">
<dim>7</dim>
<dim>1</dim>
<dim>5</dim>
</port>
</input>
<output>
<port id="2">
<dim>8</dim>
<dim>7</dim>
<dim>6</dim>
<dim>5</dim>
</port>
</output>
</layer>