V
- data type for output()
output@Operator(group="nn") public final class QuantizedConv2d<V> extends PrimitiveOp
The inputs are quantized tensors where the lowest value represents the real number of the associated minimum, and the highest represents the maximum. This means that you can only interpret the quantized output in the same way, by taking the returned minimum and maximum values into account.
Modifier and Type | Class and Description |
---|---|
static class |
QuantizedConv2d.Options
Optional attributes for
QuantizedConv2d |
operation
Modifier and Type | Method and Description |
---|---|
static <V,T,U> QuantizedConv2d<V> |
create(Scope scope,
Operand<T> input,
Operand<U> filter,
Operand<Float> minInput,
Operand<Float> maxInput,
Operand<Float> minFilter,
Operand<Float> maxFilter,
Class<V> outType,
List<Long> strides,
String padding,
QuantizedConv2d.Options... options)
Factory method to create a class wrapping a new QuantizedConv2d operation.
|
static QuantizedConv2d.Options |
dilations(List<Long> dilations) |
Output<Float> |
maxOutput()
The float value that the highest quantized output value represents.
|
Output<Float> |
minOutput()
The float value that the lowest quantized output value represents.
|
Output<V> |
output() |
equals, hashCode, op, toString
public static <V,T,U> QuantizedConv2d<V> create(Scope scope, Operand<T> input, Operand<U> filter, Operand<Float> minInput, Operand<Float> maxInput, Operand<Float> minFilter, Operand<Float> maxFilter, Class<V> outType, List<Long> strides, String padding, QuantizedConv2d.Options... options)
scope
- current scopeinput
- filter
- filter's input_depth dimension must match input's depth dimensions.minInput
- The float value that the lowest quantized input value represents.maxInput
- The float value that the highest quantized input value represents.minFilter
- The float value that the lowest quantized filter value represents.maxFilter
- The float value that the highest quantized filter value represents.outType
- strides
- The stride of the sliding window for each dimension of the input
tensor.padding
- The type of padding algorithm to use.options
- carries optional attributes valuespublic static QuantizedConv2d.Options dilations(List<Long> dilations)
dilations
- 1-D tensor of length 4. The dilation factor for each dimension of
`input`. If set to k > 1, there will be k-1 skipped cells between each
filter element on that dimension. The dimension order is determined by the
value of `data_format`, see above for details. Dilations in the batch and
depth dimensions must be 1.public Output<Float> minOutput()
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