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#include "caffe2/operators/quantized/int8_slice_op.h"
namespace caffe2 {
REGISTER_CPU_OPERATOR(Int8Slice, int8::Int8SliceOp);
OPERATOR_SCHEMA(Int8Slice)
.NumInputs(1, 3)
.NumOutputs(1)
.SetDoc(R"DOC(
Produces a slice of the input Int8 tensor. Currently, only slicing in a single
dimension is supported.
Slices are passed as 2 1D vectors or as two keyword argument lists with starting
and end indices for each dimension of the input `data` tensor. If a negative
value is passed for any of the start or end indices, it represents the number of
elements before the end of that dimension. End indices are non-inclusive unless
negative (end index -1 means up to and including the last element).
Example:
data = [
[1, 2, 3, 4],
[5, 6, 7, 8],
]
starts = [0, 1]
ends = [-1, 3]
result = [
[2, 3],
[6, 7],
]
)DOC")
.Input(0, "data", "Int8 Tensor of data to extract slices from.")
.Input(1, "starts", "1D tensor: start-indices for each dimension of data.")
.Input(2, "ends", "1D tensor: end-indices for each dimension of data.")
.Arg("Y_scale", "Output tensor quantization scale")
.Arg("Y_zero_point", "Output tensor quantization offset")
.Arg("starts", "List of starting indices")
.Arg("ends", "List of ending indices")
.Arg(
"dim",
"(Optional) The dimension to slice over. If specified start_idx and end_idx should also be given and it takes precedence over starts and ends")
.Arg("start_idx", "(Optional) The dimension to start slice from. Default is 0")
.Arg("end_idx", "(Optional) The dimension to end the slice. Default is -1")
.Output(0, "output", "Sliced Int8 data tensor.")
.InheritOnnxSchema("Slice");
} // namespace caffe2
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