Operators#
2023-06-14
18 min read time
operation#
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struct operation#
The operation interface represents an action an instruction will perform. All operation classes must be CopyConstructible.
operators#
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namespace op#
Enums
Functions
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std::ostream &operator<<(std::ostream &os, rnn_direction v)#
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struct argmax#
- #include <migraphx/op/argmax.hpp>
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struct argmin#
- #include <migraphx/op/argmin.hpp>
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struct as_shape#
- #include <migraphx/op/as_shape.hpp>
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struct batch_norm_inference#
- #include <migraphx/op/batch_norm_inference.hpp>
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template<class Derived>
struct binary : public migraphx::internal::op::op_name<Derived># - #include <migraphx/op/binary.hpp>
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struct broadcast#
- #include <migraphx/op/broadcast.hpp>
The broadcast operator performs the numpy-style broadcasting of an axis of a given tensor. This is achieved primarily by setting the stride of the broadcasted axis to zero. Linear indicies are computed from multi-indicies by computing the inner product on the multi-index with the strides. For example, if we have a tensor A(2,3) it has lengths of (2,3) and strides of (3,1). If we want to compute the linear offset that corresponds to the element on the 2nd row (i = 1) and 3rd column (j = 2), we compute the following inner product (1,2) dot (3, 1) = 1*3 + 2*1 = 5. It is obvious from there that we can negate the effects of a given axis by setting the stride of that axis to zero.
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struct capture#
- #include <migraphx/op/capture.hpp>
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struct clip#
- #include <migraphx/op/clip.hpp>
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struct concat#
- #include <migraphx/op/concat.hpp>
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struct contiguous#
- #include <migraphx/op/contiguous.hpp>
The contiguous operator takes a non-standard input tensor and returns the same tensor but in standard form. For example, if input tensor A which has lens = (4,5) is first transposed, i.e. lens = (5,4), this tensor’s data layout remained the same during the transpose operation; only it’s shape lengths and strides were changed. This leaves the tensor in a non-standard form. The contiguous operator copies the underlying data such that resulting tensor is returned to a standard form.
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struct convolution#
- #include <migraphx/op/convolution.hpp>
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struct deconvolution#
- #include <migraphx/op/deconvolution.hpp>
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struct dequantizelinear#
- #include <migraphx/op/dequantizelinear.hpp>
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struct dot#
- #include <migraphx/op/dot.hpp>
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struct elu#
- #include <migraphx/op/elu.hpp>
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struct flatten#
- #include <migraphx/op/flatten.hpp>
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struct gather#
- #include <migraphx/op/gather.hpp>
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struct get_tuple_elem#
- #include <migraphx/op/get_tuple_elem.hpp>
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struct gru#
- #include <migraphx/op/gru.hpp>
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struct highest#
- #include <migraphx/op/reduce_op.hpp>
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struct identity#
- #include <migraphx/op/identity.hpp>
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struct if_op#
- #include <migraphx/op/if_op.hpp>
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struct im2col#
- #include <migraphx/op/im2col.hpp>
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struct leaky_relu#
- #include <migraphx/op/leaky_relu.hpp>
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struct load#
- #include <migraphx/op/load.hpp>
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struct logical_and : public migraphx::internal::op::binary<logical_and>#
- #include <migraphx/op/logical_and.hpp>
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struct logical_or : public migraphx::internal::op::binary<logical_or>#
- #include <migraphx/op/logical_or.hpp>
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struct logical_xor : public migraphx::internal::op::binary<logical_xor>#
- #include <migraphx/op/logical_xor.hpp>
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struct logsoftmax#
- #include <migraphx/op/logsoftmax.hpp>
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struct loop#
- #include <migraphx/op/loop.hpp>
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struct lowest#
- #include <migraphx/op/reduce_op.hpp>
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struct lrn#
- #include <migraphx/op/lrn.hpp>
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struct lstm#
- #include <migraphx/op/lstm.hpp>
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struct multibroadcast#
- #include <migraphx/op/multibroadcast.hpp>
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struct multinomial#
- #include <migraphx/op/multinomial.hpp>
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struct nonmaxsuppression#
- #include <migraphx/op/nonmaxsuppression.hpp>
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struct nonzero#
- #include <migraphx/op/nonzero.hpp>
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struct one#
- #include <migraphx/op/reduce_op.hpp>
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template<class Derived>
struct op_name# - #include <migraphx/op/name.hpp>
Create name from class.
Subclassed by migraphx::internal::op::binary< add >, migraphx::internal::op::binary< div >, migraphx::internal::op::binary< equal >, migraphx::internal::op::binary< greater >, migraphx::internal::op::binary< less >, migraphx::internal::op::binary< logical_and >, migraphx::internal::op::binary< logical_or >, migraphx::internal::op::binary< logical_xor >, migraphx::internal::op::binary< max >, migraphx::internal::op::binary< min >, migraphx::internal::op::binary< mul >, migraphx::internal::op::binary< pow >, migraphx::internal::op::binary< prelu >, migraphx::internal::op::binary< sqdiff >, migraphx::internal::op::binary< sub >, migraphx::internal::op::prefix_scan_op< prefix_scan_sum >, migraphx::internal::op::reduce_op< reduce_max >, migraphx::internal::op::reduce_op< reduce_mean >, migraphx::internal::op::reduce_op< reduce_min >, migraphx::internal::op::reduce_op< reduce_prod >, migraphx::internal::op::reduce_op< reduce_sum >, migraphx::internal::op::unary< abs >, migraphx::internal::op::unary< acos >, migraphx::internal::op::unary< acosh >, migraphx::internal::op::unary< asin >, migraphx::internal::op::unary< asinh >, migraphx::internal::op::unary< atan >, migraphx::internal::op::unary< atanh >, migraphx::internal::op::unary< ceil >, migraphx::internal::op::unary< convert >, migraphx::internal::op::unary< cos >, migraphx::internal::op::unary< cosh >, migraphx::internal::op::unary< erf >, migraphx::internal::op::unary< exp >, migraphx::internal::op::unary< floor >, migraphx::internal::op::unary< log >, migraphx::internal::op::unary< neg >, migraphx::internal::op::unary< recip >, migraphx::internal::op::unary< relu >, migraphx::internal::op::unary< round >, migraphx::internal::op::unary< rsqrt >, migraphx::internal::op::unary< sigmoid >, migraphx::internal::op::unary< sign >, migraphx::internal::op::unary< sin >, migraphx::internal::op::unary< sinh >, migraphx::internal::op::unary< sqrt >, migraphx::internal::op::unary< tan >, migraphx::internal::op::unary< tanh >, migraphx::internal::op::unary< unary_not >, migraphx::internal::op::binary< Derived >, migraphx::internal::op::prefix_scan_op< Derived >, migraphx::internal::op::reduce_op< Derived >, migraphx::internal::op::unary< Derived >
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struct outline#
- #include <migraphx/op/outline.hpp>
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struct pad#
- #include <migraphx/op/pad.hpp>
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struct pointwise#
- #include <migraphx/op/pointwise.hpp>
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struct pooling#
- #include <migraphx/op/pooling.hpp>
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template<class Derived>
struct prefix_scan_op : public migraphx::internal::op::op_name<Derived># - #include <migraphx/op/prefix_scan_op.hpp>
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struct prefix_scan_sum : public migraphx::internal::op::prefix_scan_op<prefix_scan_sum>#
- #include <migraphx/op/prefix_scan_sum.hpp>
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struct quant_convolution#
- #include <migraphx/op/quant_convolution.hpp>
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struct quant_dot#
- #include <migraphx/op/quant_dot.hpp>
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struct quantizelinear#
- #include <migraphx/op/quantizelinear.hpp>
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struct reduce_max : public migraphx::internal::op::reduce_op<reduce_max>#
- #include <migraphx/op/reduce_max.hpp>
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struct reduce_mean : public migraphx::internal::op::reduce_op<reduce_mean>#
- #include <migraphx/op/reduce_mean.hpp>
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struct reduce_min : public migraphx::internal::op::reduce_op<reduce_min>#
- #include <migraphx/op/reduce_min.hpp>
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template<class Derived>
struct reduce_op : public migraphx::internal::op::op_name<Derived># - #include <migraphx/op/reduce_op.hpp>
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struct reduce_prod : public migraphx::internal::op::reduce_op<reduce_prod>#
- #include <migraphx/op/reduce_prod.hpp>
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struct reduce_sum : public migraphx::internal::op::reduce_op<reduce_sum>#
- #include <migraphx/op/reduce_sum.hpp>
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struct reshape#
- #include <migraphx/op/reshape.hpp>
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struct reverse#
- #include <migraphx/op/reverse.hpp>
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struct rnn#
- #include <migraphx/op/rnn.hpp>
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struct rnn_last_cell_output#
- #include <migraphx/op/rnn_last_cell_output.hpp>
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struct rnn_last_hs_output#
- #include <migraphx/op/rnn_last_hs_output.hpp>
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struct rnn_var_sl_last_output#
- #include <migraphx/op/rnn_var_sl_last_output.hpp>
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struct rnn_var_sl_shift_output#
- #include <migraphx/op/rnn_variable_seq_lens.hpp>
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struct rnn_var_sl_shift_sequence#
- #include <migraphx/op/rnn_variable_seq_lens.hpp>
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struct roialign#
- #include <migraphx/op/roialign.hpp>
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struct scalar#
- #include <migraphx/op/scalar.hpp>
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struct scatter#
- #include <migraphx/op/scatter.hpp>
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struct slice#
- #include <migraphx/op/slice.hpp>
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struct softmax#
- #include <migraphx/op/softmax.hpp>
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struct squeeze#
- #include <migraphx/op/squeeze.hpp>
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struct step#
- #include <migraphx/op/step.hpp>
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struct topk#
- #include <migraphx/op/topk.hpp>
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struct transpose#
- #include <migraphx/op/transpose.hpp>
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template<class Derived>
struct unary : public migraphx::internal::op::op_name<Derived># - #include <migraphx/op/unary.hpp>
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struct unary_not : public migraphx::internal::op::unary<unary_not>#
- #include <migraphx/op/unary_not.hpp>
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struct undefined#
- #include <migraphx/op/undefined.hpp>
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struct unknown#
- #include <migraphx/op/unknown.hpp>
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struct unsqueeze#
- #include <migraphx/op/unsqueeze.hpp>
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struct where#
- #include <migraphx/op/where.hpp>
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struct zero#
- #include <migraphx/op/reduce_op.hpp>
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std::ostream &operator<<(std::ostream &os, rnn_direction v)#