/* * The MIT License (MIT) * * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved. * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN * THE SOFTWARE. */ #ifndef MIGRAPHX_GUARD_OPERATORS_BROADCAST_HPP #define MIGRAPHX_GUARD_OPERATORS_BROADCAST_HPP #include #include #include #include namespace migraphx { inline namespace MIGRAPHX_INLINE_NS { namespace op { /** * 1 input version: * Broadcasts a tensor from the original shape to the broadcast_lens by setting the stride of * broadcasted dimensions to zero. `axis` attribute for a 1D input shape is the output dimension * that stays the same. ex: broadcasting shape [1024] -> [4, 1024, 3] has axis = 1 For higher rank * input shapes, axis is an offset parameter for the broadcasting. Such that this operator would * work in the opposite direction of NumPy broadcasting. ex: broadcasting shape [2, 2] -> [2, 2, 3] * with axis = 0 * * 2 input version: * Broadcast the first input 1D shape into the second input shape based on the axis parameter. * Handles broadcasting a 1D fixed shape into a higher rank dynamic shape. * broadcast_lens is not used */ struct broadcast { uint64_t axis = 0; std::vector broadcast_lens = {}; template static auto reflect(Self& self, F f) { return pack(f(self.axis, "axis"), f(self.broadcast_lens, "out_lens")); } std::string name() const { return "broadcast"; } shape compute_shape(std::vector inputs) const { check_shapes{inputs, *this, true}.has(1, 2); auto s0 = inputs.at(0); auto t = s0.type(); if(inputs.size() == 1) { // the ONNX broadcast op is deprecated now, so not handling the negative // value of axis anymore if(axis >= broadcast_lens.size()) MIGRAPHX_THROW("BROADCAST : axis is out of range"); if(broadcast_lens.size() - axis < s0.lens().size()) MIGRAPHX_THROW("BROADCAST: (broadcast ndims - axis) is less than s0 ndims"); if(not std::equal(s0.lens().begin(), s0.lens().end(), broadcast_lens.begin() + axis)) MIGRAPHX_THROW("BROADCAST: when broadcasting, succeeding sizes must match"); std::vector bcast_strides(broadcast_lens.size(), 0); std::copy(s0.strides().begin(), s0.strides().end(), bcast_strides.begin() + axis); shape output{t, broadcast_lens, std::move(bcast_strides)}; if(output.elements() < s0.elements()) MIGRAPHX_THROW("BROADCAST: output size must be greater than or equal to s0 size"); return output; } else { // two inputs auto s1 = inputs.at(1); if(s0.dynamic()) MIGRAPHX_THROW("BROADCAST_2in: s0 is a static shape, does not handle broadcasting " "a static shape"); if(s0.ndim() != 1) MIGRAPHX_THROW("BROADCAST_2in: s0 has ndim " + migraphx::to_string(s0.ndim()) + ", only handle ndim = 1"); if(axis > s1.ndim()) MIGRAPHX_THROW("BROADCAST_2in: axis is out of range"); if(s1.ndim() - axis < s0.ndim()) MIGRAPHX_THROW("BROADCAST_2in: (s1_ndim - axis) is less than s0 ndim"); if(s1.dynamic()) return s1; std::vector bcast_strides(s1.ndim(), 0); std::copy(s0.strides().begin(), s0.strides().end(), bcast_strides.begin() + axis); shape output{t, s1.lens(), std::move(bcast_strides)}; if(output.elements() < s0.elements()) MIGRAPHX_THROW( "BROADCAST_2in: output size must be greater than or equal to s0 size"); return output; } } argument compute(shape output_shape, std::vector args) const { return args[0].reshape(output_shape); } std::ptrdiff_t output_alias(const std::vector&) const { return 0; } }; } // namespace op } // namespace MIGRAPHX_INLINE_NS } // namespace migraphx #endif