#include "verify_program.hpp" #include #include #include struct test_conv_bn_add : verify_program { static migraphx::instruction_ref add_bn(migraphx::module& m, migraphx::instruction_ref x, int channels, int seed = 1) { migraphx::shape vars{migraphx::shape::float_type, {channels}}; auto scale = m.add_literal(migraphx::abs(migraphx::generate_literal(vars, 1 + seed))); auto bias = m.add_literal(migraphx::abs(migraphx::generate_literal(vars, 2 + seed))); auto mean = m.add_literal(migraphx::abs(migraphx::generate_literal(vars, 3 + seed))); auto variance = m.add_literal(migraphx::abs(migraphx::generate_literal(vars, 4 + seed))); return m.add_instruction( migraphx::make_op("batch_norm_inference"), x, scale, bias, mean, variance); } migraphx::program create_program() const { migraphx::program p; auto* mm = p.get_main_module(); int ichannels = 64; int ochannels = 256; auto x = mm->add_parameter("x", {migraphx::shape::float_type, {1, ichannels, 56, 56}}); auto w = mm->add_literal(migraphx::generate_literal( {migraphx::shape::float_type, {ochannels, ichannels, 1, 1}}, 1)); auto y = mm->add_parameter("y", {migraphx::shape::float_type, {1, ichannels, 56, 56}}); auto v = mm->add_literal(migraphx::generate_literal( {migraphx::shape::float_type, {ochannels, ichannels, 1, 1}}, 2)); auto relu1 = mm->add_instruction(migraphx::make_op("relu"), x); auto conv1 = mm->add_instruction(migraphx::make_op("convolution"), relu1, w); auto bn1 = add_bn(*mm, conv1, ochannels, 1); auto relu2 = mm->add_instruction(migraphx::make_op("relu"), y); auto conv2 = mm->add_instruction(migraphx::make_op("convolution"), relu2, v); auto bn2 = add_bn(*mm, conv2, ochannels, 1); auto sum = mm->add_instruction(migraphx::make_op("add"), bn1, bn2); mm->add_instruction(migraphx::make_op("relu"), sum); return p; } };