Function TEST_CASE

test/tf/tests/batchnorm_test.cpp:28–58

#include <tf_test.hpp>

TEST_CASE(batchnorm_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto x    = mm->add_parameter("x", {migraphx::shape::float_type, {1, 32, 16, 16}});
    auto bias = mm->add_parameter("bias", {migraphx::shape::float_type, {32}});
    auto mean = mm->add_parameter("mean", {migraphx::shape::float_type, {32}});
    auto var  = mm->add_parameter("variance", {migraphx::shape::float_type, {32}});

    std::vector<float> scale_data(32, 1.0);
    auto scale = mm->add_literal(migraphx::shape{migraphx::shape::float_type, {32}}, scale_data);
    auto eps   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {1e-4f}});

    auto usq_scale = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1, 2}}}), scale);
    auto usq_bias  = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", x->get_shape().lens()}}), bias);
    auto usq_mean = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", x->get_shape().lens()}}), mean);
    auto usq_var   = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1, 2}}}), var);

    auto x_sub_mean = add_common_op(*mm, migraphx::make_op("sub"), {x, usq_mean});
    auto var_eps    = add_common_op(*mm, migraphx::make_op("add"), {usq_var, eps});
    auto rsqrt      = mm->add_instruction(migraphx::make_op("rsqrt"), var_eps);
    auto mul0       = add_common_op(*mm, migraphx::make_op("mul"), {usq_scale, rsqrt});
    auto r0         = add_common_op(*mm, migraphx::make_op("mul"), {x_sub_mean, mul0});
    add_common_op(*mm, migraphx::make_op("add"), {r0, usq_bias});

    auto prog = optimize_tf("batchnorm_test.pb", true);
    EXPECT(p.sort() == prog.sort());
}