#include #include #include #include #include #include #include #include #include #include #include "test.hpp" #include "verify.hpp" template migraph::argument run_cpu() { V v; auto p = v.create_program(); p.compile(migraph::cpu::cpu_target{}); migraph::program::parameter_map m; for(auto&& x : p.get_parameter_shapes()) { m[x.first] = migraph::generate_argument(x.second); } return p.eval(m); } template migraph::argument run_gpu() { V v; auto p = v.create_program(); p.compile(migraph::gpu::target{}); migraph::program::parameter_map m; for(auto&& x : p.get_parameter_shapes()) { m[x.first] = migraph::gpu::to_gpu(migraph::generate_argument(x.second)); } return migraph::gpu::from_gpu(p.eval(m)); } template void verify_program() { auto cpu_arg = run_cpu(); auto gpu_arg = run_gpu(); visit_all(cpu_arg, gpu_arg)([](auto cpu, auto gpu) { if(not test::verify_range(cpu, gpu)) { std::cout << "FAILED: " << migraph::get_type_name() << std::endl; } }); } struct test_literals { migraph::program create_program() const { migraph::program p; auto input = p.add_literal( generate_literal(migraph::shape{migraph::shape::float_type, {4, 3, 3, 3}})); auto weights = p.add_literal( generate_literal(migraph::shape{migraph::shape::float_type, {4, 3, 3, 3}})); auto conv = p.add_instruction(migraph::convolution{}, input, weights); p.add_instruction(migraph::activation{"relu"}, conv); return p; } }; struct test_add { migraph::program create_program() const { migraph::program p; migraph::shape s{migraph::shape::float_type, {3}}; auto x = p.add_parameter("x", s); auto y = p.add_parameter("y", s); p.add_instruction(migraph::add{}, x, y); return p; } }; struct test_add_broadcast { migraph::program create_program() const { migraph::program p; migraph::shape s{migraph::shape::float_type, {3}}; auto x = p.add_parameter("x", {migraph::shape::float_type, {2, 2, 3}}); auto y = p.add_parameter("y", {migraph::shape::float_type, {2, 2}}); auto by = p.add_instruction(migraph::broadcast{0}, x, y); p.add_instruction(migraph::add{}, x, by); return p; } }; struct test_conv_relu { migraph::program create_program() const { migraph::program p; auto input = p.add_parameter("x", migraph::shape{migraph::shape::float_type, {4, 3, 3, 3}}); auto weights = p.add_parameter("w", migraph::shape{migraph::shape::float_type, {4, 3, 3, 3}}); auto conv = p.add_instruction(migraph::convolution{}, input, weights); p.add_instruction(migraph::activation{"relu"}, conv); return p; } }; struct test_conv_pooling { migraph::program create_program() const { migraph::program p; auto input = p.add_parameter("x", migraph::shape{migraph::shape::float_type, {4, 3, 32, 32}}); auto weights = p.add_parameter("w", migraph::shape{migraph::shape::float_type, {4, 3, 3, 3}}); auto conv = p.add_instruction(migraph::convolution{}, input, weights); auto pooling = p.add_instruction(migraph::pooling{"max"}, conv); p.add_instruction(migraph::activation{"relu"}, pooling); return p; } }; struct test_gemm { migraph::program create_program() const { migraph::program p; auto a = p.add_parameter("a", migraph::shape{migraph::shape::float_type, {4, 5}}); auto b = p.add_parameter("b", migraph::shape{migraph::shape::float_type, {5, 3}}); p.add_instruction(migraph::gemm{}, a, b); return p; } }; struct test_gemm_ld { migraph::program create_program() const { migraph::program p; auto a = p.add_parameter("a", migraph::shape{migraph::shape::float_type, {4, 5}, {10, 1}}); auto b = p.add_parameter("b", migraph::shape{migraph::shape::float_type, {5, 3}, {20, 1}}); p.add_instruction(migraph::gemm{}, a, b); return p; } }; struct test_gemm_transposeb { migraph::program create_program() const { migraph::program p; auto a = p.add_parameter("a", migraph::shape{migraph::shape::float_type, {4, 5}}); auto b = p.add_parameter("b", migraph::shape{migraph::shape::float_type, {3, 5}}); auto bt = p.add_instruction(migraph::transpose{{1, 0}}, b); p.add_instruction(migraph::gemm{}, a, bt); return p; } }; struct test_gemm_transposea { migraph::program create_program() const { migraph::program p; auto a = p.add_parameter("a", migraph::shape{migraph::shape::float_type, {5, 4}}); auto b = p.add_parameter("b", migraph::shape{migraph::shape::float_type, {5, 3}}); auto at = p.add_instruction(migraph::transpose{{1, 0}}, a); p.add_instruction(migraph::gemm{}, at, b); return p; } }; struct test_gemm_transposeab { migraph::program create_program() const { migraph::program p; auto a = p.add_parameter("a", migraph::shape{migraph::shape::float_type, {5, 4}}); auto b = p.add_parameter("b", migraph::shape{migraph::shape::float_type, {3, 5}}); auto at = p.add_instruction(migraph::transpose{{1, 0}}, a); auto bt = p.add_instruction(migraph::transpose{{1, 0}}, b); p.add_instruction(migraph::gemm{}, at, bt); return p; } }; struct test_contiguous { migraph::program create_program() const { migraph::program p; migraph::shape s{migraph::shape::float_type, {4, 4, 4, 3}, {48, 4, 1, 16}}; auto x = p.add_parameter("x", s); p.add_instruction(migraph::contiguous{}, x); return p; } }; struct test_transpose { migraph::program create_program() const { migraph::program p; migraph::shape s{migraph::shape::float_type, {4, 3, 4, 4}}; auto x = p.add_parameter("x", s); std::vector perm = {0, 2, 3, 1}; auto l = p.add_instruction(migraph::transpose{perm}, x); p.add_instruction(migraph::contiguous{}, l); return p; } }; struct test_batchnorm_inference { const size_t width = 3; const size_t height = 3; const size_t channels = 3; const size_t batches = 4; migraph::program create_program() const { migraph::program p; migraph::shape s{migraph::shape::float_type, {batches, channels, height, width}}; migraph::shape vars{migraph::shape::float_type, {channels}}; auto x = p.add_parameter("x", s); auto mean = p.add_parameter("mean", vars); auto variance = p.add_parameter("variance", vars); auto scale = p.add_parameter("scale", vars); auto bias = p.add_parameter("bias", vars); p.add_instruction(migraph::batch_norm_inference{}, x, mean, variance, scale, bias); return p; } }; void batch_norm_inference_test() { migraph::program p; const size_t width = 2, height = 2, channels = 4, batches = 2; const float x_val = 8.0f, mean_val = 2.0f, variance_val = 4.0f, scale_val = 2.0f, bias_val = 1.0f; const float output_val = scale_val * (x_val - mean_val) / (std::sqrt(variance_val)) + bias_val; migraph::shape s{migraph::shape::float_type, {batches, channels, height, width}}; migraph::shape vars{migraph::shape::float_type, {channels}}; std::vector x_data(width * height * channels * batches); std::vector scale_data(channels); std::vector bias_data(channels); std::vector mean_data(channels); std::vector variance_data(channels); std::fill(x_data.begin(), x_data.end(), x_val); std::fill(mean_data.begin(), mean_data.end(), mean_val); std::fill(variance_data.begin(), variance_data.end(), variance_val); std::fill(scale_data.begin(), scale_data.end(), scale_val); std::fill(bias_data.begin(), bias_data.end(), bias_val); auto x = p.add_literal(migraph::literal{s, x_data}); auto scale = p.add_literal(migraph::literal{vars, scale_data}); auto bias = p.add_literal(migraph::literal{vars, bias_data}); auto mean = p.add_literal(migraph::literal{vars, mean_data}); auto variance = p.add_literal(migraph::literal{vars, variance_data}); p.add_instruction(migraph::batch_norm_inference{}, x, mean, variance, scale, bias); p.compile(migraph::gpu::target{}); migraph::program::parameter_map m; m["output"] = migraph::gpu::to_gpu(migraph::generate_argument(p.get_parameter_shape("output"))); auto result = migraph::gpu::from_gpu(p.eval(m)); std::vector result_vector(width * height * channels * batches); std::vector gold(width * height * channels * batches); std::fill(gold.begin(), gold.end(), output_val); result.visit([&](auto output) { result_vector.assign(output.begin(), output.end()); }); EXPECT(test::verify_range(result_vector, gold)); } int main() { verify_program(); verify_program(); verify_program(); verify_program(); verify_program(); // verify_program(); verify_program(); verify_program(); verify_program(); verify_program(); verify_program(); verify_program(); batch_norm_inference_test(); }