Remove layernorm op tests

test/onnx/gen_onnx.py

@@ -2643,22 +2643,6 @@ def layernorm_test():
              bias_add], [x, scale, bias], [y], [pow_tensor, epsilon_tensor])
 
 
-@onnx_test
-def layernorm_op_test():
-    x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1, 2, 3])
-    w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [3])
-    b = helper.make_tensor_value_info('b', TensorProto.FLOAT, [3])
-    output = helper.make_tensor_value_info('output', TensorProto.FLOAT,
-                                           [1, 2, 3])
-
-    node = onnx.helper.make_node('LayerNormalization',
-                                 inputs=['x', 'w', 'b'],
-                                 outputs=["output"],
-                                 epsilon=1e-5)
-
-    return ([node], [x, w, b], [output])
-
-
 @onnx_test
 def leaky_relu_test():
     x = helper.make_tensor_value_info('0', TensorProto.FLOAT, [3])

test/onnx/layernorm_op_test.onnx

-layernorm_op_test:

-8
-
x
-
w
-
boutput"LayerNormalization*
-epsilon'7

layernorm_op_testZ
-
x
-

-

-
-Z
-
w
-
-

-Z
-
b
-
-

-b
-output
-

-

-
-B
\ No newline at end of file

test/onnx/verify_onnx.cpp

@@ -472,31 +472,6 @@ TEST_CASE(instance_norm_3d_test)
     EXPECT(migraphx::verify_range(result_vector, gold));
 }
 
-TEST_CASE(layernorm_op_test)
-{
-    migraphx::program p = migraphx::parse_onnx("layernorm_op_test.onnx");
-    p.compile(migraphx::ref::target{});
-
-    migraphx::shape sx{migraphx::shape::float_type, {1, 2, 3}};
-    migraphx::shape swb{migraphx::shape::float_type, {3}};
-    std::vector<float> x_vec{1.0, 2.0, 3.0, 4.0, 5.0, 6.0};
-    std::vector<float> w_vec{1.0, 1.0, 1.0};
-    std::vector<float> b_vec{0.0, 0.0, 0.0};
-
-    migraphx::parameter_map pp;
-    pp["x"] = migraphx::argument(sx, x_vec.data());
-    pp["w"] = migraphx::argument(swb, w_vec.data());
-    pp["b"] = migraphx::argument(swb, b_vec.data());
-
-    auto result = p.eval(pp).back();
-    std::vector<float> result_vector(6);
-    result.visit([&](auto output) { result_vector.assign(output.begin(), output.end()); });
-
-    std::vector<float> gold{-1.22474f, 0.0f, 1.22474f, -1.22474f, 0.0f, 1.22474f};
-
-    EXPECT(migraphx::verify_range(result_vector, gold));
-}
-
 TEST_CASE(lessorequal_test)
 {
     migraphx::program p = migraphx::parse_onnx("lessorequal_test.onnx");

test/ref_ops_test.cpp

@@ -2496,50 +2496,6 @@ TEST_CASE(imagescaler_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
-TEST_CASE(layernorm_test)
-{
-    {
-        // with scale and bias
-        migraphx::program p;
-        auto* mm = p.get_main_module();
-        migraphx::shape sx{migraphx::shape::float_type, {1, 2, 3}};
-        migraphx::shape swb{migraphx::shape::float_type, {3}};
-        std::vector<float> x_vec{1.0, 2.0, 3.0, 4.0, 5.0, 6.0};
-        auto x = mm->add_literal(migraphx::literal{sx, x_vec});
-        auto w = mm->add_literal(migraphx::literal{swb, {1.0, 1.0, 1.0}});
-        auto b = mm->add_literal(migraphx::literal{swb, {0.0, 0.0, 0.0}});
-        mm->add_instruction(migraphx::make_op("layernorm", {{"epsilon", 1e-5}}), x, w, b);
-        p.compile(migraphx::ref::target{});
-        auto result = p.eval({}).back();
-        std::vector<float> results_vector(1 * 2 * 3);
-        result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
-        std::vector<float> gold = {-1.22474f, 0.0f, 1.22474f, -1.22474f, 0.0f, 1.22474f};
-        for(auto&& i : results_vector)
-            std::cout << i << ", ";
-        std::cout << std::endl;
-        EXPECT(migraphx::verify_range(results_vector, gold));
-    }
-
-    {
-        // without scale and bias
-        migraphx::program p;
-        auto* mm = p.get_main_module();
-        migraphx::shape sx{migraphx::shape::float_type, {1, 2, 3}};
-        std::vector<float> x_vec{1.0, 2.0, 3.0, 4.0, 5.0, 6.0};
-        auto x = mm->add_literal(migraphx::literal{sx, x_vec});
-        mm->add_instruction(migraphx::make_op("layernorm", {{"epsilon", 1e-5}}), x);
-        p.compile(migraphx::ref::target{});
-        auto result = p.eval({}).back();
-        std::vector<float> results_vector(1 * 2 * 3);
-        result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
-        std::vector<float> gold = {-1.22474f, 0.0f, 1.22474f, -1.22474f, 0.0f, 1.22474f};
-        for(auto&& i : results_vector)
-            std::cout << i << ", ";
-        std::cout << std::endl;
-        EXPECT(migraphx::verify_range(results_vector, gold));
-    }
-}
-
 TEST_CASE(leaky_relu_test)
 {
     migraphx::program p;