Merge branch 'develop' into mlir-c

test/onnx/hardsigmoid_double_test.onnx

+hardsigmoid_double_test:

+4
+
x
y"HardSigmoid*
+alpha>

*
+beta333?

hardsigmoid_double_testZ
+
x
+
+

+
+
+b
+
y
+
+

+
+
+B
\ No newline at end of file

test/onnx/hardsigmoid_half_test.onnx

+hardsigmoid_half_test:f
+
+
x
y"HardSigmoidhardsigmoid_half_testZ
+
x
+
+
+

+
+
+b
+
y
+
+
+

+
+
+B
\ No newline at end of file

test/onnx/hardsigmoid_verify_test.onnx

+hardsigmoid_verify_test:X
+
+
x
y"HardSigmoidhardsigmoid_verify_testZ
+
x
+

+
+b
+
y
+

+
+B
\ No newline at end of file

test/onnx/hardswish_test.onnx

+hardswish_test:M
+
+
x
y"	HardSwishhardswish_testZ
+
x
+

+
+b
+
y
+

+
+B
\ No newline at end of file

test/onnx/mean_broadcast_test.onnx

+mean_broadcast_test:Ã

+
+
0
+
1
+
2
+
3
+
4mean"Meanmean_broadcast_testZ
+
0
+

+

+
+Z
+
1
+

+

+
+
+Z
+
2
+
+

+Z
+
3
+
+

+
Z
+
4
+

+
+
+
b
+mean
+

+

+
+
+B
\ No newline at end of file

test/onnx/mean_fp16_test.onnx

+mean_fp16_test:Ž

+
+
0
+
1
+
2mean"Meanmean_fp16_testZ
+
0
+
+
+

+
+Z
+
1
+
+
+

+
+Z
+
2
+
+
+

+
+b
+mean
+
+
+

+
+B
\ No newline at end of file

test/onnx/mean_invalid_broadcast_test.onnx

+mean_invalid_broadcast_test:›

+
+
0
+
1
+
2mean"Meanmean_invalid_broadcast_testZ
+
0
+

+

+
+Z
+
1
+

+

+
+Z
+
2
+

+

+
+b
+mean
+

+

+
+B
\ No newline at end of file

test/onnx/mean_single_input_test.onnx

+mean_single_input_test:^
+
+
0mean"Meanmean_single_input_testZ
+
0
+

+

+
+b
+mean
+

+

+
+B
\ No newline at end of file

test/onnx/mean_test.onnx

+	mean_test:Í
+*
+
0
+
1
+
2
+
3
+
4
+
5
+
6
+
7
+
8
+
9mean"Mean	mean_testZ
+
0
+
+
+
+Z
+
1
+
+
+
+Z
+
2
+
+
+
+Z
+
3
+
+
+
+Z
+
4
+
+
+
+Z
+
5
+
+
+
+Z
+
6
+
+
+
+Z
+
7
+
+
+
+Z
+
8
+
+
+
+Z
+
9
+
+
+
+b
+mean
+
+
+
+B
\ No newline at end of file

test/onnx/multinomial_generated_seed_test.onnx

+multinomial_generated_seed_test:

+0
+inputoutput"Multinomial*
+sample_size
+
multinomial_generated_seed_testZ
+input
+

+

+
+b
+output
+
+

+
+B
\ No newline at end of file

test/onnx/onnx_test.cpp

@@ -1549,6 +1549,24 @@ TEST_CASE(greater_bool_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(greaterorequal_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+
+    auto input1 = mm->add_parameter("x1", migraphx::shape{migraphx::shape::float_type, {3}});
+    auto input2 = mm->add_parameter("x2", migraphx::shape{migraphx::shape::float_type, {3}});
+    auto temp   = mm->add_instruction(migraphx::make_op("less"), input1, input2);
+    auto bt     = mm->add_instruction(
+        migraphx::make_op("convert", {{"target_type", migraphx::shape::bool_type}}), temp);
+    auto ge = mm->add_instruction(migraphx::make_op("not"), bt);
+
+    mm->add_return({ge});
+
+    auto prog = migraphx::parse_onnx("greaterorequal_test.onnx");
+    EXPECT(p == prog);
+}
+
 TEST_CASE(group_conv_test)
 {
     migraphx::program p;
@@ -1563,6 +1581,140 @@ TEST_CASE(group_conv_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(hardsigmoid_default_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    std::vector<std::size_t> input_lens{1, 3, 4, 5};
+    auto input_type = migraphx::shape::float_type;
+    migraphx::shape s{input_type, input_lens};
+    auto x = mm->add_parameter("x", s);
+
+    float alpha = 0.2;
+    float beta  = 0.5;
+
+    auto mb_alpha = mm->add_instruction(
+        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {alpha}}));
+    auto mb_beta = mm->add_instruction(
+        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {beta}}));
+    auto mb_zero =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {0}}));
+    auto mb_one =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));
+
+    auto mul = mm->add_instruction(migraphx::make_op("mul"), mb_alpha, x);
+    auto add = mm->add_instruction(migraphx::make_op("add"), mb_beta, mul);
+    mm->add_instruction(migraphx::make_op("clip"), add, mb_zero, mb_one);
+
+    auto prog = optimize_onnx("hardsigmoid_default_test.onnx");
+    EXPECT(p == prog);
+}
+
+TEST_CASE(hardsigmoid_double_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    std::vector<std::size_t> input_lens{1, 3, 4, 5};
+    auto input_type = migraphx::shape::double_type;
+    migraphx::shape s{input_type, input_lens};
+    auto x = mm->add_parameter("x", s);
+
+    float alpha = 0.3;
+    float beta  = 0.7;
+
+    auto mb_alpha = mm->add_instruction(
+        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {alpha}}));
+    auto mb_beta = mm->add_instruction(
+        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {beta}}));
+    auto mb_zero =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {0}}));
+    auto mb_one =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));
+
+    auto mul = mm->add_instruction(migraphx::make_op("mul"), mb_alpha, x);
+    auto add = mm->add_instruction(migraphx::make_op("add"), mb_beta, mul);
+    mm->add_instruction(migraphx::make_op("clip"), add, mb_zero, mb_one);
+
+    auto prog = optimize_onnx("hardsigmoid_double_test.onnx");
+    EXPECT(p == prog);
+}
+
+TEST_CASE(hardsigmoid_half_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    std::vector<std::size_t> input_lens{1, 3, 4, 5};
+    auto input_type = migraphx::shape::half_type;
+    migraphx::shape s{input_type, input_lens};
+    auto x = mm->add_parameter("x", s);
+
+    float alpha = 0.2;
+    float beta  = 0.5;
+
+    auto mb_alpha = mm->add_instruction(
+        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {alpha}}));
+    auto mb_beta = mm->add_instruction(
+        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {beta}}));
+    auto mb_zero =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {0}}));
+    auto mb_one =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));
+
+    auto mul = mm->add_instruction(migraphx::make_op("mul"), mb_alpha, x);
+    auto add = mm->add_instruction(migraphx::make_op("add"), mb_beta, mul);
+    mm->add_instruction(migraphx::make_op("clip"), add, mb_zero, mb_one);
+
+    auto prog = optimize_onnx("hardsigmoid_half_test.onnx");
+    EXPECT(p == prog);
+}
+
+TEST_CASE(hardswish_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    std::vector<std::size_t> input_lens{2, 5};
+    auto input_type = migraphx::shape::float_type;
+    migraphx::shape s{input_type, input_lens};
+    auto x = mm->add_parameter("x", s);
+
+    float alpha = 1.0 / 6.0;
+    float beta  = 0.5;
+
+    auto mb_alpha = mm->add_instruction(
+        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {alpha}}));
+    auto mb_beta = mm->add_instruction(
+        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {beta}}));
+    auto mb_zero =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {0}}));
+    auto mb_one =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));
+
+    auto mul         = mm->add_instruction(migraphx::make_op("mul"), mb_alpha, x);
+    auto add         = mm->add_instruction(migraphx::make_op("add"), mb_beta, mul);
+    auto hardsigmoid = mm->add_instruction(migraphx::make_op("clip"), add, mb_zero, mb_one);
+    mm->add_instruction(migraphx::make_op("mul"), x, hardsigmoid);
+
+    auto prog = optimize_onnx("hardswish_test.onnx");
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(if_else_test)
 {
     migraphx::program p;
@@ -2340,6 +2492,50 @@ TEST_CASE(maxpool_same_upper_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(mean_invalid_broadcast_test)
+{
+    EXPECT(test::throws([&] { migraphx::parse_onnx("mean_invalid_broadcast_test.onnx"); }));
+}
+
+TEST_CASE(mean_single_input_test)
+{
+    migraphx::program p;
+    auto* mm   = p.get_main_module();
+    auto data0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 2, 3}});
+    mm->add_return({data0});
+
+    auto prog = migraphx::parse_onnx("mean_single_input_test.onnx");
+
+    EXPECT(p == prog);
+}
+
+TEST_CASE(mean_test)
+{
+    const std::size_t num_data = 3;
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape s{migraphx::shape::half_type, {1, 2, 3}};
+    auto data0   = mm->add_parameter("0", s);
+    auto data1   = mm->add_parameter("1", s);
+    auto data2   = mm->add_parameter("2", s);
+    auto div_lit = mm->add_literal(migraphx::literal{migraphx::shape{s.type()}, {num_data}});
+    auto divisor =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", s.lens()}}), div_lit);
+    auto mean = mm->add_instruction(migraphx::make_op("div"), data0, divisor);
+    divisor =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", s.lens()}}), div_lit);
+    data1 = mm->add_instruction(migraphx::make_op("div"), data1, divisor);
+    mean  = mm->add_instruction(migraphx::make_op("add"), mean, data1);
+    divisor =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", s.lens()}}), div_lit);
+    data2 = mm->add_instruction(migraphx::make_op("div"), data2, divisor);
+    mean  = mm->add_instruction(migraphx::make_op("add"), mean, data2);
+
+    auto prog = optimize_onnx("mean_fp16_test.onnx");
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(min_test)
 {
     migraphx::program p;
@@ -2388,6 +2584,14 @@ TEST_CASE(multinomial_dtype_error_test)
     EXPECT(test::throws([&] { migraphx::parse_onnx("multinomial_dtype_error_test.onnx"); }));
 }
 
+TEST_CASE(multinomial_generated_seed_test)
+{
+    auto p1 = optimize_onnx("multinomial_generated_seed_test.onnx");
+    auto p2 = optimize_onnx("multinomial_generated_seed_test.onnx");
+
+    EXPECT(p1 != p2);
+}
+
 TEST_CASE(multinomial_int64_test)
 {
     migraphx::program p;
@@ -2891,6 +3095,14 @@ TEST_CASE(randomnormal_dtype_error_test)
     EXPECT(test::throws([&] { migraphx::parse_onnx("randomnormal_dtype_error_test.onnx"); }));
 }
 
+TEST_CASE(randomnormal_generated_seed_test)
+{
+    auto p1 = optimize_onnx("randomnormal_generated_seed_test.onnx");
+    auto p2 = optimize_onnx("randomnormal_generated_seed_test.onnx");
+
+    EXPECT(p1 != p2);
+}
+
 TEST_CASE(randomnormal_shape_error_test)
 {
     EXPECT(test::throws([&] { migraphx::parse_onnx("randomnormal_shape_error_test.onnx"); }));
@@ -2953,6 +3165,14 @@ TEST_CASE(randomuniform_dtype_error_test)
     EXPECT(test::throws([&] { migraphx::parse_onnx("randomuniform_dtype_error_test.onnx"); }));
 }
 
+TEST_CASE(randomuniform_generated_seed_test)
+{
+    auto p1 = optimize_onnx("randomuniform_generated_seed_test.onnx");
+    auto p2 = optimize_onnx("randomuniform_generated_seed_test.onnx");
+
+    EXPECT(p1 != p2);
+}
+
 TEST_CASE(randomuniform_shape_error_test)
 {
     EXPECT(test::throws([&] { migraphx::parse_onnx("randomuniform_shape_error_test.onnx"); }));
@@ -3423,7 +3643,7 @@ TEST_CASE(resize_nonstd_input_test)
     EXPECT(p == prog);
 }
 
-TEST_CASE(resize_upsample_linear_ac_test)
+static auto create_upsample_linear_prog()
 {
     migraphx::program p;
     auto* mm = p.get_main_module();
@@ -3514,6 +3734,12 @@ TEST_CASE(resize_upsample_linear_ac_test)
     auto add1  = mm->add_instruction(migraphx::make_op("add"), mul1, slc10);
     mm->add_return({add1});
 
+    return p;
+}
+
+TEST_CASE(resize_upsample_linear_ac_test)
+{
+    auto p    = create_upsample_linear_prog();
     auto prog = migraphx::parse_onnx("resize_upsample_linear_ac_test.onnx");
     EXPECT(p == prog);
 }
@@ -3972,6 +4198,86 @@ TEST_CASE(softmax_nonstd_input_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(softplus_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+
+    std::vector<std::size_t> input_lens{5};
+    auto input_type = migraphx::shape::float_type;
+
+    auto x = mm->add_parameter("x", migraphx::shape{input_type, input_lens});
+    auto mb_ones =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));
+    auto exp = mm->add_instruction(migraphx::make_op("exp"), x);
+    auto add = mm->add_instruction(migraphx::make_op("add"), exp, mb_ones);
+    mm->add_instruction(migraphx::make_op("log"), add);
+
+    auto prog = optimize_onnx("softplus_test.onnx");
+    EXPECT(p == prog);
+}
+
+TEST_CASE(softplus_nd_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+
+    std::vector<std::size_t> input_lens{3, 4, 5};
+    auto input_type = migraphx::shape::half_type;
+
+    auto x = mm->add_parameter("x", migraphx::shape{input_type, input_lens});
+    auto mb_ones =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));
+    auto exp = mm->add_instruction(migraphx::make_op("exp"), x);
+    auto add = mm->add_instruction(migraphx::make_op("add"), exp, mb_ones);
+    mm->add_instruction(migraphx::make_op("log"), add);
+
+    auto prog = optimize_onnx("softplus_nd_test.onnx");
+    EXPECT(p == prog);
+}
+
+TEST_CASE(softsign_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+
+    std::vector<std::size_t> input_lens{5};
+    auto input_type = migraphx::shape::float_type;
+
+    auto x = mm->add_parameter("x", migraphx::shape{input_type, input_lens});
+    auto mb_ones =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));
+    auto abs = mm->add_instruction(migraphx::make_op("abs"), x);
+    auto add = mm->add_instruction(migraphx::make_op("add"), abs, mb_ones);
+    mm->add_instruction(migraphx::make_op("div"), x, add);
+
+    auto prog = optimize_onnx("softsign_test.onnx");
+    EXPECT(p == prog);
+}
+
+TEST_CASE(softsign_nd_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+
+    std::vector<std::size_t> input_lens{3, 4, 5};
+    auto input_type = migraphx::shape::half_type;
+
+    auto x = mm->add_parameter("x", migraphx::shape{input_type, input_lens});
+    auto mb_ones =
+        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));
+    auto abs = mm->add_instruction(migraphx::make_op("abs"), x);
+    auto add = mm->add_instruction(migraphx::make_op("add"), abs, mb_ones);
+    mm->add_instruction(migraphx::make_op("div"), x, add);
+
+    auto prog = optimize_onnx("softsign_nd_test.onnx");
+    EXPECT(p == prog);
+}
+
 TEST_CASE(split_minus_axis_test)
 {
     migraphx::program p;
@@ -4453,6 +4759,13 @@ TEST_CASE(unknown_test_throw)
     EXPECT(test::throws([&] { migraphx::parse_onnx("unknown_test.onnx"); }));
 }
 
+TEST_CASE(upsample_linear_test)
+{
+    auto p    = create_upsample_linear_prog();
+    auto prog = migraphx::parse_onnx("upsample_linear_test.onnx");
+    EXPECT(p == prog);
+}
+
 TEST_CASE(upsample_test)
 {
     migraphx::program p;

test/onnx/randomnormal_generated_seed_test.onnx

+ randomnormal_generated_seed_test:

+1
+inputoutput"RandomNormal*
+sample_size
+
 randomnormal_generated_seed_testZ
+input
+

+

+
+b
+output
+
+

+
+B
\ No newline at end of file

test/onnx/randomuniform_generated_seed_test.onnx

+!randomuniform_generated_seed_test:

+2
+inputoutput"
RandomUniform*
+sample_size
+
!randomuniform_generated_seed_testZ
+input
+

+

+
+b
+output
+
+

+
+B
\ No newline at end of file

test/onnx/softplus_nd_test.onnx

+softplus_nd_test:V
+
+
x
y"Softplussoftplus_nd_testZ
+
x
+
+
+
+
+b
+
y
+
+
+
+
+B
\ No newline at end of file

test/onnx/softplus_test.onnx

+
softplus_test:C
+
+
x
y"Softplus
softplus_testZ
+
x
+
+

+b
+
y
+
+

+B
\ No newline at end of file

test/onnx/softsign_nd_test.onnx

+softsign_nd_test:V
+
+
x
y"Softsignsoftsign_nd_testZ
+
x
+
+
+
+
+b
+
y
+
+
+
+
+B
\ No newline at end of file

test/onnx/softsign_test.onnx

+
softsign_test:C
+
+
x
y"Softsign
softsign_testZ
+
x
+
+

+b
+
y
+
+

+B
\ No newline at end of file

test/onnx/verify_onnx.cpp

@@ -126,6 +126,51 @@ TEST_CASE(gather_elements)
     EXPECT(migraphx::verify_range(result_vector, gold));
 }
 
+TEST_CASE(greaterorequal_test)
+{
+    migraphx::program p = migraphx::parse_onnx("greaterorequal_test.onnx");
+    p.compile(migraphx::ref::target{});
+
+    migraphx::shape s{migraphx::shape::float_type, {3}};
+    std::vector<float> data1 = {0.25, 0.75, 0.9375};
+    std::vector<float> data2 = {0.25, 0.74, 0.9411};
+
+    migraphx::parameter_map pp;
+    pp["x1"] = migraphx::argument(s, data1.data());
+    pp["x2"] = migraphx::argument(s, data2.data());
+
+    auto result = p.eval(pp).back();
+    std::vector<float> result_vector;
+    result.visit([&](auto output) { result_vector.assign(output.begin(), output.end()); });
+
+    std::vector<float> gold = {1.0, 1.0, 0.0};
+    EXPECT(migraphx::verify_range(result_vector, gold));
+}
+
+TEST_CASE(hardsigmoid_verify_test)
+{
+    migraphx::program p = migraphx::parse_onnx("hardsigmoid_verify_test.onnx");
+    p.compile(migraphx::ref::target{});
+
+    migraphx::shape s{migraphx::shape::float_type, {2, 5}};
+    std::vector<float> data = {-10.0, -2.5, -1.0, -0.5, 0, 1.0, 2.0, 2.5, 2.6, 100.0};
+
+    float alpha = 0.2;
+    float beta  = 0.5;
+    migraphx::parameter_map pp;
+    pp["x"] = migraphx::argument(s, data.data());
+
+    auto result = p.eval(pp).back();
+    std::vector<float> result_vector;
+    result.visit([&](auto output) { result_vector.assign(output.begin(), output.end()); });
+
+    std::vector<float> gold(10);
+    std::transform(data.begin(), data.end(), gold.begin(), [&](auto x) {
+        return std::max(0.0f, std::min(x * alpha + beta, 1.0f));
+    });
+    EXPECT(migraphx::verify_range(result_vector, gold));
+}
+
 TEST_CASE(if_else_test)
 {
     migraphx::program p = migraphx::parse_onnx("if_else_test.onnx");
@@ -348,6 +393,64 @@ TEST_CASE(lessorequal_test)
     EXPECT(migraphx::verify_range(result_vector, gold));
 }
 
+TEST_CASE(mean_broadcast_test)
+{
+    migraphx::program p = migraphx::parse_onnx("mean_broadcast_test.onnx");
+    p.compile(migraphx::ref::target{});
+
+    migraphx::shape s0{migraphx::shape::float_type, {1, 3, 4}};
+    std::vector<float> data0(12, 1);
+    migraphx::shape s1{migraphx::shape::float_type, {1, 2, 3, 4}};
+    std::vector<float> data1(24, 2);
+    migraphx::shape s2{migraphx::shape::float_type, {4}};
+    std::vector<float> data2(4, 3);
+    migraphx::shape s3{migraphx::shape::float_type, {1}};
+    std::vector<float> data3(1, 4);
+    migraphx::shape s4{migraphx::shape::float_type, {2, 3, 1}};
+    std::vector<float> data4(6, 5);
+
+    migraphx::parameter_map pp;
+    pp["0"] = migraphx::argument(s0, data0.data());
+    pp["1"] = migraphx::argument(s1, data1.data());
+    pp["2"] = migraphx::argument(s2, data2.data());
+    pp["3"] = migraphx::argument(s3, data3.data());
+    pp["4"] = migraphx::argument(s4, data4.data());
+
+    auto result = p.eval(pp).back();
+    std::vector<float> result_vector;
+    result.visit([&](auto output) { result_vector.assign(output.begin(), output.end()); });
+
+    std::vector<float> gold(24, 3);
+    EXPECT(migraphx::verify_range(result_vector, gold));
+}
+
+TEST_CASE(mean_test)
+{
+    migraphx::program p = migraphx::parse_onnx("mean_test.onnx");
+    p.compile(migraphx::ref::target{});
+
+    migraphx::shape s{migraphx::shape::double_type, {2, 2, 2}};
+    const int num_elms = 8;
+    const int num_data = 10;
+    const std::vector<double> scalars{1.0, 2.0, -2.5, 3.3, 10.7, -1.0, 100.0, 7.9, 0.01, -56.8};
+    std::vector<std::vector<double>> data;
+    std::transform(scalars.begin(), scalars.end(), std::back_inserter(data), [&](const auto& i) {
+        return std::vector<double>(num_elms, i);
+    });
+
+    migraphx::parameter_map pp;
+    for(std::size_t i = 0; i < num_data; ++i)
+        pp[std::to_string(i)] = migraphx::argument(s, data[i].data());
+
+    auto result = p.eval(pp).back();
+    std::vector<double> result_vector;
+    result.visit([&](auto output) { result_vector.assign(output.begin(), output.end()); });
+
+    const auto mean = std::accumulate(scalars.begin(), scalars.end(), 0.0) / num_data;
+    std::vector<double> gold(num_elms, mean);
+    EXPECT(migraphx::verify_range(result_vector, gold));
+}
+
 TEST_CASE(nonzero_test)
 {
     migraphx::program p = migraphx::parse_onnx("nonzero_dynamic_test.onnx");
@@ -564,6 +667,48 @@ TEST_CASE(slice_step_test)
     EXPECT(migraphx::verify_range(result_vector, gold));
 }
 
+TEST_CASE(softplus_test)
+{
+    migraphx::program p = migraphx::parse_onnx("softplus_test.onnx");
+    p.compile(migraphx::ref::target{});
+
+    migraphx::shape s{migraphx::shape::float_type, {5}};
+    std::vector<float> data = {0, 1, 2, 3, 4};
+
+    migraphx::parameter_map pp;
+    pp["x"] = migraphx::argument(s, data.data());
+
+    auto result = p.eval(pp).back();
+    std::vector<float> result_vector;
+    result.visit([&](auto output) { result_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold(5);
+    std::transform(
+        data.begin(), data.end(), gold.begin(), [](auto x) { return std::log1p(std::exp(x)); });
+
+    EXPECT(migraphx::verify_range(result_vector, gold));
+}
+
+TEST_CASE(softsign_test)
+{
+    migraphx::program p = migraphx::parse_onnx("softsign_test.onnx");
+    p.compile(migraphx::ref::target{});
+
+    migraphx::shape s{migraphx::shape::float_type, {5}};
+    std::vector<float> data = {0, 1, 2, 3, 4};
+
+    migraphx::parameter_map pp;
+    pp["x"] = migraphx::argument(s, data.data());
+
+    auto result = p.eval(pp).back();
+    std::vector<float> result_vector;
+    result.visit([&](auto output) { result_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold(5);
+    std::transform(
+        data.begin(), data.end(), gold.begin(), [](auto x) { return x / (1.0 + std::abs(x)); });
+
+    EXPECT(migraphx::verify_range(result_vector, gold));
+}
+
 TEST_CASE(upsample_test)
 {
     migraphx::program p = migraphx::parse_onnx("upsample_test.onnx");

test/py/onnx_backend_test.py

@@ -119,6 +119,7 @@ def create_backend_test(testname=None, target_device=None):
         backend_test.include(r'.*test_globalmaxpool.*')
         backend_test.include(r'.*test_greater.*')
         backend_test.include(r'.*test_hardsigmoid.*')
+        backend_test.include(r'.*test_hardswish.*')
         backend_test.include(r'.*test_identity.*')
         backend_test.include(r'.*test_if.*')
         backend_test.include(r'.*test_LeakyReLU*')
@@ -266,18 +267,8 @@ def create_backend_test(testname=None, target_device=None):
         backend_test.exclude(r'test_gathernd_example_float32_cpu')
         backend_test.exclude(r'test_gathernd_example_int32_batch_dim1_cpu')
         backend_test.exclude(r'test_gathernd_example_int32_cpu')
-        backend_test.exclude(r'test_greater_equal_bcast_cpu')
-        backend_test.exclude(r'test_greater_equal_bcast_expanded_cpu')
-        backend_test.exclude(r'test_greater_equal_cpu')
-        backend_test.exclude(r'test_greater_equal_expanded_cpu')
-        backend_test.exclude(r'test_hardsigmoid_cpu')
-        backend_test.exclude(r'test_hardsigmoid_default_cpu')
-        backend_test.exclude(r'test_hardsigmoid_example_cpu')
         backend_test.exclude(r'test_identity_sequence_cpu')
         backend_test.exclude(r'test_maxpool_2d_uint8_cpu')
-        backend_test.exclude(r'test_mean_example_cpu')
-        backend_test.exclude(r'test_mean_one_input_cpu')
-        backend_test.exclude(r'test_mean_two_inputs_cpu')
         backend_test.exclude(r'test_negative_log_likelihood_loss_*')
         backend_test.exclude(r'test_scatternd_*')
 
@@ -285,12 +276,7 @@ def create_backend_test(testname=None, target_device=None):
         backend_test.exclude(r'test_size_cpu')
         backend_test.exclude(r'test_size_example_cpu')
         backend_test.exclude(r'test_softmax_cross_entropy_*')
-        backend_test.exclude(r'test_softplus_cpu')
-        backend_test.exclude(r'test_softplus_example_cpu')
-        backend_test.exclude(r'test_softsign_cpu')
-        backend_test.exclude(r'test_softsign_example_cpu')
         backend_test.exclude(r'test_Embedding_cpu')
-        backend_test.exclude(r'test_Softplus_cpu')
 
         # real model tests
         backend_test.exclude(r'test_inception_v1_cpu')