Add tests for more operators

test/onnx/cos_fp8_test.onnx

@@ -0,0 +1,13 @@
+	cos_fp8_test:=
+
+
x
y"Coscos_fp8_testZ
+
x
+
+
+
+b
+
y
+
+
+
+B

test/onnx/div_fp8_test.onnx

@@ -0,0 +1,16 @@
+	div_fp8_test:a
+
+
0
+
1out"Divdiv_fp8_testZ
+
0
+
+
+Z
+
1
+
+
+b
+out
+
+
+B

test/onnx/gen_onnx.py

@@ -633,6 +633,38 @@ def binary_dyn_brcst_mul_test():
     return ([node], [arg0, arg1], [arg_out])
 
 
+@onnx_test()
+def binary_dyn_brcst_mul_fp8_test():
+    arg0 = helper.make_tensor_value_info('0', TensorProto.FLOAT8E4M3FNUZ,
+                                         [None, 3, 4, 5])
+    arg1 = helper.make_tensor_value_info('1', TensorProto.FLOAT8E4M3FNUZ, [4, 1])
+    arg_out = helper.make_tensor_value_info('out', TensorProto.FLOAT8E4M3FNUZ,
+                                            [None, 3, 4, 5])
+
+    node = onnx.helper.make_node(
+        'Mul',
+        inputs=['0', '1'],
+        outputs=['out'],
+    )
+
+    return ([node], [arg0, arg1], [arg_out])
+
+
+@onnx_test()
+def div_fp8_test():
+    arg0 = helper.make_tensor_value_info('0', TensorProto.FLOAT8E4M3FNUZ, [2, 3])
+    arg1 = helper.make_tensor_value_info('1', TensorProto.FLOAT8E4M3FNUZ, [2, 3])
+    arg_out = helper.make_tensor_value_info('out', TensorProto.FLOAT8E4M3FNUZ, [2, 3])
+
+    node = onnx.helper.make_node(
+        'Div',
+        inputs=['0', '1'],
+        outputs=['out'],
+    )
+
+    return ([node], [arg0, arg1], [arg_out])
+
+
 @onnx_test()
 def cast_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT16, [10])
@@ -1588,6 +1620,20 @@ def cos_test():
     return ([node], [x], [y])
 
 
+@onnx_test()
+def cos_fp8_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT8E4M3FNUZ, [10])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT8E4M3FNUZ, [10])
+
+    node = onnx.helper.make_node(
+        'Cos',
+        inputs=['x'],
+        outputs=['y'],
+    )
+
+    return ([node], [x], [y])
+
+
 @onnx_test()
 def cosh_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1])
@@ -2844,6 +2890,20 @@ def globalavgpool_test():
     return ([node], [x], [y])
 
 
+@onnx_test()
+def globalavgpool_fp8_test():
+    x = helper.make_tensor_value_info('0', TensorProto.FLOAT8E4M3FNUZ, [1, 3, 16, 16])
+    y = helper.make_tensor_value_info('1', TensorProto.FLOAT8E4M3FNUZ, [1, 3, 1, 1])
+
+    node = onnx.helper.make_node(
+        'GlobalAveragePool',
+        inputs=['0'],
+        outputs=['1'],
+    )
+
+    return ([node], [x], [y])
+
+
 @onnx_test()
 def globalavgpool_dyn_test():
     x = helper.make_tensor_value_info('0', TensorProto.FLOAT,
@@ -2902,6 +2962,20 @@ def globalmaxpool_test():
     return ([node], [x], [y])
 
 
+@onnx_test()
+def globalmaxpool_fp8_test():
+    x = helper.make_tensor_value_info('0', TensorProto.FLOAT8E4M3FNUZ, [1, 3, 16, 16])
+    y = helper.make_tensor_value_info('1', TensorProto.FLOAT8E4M3FNUZ, [1, 3, 1, 1])
+
+    node = onnx.helper.make_node(
+        'GlobalMaxPool',
+        inputs=['0'],
+        outputs=['1'],
+    )
+
+    return ([node], [x], [y])
+
+
 @onnx_test()
 def globalmaxpool_dyn_test():
     x = helper.make_tensor_value_info('0', TensorProto.FLOAT,
@@ -7749,6 +7823,22 @@ def reducemax_test():
     return ([node], [x], [y])
 
 
+@onnx_test()
+def reducemax_fp8_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT8E4M3FNUZ, [3, 4, 5, 6])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT8E4M3FNUZ, [3, 4, 6])
+
+    axes = [2]
+
+    node = onnx.helper.make_node('ReduceMax',
+                                 inputs=['x'],
+                                 outputs=['y'],
+                                 axes=axes,
+                                 keepdims=0)
+
+    return ([node], [x], [y])
+
+
 @onnx_test
 def reducemax_dyn_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [None, 4, 5, 6])
@@ -7838,6 +7928,20 @@ def reducesum_test():
     return ([node], [x], [y])
 
 
+@onnx_test()
+def reducesum_fp8_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT8E4M3FNUZ, [3, 4, 5, 6])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT8E4M3FNUZ, [3, 4, 1, 6])
+
+    node = onnx.helper.make_node('ReduceSum',
+                                 inputs=['x'],
+                                 outputs=['y'],
+                                 axes=[2],
+                                 keepdims=0)
+
+    return ([node], [x], [y])
+
+
 @onnx_test()
 def reducesum_empty_axes_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [3, 4, 5, 6])
@@ -9161,6 +9265,20 @@ def sin_test():
     return ([node], [x], [y])
 
 
+@onnx_test()
+def sin_fp8_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT8E4M3FNUZ, [10])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT8E4M3FNUZ, [10])
+
+    node = onnx.helper.make_node(
+        'Sin',
+        inputs=['x'],
+        outputs=['y'],
+    )
+
+    return ([node], [x], [y])
+
+
 @onnx_test()
 def sinh_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [10])
@@ -10010,6 +10128,20 @@ def sqrt_test():
     return ([node], [x], [y])
 
 
+@onnx_test()
+def sqrt_fp8_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT8E4M3FNUZ, [10, 15])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT8E4M3FNUZ, [10, 15])
+
+    node = onnx.helper.make_node(
+        'Sqrt',
+        inputs=['x'],
+        outputs=['y'],
+    )
+
+    return ([node], [x], [y])
+
+
 @onnx_test()
 def squeeze_axes_input_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [3, 1, 5, 1])

test/onnx/globalavgpool_fp8_test.onnx

@@ -0,0 +1,15 @@
+	globalavgpool_fp8_test:m
+
+
0
1"GlobalAveragePoolglobalavgpool_fp8_testZ
+
0
+
+

+
+
+b
+
1
+
+

+
+

+
B

test/onnx/globalmaxpool_fp8_test.onnx

@@ -0,0 +1,15 @@
+	globalmaxpool_fp8_test:i
+
+
0
1"GlobalMaxPoolglobalmaxpool_fp8_testZ
+
0
+
+

+
+
+b
+
1
+
+

+
+

+
B

test/onnx/parse/binary_dyn_brcst_mul_fp8_test.cpp

@@ -0,0 +1,53 @@
+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2024 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+
+#include <onnx_test.hpp>
+
+TEST_CASE(binary_dyn_brcst_mul_fp8_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    auto l0  = mm->add_parameter(
+        "0", migraphx::shape{migraphx::shape::fp8e4m3fnuz_type, {{1, 4}, {3, 3}, {4, 4}, {5, 5}}});
+    auto l1 = mm->add_parameter("1", migraphx::shape{migraphx::shape::fp8e4m3fnuz_type, {4, 1}});
+
+    auto bl0 = mm->add_instruction(
+        migraphx::make_op("multibroadcast",
+                          {{"out_dyn_dims", to_value(l0->get_shape().dyn_dims())}}),
+        l0,
+        l1);
+    auto bl1 = mm->add_instruction(
+        migraphx::make_op("multibroadcast",
+                          {{"out_dyn_dims", to_value(l0->get_shape().dyn_dims())}}),
+        l1,
+        bl0);
+    auto ret = mm->add_instruction(migraphx::make_op("mul"), bl0, bl1);
+    mm->add_return({ret});
+
+    migraphx::onnx_options options;
+    options.default_dyn_dim_value = {1, 4};
+    auto prog                     = migraphx::parse_onnx("binary_dyn_brcst_mul_fp8_test.onnx", options);
+
+    EXPECT(p == prog);
+}

test/onnx/parse/cos_fp8_test.cpp

@@ -0,0 +1,36 @@
+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2024 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+
+#include <onnx_test.hpp>
+
+TEST_CASE(cos_fp8_test)
+{
+    migraphx::program p;
+    auto* mm   = p.get_main_module();
+    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::fp8e4m3fnuz_type, {10}});
+    mm->add_instruction(migraphx::make_op("cos"), input);
+
+    auto prog = optimize_onnx("cos_fp8_test.onnx");
+    EXPECT(p == prog);
+}

test/onnx/parse/div_fp8_test.cpp

@@ -0,0 +1,39 @@
+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2024 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+
+#include <onnx_test.hpp>
+
+TEST_CASE(div_fp8_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    auto p0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::fp8e4m3fnuz_type, {2, 3}});
+    auto p1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::fp8e4m3fnuz_type, {2, 3}});
+
+    mm->add_instruction(migraphx::make_op("div"), p0, p1);
+
+    auto prog = optimize_onnx("div_fp8_test.onnx");
+
+    EXPECT(p == prog);
+}