Merge branch 'dyn_contiguous' of github.com:ROCmSoftwarePlatform/AMDMIGraphX into dyn_unsqueeze

test/ref_ops_test.cpp

@@ -918,11 +918,71 @@ TEST_CASE(contiguous_test)
     p.compile(migraphx::ref::target{});
     auto result = p.eval({}).back();
 
+    result.visit([&](auto output) {
+        std::vector<size_t> new_strides = {12, 4, 2, 1};
+        EXPECT(bool{output.get_shape().strides() == new_strides});
+    });
+
+    std::vector<float> results_vector(12);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+
+    std::vector<float> gold = {0, 3, 6, 9, 1, 4, 7, 10, 2, 5, 8, 11};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
+TEST_CASE(contiguous_param_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape a_shape{migraphx::shape::float_type, {1, 3, 2, 2}, {12, 1, 6, 3}};
+    auto a = mm->add_parameter("X", a_shape);
+    mm->add_instruction(migraphx::make_op("contiguous"), a);
+    p.compile(migraphx::ref::target{});
+
+    std::vector<float> data(12);
+    std::iota(data.begin(), data.end(), 0);
+    migraphx::parameter_map params;
+    params["X"] = migraphx::argument(a_shape, data.data());
+    auto result = p.eval(params).back();
+
+    result.visit([&](auto output) {
+        std::vector<size_t> new_strides = {12, 4, 2, 1};
+        EXPECT(bool{output.get_shape().strides() == new_strides});
+    });
+
+    std::vector<float> results_vector(12);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = {0, 3, 6, 9, 1, 4, 7, 10, 2, 5, 8, 11};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
+TEST_CASE(contiguous_dyn_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape dyn_shape{migraphx::shape::float_type,
+                              {{1, 1, 0}, {2, 6, 0}, {2, 2, 0}, {2, 2, 0}}};
+    auto input = mm->add_parameter("X", dyn_shape);
+    mm->add_instruction(migraphx::make_op("contiguous"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::shape static_shape{migraphx::shape::float_type, {1, 3, 2, 2}, {12, 1, 6, 3}};
+    std::vector<float> data(12);
+    std::iota(data.begin(), data.end(), 0);
+    migraphx::parameter_map params;
+    params["X"] = migraphx::argument(static_shape, data.data());
+    auto result = p.eval(params).back();
+
+    result.visit([&](auto output) {
+        std::vector<size_t> new_strides = {12, 4, 2, 1};
+        EXPECT(bool{output.get_shape().strides() == new_strides});
+    });
+
     std::vector<float> results_vector(12);
     result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
-    std::vector<size_t> new_lens    = {1, 3, 2, 2};
-    std::vector<size_t> new_strides = {12, 1, 6, 3};
-    EXPECT(migraphx::verify_range(results_vector, data));
+
+    std::vector<float> gold = {0, 3, 6, 9, 1, 4, 7, 10, 2, 5, 8, 11};
+    EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
 TEST_CASE(conv_dynamic_batch_test)

test/verify/test_concat_broadcast_add.cpp

+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2022 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 "verify_program.hpp"
+#include <migraphx/program.hpp>
+#include <migraphx/generate.hpp>
+#include <migraphx/make_op.hpp>
+
+struct test_concat_broadcast_add : verify_program<test_concat_broadcast_add>
+{
+    migraphx::program create_program() const
+    {
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        migraphx::shape s0{migraphx::shape::float_type, {1, 2, 4}};
+        migraphx::shape s1{migraphx::shape::float_type, {1, 6, 4}};
+        migraphx::shape s2{migraphx::shape::float_type, {6, 1}};
+        auto x      = mm->add_parameter("x", s0);
+        auto y      = mm->add_parameter("y", s0);
+        auto z      = mm->add_parameter("z", s0);
+        auto concat = mm->add_instruction(migraphx::make_op("concat", {{"axis", 1}}), x, y, z);
+        auto b      = mm->add_literal(migraphx::generate_literal(s2, 15));
+        auto bb =
+            mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", s1.lens()}}), b);
+        mm->add_instruction(migraphx::make_op("add"), concat, bb);
+        return p;
+    }
+};

test/verify/test_slice_concat_add.cpp

+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2022 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 "verify_program.hpp"
+#include <migraphx/program.hpp>
+#include <migraphx/generate.hpp>
+#include <migraphx/make_op.hpp>
+
+struct test_slice_concat_add : verify_program<test_slice_concat_add>
+{
+    migraphx::program create_program() const
+    {
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        migraphx::shape s0{migraphx::shape::float_type, {1, 24, 2, 2}};
+        migraphx::shape s1{migraphx::shape::float_type, {1, 8, 2, 2}};
+        auto x     = mm->add_parameter("x", s0);
+        auto y     = mm->add_parameter("y", s1);
+        auto z     = mm->add_parameter("z", s0);
+        auto slice = mm->add_instruction(
+            migraphx::make_op("slice", {{"axes", {1}}, {"starts", {0}}, {"ends", {8}}}), x);
+        auto concat = mm->add_instruction(migraphx::make_op("concat", {{"axis", 1}}), slice, y, y);
+        mm->add_instruction(migraphx::make_op("add"), concat, z);
+        return p;
+    }
+};

tools/convert_onnx_version.py

+#####################################################################################
+# The MIT License (MIT)
+#
+# Copyright (c) 2015-2022 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.
+#####################################################################################
+import argparse
+import onnx
+from onnx import version_converter
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(
+        description=
+        'MIGraphX Onnx Model Convertion. Use to convert the opset of the input model to MIGraphX\'s'
+    )
+    req_args = parser.add_argument_group(title='required arguments')
+    req_args.add_argument('--model',
+                          type=str,
+                          required=True,
+                          help='path to onnx file')
+    req_args.add_argument('--output',
+                          type=str,
+                          required=True,
+                          help='path to output onnx file')
+    req_args.add_argument('--opset',
+                          type=int,
+                          required=True,
+                          help='The output opset')
+    req_args.add_argument('--infer_shapes',
+                          action='store_true',
+                          help='Infer shapes for output model')
+    parser.add_argument('--verbose',
+                        action='store_true',
+                        help='show verbose information (for debugging)')
+    args = parser.parse_args()
+
+    return args
+
+
+def main():
+    args = parse_args()
+
+    model_path = args.model
+    out_model_path = args.output
+    target_opset = args.opset
+    verbose = args.verbose
+    infer_shapes = args.infer_shapes
+
+    original_model = onnx.load(model_path)
+    if verbose:
+        print(f"The model before conversion:\n{original_model}")
+
+    # A full list of supported adapters can be found here:
+    # https://github.com/onnx/onnx/blob/main/onnx/version_converter.py#L21
+    # Apply the version conversion on the original model
+    converted_model = version_converter.convert_version(
+        original_model, target_opset)
+
+    if infer_shapes:
+        converted_model = onnx.shape_inference.infer_shapes(converted_model)
+
+    if verbose:
+        print(f"The model after conversion:\n{converted_model}")
+
+    # Save the ONNX model
+    onnx.save(converted_model, out_model_path)
+
+
+if __name__ == '__main__':
+    main()