fixed tests or pad_rewrite

src/include/migraphx/eliminate_identity.hpp

@@ -11,7 +11,9 @@ inline namespace MIGRAPHX_INLINE_NS {
 struct program;
 
 /**
- * Remove identity instructions.
+ * Remove identity instructions. Currently when used as the last pass, it will
+ * preserve the semantics of previous program state, therefore dead code elimination
+ * should not be used afterwards.
  */
 struct eliminate_identity
 {

src/include/migraphx/pad_rewrite.hpp

@@ -13,14 +13,16 @@ inline namespace MIGRAPHX_INLINE_NS {
 struct program;
 
 /**
- * Rewrite pads to use attribute from other instructions instead.
+ * Remove identity instructions. Currently when used as the last pass, it will
+ * preserve the semantics of previous program state, therefore dead code elimination
+ * should not be used afterwards.
  */
 struct pad_rewrite
 {
     std::string name() const { return "pad_rewrite"; }
     void apply(program& p) const;
     template <class T>
-    void update_op(T, instruction_ref ins, instruction_ref output, program& p) const;
+    void update_op(T, const instruction_ref& input, const instruction_ref& ins, program& p) const;
 };
 
 } // namespace MIGRAPHX_INLINE_NS

src/pad_rewrite.cpp

@@ -12,39 +12,38 @@ void pad_rewrite::apply(program& p) const
 {
     for(auto ins : iterator_for(p))
     {
-        if(ins->name() != "pad")
+        const std::string& op_name = ins->name();
+        if(op_name != "convolution" and op_name != "im2col" and op_name != "pooling")
             continue;
-        for(auto output : ins->outputs())
-        {
-            auto op_name = output->name();
-            if(op_name == "convolution")
-                update_op(op::convolution{}, ins, output, p);
-            else if(op_name == "im2col")
-                update_op(op::im2col{}, ins, output, p);
-            else if(op_name == "pooling")
-                update_op(op::pooling{}, ins, output, p);
-        }
+        auto input = ins->inputs().front();
+        if(input->name() != "pad")
+            continue;
+        if(op_name == "convolution")
+            update_op(op::convolution{}, input, ins, p);
+        else if(op_name == "im2col")
+            update_op(op::im2col{}, input, ins, p);
+        else if(op_name == "pooling")
+            update_op(op::pooling{}, input, ins, p);
     }
 }
 
 template <class T>
-void pad_rewrite::update_op(T, instruction_ref ins, instruction_ref output, program& p) const
+void pad_rewrite::update_op(T, const instruction_ref& input, const instruction_ref& ins, program& p) const
 {
-    auto pad_op = any_cast<op::pad>(ins->get_operator());
+    auto pad_op = any_cast<op::pad>(input->get_operator());
     if(!pad_op.symmetric())
         return;
 
     std::vector<int64_t> pads = pad_op.pads;
-    assert(pads.size() == 8); // ensure input being padded has 4 dims (*2 for font and back padding)
     std::array<size_t, 2> new_pads{static_cast<size_t>(pads[2]), static_cast<size_t>(pads[3])};
 
-    T op       = any_cast<T>(output->get_operator());
+    T op       = any_cast<T>(ins->get_operator());
     op.padding = new_pads;
 
-    std::vector<instruction_ref> new_inputs{output->inputs()};
-    new_inputs.front() = ins->inputs().front();
+    std::vector<instruction_ref> new_inputs{ins->inputs()};
+    new_inputs.front() = input->inputs().front();
 
-    p.replace_instruction(output, op, new_inputs);
+    p.replace_instruction(ins, op, new_inputs);
 }
 
 } // namespace MIGRAPHX_INLINE_NS

test/eliminate_identity_test.cpp

@@ -59,7 +59,7 @@ TEST_CASE(simple_test_end_dependency)
     p.add_instruction(sum_op{}, ans, three);
     p.add_instruction(migraphx::op::identity{}, ans);
     p.compile(eliminate_identity_target{});
-    EXPECT(!std::none_of(p.begin(), p.end(), [](const migraphx::instruction& ins) {
+    EXPECT(std::any_of(p.begin(), p.end(), [](const migraphx::instruction& ins) {
         return ins.name() == "identity";
     }));
     auto result = p.eval({});

test/pad_rewrite_test.cpp

+#include <migraphx/dead_code_elimination.hpp>
+#include <migraphx/pad_rewrite.hpp>
+#include <migraphx/instruction.hpp>
+#include <basic_ops.hpp>
+#include <migraphx/operators.hpp>
+#include <test.hpp>
+
+struct pad_rewrite_target
+{
+    std::string name() const { return "pad_rewrite"; }
+    std::vector<migraphx::pass> get_passes(migraphx::context&) const
+    {
+        return {migraphx::pad_rewrite{}, migraphx::dead_code_elimination{}};
+    }
+    migraphx::context get_context() const { return {}; }
+};
+
+migraphx::instruction_ref create_im2col(migraphx::instruction_ref& l_img, size_t channels, migraphx::program& p)
+{
+    size_t f[2]    = {1, 1};
+    std::vector<int32_t> weights(channels * f[0] * f[1]);
+
+    migraphx::shape s_weights{migraphx::shape::int32_type, {1, channels, f[0], f[1]}};
+    auto l_weights = p.add_literal(migraphx::literal{s_weights, weights});
+    return p.add_instruction(migraphx::op::im2col{}, l_img, l_weights);
+}
+
+migraphx::instruction_ref create_conv(migraphx::instruction_ref& l_img, size_t channels, migraphx::program& p)
+{
+    migraphx::shape s_weights{migraphx::shape::int32_type, {4, channels, 3, 3}};
+    std::vector<int32_t> weights(4 * channels * 3 * 3);
+
+    auto l_weights = p.add_literal(migraphx::literal{s_weights, weights});
+    return p.add_instruction(migraphx::op::convolution{}, l_img, l_weights);
+}
+
+TEST_CASE(rewrite_test)
+{
+    migraphx::program p;
+
+    size_t img_dim[2] = {2, 2};
+    size_t channels = 1;
+    std::vector<int32_t> input(channels * img_dim[0] * img_dim[1]);
+    std::iota(input.begin(), input.end(), 0);
+
+    migraphx::shape s_img{migraphx::shape::int32_type, {1, channels, img_dim[0], img_dim[1]}};
+    auto l_img   = p.add_literal(migraphx::literal{s_img, input});
+    auto padded_img = p.add_instruction(migraphx::op::pad{{0,0,1,1,0,0,1,1}}, l_img);
+
+    auto l0 = create_im2col(padded_img, channels, p);
+    auto l1 = create_conv(padded_img, channels, p);
+    auto l2 = p.add_instruction(migraphx::op::pooling{}, padded_img);
+    p.add_instruction(migraphx::op::identity{}, l0, l1, l2);
+
+    p.compile(pad_rewrite_target{});
+    EXPECT(std::none_of(p.begin(), p.end(), [](const migraphx::instruction& ins) {
+        return ins.name() == "pad";
+    }));
+}
+
+TEST_CASE(rewrite_test_asymmetric)
+{
+    migraphx::program p;
+    size_t img_dim[2] = {2, 2};
+    size_t channels = 1;
+    std::vector<int32_t> input(channels * img_dim[0] * img_dim[1]);
+    std::iota(input.begin(), input.end(), 0);
+
+    migraphx::shape s_img{migraphx::shape::int32_type, {1, channels, img_dim[0], img_dim[1]}};
+    auto l_img   = p.add_literal(migraphx::literal{s_img, input});
+    auto padded_img = p.add_instruction(migraphx::op::pad{{0,0,0,0,0,0,2,2}}, l_img);
+
+    create_im2col(padded_img, channels, p);
+
+    p.compile(pad_rewrite_target{});
+    EXPECT(std::any_of(p.begin(), p.end(), [](const migraphx::instruction& ins) {
+        return ins.name() == "pad";
+    }));
+}
+
+int main(int argc, const char* argv[]) { test::run(argc, argv); }