Merge branch 'master' into remove_concat

test/cpu_ops_test.cpp

@@ -556,7 +556,7 @@ void relu_test()
     migraph::program p;
     migraph::shape s{migraph::shape::float_type, {3}};
     auto l = p.add_literal(migraph::literal{s, {-1.f, 0.f, 1.f}});
-    p.add_instruction(migraph::op::activation{"relu"}, l);
+    p.add_instruction(migraph::op::relu{}, l);
     p.compile(migraph::cpu::target{});
     auto result = p.eval({});
     std::vector<float> results_vector(3);

test/gpu/miopen.cpp

@@ -158,7 +158,7 @@ struct test_literals
         auto weights = p.add_literal(
             generate_literal(migraph::shape{migraph::shape::float_type, {4, 3, 3, 3}}));
         auto conv = p.add_instruction(migraph::op::convolution{}, input, weights);
-        p.add_instruction(migraph::op::activation{"relu"}, conv);
+        p.add_instruction(migraph::op::relu{}, conv);
         return p;
     }
 };
@@ -392,7 +392,7 @@ struct test_conv_relu
         auto weights =
             p.add_parameter("w", migraph::shape{migraph::shape::float_type, {4, 3, 3, 3}});
         auto conv = p.add_instruction(migraph::op::convolution{}, input, weights);
-        p.add_instruction(migraph::op::activation{"relu"}, conv);
+        p.add_instruction(migraph::op::relu{}, conv);
         return p;
     }
 };
@@ -406,7 +406,7 @@ struct test_conv_relu_half
         auto weights =
             p.add_parameter("w", migraph::shape{migraph::shape::half_type, {4, 3, 3, 3}});
         auto conv = p.add_instruction(migraph::op::convolution{}, input, weights);
-        p.add_instruction(migraph::op::activation{"relu"}, conv);
+        p.add_instruction(migraph::op::relu{}, conv);
         return p;
     }
 };
@@ -419,7 +419,7 @@ struct test_add_relu
         auto x   = p.add_parameter("x", migraph::shape{migraph::shape::float_type, {4, 3, 3, 3}});
         auto y   = p.add_parameter("y", migraph::shape{migraph::shape::float_type, {4, 3, 3, 3}});
         auto add = p.add_instruction(migraph::op::add{}, x, y);
-        p.add_instruction(migraph::op::activation{"relu"}, add);
+        p.add_instruction(migraph::op::relu{}, add);
         return p;
     }
 };
@@ -446,7 +446,7 @@ struct test_conv_pooling
             p.add_parameter("w", migraph::shape{migraph::shape::float_type, {4, 3, 3, 3}});
         auto conv    = p.add_instruction(migraph::op::convolution{}, input, weights);
         auto pooling = p.add_instruction(migraph::op::pooling{"max"}, conv);
-        p.add_instruction(migraph::op::activation{"relu"}, pooling);
+        p.add_instruction(migraph::op::relu{}, pooling);
         return p;
     }
 };
@@ -657,7 +657,7 @@ struct test_conv_bn_relu_pooling
         auto variance = p.add_literal(migraph::abs(migraph::generate_literal(vars, 4)));
         auto bn       = p.add_instruction(
             migraph::op::batch_norm_inference{}, conv, scale, bias, mean, variance);
-        auto relu = p.add_instruction(migraph::op::activation{"relu"}, bn);
+        auto relu = p.add_instruction(migraph::op::relu{}, bn);
         p.add_instruction(migraph::op::pooling{"average", {1, 1}, {2, 2}, {3, 3}}, relu);
         return p;
     }
@@ -794,7 +794,7 @@ struct test_conv_bn_relu_pooling2
         auto conv2 = p.add_instruction(migraph::op::convolution{{0, 0}, {2, 2}, {1, 1}}, x2, w2);
         auto bn2   = add_bn(p, conv2, 2048);
         auto add   = p.add_instruction(migraph::op::add{}, bn1, bn2);
-        auto relu  = p.add_instruction(migraph::op::activation{"relu"}, add);
+        auto relu  = p.add_instruction(migraph::op::relu{}, add);
         p.add_instruction(migraph::op::pooling{"average", {1, 1}, {2, 2}, {3, 3}}, relu);
         return p;
     }

test/include/basic_ops.hpp

@@ -79,6 +79,7 @@ struct pass_op
             return {};
         return inputs.front();
     }
+    int output_alias(const std::vector<migraph::shape>&) const { return 0; }
 };
 
 struct pass_standard_op
@@ -103,6 +104,7 @@ struct pass_standard_op
             return {};
         return inputs.front();
     }
+    int output_alias(const std::vector<migraph::shape>&) const { return 0; }
 };
 
 struct nop

test/onnx/onnx_test.cpp

@@ -32,7 +32,7 @@ void pytorch_conv_relu_maxpool()
     auto l3       = p.add_instruction(migraph::op::convolution{}, l0, l1);
     auto l4       = p.add_instruction(migraph::op::broadcast{axis, l3->get_shape()}, l2);
     auto l5       = p.add_instruction(migraph::op::add{}, l3, l4);
-    auto l6       = p.add_instruction(migraph::op::activation{"relu"}, l5);
+    auto l6       = p.add_instruction(migraph::op::relu{}, l5);
     p.add_instruction(migraph::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l6);
 
     auto prog = migraph::parse_onnx("conv_relu_maxpool.onnx");
@@ -55,7 +55,7 @@ void pytorch_conv_bn_relu_maxpool()
     auto l4       = p.add_instruction(migraph::op::broadcast{axis, l3->get_shape()}, l2);
     auto l5       = p.add_instruction(migraph::op::add{}, l3, l4);
     auto l6 = p.add_instruction(migraph::op::batch_norm_inference{1.0e-5f}, l5, p3, p4, p5, p6);
-    auto l7 = p.add_instruction(migraph::op::activation{"relu"}, l6);
+    auto l7 = p.add_instruction(migraph::op::relu{}, l6);
     p.add_instruction(migraph::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l7);
 
     auto prog = migraph::parse_onnx("conv_bn_relu_maxpool.onnx");
@@ -72,7 +72,7 @@ void pytorch_conv_relu_maxpool_x2()
     auto l3       = p.add_instruction(migraph::op::convolution{}, l0, l1);
     auto l4       = p.add_instruction(migraph::op::broadcast{axis, l3->get_shape()}, l2);
     auto l5       = p.add_instruction(migraph::op::add{}, l3, l4);
-    auto l6       = p.add_instruction(migraph::op::activation{"relu"}, l5);
+    auto l6       = p.add_instruction(migraph::op::relu{}, l5);
     auto l7 = p.add_instruction(migraph::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l6);
 
     auto l8  = p.add_parameter("3", {migraph::shape::float_type, {1, 5, 5, 5}});
@@ -80,7 +80,7 @@ void pytorch_conv_relu_maxpool_x2()
     auto l10 = p.add_instruction(migraph::op::convolution{}, l7, l8);
     auto l11 = p.add_instruction(migraph::op::broadcast{axis, l10->get_shape()}, l9);
     auto l12 = p.add_instruction(migraph::op::add{}, l10, l11);
-    auto l13 = p.add_instruction(migraph::op::activation{"relu"}, l12);
+    auto l13 = p.add_instruction(migraph::op::relu{}, l12);
     p.add_instruction(migraph::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l13);
 
     auto prog = migraph::parse_onnx("conv_relu_maxpoolX2.onnx");

test/output_alias.cpp

+#include <migraph/program.hpp>
+#include <migraph/instruction.hpp>
+#include <test.hpp>
+#include <basic_ops.hpp>
+
+void simple_alias()
+{
+    migraph::program p;
+    auto l  = p.add_literal(1);
+    auto p1 = p.add_instruction(pass_op{}, l);
+    EXPECT(bool{migraph::instruction::get_output_alias(l) == l});
+    EXPECT(bool{migraph::instruction::get_output_alias(p1) == l});
+}
+
+void cascade_alias()
+{
+    migraph::program p;
+    auto l  = p.add_literal(1);
+    auto p1 = p.add_instruction(pass_op{}, l);
+    auto p2 = p.add_instruction(pass_op{}, p1);
+    auto p3 = p.add_instruction(pass_op{}, p2);
+    EXPECT(bool{migraph::instruction::get_output_alias(l) == l});
+    EXPECT(bool{migraph::instruction::get_output_alias(p1) == l});
+    EXPECT(bool{migraph::instruction::get_output_alias(p2) == l});
+    EXPECT(bool{migraph::instruction::get_output_alias(p3) == l});
+}
+
+void no_alias()
+{
+    migraph::program p;
+    auto x   = p.add_literal(1);
+    auto y   = p.add_literal(2);
+    auto sum = p.add_instruction(sum_op{}, x, y);
+    EXPECT(bool{migraph::instruction::get_output_alias(sum) == sum});
+}
+
+int main()
+{
+    simple_alias();
+    cascade_alias();
+    no_alias();
+}

tools/include/operation.hpp

@@ -43,6 +43,9 @@ struct operation
      * the same the `output` shape.
      */
     argument compute(context& ctx, const shape& output, const std::vector<argument>& input) const;
+    /// An optional method to return which argument the output will alias. If
+    /// there is no aliased output then -1 can be returned.
+    int output_alias(const std::vector<shape>& input) const;
     /// An optional stream operator to print the operation. When this is not
     /// implemented, it will just print the operation's name.
     friend std::ostream& operator<<(std::ostream& os, const operation& op);
@@ -108,10 +111,34 @@ compute_op(const T& x, context& ctx, const shape& output_shape, const std::vecto
     return compute_op(rank<1>{}, x, ctx, output_shape, input);
 }
 
+template <class T>
+int output_alias_op(rank<0>, const T&, const std::vector<shape>&)
+{
+    return -1;
+}
+
+template <class T>
+auto output_alias_op(rank<1>, const T& x, const std::vector<shape>& shapes)
+    -> decltype(x.output_alias(shapes))
+{
+    return x.output_alias(shapes);
+}
+
+template <class T>
+int output_alias_op(const T& x, const std::vector<shape>& shapes)
+{
+    return output_alias_op(rank<1>{}, x, shapes);
+}
+
 <%
  interface(
      'operation',
      virtual('name', returns = 'std::string', const = True),
+     virtual('output_alias',
+             returns = 'int',
+             input   = 'const std::vector<shape>&',
+             const   = True,
+             default = 'output_alias_op'),
      virtual('compute_shape', returns = 'shape', input = 'const std::vector<shape>&', const = True),
      virtual('compute',
              returns = 'argument',