Merge branch 'develop' of https://github.com/ROCmSoftwarePlatform/AMDMIGraphX...

Merge branch 'develop' of https://github.com/ROCmSoftwarePlatform/AMDMIGraphX into conv_same_padding

test/tf/relu6_test.pb

+
+:
+
0Placeholder*
+dtype0
*
+shape:

+
+relu6Relu6
0*
+
T0
"
\ No newline at end of file

test/tf/tf_test.cpp

@@ -63,7 +63,7 @@ TEST_CASE(biasadd_test)
     uint64_t axis = 1;
     auto l0       = p.add_parameter("0", s0);
     auto l1       = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {500}});
-    auto l2       = p.add_instruction(migraphx::op::broadcast{axis, l0->get_shape()}, l1);
+    auto l2       = p.add_instruction(migraphx::op::broadcast{axis, l0->get_shape().lens()}, l1);
     p.add_instruction(migraphx::op::add{}, l0, l2);
     auto prog = migraphx::parse_tf("biasadd_test.pb", true);
 
@@ -80,7 +80,7 @@ TEST_CASE(concat_test)
     int axis = 1;
     // tf uses axis as the third input, and it is in int32 format
     // add the literal using a vector in order to set stride to 1 (like in tf parser)
-    p.add_literal(migraphx::shape{migraphx::shape::int32_type, {1}}, std::vector<int>{axis});
+    p.add_literal(migraphx::shape{migraphx::shape::int32_type}, std::vector<int>{axis});
 
     p.add_instruction(migraphx::op::concat{static_cast<std::size_t>(axis)}, l0, l1);
     auto prog = migraphx::parse_tf("concat_test.pb", false);
@@ -91,7 +91,7 @@ TEST_CASE(concat_test)
 TEST_CASE(const_test)
 {
     migraphx::program p;
-    p.add_literal(migraphx::shape{migraphx::shape::float_type, {1}}, std::vector<float>{1.0f});
+    p.add_literal(migraphx::shape{migraphx::shape::float_type}, std::vector<float>{1.0f});
     auto prog = migraphx::parse_tf("constant_test.pb", false);
 
     EXPECT(p == prog);
@@ -119,6 +119,30 @@ TEST_CASE(conv_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(depthwiseconv_test)
+{
+    migraphx::program p;
+
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 16, 16}});
+    std::vector<float> weight_data(3 * 3 * 3 * 1);
+    std::fill(weight_data.begin(), weight_data.end(), 1.0f);
+    auto l1 =
+        p.add_literal(migraphx::shape{migraphx::shape::float_type, {3, 3, 3, 1}}, weight_data);
+
+    migraphx::op::convolution op;
+    op.padding_mode = migraphx::op::padding_mode_t::same;
+    op.stride       = {1, 1};
+    op.dilation     = {1, 1};
+    op.group        = 3;
+    auto l2         = p.add_instruction(migraphx::op::transpose{{0, 3, 1, 2}}, l1);
+    auto l3         = p.add_instruction(migraphx::op::transpose{{1, 3, 0, 2}}, l2);
+    auto l4         = p.add_instruction(migraphx::op::reshape{{3, 1, 3, 3}}, l3);
+    p.add_instruction(op, l0, l4);
+    auto prog = migraphx::parse_tf("depthwise_conv_test.pb", true);
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(identity_test)
 {
     migraphx::program p;
@@ -129,6 +153,77 @@ TEST_CASE(identity_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(matmul_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {8, 4}});
+    auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {4, 8}});
+
+    auto trans_l0 = p.add_instruction(migraphx::op::transpose{{1, 0}}, l0);
+    auto trans_l1 = p.add_instruction(migraphx::op::transpose{{1, 0}}, l1);
+
+    p.add_instruction(migraphx::op::dot{}, trans_l0, trans_l1);
+    auto prog = migraphx::parse_tf("matmul_test.pb", false);
+
+    EXPECT(p == prog);
+}
+
+TEST_CASE(mul_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 1, 1, 16}});
+    auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {1, 1, 1, 16}});
+
+    p.add_instruction(migraphx::op::mul{}, l0, l1);
+    auto prog = migraphx::parse_tf("mul_test.pb", false);
+
+    EXPECT(p == prog);
+}
+
+TEST_CASE(pack_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2}});
+    auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {2}});
+    auto l2 = p.add_parameter("2", migraphx::shape{migraphx::shape::float_type, {2}});
+    std::vector<migraphx::instruction_ref> args{l0, l1, l2};
+    std::vector<migraphx::instruction_ref> unsqueezed_args;
+    int64_t axis = 1;
+
+    std::transform(args.begin(),
+                   args.end(),
+                   std::back_inserter(unsqueezed_args),
+                   [&](migraphx::instruction_ref arg) {
+                       return p.add_instruction(migraphx::op::unsqueeze{{axis}}, arg);
+                   });
+    p.add_instruction(migraphx::op::concat{static_cast<size_t>(axis)}, unsqueezed_args);
+    auto prog = migraphx::parse_tf("pack_test.pb", false);
+
+    EXPECT(p == prog);
+}
+
+TEST_CASE(pack_test_nhwc)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 2, 1, 1}});
+    auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {1, 2, 1, 1}});
+    auto l2 = p.add_parameter("2", migraphx::shape{migraphx::shape::float_type, {1, 2, 1, 1}});
+    std::vector<migraphx::instruction_ref> args{l0, l1, l2};
+    std::vector<migraphx::instruction_ref> unsqueezed_args;
+    int64_t nchw_axis = 1;
+
+    std::transform(args.begin(),
+                   args.end(),
+                   std::back_inserter(unsqueezed_args),
+                   [&](migraphx::instruction_ref arg) {
+                       return p.add_instruction(migraphx::op::unsqueeze{{nchw_axis}}, arg);
+                   });
+    p.add_instruction(migraphx::op::concat{static_cast<size_t>(nchw_axis)}, unsqueezed_args);
+    auto prog = migraphx::parse_tf("pack_test_nhwc.pb", true);
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(pooling_test)
 {
     migraphx::program p;
@@ -158,6 +253,16 @@ TEST_CASE(relu_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(relu6_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 16, 16}});
+    p.add_instruction(migraphx::op::clip{6.0, 0.0}, l0);
+    auto prog = migraphx::parse_tf("relu6_test.pb", false);
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(reshape_test)
 {
     migraphx::program p;
@@ -193,4 +298,28 @@ TEST_CASE(squeeze_test)
 
     EXPECT(p == prog);
 }
+
+TEST_CASE(stridedslice_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 10, 1, 1}});
+    std::size_t num_axes = 4;
+    migraphx::op::slice op;
+    op.starts = {0, 0, 0, 0};
+    op.ends   = {1, 5, 1, 1};
+    op.axes   = std::vector<int64_t>(num_axes);
+    std::iota(op.axes.begin(), op.axes.end(), 0);
+    // add literals for starts, ends, and strides in tf (NHWC format)
+    p.add_literal(migraphx::shape{migraphx::shape::int32_type, {4}}, std::vector<int>{0, 0, 0, 0});
+    p.add_literal(migraphx::shape{migraphx::shape::int32_type, {4}}, std::vector<int>{1, 1, 1, 5});
+    p.add_literal(migraphx::shape{migraphx::shape::int32_type, {4}}, std::vector<int>{1, 1, 1, 1});
+
+    auto l1          = p.add_instruction(op, l0);
+    auto shrink_axis = 2;
+    p.add_instruction(migraphx::op::squeeze{{shrink_axis}}, l1);
+    auto prog = migraphx::parse_tf("stridedslice_test.pb", true);
+
+    EXPECT(p == prog);
+}
+
 int main(int argc, const char* argv[]) { test::run(argc, argv); }

tools/include/concat_opt.hpp

@@ -9,7 +9,7 @@
 #include <utility>
 
 #include <migraphx/operation.hpp>
-#include <migraphx/operators.hpp>
+#include <migraphx/op/concat.hpp>
 #include <migraphx/config.hpp>
 
 namespace migraphx {

tools/include/operation.hpp

@@ -49,7 +49,7 @@ struct operation
     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;
+    std::ptrdiff_t 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);
@@ -69,7 +69,7 @@ auto operator<<(std::ostream& os, const T& x) -> decltype(os << x.name())
 {
     os << x.name();
     char delim = '[';
-    reflect_each(x, [&](auto& y, auto name) {
+    reflect_each(x, [&](auto&& y, auto name) {
         os << delim;
         os << name << "=";
         stream_write_value(os, y);
@@ -87,6 +87,8 @@ namespace operation_equal {
 template <class T, class U>
 auto operator==(const T& x, const U& y) -> decltype(x.name() == y.name())
 {
+    static_assert(is_reflectable<T>{} or sizeof(T) <= 1,
+                  "Missing equality operator or reflect method.");
     if(x.name() != y.name())
         return false;
     const auto& yy = any_cast<T>(y);
@@ -175,7 +177,7 @@ auto is_context_free_op(const T& x) -> decltype(is_context_free_op(
 }
 
 template <class T>
-int output_alias_op(rank<0>, const T&, const std::vector<shape>&)
+std::ptrdiff_t output_alias_op(rank<0>, const T&, const std::vector<shape>&)
 {
     return -1;
 }
@@ -188,7 +190,7 @@ auto output_alias_op(rank<1>, const T& x, const std::vector<shape>& shapes)
 }
 
 template <class T>
-int output_alias_op(const T& x, const std::vector<shape>& shapes)
+std::ptrdiff_t output_alias_op(const T& x, const std::vector<shape>& shapes)
 {
     return output_alias_op(rank<1>{}, x, shapes);
 }
@@ -238,7 +240,7 @@ auto has_finalize_op(const T&) -> decltype(has_finalize_op(rank<1>{},
      virtual('is_context_free', returns = 'bool', const = True, default = 'is_context_free_op'),
      virtual('has_finalize', returns = 'bool', const = True, default = 'has_finalize_op'),
      virtual('output_alias',
-             returns = 'int',
+             returns = 'std::ptrdiff_t',
              input   = 'const std::vector<shape>&',
              const   = True,
              default = 'output_alias_op'),