Merge branch 'develop' into cast_op

src/tf/tf.cpp

@@ -164,6 +164,7 @@ struct tf_parser
         add_binary_op("Sub", op::sub{});
 
         add_mem_op("AvgPool", &tf_parser::parse_pooling);
+        add_mem_op("BatchMatMul", &tf_parser::parse_matmul, false);
         add_mem_op("BiasAdd", &tf_parser::parse_biasadd);
         add_mem_op("Cast", &tf_parser::parse_cast, false);
         add_mem_op("ConcatV2", &tf_parser::parse_concat, false);
@@ -538,6 +539,15 @@ struct tf_parser
             transb = attributes.at("transpose_a").b();
         }
 
+        if(contains(attributes, "adj_x"))
+        {
+            transa = attributes.at("adj_x").b();
+        }
+        if(contains(attributes, "adj_y"))
+        {
+            transb = attributes.at("adj_y").b();
+        }
+
         std::vector<int64_t> perm(args[0]->get_shape().lens().size());
         std::iota(perm.begin(), perm.end(), int64_t{0});
         // swap the last two elements

test/tf/batchmatmul_test.pb

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

+:
+
1Placeholder*
+dtype0
*
+shape:

+D
+batchmatmul1BatchMatMul
0
1*
+adj_x(
*
+adj_y(
*
+
T0
"
\ No newline at end of file

test/tf/tf_test.cpp

@@ -48,6 +48,21 @@ TEST_CASE(add_bcast_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(batchmatmul_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 2, 8, 4}});
+    auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {1, 2, 4, 8}});
+
+    auto trans_l0 = p.add_instruction(migraphx::op::transpose{{0, 1, 3, 2}}, l0);
+    auto trans_l1 = p.add_instruction(migraphx::op::transpose{{0, 1, 3, 2}}, l1);
+
+    p.add_instruction(migraphx::op::dot{}, trans_l0, trans_l1);
+    auto prog = optimize_tf("batchmatmul_test.pb", false);
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(batchnorm_test)
 {
     float epsilon  = 1.001e-5f;