fix shape constructor and data types

src/include/migraphx/op/squeeze.hpp

@@ -58,7 +58,7 @@ struct squeeze
 
         if(new_lens.empty())
         {
-            return shape{type, {1}, {0}};
+            return shape{type};
         }
         else
         {

src/onnx/onnx.cpp

@@ -1432,7 +1432,7 @@ struct onnx_parser
     {
         // in case of scalar constants in onnx file, use dims=1 to fill initializer data
         if(dims.empty())
-            return literal{{shape_type, {1}, {0}}, data};
+            return literal{{shape_type}, data};
         return literal{{shape_type, dims}, data};
     }
 
@@ -1440,7 +1440,7 @@ struct onnx_parser
     static literal create_literal(shape::type_t shape_type, const std::vector<size_t>& dims, T data)
     {
         if(dims.empty())
-            return literal{{shape_type, {1}, {0}}, data.begin(), data.end()};
+            return literal{{shape_type}, data.begin(), data.end()};
         return literal{{shape_type, dims}, data.begin(), data.end()};
     }
 

src/tf/tf.cpp

@@ -751,17 +751,17 @@ struct tf_parser
             case tensorflow::DataType::DT_FLOAT:
                 return literal{{shape::float_type, dims}, s.data()};
             case tensorflow::DataType::DT_UINT8: throw std::runtime_error("");
-            case tensorflow::DataType::DT_INT8: return literal{{shape::int32_type, dims}, s.data()};
+            case tensorflow::DataType::DT_INT8: return literal{{shape::int8_type, dims}, s.data()};
             case tensorflow::DataType::DT_UINT16:
-                return literal{{shape::int32_type, dims}, s.data()};
+                return literal{{shape::uint16_type, dims}, s.data()};
             case tensorflow::DataType::DT_INT16:
-                return literal{{shape::int32_type, dims}, s.data()};
+                return literal{{shape::int16_type, dims}, s.data()};
             case tensorflow::DataType::DT_INT32:
                 return literal{{shape::int32_type, dims}, s.data()};
             case tensorflow::DataType::DT_INT64:
                 return literal{{shape::int64_type, dims}, s.data()};
             case tensorflow::DataType::DT_STRING: throw std::runtime_error("");
-            case tensorflow::DataType::DT_BOOL: return literal{{shape::int32_type, dims}, s.data()};
+            case tensorflow::DataType::DT_BOOL: return literal{{shape::int8_type, dims}, s.data()};
             case tensorflow::DataType::DT_HALF: return literal{{shape::half_type, dims}, s.data()};
             case tensorflow::DataType::DT_DOUBLE:
                 return literal{{shape::double_type, dims}, s.data()};
@@ -815,11 +815,11 @@ struct tf_parser
                 shape::float_type, dims, get_data_vals(t.float_val(), shape_size));
         case tensorflow::DataType::DT_UINT8: throw std::runtime_error("");
         case tensorflow::DataType::DT_INT8:
-            return create_literal(shape::int32_type, dims, get_data_vals(t.int_val(), shape_size));
+            return create_literal(shape::int8_type, dims, get_data_vals(t.int_val(), shape_size));
         case tensorflow::DataType::DT_UINT16:
-            return create_literal(shape::int32_type, dims, get_data_vals(t.int_val(), shape_size));
+            return create_literal(shape::uint16_type, dims, get_data_vals(t.int_val(), shape_size));
         case tensorflow::DataType::DT_INT16:
-            return create_literal(shape::int32_type, dims, get_data_vals(t.int_val(), shape_size));
+            return create_literal(shape::int16_type, dims, get_data_vals(t.int_val(), shape_size));
         case tensorflow::DataType::DT_INT32:
             return create_literal(shape::int32_type, dims, get_data_vals(t.int_val(), shape_size));
         case tensorflow::DataType::DT_INT64:
@@ -916,7 +916,7 @@ struct tf_parser
     {
         // assume if explicit value is mentioned in protobuf and dim size <= 1, treat as scalar
         if(dims.empty() or (dims.size() == 1 and dims.front() == 1))
-            return literal{{shape_type, {1}, {0}}, data};
+            return literal{{shape_type}, data};
         return literal{{shape_type, dims}, data};
     }
 };

test/tf/tf_test.cpp

@@ -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}, {0}}, 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}, {0}}, 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);