changes to make bert model work

src/include/migraphx/op/dot.hpp

@@ -48,6 +48,7 @@ struct dot
                            "} x {" + to_string_range(b.lens()) + "}");
         }
 
+        // dims for batch should be standard
         std::size_t dim_0 = a.lens().size() - 2;
         std::size_t dim_1 = a.lens().size() - 1;
         if(a.lens()[dim_1] != b.lens()[dim_0])

src/onnx/onnx.cpp

@@ -691,14 +691,6 @@ struct onnx_parser
             }
         }
 
-        if(!bl1->get_shape().standard())
-        {
-            bl1 = prog.add_instruction(op::contiguous{}, bl1);
-        }
-        if(!bl0->get_shape().standard())
-        {
-            bl0 = prog.add_instruction(op::contiguous{}, bl0);
-        }
         auto dot_res     = prog.add_instruction(op::dot{1.0f, 0.0f}, bl0, bl1);
         int64_t num_axis = static_cast<int64_t>(dot_res->get_shape().lens().size());
         if(is_a_prepended)

src/targets/gpu/gemm.cpp

@@ -170,7 +170,34 @@ rocblas_half to_rocblas_type(half x) { return reinterpret_cast<const rocblas_hal
 shape miopen_gemm::compute_shape(const std::vector<shape>& inputs) const
 {
     std::vector<shape> input_shapes(inputs.begin(), inputs.begin() + inputs.size() - 1);
-    check_shapes{input_shapes}.standard();
+    check_shapes{input_shapes}.not_broadcasted();
+    auto a_strides = inputs[0].strides();
+    auto dim_0 = a_strides.size() - 2;
+    if (a_strides.size() > 2)
+    {
+        if (!std::all_of(a_strides.begin(), a_strides.begin() + dim_0, [&](auto batch_size) {
+            return std::all_of(a_strides.begin() + dim_0, a_strides.end(), [&](auto data_size) {
+                return batch_size >= data_size;
+            });
+        }))
+        {
+            MIGRAPHX_THROW("DOT: batch size of a {" + to_string_range(a_strides) + "} is transposed!");
+        }
+    }
+
+    auto b_strides = inputs[1].strides();
+    if (b_strides.size() > 2)
+    {
+        if (!std::all_of(b_strides.begin(), b_strides.begin() + dim_0, [&](auto batch_size) {
+            return std::all_of(b_strides.begin() + dim_0, b_strides.end(), [&](auto data_size) {
+                return batch_size >= data_size;
+            });
+        }))
+        {
+            MIGRAPHX_THROW("DOT: batch size of b {" + to_string_range(b_strides) + "} is transposed!");
+        }
+    }
+    
     return op.compute_shape(input_shapes);
 }