Deleted memcpy for Paul. Added fix in Reshape for cases with -1 dimension.

src/include/migraph/operators.hpp

@@ -341,11 +341,25 @@ struct reshape
         check_shapes{inputs, *this}.has(1);
         auto&& idims = inputs.front().lens();
         std::vector<std::size_t> rdims(dims.begin(), dims.end());
+        auto n_neg_dims = std::count(dims.begin(), dims.end(), -1);
+        if(n_neg_dims > 1)
+            MIGRAPH_THROW("Dimensions for reshape can only have one -1 dim");
         for(std::size_t i = 0; i < dims.size(); i++)
         {
             if(dims[i] == 0)
                 rdims[i] = idims[i];
         }
+        if(n_neg_dims > 0)
+        {
+            size_t missing_dim =
+                -inputs.front().elements() /
+                std::accumulate(rdims.begin(), rdims.end(), 1, std::multiplies<int64_t>());
+            for(std::size_t i = 0; i < rdims.size(); i++)
+            {
+                if(dims[i] == -1)
+                    rdims[i] = missing_dim;
+            }
+        }
         if(dims.back() == -1)
         {
             rdims.pop_back();

src/onnx/onnx.cpp

@@ -320,10 +320,7 @@ struct onnx_parser
             std::string s = t.raw_data();
             if(t.data_type() == onnx::TensorProto::FLOAT)
             {
-                std::vector<float> raw(
-                    std::accumulate(dims.begin(), dims.end(), 1, std::multiplies<size_t>()));
-                memcpy(raw.data(), s.data(), s.length());
-                return literal{{shape::float_type, dims}, raw};
+                return literal{{shape::float_type, dims}, s.data()};
             }
             else if(t.data_type() == onnx::TensorProto::UINT8)
             {
@@ -331,38 +328,23 @@ struct onnx_parser
             }
             else if(t.data_type() == onnx::TensorProto::INT8)
             {
-                std::vector<int32_t> raw(
-                    std::accumulate(dims.begin(), dims.end(), 1, std::multiplies<size_t>()));
-                memcpy(raw.data(), s.data(), s.length());
-                return literal{{shape::int32_type, dims}, raw};
+                return literal{{shape::int32_type, dims}, s.data()};
             }
             else if(t.data_type() == onnx::TensorProto::UINT16)
             {
-                std::vector<int32_t> raw(
-                    std::accumulate(dims.begin(), dims.end(), 1, std::multiplies<size_t>()));
-                memcpy(raw.data(), s.data(), s.length());
-                return literal{{shape::int32_type, dims}, raw};
+                return literal{{shape::int32_type, dims}, s.data()};
             }
             else if(t.data_type() == onnx::TensorProto::INT16)
             {
-                std::vector<int32_t> raw(
-                    std::accumulate(dims.begin(), dims.end(), 1, std::multiplies<size_t>()));
-                memcpy(raw.data(), s.data(), s.length());
-                return literal{{shape::int32_type, dims}, raw};
+                return literal{{shape::int32_type, dims}, s.data()};
             }
             else if(t.data_type() == onnx::TensorProto::INT32)
             {
-                std::vector<int32_t> raw(
-                    std::accumulate(dims.begin(), dims.end(), 1, std::multiplies<size_t>()));
-                memcpy(raw.data(), s.data(), s.length());
-                return literal{{shape::int32_type, dims}, raw};
+                return literal{{shape::int32_type, dims}, s.data()};
             }
             else if(t.data_type() == onnx::TensorProto::INT64)
             {
-                std::vector<int64_t> raw(
-                    std::accumulate(dims.begin(), dims.end(), 1, std::multiplies<size_t>()));
-                memcpy(raw.data(), s.data(), s.length());
-                return literal{{shape::int64_type, dims}, raw};
+                return literal{{shape::int64_type, dims}, s.data()};
             }
             else if(t.data_type() == onnx::TensorProto::STRING)
             {
@@ -370,10 +352,7 @@ struct onnx_parser
             }
             else if(t.data_type() == onnx::TensorProto::BOOL)
             {
-                std::vector<int32_t> raw(
-                    std::accumulate(dims.begin(), dims.end(), 1, std::multiplies<size_t>()));
-                memcpy(raw.data(), s.data(), s.length());
-                return literal{{shape::int32_type, dims}, raw};
+                return literal{{shape::int32_type, dims}, s.data()};
             }
             else if(t.data_type() == onnx::TensorProto::FLOAT16)
             {
@@ -381,10 +360,7 @@ struct onnx_parser
             }
             else if(t.data_type() == onnx::TensorProto::DOUBLE)
             {
-                std::vector<double> raw(
-                    std::accumulate(dims.begin(), dims.end(), 1, std::multiplies<size_t>()));
-                memcpy(raw.data(), s.data(), s.length());
-                return literal{{shape::double_type, dims}, raw};
+                return literal{{shape::double_type, dims}, s.data()};
             }
             else if(t.data_type() == onnx::TensorProto::UINT32)
             {