#0: Minor refactor of pytensor and tensor implementation files (#16108)

### Checklist
- [X] Local build and sanity check ttnn unit tests.
- [X] [T3K unit
tests](https://github.com/tenstorrent/tt-metal/actions/runs/12384480452/job/34570062697).

ttnn/cpp/pybind11/pytensor.cpp

@@ -9,7 +9,7 @@
 #include <chrono>
 #include <memory>
 
-#include "tensor.hpp"
+#include "ttnn/tensor/tensor.hpp"
 #include "tt_metal/graph/graph_tracking.hpp"
 #include "tt_metal/host_api.hpp"
 #include "tt_metal/tt_stl/overloaded.hpp"
@@ -150,15 +150,12 @@ Tensor create_tt_tensor_from_py_data(
     std::size_t py_data_ptr,
     const TensorSpec& tensor_spec,
     Device* device,
-    bool override_enable_borrow,
+    bool force_disable_borrow,
     const std::function<void()>& on_creation_callback,
     const std::function<void()>& on_destruction_callback) {
     auto layout = tensor_spec.layout();
 
-    bool enable_borrow = true;
-    if (layout != Layout::ROW_MAJOR or override_enable_borrow) {
-        enable_borrow = false;
-    }
+    const bool enable_borrow = layout == Layout::ROW_MAJOR and not force_disable_borrow;
 
     auto data_type = tensor_spec.data_type();
     std::size_t num_elements = tensor_spec.logical_shape().volume();
@@ -256,7 +253,7 @@ Tensor convert_python_tensor_to_tt_tensor(
     const std::optional<Tile>& optional_tile,
     const MemoryConfig& memory_config,
     Device* device,
-    bool override_enable_borrow = false) {
+    bool force_disable_borrow = false) {
     GraphTracker::instance().track_function_start(
         "tt::tt_metal::detail::convert_python_tensor_to_tt_tensor",
         py_tensor,
@@ -265,7 +262,7 @@ Tensor convert_python_tensor_to_tt_tensor(
         optional_tile,
         memory_config,
         device,
-        override_enable_borrow);
+        force_disable_borrow);
     py::object torch = py::module_::import("torch");
     py::object np = py::module_::import("numpy");
 
@@ -342,7 +339,7 @@ Tensor convert_python_tensor_to_tt_tensor(
         num_elements = py::cast<std::size_t>(contiguous_py_tensor.attr("numel")());
         py_data_ptr = py::cast<std::size_t>(contiguous_py_tensor.attr("data_ptr")());
     } else if (py::isinstance(py_tensor, np.attr("ndarray"))) {
-        TT_FATAL(!override_enable_borrow, "Disabling borrowed buffers for numpy tensors is untested!");
+        TT_FATAL(!force_disable_borrow, "Disabling borrowed buffers for numpy tensors is untested!");
 
         contiguous_py_tensor = np.attr("ascontiguousarray")(py_tensor);
 
@@ -429,7 +426,7 @@ Tensor convert_python_tensor_to_tt_tensor(
     auto on_creation_callback = [tensor = contiguous_py_tensor] { tensor.inc_ref(); };
     auto on_destruction_callback = [tensor = contiguous_py_tensor] { tensor.dec_ref(); };
     auto output = create_tt_tensor_from_py_data(
-        py_data_ptr, tensor_spec, device, override_enable_borrow, on_creation_callback, on_destruction_callback);
+        py_data_ptr, tensor_spec, device, force_disable_borrow, on_creation_callback, on_destruction_callback);
 
     if (device) {
         output = output.to(device, memory_config);

ttnn/cpp/ttnn/tensor/tensor.cpp

@@ -8,10 +8,10 @@
 #include <memory>
 #include <utility>
 
-#include "common/bfloat16.hpp"
+#include "tt_metal/common/bfloat16.hpp"
 #include "impl/buffers/buffer_constants.hpp"
 #include "tt_metal/tt_stl/overloaded.hpp"
-#include "tensor_ops.hpp"
+#include "ttnn/tensor/tensor_ops.hpp"
 #include "ttnn/tensor/tensor_impl.hpp"
 #include "ttnn/tensor/tensor_impl_wrapper.hpp"
 #include "ttnn/tensor/tensor_utils.hpp"
@@ -28,26 +28,9 @@
 #include "ttnn/tensor/layout/tensor_layout.hpp"
 #include "ttnn/distributed/api.hpp"
 
-using namespace tt::constants;
-
 namespace tt::tt_metal {
 namespace {
 
-MemoryConfig extract_memory_config(const Storage& storage) {
-    return std::visit(
-        [](const auto& storage) -> MemoryConfig {
-            using T = std::decay_t<decltype(storage)>;
-            if constexpr (std::is_same_v<T, DeviceStorage>) {
-                return storage.memory_config();
-            } else if constexpr (std::is_same_v<T, MultiDeviceStorage>) {
-                return storage.memory_config();
-            } else {
-                return MemoryConfig{};
-            }
-        },
-        storage);
-}
-
 template <typename T>
 Tensor create_owned_tensor_from_span(tt::stl::Span<const T> data, const TensorSpec& spec) {
     // TODO: support tilized layouts.
@@ -154,14 +137,22 @@ void Tensor::TensorAttributes::update_main_thread_ref_count(Device* worker, uint
 
 Tensor::Tensor(
     Storage storage, const ttnn::Shape& shape, DataType dtype, Layout layout, const std::optional<Tile>& tile) {
-    if (tile.has_value()) {
-        if (tile->get_tile_shape()[0] != TILE_WIDTH or tile->get_tile_shape()[1] != TILE_HEIGHT) {
-            tt::log_warning(
-                "only matmul op and ccl all-gather currently supports the customized tile shape: {}",
-                tile->get_tile_shape());
-        }
+    using namespace tt::constants;
+
+    if (tile.has_value() and  //
+        (tile->get_tile_shape()[0] != TILE_WIDTH or tile->get_tile_shape()[1] != TILE_HEIGHT)) {
+        tt::log_warning(
+            "only matmul op and ccl all-gather currently supports the customized tile shape: {}",
+            tile->get_tile_shape());
     }
-    auto memory_config = extract_memory_config(storage);
+
+    const auto memory_config = std::visit(
+        tt::stl::overloaded{
+            [](const DeviceStorage& s) { return s.memory_config(); },
+            [](const MultiDeviceStorage& s) { return s.memory_config(); },
+            []<typename Other>(const Other&) { return MemoryConfig{}; }},
+        storage);
+
     init(
         std::move(storage),
         TensorSpec(