#0: Fix failing Llama TG tests by preserving old behavior for ShardTe…

…nsorToMesh

Previously, when we had a MxN MeshDevice, a mesh_mapper of
ShardTensorToMesh would behave differently based on whether `mesh_type`
passed into the MeshDevice was MeshType::RowMajor, MeshType::Ring.

With the removal of `MeshType` from MeshDevice specification, this
changed the default behavior for users constructing a MeshDevice
with default mesh_type=MeshType::RowMajor. This change now preserves the
old behavior so that shards are distributed in row-major instead of a
line.

conftest.py

@@ -258,6 +258,7 @@ def pcie_mesh_device(request, silicon_arch_name, silicon_arch_wormhole_b0, devic
         **updated_device_params,
         offset=ttnn.MeshOffset(0, 1),
     )
+    mesh_device.reshape(ttnn.MeshShape(1, 4))
 
     logger.debug(f"multidevice with {mesh_device.get_num_devices()} devices is created")
     yield mesh_device

ttnn/cpp/ttnn/distributed/api.cpp

@@ -153,7 +153,6 @@ std::vector<IDevice*> get_mapped_devices(const Tensor& tensor, MeshDevice& mesh_
                 [&](const ShardTensor2D& s) {
                     return mesh_device.get_view().get_devices(MeshShape{s.shard_mesh.y, s.shard_mesh.x});
                 },
-                [&](const ShardTensor& s) { return get_workers_for_tensor(mesh_device.get_view().get_line_devices()); },
                 [&](const auto&) { return get_workers_for_tensor(mesh_device.get_devices()); }},
             host_storage.strategy);
     } else if (std::holds_alternative<MultiDeviceStorage>(tensor.get_storage())) {