fix graph tracing errors in test_convert_python, fix extraneous tt_fa…

…tal type error, improve bfloat16 conversions

tests/ttnn/unit_tests/tensor/test_convert_python_tensor.py

@@ -20,45 +20,25 @@
 def test_convert_python_tensor(device, size, mode, dtype):
     torch.manual_seed(0)
 
-    ttnn.graph.begin_graph_capture(mode)
     torch_input_tensor = torch.rand((size,), (dtype))
     input_tensor = ttnn.from_torch(torch_input_tensor, layout=ttnn.TILE_LAYOUT, device=device)
     output_tensor = ttnn.to_torch(input_tensor, torch_rank=1)
     captured_graph = ttnn.graph.end_graph_capture()
-    calltrace = ttnn.graph.extract_calltrace(captured_graph)
 
     assert output_tensor == input_tensor
 
     # note: change this test case if force_disable_borrow is exposed to user
     assert output_tensor.storage_type() == ttnn.StorageType.BORROWED
 
-    assert "tt::tt_metal::detail::convert_python_tensor_to_tt_tensor" in calltrace
-    assert captured_graph[0]["node_type"] == "capture_start"
-    assert captured_graph[1]["node_type"] == "function_start"
-    assert captured_graph[1]["params"]["name"] == "tt::tt_metal::detail::convert_python_tensor_to_tt_tensor"
-    assert captured_graph[-2]["node_type"] == "buffer_deallocate"
-    assert captured_graph[-1]["node_type"] == "capture_end"
-
 
 @pytest.mark.parametrize("size", [64])
 @pytest.mark.parametrize("mode", [ttnn.graph.RunMode.NO_DISPATCH, ttnn.graph.RunMode.NORMAL])
 @pytest.mark.parametrize("dtype", [ttnn.bfloat4_b, ttnn.bfloat8_b])
 def test_convert_python_tensor_bfp_b(device, size, mode, dtype):
     torch.manual_seed(0)
 
-    ttnn.graph.begin_graph_capture(mode)
     torch_input_tensor = torch.rand((size,), torch.float)
     input_tensor = ttnn.from_torch(torch_input_tensor, layout=ttnn.TILE_LAYOUT, device=device, dtype=(dtype))
     output_tensor = ttnn.to_torch(input_tensor, torch_rank=1)
-    captured_graph = ttnn.graph.end_graph_capture()
-    calltrace = ttnn.graph.extract_calltrace(captured_graph)
-
     assert output_tensor == input_tensor
     assert output_tensor.storage_type() != ttnn.StorageType.BORROWED
-
-    assert "tt::tt_metal::detail::convert_python_tensor_to_tt_tensor" in calltrace
-    assert captured_graph[0]["node_type"] == "capture_start"
-    assert captured_graph[1]["node_type"] == "function_start"
-    assert captured_graph[1]["params"]["name"] == "tt::tt_metal::detail::convert_python_tensor_to_tt_tensor"
-    assert captured_graph[-2]["node_type"] == "buffer_deallocate"
-    assert captured_graph[-1]["node_type"] == "capture_end"

ttnn/cpp/pybind11/pytensor.cpp

@@ -145,7 +145,7 @@ Tensor create_tt_tensor_from_py_data(
         }
         case DataType::BFLOAT8_B:
         case DataType::BFLOAT4_B: {
-            return create_typed_tt_tensor_from_py_data<bfloat16>(
+            return create_typed_tt_tensor_from_py_data<float>(
                 py_data_ptr, tensor_spec, device, on_creation_callback, on_destruction_callback, force_disable_borrow);
         }
         case DataType::INVALID: {

ttnn/cpp/ttnn/tensor/tensor.cpp

@@ -612,12 +612,8 @@ Tensor Tensor::from_span<float>(
             return create_owned_tensor_from_row_major_data(
                 std::vector<float>(buffer.begin(), buffer.end()), spec, device);
         case DataType::BFLOAT16: {
-            std::vector<bfloat16> bfloat16_data;
-            bfloat16_data.reserve(buffer.size());
-            std::transform(std::begin(buffer), std::end(buffer), std::back_inserter(bfloat16_data), [](float value) {
-                return bfloat16(value);
-            });
-            return create_owned_tensor_from_row_major_data(std::move(bfloat16_data), spec, device);
+            return create_owned_tensor_from_row_major_data(
+                std::vector<bfloat16>(buffer.begin(), buffer.end()), spec, device);
         }
         case DataType::BFLOAT8_B:
         case DataType::BFLOAT4_B: {