Ask NumPy for read only array when converting it to Tensor.

ezhulenev · tensorflower-gardener · commit 7bb79ee219d4 · 2018-06-08T12:49:36.000-07:00
Fix for: tensorflow#17315 If numpy array is read-only, calling PyArray_FromAny with NPY_ARRAY_CARRAY flags introduce extra memory copy. Before: feed_cpu_variable_read_only: 5.6 GB/sec, min: 17.99, median: 19.54, mean: 19.76 After: feed_cpu_variable_read_only: 13.2 GB/sec, min: 7.60, median: 7.78, mean: 8.13 PiperOrigin-RevId: 199835695
diff --git a/tensorflow/python/lib/core/ndarray_tensor.cc b/tensorflow/python/lib/core/ndarray_tensor.cc
@@ -411,7 +411,7 @@ Status PyArrayToTF_Tensor(PyObject* ndarray, Safe_TF_TensorPtr* out_tensor) {
 
   // Make sure we dereference this array object in case of error, etc.
   Safe_PyObjectPtr array_safe(make_safe(
-      PyArray_FromAny(ndarray, nullptr, 0, 0, NPY_ARRAY_CARRAY, nullptr)));
+      PyArray_FromAny(ndarray, nullptr, 0, 0, NPY_ARRAY_CARRAY_RO, nullptr)));
   if (!array_safe) return errors::InvalidArgument("Not a ndarray.");
   PyArrayObject* array = reinterpret_cast<PyArrayObject*>(array_safe.get());
 
