|---| | [ View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.15.1/tensorflow/python/ops/numpy_ops/np_config.py#L25-L58) | Enable NumPy behavior on Tensors. ```python tf.experimental.numpy.experimental_enable_numpy_behavior( prefer_float32=False, dtype_conversion_mode='legacy' ) ``` Enabling NumPy behavior has three effects: - It adds to [`tf.Tensor`](https://www.tensorflow.org/versions/r2.15/api_docs/python/tf/Tensor.md.txt) some common NumPy methods such as `T`, `reshape` and `ravel`. - It changes dtype promotion in [`tf.Tensor`](https://www.tensorflow.org/versions/r2.15/api_docs/python/tf/Tensor.md.txt) operators to be compatible with NumPy. For example, `tf.ones([], tf.int32) + tf.ones([], tf.float32)` used to throw a "dtype incompatible" error, but after this it will return a float64 tensor (obeying NumPy's promotion rules). - It enhances [`tf.Tensor`](https://www.tensorflow.org/versions/r2.15/api_docs/python/tf/Tensor.md.txt)'s indexing capability to be on par with [NumPy's](https://numpy.org/doc/stable/reference/arrays.indexing.html).


| ## Args || |---|---| | `prefer_float32` | Controls whether dtype inference will use float32 for Python floats, or float64 (the default and the NumPy-compatible behavior). | | `dtype_conversion_mode` | a string that specifies promotion mode. This string corresponds to a PromoMode Enum and can be 'off', 'legacy', 'safe', or 'all'. 'safe' or 'all' mode enables the auto dtype conversion semantics. |