Replace tfnp with native tf ops wherever possible (#18998)

* Add dtype test for `floor_divide`

* Use native `tf.*` if possible in `backend.numpy`

* Apply `result_type` to np's `floor_divide`

* Increase test coverage

* Fix failed test

keras/backend/jax/numpy.py

@@ -207,6 +207,9 @@ def argmin(x, axis=None):
 
 
 def argsort(x, axis=-1):
+    x = convert_to_tensor(x)
+    if x.ndim == 0:
+        return jnp.argsort(x, axis=None)
     return jnp.argsort(x, axis=axis)
 
 

keras/backend/numpy/numpy.py

@@ -1037,6 +1037,15 @@ def eye(N, M=None, k=0, dtype=None):
 
 
 def floor_divide(x1, x2):
+    if not isinstance(x1, (int, float)):
+        x1 = convert_to_tensor(x1)
+    if not isinstance(x2, (int, float)):
+        x2 = convert_to_tensor(x2)
+    dtype = dtypes.result_type(
+        getattr(x1, "dtype", type(x1)), getattr(x2, "dtype", type(x2))
+    )
+    x1 = convert_to_tensor(x1, dtype)
+    x2 = convert_to_tensor(x2, dtype)
     return np.floor_divide(x1, x2)