fixes to get some meta tests passing

PeaceBello · Jun 15, 2022 · 6ffd32f · 6ffd32f
1 parent de19394
commit 6ffd32f
Show file tree

Hide file tree

Showing 5 changed files with 9 additions and 5 deletions.
diff --git a/ivy/container/statistical.py b/ivy/container/statistical.py
@@ -110,7 +110,7 @@ def prod(
     ) -> ivy.Container:
         return self.handle_inplace(
             self.map(
-                lambda x_, _: ivy.prod(x_, axis, keepdims, dtype=dtype)
+                lambda x_, _: ivy.prod(x_, axis=axis, keepdims=keepdims, dtype=dtype)
                 if ivy.is_array(x_)
                 else x_,
                 key_chains,
@@ -134,7 +134,7 @@ def sum(
     ) -> ivy.Container:
         return self.handle_inplace(
             self.map(
-                lambda x_, _: ivy.sum(x_, axis, dtype, keepdims)
+                lambda x_, _: ivy.sum(x_, axis=axis, dtype=dtype, keepdims=keepdims)
                 if ivy.is_array(x_)
                 else x_,
                 key_chains,

diff --git a/ivy/functional/backends/tensorflow/elementwise.py b/ivy/functional/backends/tensorflow/elementwise.py
@@ -26,6 +26,8 @@ def add(
         promoted_type = tf.experimental.numpy.promote_types(x1.dtype, x2.dtype)
         x1 = tf.cast(x1, promoted_type)
         x2 = tf.cast(x2, promoted_type)
+    elif not isinstance(x1, tf.Tensor):
+        x1 = tf.constant(x1, dtype=x2.dtype)
     return tf.add(x1, x2)
 
 

diff --git a/ivy/functional/backends/tensorflow/general.py b/ivy/functional/backends/tensorflow/general.py
@@ -18,7 +18,7 @@
 
 
 def is_native_array(x, exclusive=False):
-    if isinstance(x, tf.Tensor):
+    if isinstance(x, tf.Tensor) or isinstance(x, tf.Variable):
         if exclusive and isinstance(x, tf.Variable):
             return False
         return True

diff --git a/ivy/functional/backends/torch/elementwise.py b/ivy/functional/backends/torch/elementwise.py
@@ -344,6 +344,8 @@ def subtract(
         x1 = x1.to(promoted_type)
         x2 = x2.to(promoted_type)
         return torch.subtract(x1, x2, out=out)
+    elif not isinstance(x1, torch.Tensor):
+        x1 = torch.tensor(x1, dtype=x2.dtype)
     return torch.subtract(x1, x2)
 
 

diff --git a/ivy/functional/ivy/meta.py b/ivy/functional/ivy/meta.py
@@ -35,7 +35,7 @@ def _compute_cost_and_update_grads(
             retain_grads=False,
         )
         if batched:
-            inner_grads = inner_grads * num_tasks
+            inner_grads = ivy.multiply(inner_grads, num_tasks)
         if average_across_steps_or_final:
             all_grads.append(inner_grads)
     else:
@@ -85,7 +85,7 @@ def _train_task(
             retain_grads=order > 1,
         )
         if batched:
-            inner_update_grads = inner_update_grads * num_tasks
+            inner_update_grads = ivy.multiply(inner_update_grads, num_tasks)
 
         # compute the cost to be optimized, and update all_grads if fist order method
         if outer_cost_fn is None and not unique_inner and not unique_outer: