auto-lint code

ivy/compiler/_cache/Translated_Outputs/Translated_BatchNorm2d_output/run_0/Translated__BatchNorm.py

@@ -47,9 +47,11 @@ def forward(self, input):
         """
         return F.batch_norm(
             input,
-            self.running_mean
-            if not self.training or self.track_running_stats
-            else None,
+            (
+                self.running_mean
+                if not self.training or self.track_running_stats
+                else None
+            ),
             self.running_var if not self.training or self.track_running_stats else None,
             self.weight,
             self.bias,

ivy/compiler/_cache/Translated_Outputs/ivy_BatchNorm2d_output/run_0/ivy__BatchNorm.py

@@ -47,9 +47,11 @@ def forward(self, input):
         """
         normalized, self.running_mean, self.running_var = ivy_batch_norm_frnt(
             input,
-            self.running_mean
-            if not self.training or self.track_running_stats
-            else None,
+            (
+                self.running_mean
+                if not self.training or self.track_running_stats
+                else None
+            ),
             self.running_var if not self.training or self.track_running_stats else None,
             self.weight,
             self.bias,

ivy/compiler/_cache/Translated_Outputs/tensorflow_BatchNorm2d_output/run_0/tensorflow__BatchNorm.py

@@ -55,12 +55,16 @@ def call(self, input):
             normalized, self.running_mean, self.running_var = (
                 tensorflow_batch_norm_frnt(
                     input,
-                    self.running_mean
-                    if not self.training or self.track_running_stats
-                    else None,
-                    self.running_var
-                    if not self.training or self.track_running_stats
-                    else None,
+                    (
+                        self.running_mean
+                        if not self.training or self.track_running_stats
+                        else None
+                    ),
+                    (
+                        self.running_var
+                        if not self.training or self.track_running_stats
+                        else None
+                    ),
                     self.weight,
                     self.bias,
                     bn_training,

ivy/compiler/_cache/Translated_Outputs/tensorflow_BatchNorm2d_output/run_0/tensorflow__NormBase.py

@@ -133,11 +133,13 @@ def _load_from_state_dict(
                     state_dict = tensorflow_set_item_bknd(
                         state_dict,
                         num_batches_tracked_key,
-                        self.num_batches_tracked
-                        if self.num_batches_tracked is not None
-                        and self.num_batches_tracked.device
-                        != tensorflow_device_frnt("meta")
-                        else tensorflow_tensor_frnt(0, dtype=tf.int64),
+                        (
+                            self.num_batches_tracked
+                            if self.num_batches_tracked is not None
+                            and self.num_batches_tracked.device
+                            != tensorflow_device_frnt("meta")
+                            else tensorflow_tensor_frnt(0, dtype=tf.int64)
+                        ),
                     )
         super()._load_from_state_dict(
             state_dict,

ivy/compiler/_cache/Translated_Outputs/tensorflow_BatchNorm2d_output/run_0/tensorflow__helpers.py

@@ -470,9 +470,7 @@ def tensorflow_default_bknd(
     return (
         x
         if tensorflow_exists_bknd(x)
-        else default_val()
-        if default_callable
-        else default_val
+        else default_val() if default_callable else default_val
     )
 
 
@@ -905,17 +903,21 @@ def tensorflow_default_int_dtype_bknd(
         elif isinstance(input, (list, tuple, dict)):
             if tensorflow_nested_argwhere_bknd(
                 input,
-                lambda x: tensorflow_dtype(x) == "uint64"
-                if tensorflow_is_array_bknd(x)
-                else x > 9223372036854775807 and x != math.inf,
+                lambda x: (
+                    tensorflow_dtype(x) == "uint64"
+                    if tensorflow_is_array_bknd(x)
+                    else x > 9223372036854775807 and x != math.inf
+                ),
                 stop_after_n_found=1,
             ):
                 ret = tf.uint64
             elif tensorflow_nested_argwhere_bknd(
                 input,
-                lambda x: tensorflow_dtype(x) == "int64"
-                if tensorflow_is_array_bknd(x)
-                else x > 2147483647 and x != math.inf,
+                lambda x: (
+                    tensorflow_dtype(x) == "int64"
+                    if tensorflow_is_array_bknd(x)
+                    else x > 2147483647 and x != math.inf
+                ),
                 stop_after_n_found=1,
             ):
                 ret = tf.int64
@@ -1300,21 +1302,27 @@ def tensorflow_nested_map_bknd(
         to_ignore = to_ignore + (class_instance,)
     tuple_check_fn = tensorflow_default_bknd(
         _tuple_check_fn,
-        (lambda x_, t_: isinstance(x_, t_))
-        if include_derived["tuple"]
-        else lambda x_, t_: type(x_) is t_,
+        (
+            (lambda x_, t_: isinstance(x_, t_))
+            if include_derived["tuple"]
+            else lambda x_, t_: type(x_) is t_
+        ),
     )
     list_check_fn = tensorflow_default_bknd(
         _list_check_fn,
-        (lambda x_, t_: isinstance(x_, t_))
-        if include_derived["list"]
-        else lambda x_, t_: type(x_) is t_,
+        (
+            (lambda x_, t_: isinstance(x_, t_))
+            if include_derived["list"]
+            else lambda x_, t_: type(x_) is t_
+        ),
     )
     dict_check_fn = tensorflow_default_bknd(
         _dict_check_fn,
-        (lambda x_, t_: isinstance(x_, t_))
-        if include_derived["dict"]
-        else lambda x_, t_: type(x_) is t_,
+        (
+            (lambda x_, t_: isinstance(x_, t_))
+            if include_derived["dict"]
+            else lambda x_, t_: type(x_) is t_
+        ),
     )
     if tuple_check_fn(x, tuple) and not isinstance(x, to_ignore):
         ret_list = [
@@ -1735,9 +1743,7 @@ def tensorflow_where(
         dtype = (
             x1.dtype
             if hasattr(x1, "dtype")
-            else x2.dtype
-            if hasattr(x2, "dtype")
-            else tensorflow_default_dtype_bknd()
+            else x2.dtype if hasattr(x2, "dtype") else tensorflow_default_dtype_bknd()
         )
         if not tensorflow_is_array_bknd(x1):
             x1 = tensorflow_asarray(x1, dtype=dtype)
@@ -2149,9 +2155,7 @@ def tensorflow__parse_query_bknd(query, x_shape, scatter=False):
             (
                 tensorflow_reshape_bknd_(arr, (-1,))
                 if len(arr.shape) > 1
-                else tensorflow_expand_dims(arr)
-                if not len(arr.shape)
-                else arr
+                else tensorflow_expand_dims(arr) if not len(arr.shape) else arr
             )
             for arr in array_queries
         ]
@@ -2265,9 +2269,11 @@ def is_native(x):
 
             if tensorflow_nested_argwhere_bknd(
                 input,
-                lambda x: tensorflow_dtype(x) == "uint64"
-                if is_native(x)
-                else x > 9223372036854775807 and x != math.inf,
+                lambda x: (
+                    tensorflow_dtype(x) == "uint64"
+                    if is_native(x)
+                    else x > 9223372036854775807 and x != math.inf
+                ),
                 stop_after_n_found=1,
             ):
                 ret = tf.uint64
@@ -2475,9 +2481,7 @@ def tensorflow_multiply(
         dtype = (
             x1.dtype
             if hasattr(x1, "dtype")
-            else x2.dtype
-            if hasattr(x2, "dtype")
-            else tensorflow_default_dtype_bknd()
+            else x2.dtype if hasattr(x2, "dtype") else tensorflow_default_dtype_bknd()
         )
         if not tensorflow_is_array_bknd(x1):
             x1 = tensorflow_asarray(x1, dtype=dtype)
@@ -2641,9 +2645,11 @@ def tensorflow_scatter_nd(
         dtype = tensorflow_promote_types_bknd(out.dtype, updates_dtype)
     updates = tensorflow.cast(
         updates,
-        tensorflow_as_native_dtype(dtype)
-        if tensorflow_exists_bknd(out)
-        else updates_dtype,
+        (
+            tensorflow_as_native_dtype(dtype)
+            if tensorflow_exists_bknd(out)
+            else updates_dtype
+        ),
     )
     expected_shape = (
         list(tensorflow.shape(indices)[:-1])
@@ -3022,9 +3028,7 @@ def tensorflow_add(
         dtype = (
             x1.dtype
             if hasattr(x1, "dtype")
-            else x2.dtype
-            if hasattr(x2, "dtype")
-            else tensorflow_default_dtype_bknd()
+            else x2.dtype if hasattr(x2, "dtype") else tensorflow_default_dtype_bknd()
         )
         if not tensorflow_is_array_bknd(x1):
             x1 = tensorflow_asarray(x1, dtype=dtype)

ivy/compiler/_cache/Translated_Outputs/tensorflow_Conv2d_output/run_0/tensorflow__helpers.py

@@ -475,9 +475,7 @@ def tensorflow_default_bknd(
     return (
         x
         if tensorflow_exists_bknd(x)
-        else default_val()
-        if default_callable
-        else default_val
+        else default_val() if default_callable else default_val
     )
 
 
@@ -912,17 +910,21 @@ def tensorflow_default_int_dtype_bknd(
         elif isinstance(input, (list, tuple, dict)):
             if tensorflow_nested_argwhere_bknd(
                 input,
-                lambda x: tensorflow_dtype(x) == "uint64"
-                if tensorflow_is_array_bknd(x)
-                else x > 9223372036854775807 and x != math.inf,
+                lambda x: (
+                    tensorflow_dtype(x) == "uint64"
+                    if tensorflow_is_array_bknd(x)
+                    else x > 9223372036854775807 and x != math.inf
+                ),
                 stop_after_n_found=1,
             ):
                 ret = tf.uint64
             elif tensorflow_nested_argwhere_bknd(
                 input,
-                lambda x: tensorflow_dtype(x) == "int64"
-                if tensorflow_is_array_bknd(x)
-                else x > 2147483647 and x != math.inf,
+                lambda x: (
+                    tensorflow_dtype(x) == "int64"
+                    if tensorflow_is_array_bknd(x)
+                    else x > 2147483647 and x != math.inf
+                ),
                 stop_after_n_found=1,
             ):
                 ret = tf.int64
@@ -1308,21 +1310,27 @@ def tensorflow_nested_map_bknd(
         to_ignore = to_ignore + (class_instance,)
     tuple_check_fn = tensorflow_default_bknd(
         _tuple_check_fn,
-        (lambda x_, t_: isinstance(x_, t_))
-        if include_derived["tuple"]
-        else lambda x_, t_: type(x_) is t_,
+        (
+            (lambda x_, t_: isinstance(x_, t_))
+            if include_derived["tuple"]
+            else lambda x_, t_: type(x_) is t_
+        ),
     )
     list_check_fn = tensorflow_default_bknd(
         _list_check_fn,
-        (lambda x_, t_: isinstance(x_, t_))
-        if include_derived["list"]
-        else lambda x_, t_: type(x_) is t_,
+        (
+            (lambda x_, t_: isinstance(x_, t_))
+            if include_derived["list"]
+            else lambda x_, t_: type(x_) is t_
+        ),
     )
     dict_check_fn = tensorflow_default_bknd(
         _dict_check_fn,
-        (lambda x_, t_: isinstance(x_, t_))
-        if include_derived["dict"]
-        else lambda x_, t_: type(x_) is t_,
+        (
+            (lambda x_, t_: isinstance(x_, t_))
+            if include_derived["dict"]
+            else lambda x_, t_: type(x_) is t_
+        ),
     )
     if tuple_check_fn(x, tuple) and not isinstance(x, to_ignore):
         ret_list = [
@@ -1743,9 +1751,7 @@ def tensorflow_where(
         dtype = (
             x1.dtype
             if hasattr(x1, "dtype")
-            else x2.dtype
-            if hasattr(x2, "dtype")
-            else tensorflow_default_dtype_bknd()
+            else x2.dtype if hasattr(x2, "dtype") else tensorflow_default_dtype_bknd()
         )
         if not tensorflow_is_array_bknd(x1):
             x1 = tensorflow_asarray(x1, dtype=dtype)
@@ -2157,9 +2163,7 @@ def tensorflow__parse_query_bknd(query, x_shape, scatter=False):
             (
                 tensorflow_reshape_bknd_(arr, (-1,))
                 if len(arr.shape) > 1
-                else tensorflow_expand_dims(arr)
-                if not len(arr.shape)
-                else arr
+                else tensorflow_expand_dims(arr) if not len(arr.shape) else arr
             )
             for arr in array_queries
         ]
@@ -2307,9 +2311,11 @@ def is_native(x):
 
             if tensorflow_nested_argwhere_bknd(
                 input,
-                lambda x: tensorflow_dtype(x) == "uint64"
-                if is_native(x)
-                else x > 9223372036854775807 and x != math.inf,
+                lambda x: (
+                    tensorflow_dtype(x) == "uint64"
+                    if is_native(x)
+                    else x > 9223372036854775807 and x != math.inf
+                ),
                 stop_after_n_found=1,
             ):
                 ret = tf.uint64
@@ -2517,9 +2523,7 @@ def tensorflow_multiply(
         dtype = (
             x1.dtype
             if hasattr(x1, "dtype")
-            else x2.dtype
-            if hasattr(x2, "dtype")
-            else tensorflow_default_dtype_bknd()
+            else x2.dtype if hasattr(x2, "dtype") else tensorflow_default_dtype_bknd()
         )
         if not tensorflow_is_array_bknd(x1):
             x1 = tensorflow_asarray(x1, dtype=dtype)
@@ -2683,9 +2687,11 @@ def tensorflow_scatter_nd(
         dtype = tensorflow_promote_types_bknd(out.dtype, updates_dtype)
     updates = tensorflow.cast(
         updates,
-        tensorflow_as_native_dtype(dtype)
-        if tensorflow_exists_bknd(out)
-        else updates_dtype,
+        (
+            tensorflow_as_native_dtype(dtype)
+            if tensorflow_exists_bknd(out)
+            else updates_dtype
+        ),
     )
     expected_shape = (
         list(tensorflow.shape(indices)[:-1])
@@ -3090,9 +3096,7 @@ def tensorflow_add(
         dtype = (
             x1.dtype
             if hasattr(x1, "dtype")
-            else x2.dtype
-            if hasattr(x2, "dtype")
-            else tensorflow_default_dtype_bknd()
+            else x2.dtype if hasattr(x2, "dtype") else tensorflow_default_dtype_bknd()
         )
         if not tensorflow_is_array_bknd(x1):
             x1 = tensorflow_asarray(x1, dtype=dtype)