diff --git a/ivy/functional/frontends/tensorflow/nn.py b/ivy/functional/frontends/tensorflow/nn.py
index 2f96c984fc881..3c24579a442ca 100644
--- a/ivy/functional/frontends/tensorflow/nn.py
+++ b/ivy/functional/frontends/tensorflow/nn.py
@@ -19,13 +19,13 @@ def _reduce_strides_dilations(dim, stride, dilations):
 
 @to_ivy_arrays_and_back
 def atrous_conv2d(value, filters, rate, padding):
-    return ivy.conv2d(value, filters, 1, padding, dilations=[rate]*2)
+    return ivy.conv2d(value, filters, 1, padding, dilations=[rate] * 2)
 
 
 @to_ivy_arrays_and_back
 def atrous_conv2d_transpose(value, filters, output_shape, rate, padding):
     return ivy.conv2d_transpose(
-        value, filters, 1, padding, output_shape=output_shape, dilations=[rate]*2
+        value, filters, 1, padding, output_shape=output_shape, dilations=[rate] * 2
     )
 
 
@@ -145,13 +145,15 @@ def depthwise_conv2d(
 ):
     strides, dilations = _reduce_strides_dilations(2, strides, dilations)
     fc = filter.shape[-2]
-    filter = filter.reshape([*filter.shape[0:2], 1, filter.shape[-2]*filter.shape[-1]])
+    filter = filter.reshape(
+        [*filter.shape[0:2], 1, filter.shape[-2] * filter.shape[-1]]
+    )
     return ivy.conv_general_dilated(
         input,
         filter,
         strides,
         padding,
-        data_format='channel_last' if data_format[-1] == 'C' else 'channel_first',
+        data_format="channel_last" if data_format[-1] == "C" else "channel_first",
         dilations=dilations,
         feature_group_count=fc,
     )
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_nn.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_nn.py
index f09829901ff1e..23e3f75b9fe75 100644
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_nn.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_nn.py
@@ -49,7 +49,9 @@ def _x_and_filters(
         dilations = draw(
             st.one_of(
                 st.integers(dilation_min, dilation_max),
-                st.lists(st.integers(dilation_min, dilation_max), min_size=dim, max_size=dim),
+                st.lists(
+                    st.integers(dilation_min, dilation_max), min_size=dim, max_size=dim
+                ),
             )
         )
     if atrous:
@@ -58,7 +60,9 @@ def _x_and_filters(
         stride = draw(
             st.one_of(
                 st.integers(stride_min, stride_max),
-                st.lists(st.integers(stride_min, stride_max), min_size=dim, max_size=dim),
+                st.lists(
+                    st.integers(stride_min, stride_max), min_size=dim, max_size=dim
+                ),
             )
         )
     fstride = [stride] * dim if isinstance(stride, int) else stride
@@ -104,7 +108,9 @@ def _x_and_filters(
         if transpose:
             output_shape = [
                 x_shape[0],
-                _deconv_length(x_w, fstride[0], filter_shape[0], padding, fdilations[0]),
+                _deconv_length(
+                    x_w, fstride[0], filter_shape[0], padding, fdilations[0]
+                ),
                 d_in,
             ]
     elif dim == 2: