implement tf.nn.bias_add (#8835)

ivy/functional/frontends/tensorflow/nn.py

@@ -237,3 +237,16 @@ def moments(x, axes, shift=None, keepdims=False, name=None):
     return ivy.mean(x, axis=axes, keepdims=keepdims), ivy.var(
         x, axis=axes, keepdims=keepdims
     )
+
+
+@to_ivy_arrays_and_back
+def bias_add(value, bias, data_format=None, name=None):
+    if data_format is None:
+        data_format = "N...C"
+
+    if data_format == "N...C":
+        return ivy.add(value, bias)
+    else:
+        value = ivy.swapaxes(value, 1, -1)
+        res = ivy.add(value, bias)
+        return ivy.swapaxes(res, 1, -1)

ivy_tests/test_ivy/test_frontends/test_tensorflow/test_nn.py

@@ -958,3 +958,49 @@ def test_tensorflow_moments(
         axes=axis,
         keepdims=keepdims,
     )
+
+
+@st.composite
+def _generate_bias_data(draw):
+    data_format = draw(st.sampled_from(["NC...", "N...C", None]))
+    channel_dim = 1 if data_format == "NC..." else -1
+    dtype, value, shape = draw(
+        helpers.dtype_and_values(
+            available_dtypes=helpers.get_dtypes("numeric"),
+            min_num_dims=3,
+            ret_shape=True,
+        )
+    )
+    channel_size = shape[channel_dim]
+    bias = draw(helpers.array_values(dtype=dtype[0], shape=(channel_size,)))
+    return data_format, dtype, value, bias
+
+
+@handle_frontend_test(
+    fn_tree="tensorflow.nn.bias_add",
+    data=_generate_bias_data(),
+)
+def test_tensorflow_bias_add(
+    *,
+    data,
+    as_variable,
+    num_positional_args,
+    native_array,
+    frontend,
+    fn_tree,
+    on_device,
+):
+    data_format, dtype, value, bias = data
+    helpers.test_frontend_function(
+        input_dtypes=dtype * 2,
+        as_variable_flags=as_variable,
+        with_out=False,
+        num_positional_args=num_positional_args,
+        native_array_flags=native_array,
+        frontend=frontend,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        value=value[0],
+        bias=bias,
+        data_format=data_format,
+    )