diff --git a/pandas/core/indexes/interval.py b/pandas/core/indexes/interval.py
index 24fcb32d09d27..18aa0580d7df7 100644
--- a/pandas/core/indexes/interval.py
+++ b/pandas/core/indexes/interval.py
@@ -1061,11 +1061,9 @@ def _format_with_header(self, header, **kwargs):
 
     def _format_native_types(self, na_rep='NaN', quoting=None, **kwargs):
         """ actually format my specific types """
-        from pandas.io.formats.format import ExtensionArrayFormatter
-        return ExtensionArrayFormatter(values=self,
-                                       na_rep=na_rep,
-                                       justify='all',
-                                       leading_space=False).get_result()
+        from pandas.io.formats.format import format_array
+        return format_array(values=self, na_rep=na_rep, justify='all',
+                            leading_space=False)
 
     def _format_data(self, name=None):
 
diff --git a/pandas/io/formats/format.py b/pandas/io/formats/format.py
index f632bc13a5b24..66af6c2172344 100644
--- a/pandas/io/formats/format.py
+++ b/pandas/io/formats/format.py
@@ -849,7 +849,7 @@ def _get_column_name_list(self):
 # Array formatters
 
 
-def format_array(values, formatter, float_format=None, na_rep='NaN',
+def format_array(values, formatter=None, float_format=None, na_rep='NaN',
                  digits=None, space=None, justify='right', decimal='.',
                  leading_space=None):
     """
@@ -879,14 +879,23 @@ def format_array(values, formatter, float_format=None, na_rep='NaN',
     List[str]
     """
 
+    if is_extension_array_dtype(values.dtype):
+        if isinstance(values, (ABCIndexClass, ABCSeries)):
+            values = values._values
+
+        if is_categorical_dtype(values.dtype):
+            # Categorical is special for now, so that we can preserve tzinfo
+            values = values.get_values()
+
+        if not is_datetime64tz_dtype(values.dtype):
+            values = np.asarray(values)
+
     if is_datetime64_dtype(values.dtype):
         fmt_klass = Datetime64Formatter
     elif is_datetime64tz_dtype(values):
         fmt_klass = Datetime64TZFormatter
     elif is_timedelta64_dtype(values.dtype):
         fmt_klass = Timedelta64Formatter
-    elif is_extension_array_dtype(values.dtype):
-        fmt_klass = ExtensionArrayFormatter
     elif is_float_dtype(values.dtype) or is_complex_dtype(values.dtype):
         fmt_klass = FloatArrayFormatter
     elif is_integer_dtype(values.dtype):
@@ -1181,29 +1190,6 @@ def _format_strings(self):
         return fmt_values.tolist()
 
 
-class ExtensionArrayFormatter(GenericArrayFormatter):
-    def _format_strings(self):
-        values = self.values
-        if isinstance(values, (ABCIndexClass, ABCSeries)):
-            values = values._values
-
-        formatter = values._formatter(boxed=True)
-
-        if is_categorical_dtype(values.dtype):
-            # Categorical is special for now, so that we can preserve tzinfo
-            array = values.get_values()
-        else:
-            array = np.asarray(values)
-
-        fmt_values = format_array(array,
-                                  formatter,
-                                  float_format=self.float_format,
-                                  na_rep=self.na_rep, digits=self.digits,
-                                  space=self.space, justify=self.justify,
-                                  leading_space=self.leading_space)
-        return fmt_values
-
-
 def format_percentiles(percentiles):
     """
     Outputs rounded and formatted percentiles.