diff --git a/docs/source/functional.rst b/docs/source/functional.rst
index 284153c7fd..16899815ef 100644
--- a/docs/source/functional.rst
+++ b/docs/source/functional.rst
@@ -76,10 +76,6 @@ resample
 
 Utilities for pseudo complex tensor. This is not for the native complex dtype, such as `cfloat64`, but for tensors with real-value type and have extra dimension at the end for real and imaginary parts.
 
-angle
------
-
-.. autofunction:: angle
 
 complex_norm
 ------------
diff --git a/torchaudio/functional/__init__.py b/torchaudio/functional/__init__.py
index 494f1bdc23..ad90516d42 100644
--- a/torchaudio/functional/__init__.py
+++ b/torchaudio/functional/__init__.py
@@ -1,6 +1,5 @@
 from .functional import (
     amplitude_to_DB,
-    angle,
     complex_norm,
     compute_deltas,
     compute_kaldi_pitch,
@@ -53,7 +52,6 @@
 
 __all__ = [
     'amplitude_to_DB',
-    'angle',
     'complex_norm',
     'compute_deltas',
     'compute_kaldi_pitch',
diff --git a/torchaudio/functional/functional.py b/torchaudio/functional/functional.py
index 1340216f40..c55e61603e 100644
--- a/torchaudio/functional/functional.py
+++ b/torchaudio/functional/functional.py
@@ -29,7 +29,6 @@
     "mu_law_encoding",
     "mu_law_decoding",
     "complex_norm",
-    "angle",
     "phase_vocoder",
     'mask_along_axis',
     'mask_along_axis_iid',
@@ -749,27 +748,6 @@ def complex_norm(
     return complex_tensor.pow(2.).sum(-1).pow(0.5 * power)
 
 
-@_mod_utils.deprecated(
-    "Please convert the input Tensor to complex type with `torch.view_as_complex` then "
-    "use `torch.angle`. "
-    "Please refer to https://github.com/pytorch/audio/issues/1337 "
-    "for more details about torchaudio's plan to migrate to native complex type.",
-    version="0.11",
-)
-def angle(
-        complex_tensor: Tensor
-) -> Tensor:
-    r"""Compute the angle of complex tensor input.
-
-    Args:
-        complex_tensor (Tensor): Tensor shape of `(..., complex=2)`
-
-    Return:
-        Tensor: Angle of a complex tensor. Shape of `(..., )`
-    """
-    return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0])
-
-
 def phase_vocoder(
         complex_specgrams: Tensor,
         rate: float,