chore: import upstream snapshot with attribution

python/tvm/topi/testing/instance_norm_python.py

@@ -0,0 +1,54 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+# pylint: disable=invalid-name, line-too-long, unused-variable, too-many-locals
+"""Instance normalization in python"""
+
+import numpy as np
+
+
+def instance_norm_python(data, gamma, beta, axis, epsilon=1e-5):
+    """Instance normalization operator in Python.
+
+    Parameters
+    ----------
+    data : numpy.ndarray
+        N-D with shape (d_0, d_1, ..., d_{N-1})
+
+    gamma: numpy.ndarray
+        K-D with shape (r_0, r_1, ..., r_{K-1}) where K == len(axis) and d_{axis_k} == r_k
+
+    beta: numpy.ndarray
+        Optional, K-D with shape (r_0, r_1, ..., r_{K-1}) where K == len(axis) and d_{axis_k} == r_k
+
+    axis : int or tuple of ints
+        Axis over the normalization applied
+
+    epsilon : float
+        The epsilon value to avoid division by zero.
+
+    Returns
+    -------
+    result : np.ndarray
+        N-D with shape (d_0, d_1, ..., d_{N-1})
+    """
+    mean = np.mean(data, axis, keepdims=True)
+    var = np.var(data, axis, keepdims=True)
+    result = (data - mean) / np.sqrt(var + epsilon)
+    result *= gamma
+    if beta is not None:
+        result += beta
+    return result