chore: import upstream snapshot with attribution

python/tvm/topi/testing/softmax_python.py

@@ -0,0 +1,58 @@
+# 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, trailing-whitespace
+"""Softmax and log_softmax operation in python"""
+
+import numpy as np
+
+
+def softmax_python(a_np, axis=1):
+    """Softmax operator.
+    Parameters
+    ----------
+    a_np : numpy.ndarray
+        N-D input data
+
+    Returns
+    -------
+    output_np : numpy.ndarray
+        N-D output with same shape
+    """
+    max_elem = np.amax(a_np, axis=axis, keepdims=True)
+    e = np.exp(a_np - max_elem)
+    expsum = np.sum(e, axis=axis, keepdims=True)
+    out_np = e / expsum
+    return out_np
+
+
+def log_softmax_python(a_np, axis=1):
+    """Log_softmax operator.
+    Parameters
+    ----------
+    a_np : numpy.ndarray
+        N-D input data
+
+    Returns
+    -------
+    output_np : numpy.ndarray
+        N-D output with same shape
+    """
+    max_elem = np.amax(a_np, axis=axis, keepdims=True)
+    e = np.exp(a_np - max_elem)
+    expsum = np.sum(e, axis=axis, keepdims=True)
+    out_np = a_np - max_elem - np.log(expsum)
+    return out_np