chore: import upstream snapshot with attribution

python/tvm/topi/testing/searchsorted.py

@@ -0,0 +1,36 @@
+# 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.
+"""The reference implementation of searchsorted in Numpy."""
+
+import numpy as np
+
+
+def searchsorted_ref(sorted_sequence, values, right, out_dtype):
+    """Run Numpy searchsorted on 1-D or N-D sorted_sequence."""
+    side = "right" if right else "left"
+    if len(sorted_sequence.shape) == 1 and len(values.shape) > 1:
+        sorted_sequence_2d = np.tile(sorted_sequence, (np.prod(values.shape[:-1]), 1))
+    else:
+        sorted_sequence_2d = np.reshape(sorted_sequence, (-1, sorted_sequence.shape[-1]))
+
+    values_2d = np.reshape(values, (-1, values.shape[-1]))
+    indices = np.zeros(values_2d.shape, dtype=out_dtype)
+
+    for i in range(indices.shape[0]):
+        indices[i] = np.searchsorted(sorted_sequence_2d[i], values_2d[i], side=side)
+
+    return np.reshape(indices, values.shape)