chore: import upstream snapshot with attribution

python/tvm/topi/testing/batch_matmul.py

@@ -0,0 +1,60 @@
+# 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
+"""Batch matmul in python"""
+
+import numpy as np
+
+
+def batch_matmul(x, y, out_dtype=None, trans_x=False, trans_y=True):
+    """batch_matmul operator implemented in numpy.
+
+    Parameters
+    ----------
+    x : numpy.ndarray
+        3-D with shape [batch, M, K]
+
+    y : numpy.ndarray
+        3-D with shape [batch, N, K]
+
+    out_dtype: string, optional
+        Specify the dtype of output
+
+    Returns
+    -------
+    out : numpy.ndarray
+        3-D with shape [batch, M, N]
+    """
+    if trans_x:
+        XB, _, M = x.shape
+    else:
+        XB, M, _ = x.shape
+    if trans_y:
+        YB, N, _ = y.shape
+    else:
+        YB, _, N = y.shape
+    batch = max(XB, YB)
+    dtype = x.dtype if out_dtype is None else out_dtype
+    out = np.zeros((batch, M, N)).astype(dtype)
+    for i in range(batch):
+        xx = x[i if XB != 1 else 0].astype(dtype)
+        yy = y[i if YB != 1 else 0].astype(dtype)
+        out[i] = np.dot(
+            xx.T if trans_x else xx,
+            yy.T if trans_y else yy,
+        )
+    return out