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apache--tvm/python/tvm/topi/testing/batch_matmul.py
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chore: import upstream snapshot with attribution
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Python

# 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