chore: import upstream snapshot with attribution

python/tvm/topi/testing/dense.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
+"""Dense in python"""
+
+import numpy as np
+
+
+def dense(x, y, bias, use_bias=False, use_relu=False, out_dtype=None):
+    """dense operator implemented in numpy.
+
+    Parameters
+    ----------
+    x : numpy.ndarray
+        2-D with shape [M, K]
+
+    y : numpy.ndarray
+        2-D with shape [N, K]
+
+    bias: numpy.ndarray
+        1-D with shape [M,]
+
+    out_dtype: string, optional
+        Specify the dtype of output
+
+    Returns
+    -------
+    out : numpy.ndarray
+        2-D with shape [M, N]
+    """
+    dtype = x.dtype if out_dtype is None else out_dtype
+    if use_bias:
+        out = np.dot(x.astype(dtype), y.T.astype(dtype)) + bias
+    else:
+        out = np.dot(x.astype(dtype), y.T.astype(dtype))
+
+    if use_relu:
+        out = np.maximum(out, 0)
+
+    return out