chore: import upstream snapshot with attribution

python/tvm/contrib/cblas.py

@@ -0,0 +1,94 @@
+# 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.
+"""External function interface to BLAS libraries."""
+
+import tvm
+from tvm import te
+
+
+def matmul(lhs, rhs, transa=False, transb=False, **kwargs):
+    """Create an extern op that compute matrix mult of A and rhs with CrhsLAS
+    This function serves as an example on how to call external libraries.
+
+    Parameters
+    ----------
+    lhs: Tensor
+        The left matrix operand
+    rhs: Tensor
+        The right matrix operand
+    transa: bool
+        Whether transpose lhs
+    transb: bool
+        Whether transpose rhs
+
+    Returns
+    -------
+    C: Tensor
+        The result tensor.
+    """
+    n = lhs.shape[1] if transa else lhs.shape[0]
+    m = rhs.shape[0] if transb else rhs.shape[1]
+    return te.extern(
+        (n, m),
+        [lhs, rhs],
+        lambda ins, outs: tvm.tirx.call_packed(
+            "tvm.contrib.cblas.matmul", ins[0], ins[1], outs[0], transa, transb
+        ),
+        name="C",
+        **kwargs,
+    )
+
+
+def batch_matmul(lhs, rhs, transa=False, transb=False, iterative=False, **kwargs):
+    """Create an extern op that compute batched matrix mult of A and rhs with CBLAS
+    This function serves as an example on how to call external libraries.
+
+    Parameters
+    ----------
+    lhs: Tensor
+        The left matrix operand
+    rhs: Tensor
+        The right matrix operand
+    transa: bool
+        Whether transpose lhs
+    transb: bool
+        Whether transpose rhs
+
+    Returns
+    -------
+    C: Tensor
+        The result tensor.
+    """
+    b = te.max(lhs.shape[0], rhs.shape[0])
+    n = lhs.shape[2] if transa else lhs.shape[1]
+    m = rhs.shape[1] if transb else rhs.shape[2]
+    return te.extern(
+        (b, n, m),
+        [lhs, rhs],
+        lambda ins, outs: tvm.tirx.call_packed(
+            "tvm.contrib.cblas.batch_matmul"
+            if not iterative
+            else "tvm.contrib.cblas.batch_matmul_iterative",
+            ins[0],
+            ins[1],
+            outs[0],
+            transa,
+            transb,
+        ),
+        name="C",
+        **kwargs,
+    )