[GitHub] [tvm] tkonolige commented on a change in pull request #7313: [AutoSchedule] Sparse dense tuning support with custom sketch rule

[GitBox <gi...@apache.org>]

tkonolige commented on a change in pull request #7313:
URL: https://github.com/apache/tvm/pull/7313#discussion_r586586361



##########
File path: python/tvm/auto_scheduler/measure.py
##########
@@ -719,6 +720,45 @@ def local_builder_build(inputs, timeout, n_parallel, build_func="default", verbo
     return results
 
 
+def _prepare_input_map(args):
+    """This function deals with special task inputs.
+
+    Parameters
+    ----------
+    args : List[Tensor]
+        Input/output Tensor of a TVM subgraph.
+
+    Returns
+    -------
+    A Dict[Tensor, str] that maps the input Tensor to a buffer name.
+
+    Note
+    ----
+    The buffer name is specially designed, and these buffer should be provided in
+    `SearchTask(..., task_inputs={...})`.
+    """
+    # pylint: disable=import-outside-toplevel
+    from tvm import topi  # lazily import to avoid recursive dependency
+
+    # A dict that maps the input tensor arg to a buffer name
+    tensor_input_map = {}
+
+    # Case 0: Check placeholder name
+    for arg in args:
+        if isinstance(arg.op, tvm.te.PlaceholderOp):
+            if arg.op.name != "placeholder":
+                tensor_input_map[arg] = arg.op.name
+
+    # Case 1: Check sparse op
+    sparse_input_map = topi.nn.sparse.try_get_sparse_input(args)

Review comment:
       I think I asked this before, but can we have a more general mechanism than checking only for sparse. There are other use cases that require specific input (sorting, scatter).

##########
File path: tests/python/unittest/test_auto_scheduler_search_task.py
##########
@@ -0,0 +1,211 @@
+# 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.
+
+"""Test search policy"""
+
+import random
+import multiprocessing
+import numpy as np
+import tempfile
+
+import tvm
+import tvm.testing
+from tvm import auto_scheduler
+from tvm.auto_scheduler.utils import get_const_tuple
+
+from test_auto_scheduler_common import (
+    matmul_auto_scheduler_test,
+    zero_rank_compute_auto_scheduler_test,
+    zero_rank_reduce_auto_scheduler_test,
+)
+import multiprocessing

Review comment:
       Double unused import of multiprocessing.




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