chore: import upstream snapshot with attribution

tests/python/relax/test_op_sampling.py

@@ -0,0 +1,69 @@
+# 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.
+import tvm
+import tvm.testing
+from tvm import relax
+from tvm.script import relax as R
+
+
+def _check_inference(bb: relax.BlockBuilder, call: relax.Call, expected_ty: relax.Type):
+    ret = bb.normalize(call)
+    tvm.ir.assert_structural_equal(ret.ty, expected_ty)
+
+
+def test_multinomial_from_uniform():
+    bb = relax.BlockBuilder()
+    prob0 = relax.Var("prob", R.Tensor((3, 5), "float32"))
+    prob1 = relax.Var("prob", R.Tensor(ndim=2, dtype="float32"))
+    prob2 = relax.Var("prob", R.Tensor(dtype="float32"))
+
+    uniform_sample0 = relax.Var("u", R.Tensor((6, 1), "float32"))
+    uniform_sample1 = relax.Var("u", R.Tensor(ndim=2, dtype="float32"))
+    uniform_sample2 = relax.Var("u", R.Tensor(dtype="float32"))
+
+    sample_indices0 = relax.Var("s", R.Tensor((6, 1), "int64"))
+    sample_indices1 = relax.Var("s", R.Tensor((6, 1), "int32"))
+
+    _check_inference(
+        bb,
+        relax.op.multinomial_from_uniform(prob0, uniform_sample0, sample_indices0),
+        R.Tensor((6, 1), "int64"),
+    )
+    _check_inference(
+        bb,
+        relax.op.multinomial_from_uniform(prob0, uniform_sample0, sample_indices0, dtype="int32"),
+        R.Tensor((6, 1), "int32"),
+    )
+    _check_inference(
+        bb,
+        relax.op.multinomial_from_uniform(prob1, uniform_sample1, sample_indices1),
+        R.Tensor(ndim=2, dtype="int64"),
+    )
+    _check_inference(
+        bb,
+        relax.op.multinomial_from_uniform(prob1, uniform_sample1, sample_indices1, dtype="int32"),
+        R.Tensor(ndim=2, dtype="int32"),
+    )
+    _check_inference(
+        bb,
+        relax.op.multinomial_from_uniform(prob2, uniform_sample2, sample_indices0),
+        R.Tensor(dtype="int64"),
+    )
+
+
+if __name__ == "__main__":
+    tvm.testing.main()