[GitHub] [tvm] masahi commented on a diff in pull request #12919: [HEXAGON][QHL] Clippling the inputs of HVX version of QHL Sigmoid operation

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

masahi commented on code in PR #12919:
URL: https://github.com/apache/tvm/pull/12919#discussion_r981635192


##########
tests/python/contrib/test_hexagon/test_sigmoid.py:
##########
@@ -0,0 +1,118 @@
+# 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 numpy as np
+import pytest
+
+import tvm
+import tvm.testing
+from tvm import te
+from tvm import tir
+from tvm import topi
+from tvm.contrib.hexagon.build import HexagonLauncher
+
+from .infrastructure import allocate_hexagon_array, transform_numpy
+
+def sigmoid_compute(Input):
+    return topi.sigmoid(Input)
+
+
+def sigmoid_stir_schedule(Input, Output):
+    sigmoid_func = te.create_prim_func([Input, Output])
+    sch = tir.Schedule(sigmoid_func, debug_mask="all")
+    block = sch.get_block("compute")
+
+    n, = sch.get_loops(block)
+    sch.vectorize(n)
+    return sch
+
+
+@tvm.testing.fixture
+def input_np(in_shape, dtype, min_val, max_val):
+    return np.random.uniform(low=min_val, high=max_val, size=in_shape).astype(dtype)
+
+
+@tvm.testing.fixture
+def ref_output_np(input_np):
+    output_np = 1 / (1 + np.exp(-input_np))
+    return output_np
+
+
+class BaseSigmoid:
+    (
+        in_shape,
+        dtype,
+        min_val,
+        max_val,
+    ) = tvm.testing.parameters(
+        ((64,), "float16", -8.0, 8.0),
+        ((64,), "float16", -6.0, 7.0),
+        ((64,), "float16", -10.0, 15.0),
+        ((64,), "float16", -10.0, 0.0),
+        ((64,), "float16", 0.0, 10.0),
+    )
+
+
+class TestSigmoid(BaseSigmoid):
+    @tvm.testing.requires_hexagon
+    def test_sigmoid(
+        self,
+        in_shape,
+        dtype,
+        input_np,
+        ref_output_np,
+        target,
+        hexagon_session,
+    ):
+        InputTensor = te.placeholder(in_shape, name="InputTensor", dtype=dtype)
+
+        OutputTensor = sigmoid_compute(InputTensor)
+
+        target_hexagon = tvm.target.hexagon("v69")
+        target = tvm.target.Target(target_hexagon, host=target_hexagon)
+
+        tir_s = sigmoid_stir_schedule(InputTensor, OutputTensor)
+
+        input_data = allocate_hexagon_array(
+            hexagon_session.device,
+            data=input_np,
+        )
+        output_data = allocate_hexagon_array(
+            hexagon_session.device,
+            tensor_shape=ref_output_np.shape,
+            dtype=ref_output_np.dtype,
+        )
+
+        func_name = "sigmoid"
+        with tvm.transform.PassContext(opt_level=3):
+            runtime_module = tvm.build(tir_s.mod, target=target, name=func_name)

Review Comment:
   Can we check the generated asm to make sure that the HVX sigmoid is generated? It needs QHL to be enabled on Hexagon CI.



-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: commits-unsubscribe@tvm.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org