[GitHub] [tvm] mehrdadh commented on a diff in pull request #12165: [TOPI] [HEXAGON] Tanh Float16 Slice Op

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

mehrdadh commented on code in PR #12165:
URL: https://github.com/apache/tvm/pull/12165#discussion_r929112740


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tests/python/contrib/test_hexagon/topi/test_tanh_slice.py:
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@@ -0,0 +1,109 @@
+# 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 for Hexagon slice tanh op """
+import numpy as np
+import pytest
+
+import tvm
+import tvm.testing
+from tvm import te
+import tvm.topi.hexagon.slice_ops as sl
+import tvm.contrib.hexagon
+from ..infrastructure import allocate_hexagon_array, transform_numpy
+
+# pylint: disable=invalid-name
+
+
+class TestTanhSlice:
+    """For Testing Tanh fp16 op"""
+
+    input_shape, orig_layout, input_layout, output_layout, axis_sep = tvm.testing.parameters(
+        ((1, 8, 4, 32), "nhwc", "nhwc-8h2w32c2w-2d", "nhwc-8h2w32c2w-2d", [4]),
+        ((1, 16, 12, 64), "nhwc", "nhwc-8h2w32c2w-2d", "nhwc-8h2w32c2w-2d", [4]),
+        ((1, 64, 64, 32), "nhwc", "nhwc-8h2w32c2w-2d", "nhwc-8h2w32c2w-2d", [4]),
+    )
+    dtype = tvm.testing.parameter("float16")
+    working_scope = tvm.testing.parameter("global.vtcm")
+
+    @tvm.testing.fixture
+    def input_np(self, input_shape, dtype):
+        return np.random.uniform(size=input_shape).astype(dtype)
+
+    @tvm.testing.fixture
+    def transformed_input_np(self, input_np, orig_layout, input_layout):
+        return transform_numpy(input_np, orig_layout, input_layout)
+
+    @tvm.testing.fixture
+    def expected_output_np(self, input_np):
+        ref_np = np.tanh(input_np)
+        return ref_np
+
+    @tvm.testing.fixture
+    def transformed_expected_output_np(self, expected_output_np, orig_layout, output_layout):
+        return transform_numpy(expected_output_np, orig_layout, output_layout)
+
+    @tvm.testing.requires_hexagon
+    def test_tanh(
+        self,
+        input_shape,
+        dtype,
+        input_layout,
+        output_layout,
+        transformed_input_np,
+        transformed_expected_output_np,
+        axis_sep,
+        hexagon_session,
+        working_scope,
+    ):
+        """Top Level testing function for tanh fp16 op"""
+
+        target_hexagon = tvm.target.hexagon("v69")
+        target = tvm.target.Target(target_hexagon, host=target_hexagon)
+        A = te.placeholder(input_shape, name="A", dtype=dtype)
+        M = sl.tanh_te_compute(A)
+        tanhf16_func = te.create_prim_func([A, M])
+        tir_s = sl.tanhf16_schedule(tanhf16_func, input_layout, output_layout)
+        A_data = allocate_hexagon_array(
+            hexagon_session.device,
+            data=transformed_input_np,
+            axis_separators=axis_sep,
+            mem_scope=working_scope,
+        )
+        M_data = allocate_hexagon_array(
+            hexagon_session.device,
+            tensor_shape=transformed_expected_output_np.shape,
+            dtype=transformed_expected_output_np.dtype,
+            axis_separators=axis_sep,
+            mem_scope=working_scope,
+        )
+        with tvm.transform.PassContext(opt_level=3):
+            tir_irm = tvm.lower(tir_s.mod, [A, M], name="tanhf16")
+            runtime_module = tvm.build(tir_irm, target=target, name="tanhf16")
+        mod = hexagon_session.load_module(runtime_module)
+
+        mod(A_data, M_data)
+        output_np = M_data.numpy()
+        tvm.testing.assert_allclose(
+            output_np,
+            transformed_expected_output_np,
+            1e-3,
+            1e-3,
+        )
+
+
+if __name__ == "__main__":
+    sys.exit(pytest.main(sys.argv))

Review Comment:
   please change this to tvm convention in a future PR:
   tvm.testing.main()



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