tanh float16 (apache#12165)

Co-authored-by: aakaverm <aakaverm@qti.qualcomm.com>

python/tvm/topi/hexagon/slice_ops/__init__.py

@@ -32,3 +32,4 @@
 from .conv2d import *
 from .reshape import reshape_compute, reshape_stir_schedule
 from .relu import relu_compute, relu_stir_schedule
+from .tanh import tanh_te_compute, tanhf16_schedule

python/tvm/topi/hexagon/slice_ops/tanh.py

@@ -0,0 +1,56 @@
+# 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.
+# pylint: disable=invalid-name
+
+""" Hexagon tanh slice op compute and schedule """
+import tvm
+from tvm import te, tir
+from ..utils import get_layout_transform_fn
+
+
+def tanh_te_compute(in_tensor):
+    out_tensor = te.compute(
+        in_tensor.shape, lambda n, h, w, c: tvm.tir.tanh(in_tensor[n, h, w, c]), name="tanhf16"
+    )
+    return out_tensor
+
+
+def tanhf16_stir_sched_nhwc(func, in_layout, out_layout, h_split_factor=8):
+    """Schedule for nhwc fp16 to nchw fp16 layout"""
+    sch = tir.Schedule(func, debug_mask="all")
+    block_name = "tanhf16"
+    n, h, w, c = sch.get_loops(sch.get_block(block_name))
+    h_outer, h_inner = sch.split(h, [None, h_split_factor])
+    w_outer, w_inner = sch.split(w, [None, 4])
+    c_outer, c_inner = sch.split(c, [None, 32])
+    w_inner_o, w_inner_i = sch.split(w_inner, [None, 2])
+    sch.reorder(n, h_outer, w_outer, c_outer, h_inner, w_inner_o, c_inner, w_inner_i)
+    sch.transform_layout(block_name, "A", in_layout)
+    sch.transform_layout(block_name, block_name, out_layout)
+    fused = sch.fuse(c_inner, w_inner_i)
+    sch.vectorize(fused)
+    return sch
+
+
+def tanhf16_schedule(tanh_func, in_layout_str, out_layout_str):
+    in_layout_transform_func = get_layout_transform_fn(in_layout_str)
+    out_layout_transform_func = get_layout_transform_fn(out_layout_str)
+    return tanhf16_stir_sched_nhwc(
+        tanh_func,
+        in_layout_transform_func,
+        out_layout_transform_func,
+    )

tests/python/contrib/test_hexagon/topi/test_tanh_slice.py

@@ -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))