From 4cabff12d45dd3426557aea7307255bc2d0eb4d1 Mon Sep 17 00:00:00 2001
From: Ted Themistokleous <tthemist@amd.com>
Date: Wed, 25 Oct 2023 11:55:30 -0700
Subject: [PATCH] Add converter for harswish activation

Had to add my owwn migraphx converter as the order of value return to clip would fail the test
---
 .../fx/converters/acc_ops_converters.py       | 26 +++++++++++++++++++
 .../fx/converters/aten_ops_converters.py      | 10 ++++++-
 .../fx/tracer/acc_tracer/acc_ops.py           |  5 ++++
 .../converters/test_activations_dynamo.py     |  1 +
 4 files changed, 41 insertions(+), 1 deletion(-)

diff --git a/py/torch_migraphx/fx/converters/acc_ops_converters.py b/py/torch_migraphx/fx/converters/acc_ops_converters.py
index ef60342b..ba1b6a20 100644
--- a/py/torch_migraphx/fx/converters/acc_ops_converters.py
+++ b/py/torch_migraphx/fx/converters/acc_ops_converters.py
@@ -589,6 +589,32 @@ def acc_ops_hard_sigmoid(mgx_module, node, args, kwargs):
     return mgx_module.add_instruction(migraphx.op('clip'), [add, zeros, ones])
 
 
+@migraphx_converter(acc_ops.hardswish)
+def acc_ops_hard_swish(mgx_module, node, args, kwargs):
+
+    inp = kwargs['input']
+    dtype = get_arg_dtype(inp)
+    shape = inp.shape().lens()
+
+    alpha = mgx_module.add_instruction(
+        migraphx.op('multibroadcast', out_lens=shape),
+        [mgx_module.add_literal(torch.tensor([1 / 6], dtype=dtype).numpy())])
+
+    beta = mgx_module.add_instruction(
+        migraphx.op('multibroadcast', out_lens=shape),
+        [mgx_module.add_literal(torch.tensor([1 / 2], dtype=dtype).numpy())])
+
+    zeros = mgx_module.add_instruction(
+        migraphx.op('multibroadcast', out_lens=shape),
+        [mgx_module.add_literal(torch.tensor([0], dtype=dtype).numpy())])
+
+    mul  = mgx_module.add_instruction(migraphx.op('mul'), [alpha, inp])
+    add = mgx_module.add_instruction(migraphx.op('add'), [beta, mul])
+
+    mul2 = mgx_module.add_instruction(migraphx.op('mul'), [add, inp])
+    return mgx_module.add_instruction(migraphx.op('clip'), [zeros, inp, mul2])
+
+
 @migraphx_converter(acc_ops.softmax)
 def acc_ops_softmax(mgx_module, node, args, kwargs):
 
diff --git a/py/torch_migraphx/fx/converters/aten_ops_converters.py b/py/torch_migraphx/fx/converters/aten_ops_converters.py
index fd3034b8..a61e5fd9 100644
--- a/py/torch_migraphx/fx/converters/aten_ops_converters.py
+++ b/py/torch_migraphx/fx/converters/aten_ops_converters.py
@@ -288,7 +288,15 @@ def aten_ops_leaky_relu(mgx_module, node, args, kwargs):
 
     acc_kwargs = {'input': inp, 'negative_slope': neg_slope}
     return acc_ops_converters.acc_ops_leaky_relu(mgx_module, node, (),
-                                                 acc_kwargs)
+
+
+@migraphx_converter(torch.ops.aten.hardswish.default)
+def aten_ops_hardsigmoid(mgx_module, node, args, kwargs):
+    assert len(args) == 1
+    acc_kwargs = {"input": args[0]}
+
+    return acc_ops_converters.acc_ops_hard_swish(mgx_module, node, (),
+                                                   acc_kwargs)
 
 
 @migraphx_converter(torch.ops.aten.hardsigmoid.default)
diff --git a/py/torch_migraphx/fx/tracer/acc_tracer/acc_ops.py b/py/torch_migraphx/fx/tracer/acc_tracer/acc_ops.py
index f4af53b0..5b53276a 100644
--- a/py/torch_migraphx/fx/tracer/acc_tracer/acc_ops.py
+++ b/py/torch_migraphx/fx/tracer/acc_tracer/acc_ops.py
@@ -446,6 +446,11 @@ def hardsigmoid(*, input):
     return nn.functional.hardsigmoid(input)
 
 
+@register_acc_op
+def hardswish(*, input):
+    return nn.functional.hardswish(input)
+
+
 @register_acc_op_mapping(
     op_and_target=("call_method", "softmax"),
     arg_replacement_tuples=[
diff --git a/tests/dynamo/converters/test_activations_dynamo.py b/tests/dynamo/converters/test_activations_dynamo.py
index b842cd7b..a7321419 100644
--- a/tests/dynamo/converters/test_activations_dynamo.py
+++ b/tests/dynamo/converters/test_activations_dynamo.py
@@ -23,6 +23,7 @@ def test_clamp(op_alias, inp_size):
     torch.ops.aten.relu.default,
     torch.ops.aten.tanh.default,
     torch.ops.aten.hardsigmoid.default,
+    torch.ops.aten.hardswish.default,
     torch.ops.aten.sigmoid.default,
     torch.ops.aten.gelu.default,
     torch.ops.aten.silu.default,