Add converter for harswish activation

Had to add my owwn migraphx converter as the order of value return to clip would fail the test

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):
 

py/torch_migraphx/fx/converters/aten_ops_converters.py

@@ -290,6 +290,14 @@ def aten_ops_leaky_relu(mgx_module, node, args, kwargs):
     return acc_ops_converters.acc_ops_leaky_relu(mgx_module, node, (),
                                                  acc_kwargs)
 
+@migraphx_converter(torch.ops.aten.hardswish.default)
+def aten_ops_hardswish(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)
 def aten_ops_hardsigmoid(mgx_module, node, args, kwargs):

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=[

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,