Don't set requires_grad in Arm-backend fold_qdq-pass

It was previously manually set to True for all placeholders as a workaround for an issue where some params did not have requires_grad properly set.
This caused issues for placeholders which were not leaf variables, and since the work around is not needed anyore we can just remove it.

Change-Id: I258cc6ddf7205ab1948e1127f2fceadd2f942beb

Author: AdrianLundell

backends/arm/_passes/fold_qdq_with_annotated_qparams_pass.py

@@ -105,21 +105,6 @@ def fold_and_annotate_arg(
         for arg in arg_list:
             if not isinstance(arg, Node):
                 return
-            """
-             Make sure arg has requires_grad set to False
-             For parameters that are not quantized, sometimes (i.e. convolution)
-             the Parameter(FakeTensor(...)) has requires_grad set to True, which
-             causes the retracing of the graph to fail with:
-
-             E       RuntimeError: isDifferentiableType(variable.scalar_type()) INTERNAL ASSERT FAILED at "/Users/runner/work/pytorch/pytorch/pytorch/torch/csrc/autograd/functions/utils.h":74, please report a bug to PyTorch.
-             E
-             E       While executing %aten_convolution_default : [num_users=1] = call_function[target=executorch.exir.dialects.edge._ops.aten.convolution.default](args = (%quantized_decomposed_quantize_per_tensor_default, %b__frozen_param0, %p__param_constant1, [1, 1], [0, 0], [1, 1], False, [0, 0], 1), kwargs = {})
-             E       Original traceback:
-             E         File "/Users/perast01/src/executorch/backends/arm/test/ops/test_conv2d.py", line 110, in forward
-             E           x = conv(x)
-            """
-            if arg.op == "placeholder":
-                arg.meta["val"].requires_grad = False
 
             arg_quant_params = None
             if arg.target == dq_op: