[QNN] Doc fix on convolution and dequantize

[masahi]

cc @anijain2305 @vinx13 can you check if this change is correct? I'm a bit confused about input/output scale terminology.

I'm not completely sure if kernel_size is required, but I hit error if I leave it none.

[masahi]

this is the error I get if I leave out kernel_size:

  File "/home/masa/projects/dev/tvm/python/tvm/_ffi/_ctypes/function.py", line 72, in cfun
    rv = local_pyfunc(*pyargs)
  File "/home/masa/projects/dev/tvm/python/tvm/relay/op/nn/_nn.py", line 269, in alter_op_layout_conv2d
    return topi.nn.conv2d_alter_layout(attrs, inputs, tinfos, op)
  File "</home/masa/anaconda3/lib/python3.7/site-packages/decorator.py:decorator-gen-37>", line 2, in conv2d_alter_layout
  File "/home/masa/projects/dev/tvm/python/tvm/target.py", line 382, in dispatch_func
    return dispatch_dict[k](*args, **kwargs)
  File "/home/masa/projects/dev/tvm/topi/python/topi/x86/conv2d_alter_op.py", line 45, in _alter_conv2d_layout
    kh, kw = attrs.get_int_tuple("kernel_size")
  File "/home/masa/projects/dev/tvm/python/tvm/attrs.py", line 63, in get_int_tuple
    return tuple(x.value for x in self.__getattr__(key))
TypeError: 'NoneType' object is not iterable

[anijain2305]

Thank you for fixing this :) LGTM