pytorch · HDCharles · Dec 7, 2022 · Dec 7, 2022 · Dec 7, 2022 · Dec 7, 2022
diff --git a/test/allowlist_for_publicAPI.json b/test/allowlist_for_publicAPI.json
@@ -786,7 +786,7 @@
     "get_quantized_operator",
     "get_static_quant_module_class",
     "get_unique_devices_",
-    "is_activation_post_process",
+    "_is_activation_post_process",
     "load_observer_state_dict",
     "no_observer_set",
     "prepare",
@@ -894,7 +894,7 @@
     "convert",
     "get_observer_dict",
     "get_unique_devices_",
-    "is_activation_post_process",
+    "_is_activation_post_process",
     "prepare",
     "prepare_qat",
     "propagate_qconfig_",

diff --git a/test/quantization/ao_migration/test_ao_migration.py b/test/quantization/ao_migration/test_ao_migration.py
@@ -19,7 +19,7 @@ def test_function_import_quantize(self):
             'convert',
             'get_observer_dict',
             'get_unique_devices_',
-            'is_activation_post_process',
+            '_is_activation_post_process',
             'prepare',
             'prepare_qat',
             'propagate_qconfig_',

diff --git a/test/quantization/ao_migration/test_quantization.py b/test/quantization/ao_migration/test_quantization.py
@@ -22,7 +22,7 @@ def test_function_import_quantize(self):
             'convert',
             'get_observer_dict',
             'get_unique_devices_',
-            'is_activation_post_process',
+            '_is_activation_post_process',
             'prepare',
             'prepare_qat',
             'propagate_qconfig_',

diff --git a/test/quantization/fx/test_quantize_fx.py b/test/quantization/fx/test_quantize_fx.py
@@ -56,7 +56,6 @@
     get_default_qat_qconfig,
     get_default_qconfig_mapping,
     get_default_qat_qconfig_mapping,
-    is_activation_post_process,
     fuse_modules,
     fuse_modules_qat,
     prepare,
@@ -146,6 +145,7 @@
     default_fixed_qparams_range_0to1_observer,
     default_fixed_qparams_range_neg1to1_observer,
     MinMaxObserver,
+    _is_activation_post_process,
 )
 
 # test utils
@@ -3292,7 +3292,7 @@ def _check_node_not_observed(model, arg_node, node):
                     _check_node_not_observed(model, new_node, node)
             elif arg_node.op == "call_module":
                 self.assertTrue(
-                    not is_activation_post_process(getattr(model, arg_node.target)),
+                    not _is_activation_post_process(getattr(model, arg_node.target)),
                     "Arg: {0} of node: {1} is observed but is not a float tensor".format(
                         arg_node, node
                     ),
@@ -5051,7 +5051,7 @@ def forward(self, x):
                 qconfig_dict = func(backend)
                 m = prepare_fx(m, qconfig_dict, example_inputs=(torch.randn(1, 1, 1, 1)))
                 for name, mod in m.named_modules():
-                    if is_activation_post_process(mod) and mod.dtype == torch.quint8:
+                    if _is_activation_post_process(mod) and mod.dtype == torch.quint8:
                         if backend == "fbgemm":
                             lower_bnd = 0
                             upper_bnd = 127

diff --git a/torch/ao/ns/fx/graph_passes.py b/torch/ao/ns/fx/graph_passes.py
@@ -24,7 +24,7 @@
 from torch.ao.ns.fx.mappings import (
     get_node_type_to_io_type_map,
 )
-from torch.ao.quantization.quantize import is_activation_post_process
+from torch.ao.quantization.observer import _is_activation_post_process
 
 from typing import Dict, Tuple, Callable, List, Any, Union, Optional, Set
 
@@ -38,7 +38,7 @@ def _maybe_get_fqn(node: Node, gm: GraphModule) -> Optional[str]:
         if node.op == 'call_module':
             assert isinstance(node.target, str)
             module = getattr_from_fqn(gm, node.target)
-            if is_activation_post_process(module):
+            if _is_activation_post_process(module):
                 node_to_use_for_fqn = get_normalized_nth_input(node, gm, 0)
         fqn = gm._node_name_to_scope[node_to_use_for_fqn.name][0]  # type: ignore[index]
     return fqn  # type: ignore[return-value]

diff --git a/torch/ao/ns/fx/utils.py b/torch/ao/ns/fx/utils.py
@@ -16,7 +16,7 @@
     FakeQuantizeBase,
 )
 from torch.ao.quantization.utils import getattr_from_fqn
-from torch.ao.quantization.quantize import is_activation_post_process
+from torch.ao.quantization.observer import _is_activation_post_process
 
 from .ns_types import NSNodeTargetType, NSResultsType
 
@@ -256,14 +256,14 @@ def return_first_non_observer_node(
     """
     if node.op == "call_module":
         node_obj = getattr_from_fqn(gm, node.target)  # type: ignore[arg-type]
-        if is_activation_post_process(node_obj):
+        if _is_activation_post_process(node_obj):
             assert len(node.args) == 1
             assert isinstance(node.args[0], Node)
             node = node.args[0]
             # code duplication intended, not worth refactoring
             assert isinstance(node.target, str)
             node_obj = getattr_from_fqn(gm, node.target)
-            if is_activation_post_process(node_obj):
+            if _is_activation_post_process(node_obj):
                 assert len(node.args) == 1
                 assert isinstance(node.args[0], Node)
                 node = node.args[0]

diff --git a/torch/ao/quantization/__init__.py b/torch/ao/quantization/__init__.py
@@ -114,7 +114,6 @@
     "get_quantized_operator",
     "get_static_quant_module_class",
     "get_unique_devices_",
-    "is_activation_post_process",
     "load_observer_state_dict",
     "no_observer_set",
     "per_channel_weight_observer_range_neg_127_to_127",

diff --git a/torch/ao/quantization/fx/_model_report/detector.py b/torch/ao/quantization/fx/_model_report/detector.py
@@ -23,7 +23,7 @@
     default_equalization_qconfig,
     EqualizationQConfig,
 )
-from torch.ao.quantization.quantize import is_activation_post_process
+from torch.ao.quantization.observer import _is_activation_post_process
 
 # Names for observer insert keys
 DETECTOR_TARGET_NODE_KEY = "target_node"
@@ -1273,7 +1273,7 @@ def _supports_insertion(self, module: nn.Module) -> bool:
         # case for insertion of module
         # check if the module has any children and isn't observer
         num_children = len(list(module.children()))
-        return num_children == 0 and not is_activation_post_process(module)
+        return num_children == 0 and not _is_activation_post_process(module)
 
     def get_qconfig_info(self, model) -> Dict[str, DetectorQConfigInfo]:
         r""" Returns the DetectorQConfigInfo for each module_fqn relavent

diff --git a/torch/ao/quantization/fx/convert.py b/torch/ao/quantization/fx/convert.py
@@ -40,6 +40,7 @@
     BackendConfig,
     get_native_backend_config,
 )
+from torch.ao.quantization.observer import _is_activation_post_process
 from .graph_module import (
     QuantizedGraphModule,
     is_observed_module,
@@ -62,7 +63,6 @@
 )
 from torch.ao.quantization.quantize import (
     _remove_qconfig,
-    is_activation_post_process,
 )
 from torch.ao.quantization.stubs import DeQuantStub
 from .custom_config import (
@@ -582,7 +582,7 @@ def maybe_get_observer_for_node(
     for maybe_obs_node, _ in node.users.items():
         if maybe_obs_node.op == 'call_module':
             maybe_obs = modules[str(maybe_obs_node.target)]
-            if is_activation_post_process(maybe_obs):
+            if _is_activation_post_process(maybe_obs):
                 return maybe_obs
     return None
 
@@ -1010,7 +1010,7 @@ def convert(
         elif node.op == "call_module":
             mod = _get_module(node, modules)
             assert mod is not None
-            if is_activation_post_process(mod):
+            if _is_activation_post_process(mod):
                 observed_node = node.args[0]
                 if observed_node in statically_quantized_custom_module_nodes:
                     _replace_observer_or_dequant_stub_with_dequantize_node(node, model.graph)

diff --git a/torch/ao/quantization/fx/prepare.py b/torch/ao/quantization/fx/prepare.py
@@ -16,6 +16,7 @@
 )
 from ..observer import (
     ObserverBase,
+    _is_activation_post_process
 )
 from ..qconfig import (
     _is_reuse_input_qconfig,
@@ -78,7 +79,6 @@
 )
 
 from torch.ao.quantization.quantize import (
-    is_activation_post_process,
     convert
 )
 
@@ -144,7 +144,7 @@
 
 def is_activation_post_process_node(node: Node, modules: Dict[str, torch.nn.Module]) -> bool:
     return isinstance(node, torch.fx.Node) and node.op == "call_module" and \
-        is_activation_post_process(modules[str(node.target)])
+        _is_activation_post_process(modules[str(node.target)])
 
 def is_input_arg_dtype_supported_by_backend(
     arg: Argument,

diff --git a/torch/ao/quantization/fx/qconfig_mapping_utils.py b/torch/ao/quantization/fx/qconfig_mapping_utils.py
@@ -4,8 +4,8 @@
 from typing import Callable, Any, Dict, Tuple, Set, List, Union
 from torch.ao.quantization import QConfig
 from torch.ao.quantization.qconfig import _add_module_to_qconfig_obs_ctr, QConfigAny, qconfig_equals
-from torch.ao.quantization.quantize import (
-    is_activation_post_process,
+from torch.ao.quantization.observer import (
+    _is_activation_post_process,
 )
 from torch.ao.quantization.backend_config import (
     DTypeConfig,
@@ -158,7 +158,7 @@ def generate_node_name_to_qconfig(
 
         elif node.op == 'call_module':
             # if the node is an observer, just continue - don't add it to the qconfig_map
-            if is_activation_post_process(modules[node.target]):
+            if _is_activation_post_process(modules[node.target]):
                 continue
             qconfig = _maybe_adjust_qconfig_for_module_type_or_name(
                 qconfig_mapping, type(modules[node.target]), node.target, global_qconfig)

diff --git a/torch/ao/quantization/fx/utils.py b/torch/ao/quantization/fx/utils.py
@@ -23,8 +23,10 @@
     qconfig_equals,
 )
 from torch.ao.quantization.stubs import DeQuantStub
-from torch.ao.quantization.utils import activation_is_statically_quantized
-from torch.ao.quantization.quantize import is_activation_post_process
+from torch.ao.quantization.utils import (
+    activation_is_statically_quantized,
+)
+from torch.ao.quantization.observer import _is_activation_post_process
 
 from torch.fx import GraphModule, map_arg
 
@@ -248,7 +250,7 @@ def all_node_args_have_no_tensors(node: Node, modules: Dict[str, torch.nn.Module
         result = False
     elif node.op == 'call_module':
         assert isinstance(node.target, str)
-        if is_activation_post_process(modules[node.target]):
+        if _is_activation_post_process(modules[node.target]):
             result = all_node_args_have_no_tensors(node.args[0], modules, cache)  # type: ignore[arg-type]
     elif node.op == 'call_module':
         result = False
@@ -825,7 +827,7 @@ def _activation_post_process_satisfies_dtype_config_constraints(
     satisfies_constraints = True
     if activation_post_process_ctr is not None:
         activation_post_process = activation_post_process_ctr()
-        assert is_activation_post_process(activation_post_process)
+        assert _is_activation_post_process(activation_post_process)
         # If dtypes don't match, don't check the activation_post_process and return True early
         if activation_post_process.dtype != dtype_with_constraints.dtype:
             return True

diff --git a/torch/ao/quantization/observer.py b/torch/ao/quantization/observer.py
@@ -1449,7 +1449,7 @@ def _is_observer_script_module(mod, obs_type_name):
 def _is_activation_post_process(module):
     return (
         isinstance(module, torch.ao.quantization.ObserverBase)
-        or isinstance(module, torch.ao.quantization.FakeQuantize)
+        or isinstance(module, torch.ao.quantization.FakeQuantizeBase)
         or _is_observer_script_module(module, "quantization.observer")
     )
 

diff --git a/torch/ao/quantization/quantize.py b/torch/ao/quantization/quantize.py
@@ -27,10 +27,15 @@
     float_qparams_weight_only_qconfig_4bit,
     _activation_is_memoryless)
 from torch.nn.utils.parametrize import type_before_parametrizations
+from torch.ao.quantization.observer import _is_activation_post_process
+
+# TODO remove this once BC is no longer required to avoid a SEV
+from torch.ao.quantization.observer import (   # noqa: F401
+    _is_activation_post_process as is_activation_post_process
+)
 
 __all__ = [
     "get_default_custom_config_dict",
-    "is_activation_post_process",
     "propagate_qconfig_",
     "register_activation_post_process_hook",
     "add_observer_",
@@ -62,11 +67,6 @@ def get_default_custom_config_dict():
     """
     return _DEFAULT_CUSTOM_CONFIG_DICT
 
-def is_activation_post_process(module):
-    return (isinstance(module, torch.ao.quantization.ObserverBase) or
-            isinstance(module, torch.ao.quantization.FakeQuantizeBase))
-
-
 def _propagate_qconfig_helper(module, qconfig_dict,
                               qconfig_parent=None, prefix='', prepare_custom_config_dict=None):
     r"""This is a helper function for `propagate_qconfig_`
@@ -324,7 +324,7 @@ def _remove_activation_post_process(module):
     # TODO: maybe we should change activation_post_process to _activation_post_process
     # to prevent it from being used by user
     if hasattr(module, 'activation_post_process') and \
-       is_activation_post_process(module.activation_post_process):
+       _is_activation_post_process(module.activation_post_process):
         delattr(module, 'activation_post_process')
 
     # remove activation_post_proceess pre and post hooks

diff --git a/torch/quantization/quantize.py b/torch/quantization/quantize.py
@@ -17,7 +17,7 @@
 from torch.ao.quantization.quantize import convert
 from torch.ao.quantization.quantize import get_observer_dict
 from torch.ao.quantization.quantize import get_unique_devices_
-from torch.ao.quantization.quantize import is_activation_post_process
+from torch.ao.quantization.quantize import _is_activation_post_process
 from torch.ao.quantization.quantize import prepare
 from torch.ao.quantization.quantize import prepare_qat
 from torch.ao.quantization.quantize import propagate_qconfig_