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954ce94950
This PR is part of a series attempting to re-submit https://github.com/pytorch/pytorch/pull/134592 as smaller PRs. In quantization tests: - Add and use a common raise_on_run_directly method for when a user runs a test file directly which should not be run this way. Print the file which the user should have run. - Raise a RuntimeError on tests which have been disabled (not run) Pull Request resolved: https://github.com/pytorch/pytorch/pull/154728 Approved by: https://github.com/ezyang
159 lines
5.5 KiB
Python
159 lines
5.5 KiB
Python
# Owner(s): ["oncall: quantization"]
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from torch.testing._internal.common_utils import raise_on_run_directly
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from .common import AOMigrationTestCase
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class TestAOMigrationQuantizationFx(AOMigrationTestCase):
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def test_function_import_quantize_fx(self):
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function_list = [
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"_check_is_graph_module",
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"_swap_ff_with_fxff",
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"_fuse_fx",
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"QuantizationTracer",
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"_prepare_fx",
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"_prepare_standalone_module_fx",
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"fuse_fx",
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"Scope",
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"ScopeContextManager",
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"prepare_fx",
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"prepare_qat_fx",
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"_convert_fx",
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"convert_fx",
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"_convert_standalone_module_fx",
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]
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self._test_function_import("quantize_fx", function_list)
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def test_function_import_fx(self):
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function_list = [
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"prepare",
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"convert",
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"fuse",
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]
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self._test_function_import("fx", function_list)
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def test_function_import_fx_graph_module(self):
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function_list = [
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"FusedGraphModule",
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"ObservedGraphModule",
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"_is_observed_module",
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"ObservedStandaloneGraphModule",
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"_is_observed_standalone_module",
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"QuantizedGraphModule",
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]
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self._test_function_import("fx.graph_module", function_list)
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def test_function_import_fx_pattern_utils(self):
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function_list = [
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"QuantizeHandler",
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"_register_fusion_pattern",
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"get_default_fusion_patterns",
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"_register_quant_pattern",
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"get_default_quant_patterns",
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"get_default_output_activation_post_process_map",
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]
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self._test_function_import("fx.pattern_utils", function_list)
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def test_function_import_fx_equalize(self):
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function_list = [
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"reshape_scale",
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"_InputEqualizationObserver",
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"_WeightEqualizationObserver",
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"calculate_equalization_scale",
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"EqualizationQConfig",
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"input_equalization_observer",
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"weight_equalization_observer",
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"default_equalization_qconfig",
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"fused_module_supports_equalization",
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"nn_module_supports_equalization",
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"node_supports_equalization",
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"is_equalization_observer",
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"get_op_node_and_weight_eq_obs",
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"maybe_get_weight_eq_obs_node",
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"maybe_get_next_input_eq_obs",
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"maybe_get_next_equalization_scale",
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"scale_input_observer",
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"scale_weight_node",
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"scale_weight_functional",
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"clear_weight_quant_obs_node",
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"remove_node",
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"update_obs_for_equalization",
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"convert_eq_obs",
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"_convert_equalization_ref",
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"get_layer_sqnr_dict",
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"get_equalization_qconfig_dict",
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]
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self._test_function_import("fx._equalize", function_list)
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def test_function_import_fx_quantization_patterns(self):
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function_list = [
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"QuantizeHandler",
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"BinaryOpQuantizeHandler",
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"CatQuantizeHandler",
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"ConvReluQuantizeHandler",
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"LinearReLUQuantizeHandler",
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"BatchNormQuantizeHandler",
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"EmbeddingQuantizeHandler",
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"RNNDynamicQuantizeHandler",
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"DefaultNodeQuantizeHandler",
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"FixedQParamsOpQuantizeHandler",
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"CopyNodeQuantizeHandler",
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"CustomModuleQuantizeHandler",
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"GeneralTensorShapeOpQuantizeHandler",
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"StandaloneModuleQuantizeHandler",
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]
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self._test_function_import(
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"fx.quantization_patterns",
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function_list,
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new_package_name="fx.quantize_handler",
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)
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def test_function_import_fx_match_utils(self):
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function_list = ["_MatchResult", "MatchAllNode", "_is_match", "_find_matches"]
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self._test_function_import("fx.match_utils", function_list)
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def test_function_import_fx_prepare(self):
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function_list = ["prepare"]
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self._test_function_import("fx.prepare", function_list)
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def test_function_import_fx_convert(self):
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function_list = ["convert"]
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self._test_function_import("fx.convert", function_list)
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def test_function_import_fx_fuse(self):
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function_list = ["fuse"]
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self._test_function_import("fx.fuse", function_list)
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def test_function_import_fx_fusion_patterns(self):
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function_list = ["FuseHandler", "DefaultFuseHandler"]
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self._test_function_import(
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"fx.fusion_patterns",
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function_list,
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new_package_name="fx.fuse_handler",
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)
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# we removed matching test for torch.quantization.fx.quantization_types
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# old: torch.quantization.fx.quantization_types
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# new: torch.ao.quantization.utils
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# both are valid, but we'll deprecate the old path in the future
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def test_function_import_fx_utils(self):
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function_list = [
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"get_custom_module_class_keys",
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"get_linear_prepack_op_for_dtype",
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"get_qconv_prepack_op",
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"get_new_attr_name_with_prefix",
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"graph_module_from_producer_nodes",
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"assert_and_get_unique_device",
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"create_getattr_from_value",
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"all_node_args_have_no_tensors",
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"get_non_observable_arg_indexes_and_types",
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"maybe_get_next_module",
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]
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self._test_function_import("fx.utils", function_list)
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if __name__ == "__main__":
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raise_on_run_directly("test/test_quantization.py")
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