| /external/tensorflow/tensorflow/lite/python/optimize/ |
| D | calibrator_test.py | 45 quantized_model = quantizer.calibrate_and_quantize(input_gen,
50 self.assertIsNotNone(quantized_model)
68 quantized_model = quantizer.calibrate_and_quantize(input_gen,
73 self.assertIsNotNone(quantized_model)
86 quantized_model = quantizer.calibrate_and_quantize_single(
88 self.assertIsNotNone(quantized_model)
101 quantized_model = quantizer.calibrate_and_quantize_single(
103 self.assertIsNotNone(quantized_model)
124 quantized_model = quantizer.calibrate_and_quantize(input_gen,
129 self.assertIsNotNone(quantized_model)
[all …]
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| /external/pytorch/torch/ao/quantization/ |
| D | _correct_bias.py | 98 quantized_model, argument
119 float_model, quantized_model, _supported_modules, MeanShadowLogger
123 for name, submodule in quantized_model.named_modules():
128 quantized_submodule = get_module(quantized_model, uncorrected_module)
133 quantized_model(data[0])
137 ob_dict = ns.get_logger_dict(quantized_model)
155 for name, submodule in quantized_model.named_modules():
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| /external/pytorch/test/quantization/core/experimental/ |
| D | apot_fx_graph_mode_ptq.py | 69 quantized_model = convert_fx(prepared_model) # convert the calibrated model to a quantized model … variable
71 top1, top5 = evaluate(quantized_model, criterion, data_loader_test)
80 quantized_model = convert_fx(prepared_model) # convert the calibrated model to a quantized model … variable
|
| /external/executorch/examples/mediatek/aot_utils/oss_utils/ |
| D | utils.py | 39 quantized_model = convert_pt2e(annotated_model, fold_quantize=False)
40 aten_dialect = torch.export.export(quantized_model, inputs)
|
| /external/executorch/backends/cadence/aot/ |
| D | export_example.py | 86 quantized_model = fuse_pt2(converted_model, quantizer)
90 quantized_model, example_inputs, output_dir=working_dir
|
| D | compiler.py | 222 quantized_model = quantize_pt2(model, inputs)
225 quantized_model,
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| /external/pytorch/test/mobile/ |
| D | test_lite_script_module.py | 506 quantized_model = self._create_quantized_model(
509 self._compare_script_and_mobile(model=quantized_model, input=input)
513 quantized_model = self._create_quantized_model(model_class=TwoLayerLinearModel)
514 self._compare_script_and_mobile(model=quantized_model, input=input)
518 quantized_model = self._create_quantized_model(
521 self._compare_script_and_mobile(model=quantized_model, input=input)
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| /external/pytorch/torch/ao/quantization/fx/ |
| D | _lower_to_native_backend.py | 446 quantized_model: GraphModule, node_name_to_scope: Dict[str, Tuple[str, type]]
457 for node in quantized_model.graph.nodes:
465 quantized_model, nodes_to_fold
477 for node in quantized_model.graph.nodes:
487 packed_weight_name = get_new_packed_weight_name(quantized_model)
488 setattr(quantized_model, packed_weight_name, packed_weight)
500 quantized_model = GraphModule(quantized_model, folded_graph)
501 quantized_model._register_state_dict_hook(_save_packed_weight)
502 quantized_model.register_load_state_dict_pre_hook(_load_packed_weight)
503 return quantized_model
|
| /external/executorch/examples/xnnpack/quantization/ |
| D | example.py | 182 quantized_model = quantize(model, example_inputs)
189 quantized_model, example_inputs, edge_compile_config=edge_compile_config
|
| /external/tensorflow/tensorflow/lite/java/ovic/src/testdata/ |
| D | BUILD | 14 "@tflite_ovic_testdata//:quantized_model.lite",
|
| /external/executorch/exir/tests/ |
| D | test_memory_planning.py | 430 quantized_model = eager_model
444 quantized_model,
457 quantized_model,
469 return quantized_model
|
| /external/executorch/examples/models/llama/source_transformation/ |
| D | quantize.py | 74 return WeightOnlyInt8QuantHandler(model).quantized_model()
284 def quantized_model(self) -> nn.Module: member in QuantHandler
386 def quantized_model(self) -> nn.Module: member in WeightOnlyInt8QuantHandler
640 def quantized_model(self) -> nn.Module: member in EmbeddingQuantHandler
758 ).quantized_model()
|
| /external/executorch/examples/qualcomm/ |
| D | utils.py | 274 quantized_model = convert_pt2e(annotated_model)
275 edge_prog = capture_program(quantized_model, inputs, custom_pass_config)
|
| /external/pytorch/test/quantization/eager/ |
| D | test_quantize_eager_ptq.py | 831 quantized_model = convert(model)
837 self.assertTrue('QuantizedEmbeddingBag' in str(quantized_model))
838 …self.checkDynamicQuantizedModule(quantized_model.emb, torch.ao.nn.quantized.EmbeddingBag, torch.qu…
839 …self.checkScriptable(quantized_model, [[indices, offsets, per_sample_weights]], check_save_load=Tr…
855 quantized_model = convert(model2)
857 self.assertTrue('QuantizedEmbeddingBag' in str(quantized_model))
859 …self.checkDynamicQuantizedModule(quantized_model.emb, torch.ao.nn.quantized.EmbeddingBag, torch.qu…
|
| /external/tensorflow/tensorflow/lite/g3doc/performance/ |
| D | quantization_debugger.ipynb | 235 "quantized_model = converter.convert()"
259 "eval_tflite(quantized_model, ds)"
803 "quantized_model = convert.mlir_quantize(\n",
808 " quant_debug_model_content=quantized_model,\n",
|
| /external/executorch/examples/models/llava/ |
| D | export_llava.py | 172 ).quantized_model()
|
| /external/executorch/backends/cadence/aot/tests/ |
| D | test_fusion_ops_passes.py | 390 quantized_model = quantize_pt2(model, (inputs,))
392 export_to_edge(quantized_model, (inputs,)).exported_program().graph_module
|
| D | test_replace_ops_passes.py | 840 quantized_model = quantize_pt2(model, inputs)
842 exported_program = export_to_edge(quantized_model, inputs).exported_program()
887 quantized_model = quantize_pt2(model, inputs)
889 exported_program = export_to_edge(quantized_model, inputs).exported_program()
|
| /external/executorch/docs/source/ |
| D | native-delegates-executorch-xnnpack-delegate.md | 119 quantized_model = convert_pt2e(prepared_model)
120 print(quantized_model)
|
| /external/tensorflow/tensorflow/lite/java/ovic/ |
| D | README.md | 113 "@tflite_ovic_testdata//:quantized_model.lite",
227 quantized_model.lite | 73 | 61 | 13
|
| /external/tensorflow/tensorflow/compiler/mlir/lite/quantization/lite/ |
| D | quantize_weights_test.cc | 157 const Model* quantized_model, const Model* expected_model, in FindMatchingExpectedTensor() argument
162 CreateMutableModelFromFile(quantized_model); in FindMatchingExpectedTensor()
|
| /external/tensorflow/tensorflow/lite/python/ |
| D | lite_v2_test.py | 376 quantized_model = converter.convert()
381 model_content=quantized_model,
399 quantized_model = converter.convert()
404 model_content=quantized_model,
1251 quantized_model = converter.convert()
1253 interpreter = Interpreter(model_content=quantized_model)
1333 quantized_model = converter.convert()
1335 metadata = get_conversion_metadata(quantized_model)
1346 quantized_model = converter.convert()
1348 metadata = get_conversion_metadata(quantized_model)
|
| /external/pytorch/test/quantization/fx/ |
| D | test_equalize_fx.py | 865 quantized_model = convert_fx(copy.deepcopy(prepared_model))
868 layer_to_sqnr_dict = get_layer_sqnr_dict(copy.deepcopy(prepared_model), quantized_model, x)
|
| D | test_quantize_fx.py | 6383 quantized_model = convert_fx(prepared_model)
6390 self.checkGraphModuleNodes(quantized_model, expected_node_occurrence=node_occurrence)
6415 quantized_model = convert_fx(prepared_model)
6422 self.checkGraphModuleNodes(quantized_model, expected_node_occurrence=node_occurrence)
6567 quantized_model = convert_fx(prepared_model)
6569 quantized_model(example_inputs)
6574 self.checkGraphModuleNodes(quantized_model, expected_node_occurrence=node_occurrence)
6609 quantized_model = convert_fx(prepared_model)
6611 quantized_model(example_inputs)
6616 self.checkGraphModuleNodes(quantized_model, expected_node_occurrence=node_occurrence)
[all …]
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| /external/tensorflow/tensorflow/lite/g3doc/r1/convert/ |
| D | python_api.md | 213 with open('quantized_model.tflite', 'wb') as f:
|