Paddle

Commit Graph

Author	SHA1	Message	Date
guofei	ed7956a816	Fix skip_quant in QAT (#31704 ) * Fix skip_quant in QAT	4 years ago
cc	1d197f6c97	[dgraph qat] Refine calculating output scale of dygraph qat (#31710 ) * Refine calculating output scale of dygraph qat, test=develop	4 years ago
cc	19592d2b71	Refine dygraph qat, test=develop (#31680 )	4 years ago
guofei	ef0dd3efed	Support loading parameters from checkpoint to save quantized model (#31419 ) * Support loading parameters from checkpoint to save quantized model * Fix the unittest test_moving_average_abs_max_scale_op * Add unittest of save_quantized_model from checkpoint * Add comments to explain the function	4 years ago
guofei	430f8449f1	Fix the error of save_quantized_model (#30583 ) * Fix the error of save_quantized_model	4 years ago
Bai Yifan	ad6fee2fa8	fix quantize error in speical naming model (#30354 )	4 years ago
huangxu96	ee623bff64	Implemented AddQuantDequantPass in imperative quantization. (#26692 ) * Implemented AddQuantDequantPass in imperative quantization. * Supported LeakyReLU Quantization * For meeting coverage rate. * Changed the file name of test of AddQuantDequant * Implemented more Quantized NoWeightLayers. * Fix the loss cannot align problem between static and dynamic model quantization, add swish as supported quantized layer in imperative quantization. * remove noweight_list * support 2.0 API such as Pool2D and ReLu	4 years ago
guofei	1bdf924217	Quantization supports 2.0 APIs (#30036 ) * Quantization supports 2.0 APIs * Fix the error of save_quantized_model	4 years ago
guofei	638402274a	Integrate ImperativeOutScale into ImperativeQuantAware. (#27956 ) * Optimiz the unittest test_imperative_out_scale test=develop	5 years ago
huangxu96	40f5453725	Quant nn2.0 (#28764 ) * Impelement 2.0 API version Conv2d and Linear layer quantization in imperative mode. * use cudnn softmax in static Lenet * Modified ChannelwiseQAT Unittest for 2.0 API. * For CI python coverage.	5 years ago
Leo Chen	3815d7aa40	Upgrade string literals to raw string (#28989 ) * upgrade comment string to raw string * fix string in * fix string with ' ' * revert update on comments * upgrade only necessary * fix sample code checker * fix comments with '''	5 years ago
Bai Yifan	5050e761b8	Support user-defined activation/weight quantize and preprocess. (#28570 ) * support user-defined quant and preprocess	5 years ago
guofei	6bbb6e7f45	Implement the function of OutScaleForTraining/OutScaleForInference in dygraph (#26601 ) * Implement the function of OueScaleForTraining/OutScaleForInference in dygraph test=develop	5 years ago
huangxu96	02606d45ef	Quant op dev (#25932 ) * Finished ChannelWiseQuantDequantAbsMaxOp and Passed unittests. * Finished channel-wise quantize strategy in imperative quantization. * Added Cuda code of ChannelWiseQuantDequantMaxAbsOP Add Cuda code of ChannelWiseQuantDequantMaxAbsOp * Add quant_axis for channel_wise quant. * fixed a bug in unnitests, which will not trigger axis = 1 case and cannot meet the coverage rate requirement. * Added some assert infomation and fixed some coding style mistakes.	5 years ago
Zhen Wang	d28162b97f	Remove save_quantized_model in ImperativeQuantAware. (#27240 )	5 years ago
Zhen Wang	ece74c4cd4	Update the _get_fake_quant_type definition in imperative QAT. (#27222 )	5 years ago
qingqing01	f7fb4c2212	Move hapi to python/paddle root dir. (#26442 ) * Move hapi form paddle/incubate to paddle * Remove vision/datasets/utils.py and clean code * Add sample code for conll05 * Print pull path when saving model * Fix sample code after paramter_list of SGD is changed to parameters * Fix bug in wmt16 datase	5 years ago
Aurelius84	f05613683f	[Dy2stat] Support InputSpec and Return callable class instance in @declarative (#25960 ) * add InputSpec * add unittest for tensorSpec and SimpleNet	5 years ago
Chen Weihang	23d1228c4d	remove ProgramTranslator.save_inference_model (#25740 ) * remove ProgramTranslator.save_inference_model * adapt save_quantized_model * revert buffer check implemention * remove useless import function	5 years ago
Zhen Wang	548cdbc544	Quantization-aware training for dygraph (#24634 ) * Add the imperative quantization aware training. * This is the python part of Imperative QAT. test=develop	5 years ago

20 Commits (ed7956a816130f4eb37ba3e235c09d1105ed1807)