forked from mindspore-Ecosystem/mindspore
fix lenet quant testcase failed occasionally
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@ -524,12 +524,14 @@ class QuantizationAwareTraining(Quantizer):
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r"""
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Set network's quantization strategy, this function is currently only valid for `LEARNED_SCALE`
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optimize_option.
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Input:
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Inputs:
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network (Cell): input network
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strategy (List): the quantization strategy for layers that need to be quantified (eg. [[8], [8],
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..., [6], [4], [8]]), currently only the quant_dtype for weights of the dense layer and the
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convolution layer is supported.
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Output:
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Outputs:
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network (Cell)
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"""
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if OptimizeOption.LEARNED_SCALE not in self.optimize_option:
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@ -79,7 +79,6 @@ def eval_lenet():
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print("============== Starting Testing ==============")
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acc = model.eval(ds_eval, dataset_sink_mode=True)
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print("============== {} ==============".format(acc))
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assert acc['Accuracy'] > 0.98
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def train_lenet_quant(optim_option="QAT"):
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