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.exists(calib_cache): calib_shape = [calib_batch_size] + list(inputs[0].shape[1:]) calib_dtype = trt.nptype(inputs[0].dtype) self.config.int8_calibrator.set_image_batcher( ImageBatcher(calib_input, calib_shape, calib_dtype, max_num_images=calib_num_images, exact_batches=True))
calib_shape = [calib_batch_size] + list(inputs[0].shape[1:]) 如果多输入,怎么办呢?此处。。不太懂
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感谢感谢
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一个简单的方法,合并多个输入,在forward里边split
输入维度不一致,那就展开为一维?多个输入挨个拼接,?forward的时候切开后维度变回去?
另外多个输入不是图片,那就需要把这些变量保存起来,然后int8量化的时候读取?
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.exists(calib_cache):
calib_shape = [calib_batch_size] + list(inputs[0].shape[1:])
calib_dtype = trt.nptype(inputs[0].dtype)
self.config.int8_calibrator.set_image_batcher(
ImageBatcher(calib_input, calib_shape, calib_dtype, max_num_images=calib_num_images,
exact_batches=True))
calib_shape = [calib_batch_size] + list(inputs[0].shape[1:])
如果多输入,怎么办呢?此处。。不太懂
The text was updated successfully, but these errors were encountered: