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Use a big ndarray in gluon/data/vision #7661
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use `nd.array(data)` instead of a list of ndarray to accelerate the time
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Is it actually faster? This way slicing happens at runtime |
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reduce loading time from 7s to 2s. i guest the overhead is |
piiswrong
reviewed
Sep 2, 2017
| @@ -105,7 +105,7 @@ def _get_data(self): | |||
| data = np.fromstring(fin.read(), dtype=np.uint8) | |||
| data = data.reshape(len(label), 28, 28, 1) | |||
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| self._data = [nd.array(x, dtype=x.dtype) for x in data] | |||
| self._data = nd.array(data) | |||
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does this also need a dtype?
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mbaijal
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Sep 6, 2017
use `nd.array(data)` instead of a list of ndarray to accelerate the time
cjolivier01
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Sep 11, 2017
use `nd.array(data)` instead of a list of ndarray to accelerate the time
crazy-cat
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Oct 26, 2017
use `nd.array(data)` instead of a list of ndarray to accelerate the time
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use
nd.array(data)instead of a list of ndarray to accelerate the time