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danking
previously requested changes
Jan 3, 2020
hail/python/hail/expr/types.py
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| running_shape_product = x.itemsize | ||
| for shape_element in reversed(x.shape): | ||
| strides.insert(0, running_shape_product) | ||
| running_shape_product = running_shape_product * (shape_element if shape_element > 0 else 1) |
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Agh, clearly I've been spending too much time in the emitter
hail/python/hail/expr/types.py
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| data = x.reshape(x.size).tolist() | ||
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| strides = [] | ||
| running_shape_product = x.itemsize |
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This is sort of like axis_one_step_byte_size? Like, if I want to increment this axis' index by one, I move this many bytes?
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Yes, and that's a better name
danking
approved these changes
Jan 6, 2020
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It's wrong to use the strides as given from numpy in the current implementation. When we do
x.reshape(x.size).tolist(), we are flattening the ndarray into a single contiguous list that can be thought of as being stored in row major. So I always want to generate the strides that the row major version of the numpy array would have had. Theif shape_element > 0bit is because if you have an empty numpy array of a certain type, you still don't want it to have 0 stride.