[Relay, TOPI] add onehot op support #3807
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Beya2019
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vinx13
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Aug 20, 2019
tests/python/relay/test_op_level3.py
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| shape_size = shape_size * src_shape[i] | ||
| input_data = np.arange(shape_size, dtype=data_dtype).reshape((src_shape)) | ||
| input = relay.var("input", relay.TensorType(input_data.shape, data_dtype)) | ||
| on_value = relay.var("on_value", relay.TensorType((1,), value_dtype)) |
topi/include/topi/transform.h
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| * | ||
| * \return A Tensor whose op member is the take operation | ||
| */ | ||
| inline Tensor onehot(const Tensor& a, |
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Worth noting that PR #3781 also implements this op and seems to have very similar changes. |
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Yeah, I implemented basically the same thing in #3781. Doesn't matter to me which one is checked in, it would just be nice to get this functionality committed :) |
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Sorry, this is the first time I submitted the code on the TVM community, didn't notice the previous submission #3781
You can check in the better one. we all hope to improve and use this function as soon as possible.
At 2019-08-21 06:30:53, "Jon Soifer" <[email protected]> wrote:
Yeah, I implemented basically the same thing in #3781. Doesn't matter to me which one is checked in, it would just be nice to get this functionality committed :)
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My change to add OneHot was just checked in - feel free to give it a try! |
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Closed this. You can send another PR if further changes are needed. Thanks for your contribution. |
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add the onehot op support of tensorflow in Relay and Topi. Currently onehot operator supports multiple on_values/off_value/depth, and 0 <= axis < data.shape.size(). The default value: on_value=1.0, off_value=0.0, axis=-1.
@vinx13 would you be able to take a look?