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Enable int32 on GPU for tf.tile (#12183)

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* Enable int32 on GPU for tf.tile.

This fix enabled int32 on GPU for tf.tile, to fix the following error:
```
import tensorflow as tf

with tf.device('/gpu:0'):
    tt = tf.tile(tf.range(4), [3])

with tf.Session() as sess:
    print(sess.run(tt))
```

This fix fixes 12169.

Signed-off-by: Yong Tang <yong.tang.github@outlook.com>

* Enable int32 for TileGradOp

Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
This commit is contained in:
Yong Tang 2017-08-10 10:55:28 -07:00 committed by Rasmus Munk Larsen
parent a9e2817c35
commit 92111fdd1a
1 changed files with 12 additions and 0 deletions
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12
tensorflow/core/kernels/tile_ops.cc
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@ -536,6 +536,12 @@ REGISTER_KERNEL_BUILDER(Name("Tile")
.TypeConstraint<int32>("Tmultiples")
.HostMemory("multiples"),
TileOp<GPUDevice>);
REGISTER_KERNEL_BUILDER(Name("Tile")
.Device(DEVICE_GPU)
.TypeConstraint<int32>("T")
.TypeConstraint<int32>("Tmultiples")
.HostMemory("multiples"),
TileOp<GPUDevice>);
REGISTER_KERNEL_BUILDER(Name("Tile")
.Device(DEVICE_GPU)
.TypeConstraint<complex64>("T")
@ -573,6 +579,12 @@ REGISTER_KERNEL_BUILDER(Name("TileGrad")
.TypeConstraint<int32>("Tmultiples")
.HostMemory("multiples"),
TileGradientOp<GPUDevice>);
REGISTER_KERNEL_BUILDER(Name("TileGrad")
.Device(DEVICE_GPU)
.TypeConstraint<int32>("T")
.TypeConstraint<int32>("Tmultiples")
.HostMemory("multiples"),
TileGradientOp<GPUDevice>);
REGISTER_KERNEL_BUILDER(Name("TileGrad")
.Device(DEVICE_GPU)
.TypeConstraint<complex64>("T")