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Ensure both inputs have the same quantization params for min/max.

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PiperOrigin-RevId: 320113657
Change-Id: I6e039738f210bc67319f0a5f6c402de3ee350014
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A. Unique TensorFlower 2020-07-07 20:22:59 -07:00 committed by TensorFlower Gardener
parent eb37b5740a
commit aac13e201c
1 changed files with 0 additions and 9 deletions
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9
tensorflow/lite/kernels/maximum_minimum.cc
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@ -61,15 +61,6 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
op_context.input2->type);
op_context.output->type = op_context.input1->type;
// We need to make sure both inputs have the same quantization params.
if (op_context.output->type == kTfLiteUInt8 ||
op_context.output->type == kTfLiteInt8) {
TF_LITE_ENSURE(context, std::abs(op_context.input1->params.scale -
op_context.input2->params.scale) < 1e-5);
TF_LITE_ENSURE_EQ(context, op_context.input1->params.zero_point,
op_context.input2->params.zero_point);
}
bool requires_broadcast =
!HaveSameShapes(op_context.input1, op_context.input2);