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authorGravatar A. Unique TensorFlower <gardener@tensorflow.org>2018-08-14 14:07:44 -0700
committerGravatar TensorFlower Gardener <gardener@tensorflow.org>2018-08-14 14:11:18 -0700
commitab53f852b70250286cefb3192445775d7a5491e0 (patch)
tree102fe51ff9f02b3fa40f7aa44f46c3e2ea2553b0 /tensorflow/contrib/lite/kernels/mul.cc
parentaf827be63a9d8aff06a438ac9769a6ff6870c60d (diff)
Introduce fivefold broadcast Mul op kernels for uint8.
PiperOrigin-RevId: 208709648
Diffstat (limited to 'tensorflow/contrib/lite/kernels/mul.cc')
-rw-r--r--tensorflow/contrib/lite/kernels/mul.cc5
1 files changed, 2 insertions, 3 deletions
diff --git a/tensorflow/contrib/lite/kernels/mul.cc b/tensorflow/contrib/lite/kernels/mul.cc
index 349f3e6726..561e39cfc6 100644
--- a/tensorflow/contrib/lite/kernels/mul.cc
+++ b/tensorflow/contrib/lite/kernels/mul.cc
@@ -93,7 +93,6 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
input1->params.scale * input2->params.scale / output->params.scale;
QuantizeMultiplierSmallerThanOneExp(
real_multiplier, &data->output_multiplier, &data->output_shift);
- data->output_shift *= -1;
}
return context->ResizeTensor(context, output, output_size);
@@ -161,9 +160,9 @@ TfLiteStatus EvalQuantized(TfLiteContext* context, TfLiteNode* node,
// The quantized version of Mul doesn't support activations, so we
// always use BroadcastMul.
if (kernel_type == kReference) {
- TF_LITE_MUL(reference_ops, BroadcastMul);
+ TF_LITE_MUL(reference_ops, BroadcastMul4DSlow);
} else {
- TF_LITE_MUL(optimized_ops, BroadcastMul);
+ TF_LITE_MUL(optimized_ops, BroadcastMul4DSlow);
}
#undef TF_LITE_MUL
} else if (input1->type == kTfLiteInt16 && input2->type == kTfLiteInt16 &&