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-rw-r--r--tensorflow/contrib/lite/kernels/internal/reference/reference_ops.h4
1 files changed, 2 insertions, 2 deletions
diff --git a/tensorflow/contrib/lite/kernels/internal/reference/reference_ops.h b/tensorflow/contrib/lite/kernels/internal/reference/reference_ops.h
index a2f192bbc2..1908f7fa6c 100644
--- a/tensorflow/contrib/lite/kernels/internal/reference/reference_ops.h
+++ b/tensorflow/contrib/lite/kernels/internal/reference/reference_ops.h
@@ -1934,7 +1934,7 @@ inline void LstmCell(const float* input_data, const Dims<4>& input_dims,
// The quantization of the input, output arrays is as follows:
// - The input activations are quantized as uint8 on the interval
// [-1, 127/128].
-// The rationale for that is that that is the natural interval for output
+// The rationale for that is that is the natural interval for output
// activations (see next point) and these need to be concatenated together.
// We could accommodate different ranges by re-scaling, but we empirically
// found that setting the input activations range to be [-1, 127/128] in the
@@ -1999,7 +1999,7 @@ inline void LstmCell(const float* input_data, const Dims<4>& input_dims,
// However, for a fixed-point implementation in 16-bit integers, using 5
// integer bits to represent the [-16, 16] range would leave only 11
// fractional bits, giving an increment of 2^-11 = 4.9e-4 between consecutive
-// representable values. Notice that that is higher than the
+// representable values. Notice that is higher than the
// worst-case clamping error with clamping to [-8, 8]: 3.4e-4 for Logistic.
// Using [-8, 8] thus seems like the better compromise overall, enjoying
// an increment of 2.4e-4 between representable values and a worst-case