address review comments.
diff --git a/tensorflow/lite/micro/kernels/xtensa/fully_connected.cc b/tensorflow/lite/micro/kernels/xtensa/fully_connected.cc
index e858a63..c5904ce 100644
--- a/tensorflow/lite/micro/kernels/xtensa/fully_connected.cc
+++ b/tensorflow/lite/micro/kernels/xtensa/fully_connected.cc
@@ -169,6 +169,12 @@
return kTfLiteError;
}
+ // Filter weights will always be symmetric quantized since we only support
+ // int8 quantization.
+ TFLITE_DCHECK(filter->params.zero_point == 0);
+
+ TFLITE_DCHECK(GetTensorShape(output).DimensionsCount() == 2);
+
return CalculateOpData(context, params->activation, input->type, input,
filter, bias, output, data);
}
@@ -197,11 +203,6 @@
tflite::micro::GetTensorShape(output),
tflite::micro::GetTensorData<int8_t>(output));
#elif defined(FUSION_F1)
- FullyConnectedParams op_params = FullyConnectedParamsQuantized(data);
- // Weights will always be symmetric quantized since we only support int
- // quantization.
- TFLITE_DCHECK(op_params.weights_offset == 0);
-
const RuntimeShape& output_shape = tflite::micro::GetTensorShape(output);
const int num_batches = output_shape.Dims(0);
const int output_depth = output_shape.Dims(1);
@@ -210,6 +211,7 @@
const int filter_dim_count = filter_shape.DimensionsCount();
const int accum_depth = filter_shape.Dims(filter_dim_count - 1);
+ FullyConnectedParams op_params = FullyConnectedParamsQuantized(data);
for (int b = 0; b < num_batches; ++b) {
TF_LITE_ENSURE_EQ(
context,
