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| author |  A. Unique TensorFlower <gardener@tensorflow.org> | 2018-09-27 06:12:59 -0700 |
|---|---|---|
| committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-09-27 06:16:42 -0700 |
| commit | abf26356209cba1ba895a06d9ce55ad01dad7fc6 (patch) | |
| tree | 5ef1c907a30bf89d08ba241ef985b19938427420 /tensorflow/contrib/lite/kernels/concatenation.cc | |
| parent | 19d8963bc0ea64e10ff08ad4e7cc76813a182196 (diff) | |
Update kernel evals to use new kernel signatures.
PiperOrigin-RevId: 214763814
Diffstat (limited to 'tensorflow/contrib/lite/kernels/concatenation.cc')
| -rw-r--r-- | tensorflow/contrib/lite/kernels/concatenation.cc | 39 |
1 files changed, 25 insertions, 14 deletions
diff --git a/tensorflow/contrib/lite/kernels/concatenation.cc b/tensorflow/contrib/lite/kernels/concatenation.cc index 25ea556d5a..7ad3399ffd 100644 --- a/tensorflow/contrib/lite/kernels/concatenation.cc +++ b/tensorflow/contrib/lite/kernels/concatenation.cc @@ -100,20 +100,31 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { // allocate and populate these during Prepare(). // TODO(ycling): Activation function parameter is ignored. For now we dont have // a model with a Concatenation with fused activation function. -#define TF_LITE_CONCATENATION(type, scalar) \ - VectorOfTensors<scalar> all_inputs(*context, *node->inputs); \ - type::Concatenation<FusedActivationFunctionType::kNone, scalar>( \ - RemapDim(NumDimensions(output), axis), all_inputs.data(), \ - all_inputs.dims(), node->inputs->size, GetTensorData<scalar>(output), \ - GetTensorDims(output)) - -#define TF_LITE_CONCATENATION_QUANTIZED(type) \ - VectorOfQuantizedTensors all_inputs(*context, *node->inputs); \ - type::Concatenation( \ - RemapDim(NumDimensions(output), axis), all_inputs.data(), \ - all_inputs.dims(), all_inputs.zero_point(), all_inputs.scale(), \ - node->inputs->size, GetTensorData<uint8>(output), GetTensorDims(output), \ - output->params.zero_point, output->params.scale) +#define TF_LITE_CONCATENATION(type, scalar) \ + { \ + VectorOfTensors<scalar> all_inputs(*context, *node->inputs); \ + tflite::ConcatenationParams op_params; \ + op_params.axis = axis; \ + op_params.inputs_count = node->inputs->size; \ + type::Concatenation(op_params, all_inputs.shapes(), all_inputs.data(), \ + GetTensorShape(output), \ + GetTensorData<scalar>(output)); \ + } + +#define TF_LITE_CONCATENATION_QUANTIZED(type) \ + { \ + VectorOfQuantizedTensors all_inputs(*context, *node->inputs); \ + tflite::ConcatenationParams op_params; \ + op_params.axis = axis; \ + op_params.input_zeropoint = all_inputs.zero_point(); \ + op_params.input_scale = all_inputs.scale(); \ + op_params.inputs_count = node->inputs->size; \ + op_params.output_zeropoint = output->params.zero_point; \ + op_params.output_scale = output->params.scale; \ + type::ConcatenationWithScaling(op_params, all_inputs.shapes(), \ + all_inputs.data(), GetTensorShape(output), \ + GetTensorData<uint8>(output)); \ + } switch (output->type) { // Already know in/outtypes are same. case kTfLiteFloat32: |