From b2e53b91019f9ab00fe133fe10b2d29bc7e5886c Mon Sep 17 00:00:00 2001 From: "A. Unique TensorFlower" Date: Wed, 16 May 2018 20:31:29 -0700 Subject: Making GetOptionalInput from kernel_util.h return a pointer to const data. PiperOrigin-RevId: 196932028 --- .../lite/kernels/bidirectional_sequence_lstm.cc | 52 +++++++++++----------- tensorflow/contrib/lite/kernels/fully_connected.cc | 4 +- tensorflow/contrib/lite/kernels/kernel_util.h | 5 ++- tensorflow/contrib/lite/kernels/lstm.cc | 34 +++++++------- tensorflow/contrib/lite/kernels/pad.cc | 2 +- tensorflow/contrib/lite/kernels/svdf.cc | 4 +- .../lite/kernels/unidirectional_sequence_lstm.cc | 34 +++++++------- 7 files changed, 68 insertions(+), 67 deletions(-) (limited to 'tensorflow/contrib/lite') diff --git a/tensorflow/contrib/lite/kernels/bidirectional_sequence_lstm.cc b/tensorflow/contrib/lite/kernels/bidirectional_sequence_lstm.cc index 1cd4884696..3425288f02 100644 --- a/tensorflow/contrib/lite/kernels/bidirectional_sequence_lstm.cc +++ b/tensorflow/contrib/lite/kernels/bidirectional_sequence_lstm.cc @@ -135,7 +135,7 @@ TfLiteStatus CheckLstmTensorDimensions( TF_LITE_ENSURE(context, params->cell_clip >= 0); TF_LITE_ENSURE(context, params->proj_clip >= 0); - TfLiteTensor* input_to_input_weights = + const TfLiteTensor* input_to_input_weights = GetOptionalInputTensor(context, node, input_to_input_weights_tensor); if (input_to_input_weights) { TF_LITE_ENSURE_EQ(context, input_to_input_weights->dims->size, 2); @@ -155,7 +155,7 @@ TfLiteStatus CheckLstmTensorDimensions( TF_LITE_ENSURE_EQ(context, input_to_cell_weights->dims->data[0], n_cell); TF_LITE_ENSURE_EQ(context, input_to_cell_weights->dims->data[1], n_input); - TfLiteTensor* recurrent_to_input_weights = + const TfLiteTensor* recurrent_to_input_weights = GetOptionalInputTensor(context, node, recurrent_to_input_weights_tensor); if (recurrent_to_input_weights) { TF_LITE_ENSURE_EQ(context, recurrent_to_input_weights->dims->size, 2); @@ -189,21 +189,21 @@ TfLiteStatus CheckLstmTensorDimensions( (recurrent_to_input_weights == nullptr)); TF_LITE_ENSURE(context, cifg_weights_all_or_none == true); - TfLiteTensor* cell_to_input_weights = + const TfLiteTensor* cell_to_input_weights = GetOptionalInputTensor(context, node, cell_to_input_weights_tensor); if (cell_to_input_weights) { TF_LITE_ENSURE_EQ(context, cell_to_input_weights->dims->size, 1); TF_LITE_ENSURE_EQ(context, cell_to_input_weights->dims->data[0], n_cell); } - TfLiteTensor* cell_to_forget_weights = + const TfLiteTensor* cell_to_forget_weights = GetOptionalInputTensor(context, node, cell_to_forget_weights_tensor); if (cell_to_forget_weights) { TF_LITE_ENSURE_EQ(context, cell_to_forget_weights->dims->size, 1); TF_LITE_ENSURE_EQ(context, cell_to_forget_weights->dims->data[0], n_cell); } - TfLiteTensor* cell_to_output_weights = + const TfLiteTensor* cell_to_output_weights = GetOptionalInputTensor(context, node, cell_to_output_weights_tensor); if (cell_to_output_weights) { TF_LITE_ENSURE_EQ(context, cell_to_output_weights->dims->size, 1); @@ -222,7 +222,7 @@ TfLiteStatus CheckLstmTensorDimensions( TF_LITE_ENSURE(context, peephole_weights_all_or_none == true); // Make sure the input gate bias is present only when not a CIFG-LSTM. - TfLiteTensor* input_gate_bias = + const TfLiteTensor* input_gate_bias = GetOptionalInputTensor(context, node, input_gate_bias_tensor); if (use_cifg) { TF_LITE_ENSURE_EQ(context, input_gate_bias, nullptr); @@ -246,7 +246,7 @@ TfLiteStatus CheckLstmTensorDimensions( TF_LITE_ENSURE_EQ(context, output_gate_bias->dims->size, 1); TF_LITE_ENSURE_EQ(context, output_gate_bias->dims->data[0], n_cell); - TfLiteTensor* projection_weights = + const TfLiteTensor* projection_weights = GetOptionalInputTensor(context, node, projection_weights_tensor); if (projection_weights) { TF_LITE_ENSURE_EQ(context, projection_weights->dims->size, 2); @@ -254,7 +254,7 @@ TfLiteStatus CheckLstmTensorDimensions( TF_LITE_ENSURE_EQ(context, projection_weights->dims->data[1], n_cell); } - TfLiteTensor* projection_bias = + const TfLiteTensor* projection_bias = GetOptionalInputTensor(context, node, projection_bias_tensor); if (projection_bias) { TF_LITE_ENSURE_EQ(context, projection_bias->dims->size, 1); @@ -374,7 +374,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { fw_output_state->allocation_type = kTfLiteArenaRwPersistent; fw_cell_state->allocation_type = kTfLiteArenaRwPersistent; - TfLiteTensor* fw_input_to_input_weights = + const TfLiteTensor* fw_input_to_input_weights = GetOptionalInputTensor(context, node, kFwInputToInputWeightsTensor); const bool fw_use_cifg = (fw_input_to_input_weights == nullptr); TfLiteIntArray* fw_scratch_buffer_size = TfLiteIntArrayCreate(2); @@ -442,7 +442,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { bw_output_state->allocation_type = kTfLiteArenaRwPersistent; bw_cell_state->allocation_type = kTfLiteArenaRwPersistent; - TfLiteTensor* bw_input_to_input_weights = + const TfLiteTensor* bw_input_to_input_weights = GetOptionalInputTensor(context, node, kBwInputToInputWeightsTensor); const bool bw_use_cifg = (bw_input_to_input_weights == nullptr); TfLiteIntArray* bw_scratch_buffer_size = TfLiteIntArrayCreate(2); @@ -470,7 +470,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { const int n_input = input->dims->data[2]; // Tensors for the forward cell. - TfLiteTensor* fw_input_to_input_weights = + const TfLiteTensor* fw_input_to_input_weights = GetOptionalInputTensor(context, node, kFwInputToInputWeightsTensor); const TfLiteTensor* fw_input_to_forget_weights = GetInput(context, node, kFwInputToForgetWeightsTensor); @@ -479,7 +479,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { const TfLiteTensor* fw_input_to_output_weights = GetInput(context, node, kFwInputToOutputWeightsTensor); - TfLiteTensor* fw_recurrent_to_input_weights = + const TfLiteTensor* fw_recurrent_to_input_weights = GetOptionalInputTensor(context, node, kFwRecurrentToInputWeightsTensor); const TfLiteTensor* fw_recurrent_to_forget_weights = GetInput(context, node, kFwRecurrentToForgetWeightsTensor); @@ -488,14 +488,14 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { const TfLiteTensor* fw_recurrent_to_output_weights = GetInput(context, node, kFwRecurrentToOutputWeightsTensor); - TfLiteTensor* fw_cell_to_input_weights = + const TfLiteTensor* fw_cell_to_input_weights = GetOptionalInputTensor(context, node, kFwCellToInputWeightsTensor); - TfLiteTensor* fw_cell_to_forget_weights = + const TfLiteTensor* fw_cell_to_forget_weights = GetOptionalInputTensor(context, node, kFwCellToForgetWeightsTensor); - TfLiteTensor* fw_cell_to_output_weights = + const TfLiteTensor* fw_cell_to_output_weights = GetOptionalInputTensor(context, node, kFwCellToOutputWeightsTensor); - TfLiteTensor* fw_input_gate_bias = + const TfLiteTensor* fw_input_gate_bias = GetOptionalInputTensor(context, node, kFwInputGateBiasTensor); const TfLiteTensor* fw_forget_gate_bias = GetInput(context, node, kFwForgetGateBiasTensor); @@ -504,9 +504,9 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { const TfLiteTensor* fw_output_gate_bias = GetInput(context, node, kFwOutputGateBiasTensor); - TfLiteTensor* fw_projection_weights = + const TfLiteTensor* fw_projection_weights = GetOptionalInputTensor(context, node, kFwProjectionWeightsTensor); - TfLiteTensor* fw_projection_bias = + const TfLiteTensor* fw_projection_bias = GetOptionalInputTensor(context, node, kFwProjectionBiasTensor); TfLiteTensor* fw_output_state = @@ -515,7 +515,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { TfLiteTensor* fw_output = GetOutput(context, node, kFwOutputTensor); // Tensors for the backward cell. - TfLiteTensor* bw_input_to_input_weights = + const TfLiteTensor* bw_input_to_input_weights = GetOptionalInputTensor(context, node, kBwInputToInputWeightsTensor); const TfLiteTensor* bw_input_to_forget_weights = GetInput(context, node, kBwInputToForgetWeightsTensor); @@ -524,7 +524,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { const TfLiteTensor* bw_input_to_output_weights = GetInput(context, node, kBwInputToOutputWeightsTensor); - TfLiteTensor* bw_recurrent_to_input_weights = + const TfLiteTensor* bw_recurrent_to_input_weights = GetOptionalInputTensor(context, node, kBwRecurrentToInputWeightsTensor); const TfLiteTensor* bw_recurrent_to_forget_weights = GetInput(context, node, kBwRecurrentToForgetWeightsTensor); @@ -533,14 +533,14 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { const TfLiteTensor* bw_recurrent_to_output_weights = GetInput(context, node, kBwRecurrentToOutputWeightsTensor); - TfLiteTensor* bw_cell_to_input_weights = + const TfLiteTensor* bw_cell_to_input_weights = GetOptionalInputTensor(context, node, kBwCellToInputWeightsTensor); - TfLiteTensor* bw_cell_to_forget_weights = + const TfLiteTensor* bw_cell_to_forget_weights = GetOptionalInputTensor(context, node, kBwCellToForgetWeightsTensor); - TfLiteTensor* bw_cell_to_output_weights = + const TfLiteTensor* bw_cell_to_output_weights = GetOptionalInputTensor(context, node, kBwCellToOutputWeightsTensor); - TfLiteTensor* bw_input_gate_bias = + const TfLiteTensor* bw_input_gate_bias = GetOptionalInputTensor(context, node, kBwInputGateBiasTensor); const TfLiteTensor* bw_forget_gate_bias = GetInput(context, node, kBwForgetGateBiasTensor); @@ -549,9 +549,9 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { const TfLiteTensor* bw_output_gate_bias = GetInput(context, node, kBwOutputGateBiasTensor); - TfLiteTensor* bw_projection_weights = + const TfLiteTensor* bw_projection_weights = GetOptionalInputTensor(context, node, kBwProjectionWeightsTensor); - TfLiteTensor* bw_projection_bias = + const TfLiteTensor* bw_projection_bias = GetOptionalInputTensor(context, node, kBwProjectionBiasTensor); TfLiteTensor* bw_output_state = diff --git a/tensorflow/contrib/lite/kernels/fully_connected.cc b/tensorflow/contrib/lite/kernels/fully_connected.cc index 39b108629a..1ba30649ec 100644 --- a/tensorflow/contrib/lite/kernels/fully_connected.cc +++ b/tensorflow/contrib/lite/kernels/fully_connected.cc @@ -91,7 +91,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { const TfLiteTensor* input = GetInput(context, node, kInputTensor); const TfLiteTensor* filter = GetInput(context, node, kWeightsTensor); - TfLiteTensor* bias = GetOptionalInputTensor(context, node, kBiasTensor); + const TfLiteTensor* bias = GetOptionalInputTensor(context, node, kBiasTensor); TfLiteTensor* output = GetOutput(context, node, kOutputTensor); // Check all the parameters of tensor match within themselves and match the @@ -347,7 +347,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { const TfLiteTensor* input = GetInput(context, node, kInputTensor); const TfLiteTensor* filter = GetInput(context, node, kWeightsTensor); - TfLiteTensor* bias = GetOptionalInputTensor(context, node, kBiasTensor); + const TfLiteTensor* bias = GetOptionalInputTensor(context, node, kBiasTensor); TfLiteTensor* output = GetOutput(context, node, kOutputTensor); switch (filter->type) { // Already know in/out types are same. diff --git a/tensorflow/contrib/lite/kernels/kernel_util.h b/tensorflow/contrib/lite/kernels/kernel_util.h index de0e368891..82cded36f2 100644 --- a/tensorflow/contrib/lite/kernels/kernel_util.h +++ b/tensorflow/contrib/lite/kernels/kernel_util.h @@ -47,8 +47,9 @@ inline int64_t NumElements(const TfLiteTensor* t) { return count; } -inline TfLiteTensor* GetOptionalInputTensor(TfLiteContext* context, - const TfLiteNode* node, int index) { +inline const TfLiteTensor* GetOptionalInputTensor(TfLiteContext* context, + const TfLiteNode* node, + int index) { const bool use_tensor = node->inputs->data[index] != kOptionalTensor; if (use_tensor) { return &context->tensors[node->inputs->data[index]]; diff --git a/tensorflow/contrib/lite/kernels/lstm.cc b/tensorflow/contrib/lite/kernels/lstm.cc index 8d447a2dcf..990b3da055 100644 --- a/tensorflow/contrib/lite/kernels/lstm.cc +++ b/tensorflow/contrib/lite/kernels/lstm.cc @@ -92,7 +92,7 @@ TfLiteStatus CheckInputTensorDimensions(TfLiteContext* context, TF_LITE_ENSURE(context, params->cell_clip >= 0); TF_LITE_ENSURE(context, params->proj_clip >= 0); - TfLiteTensor* input_to_input_weights = + const TfLiteTensor* input_to_input_weights = GetOptionalInputTensor(context, node, kInputToInputWeightsTensor); if (input_to_input_weights) { TF_LITE_ENSURE_EQ(context, input_to_input_weights->dims->size, 2); @@ -112,7 +112,7 @@ TfLiteStatus CheckInputTensorDimensions(TfLiteContext* context, TF_LITE_ENSURE_EQ(context, input_to_cell_weights->dims->data[0], n_cell); TF_LITE_ENSURE_EQ(context, input_to_cell_weights->dims->data[1], n_input); - TfLiteTensor* recurrent_to_input_weights = + const TfLiteTensor* recurrent_to_input_weights = GetOptionalInputTensor(context, node, kRecurrentToInputWeightsTensor); if (recurrent_to_input_weights) { TF_LITE_ENSURE_EQ(context, recurrent_to_input_weights->dims->size, 2); @@ -146,21 +146,21 @@ TfLiteStatus CheckInputTensorDimensions(TfLiteContext* context, (recurrent_to_input_weights == nullptr)); TF_LITE_ENSURE(context, cifg_weights_all_or_none == true); - TfLiteTensor* cell_to_input_weights = + const TfLiteTensor* cell_to_input_weights = GetOptionalInputTensor(context, node, kCellToInputWeightsTensor); if (cell_to_input_weights) { TF_LITE_ENSURE_EQ(context, cell_to_input_weights->dims->size, 1); TF_LITE_ENSURE_EQ(context, cell_to_input_weights->dims->data[0], n_cell); } - TfLiteTensor* cell_to_forget_weights = + const TfLiteTensor* cell_to_forget_weights = GetOptionalInputTensor(context, node, kCellToForgetWeightsTensor); if (cell_to_forget_weights) { TF_LITE_ENSURE_EQ(context, cell_to_forget_weights->dims->size, 1); TF_LITE_ENSURE_EQ(context, cell_to_forget_weights->dims->data[0], n_cell); } - TfLiteTensor* cell_to_output_weights = + const TfLiteTensor* cell_to_output_weights = GetOptionalInputTensor(context, node, kCellToOutputWeightsTensor); if (cell_to_output_weights) { TF_LITE_ENSURE_EQ(context, cell_to_output_weights->dims->size, 1); @@ -179,7 +179,7 @@ TfLiteStatus CheckInputTensorDimensions(TfLiteContext* context, TF_LITE_ENSURE(context, peephole_weights_all_or_none == true); // Make sure the input gate bias is present only when not a CIFG-LSTM. - TfLiteTensor* input_gate_bias = + const TfLiteTensor* input_gate_bias = GetOptionalInputTensor(context, node, kInputGateBiasTensor); if (use_cifg) { TF_LITE_ENSURE_EQ(context, input_gate_bias, nullptr); @@ -202,7 +202,7 @@ TfLiteStatus CheckInputTensorDimensions(TfLiteContext* context, TF_LITE_ENSURE_EQ(context, output_gate_bias->dims->size, 1); TF_LITE_ENSURE_EQ(context, output_gate_bias->dims->data[0], n_cell); - TfLiteTensor* projection_weights = + const TfLiteTensor* projection_weights = GetOptionalInputTensor(context, node, kProjectionWeightsTensor); if (projection_weights) { TF_LITE_ENSURE_EQ(context, projection_weights->dims->size, 2); @@ -210,7 +210,7 @@ TfLiteStatus CheckInputTensorDimensions(TfLiteContext* context, TF_LITE_ENSURE_EQ(context, projection_weights->dims->data[1], n_cell); } - TfLiteTensor* projection_bias = + const TfLiteTensor* projection_bias = GetOptionalInputTensor(context, node, kProjectionBiasTensor); if (projection_bias) { TF_LITE_ENSURE_EQ(context, projection_bias->dims->size, 1); @@ -298,7 +298,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { output_state->allocation_type = kTfLiteArenaRwPersistent; cell_state->allocation_type = kTfLiteArenaRwPersistent; - TfLiteTensor* input_to_input_weights = + const TfLiteTensor* input_to_input_weights = GetOptionalInputTensor(context, node, kInputToInputWeightsTensor); const bool use_cifg = (input_to_input_weights == nullptr); if (use_cifg) { @@ -324,7 +324,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { auto* params = reinterpret_cast(node->builtin_data); const TfLiteTensor* input = GetInput(context, node, kInputTensor); - TfLiteTensor* input_to_input_weights = + const TfLiteTensor* input_to_input_weights = GetOptionalInputTensor(context, node, kInputToInputWeightsTensor); const TfLiteTensor* input_to_forget_weights = GetInput(context, node, kInputToForgetWeightsTensor); @@ -333,7 +333,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { const TfLiteTensor* input_to_output_weights = GetInput(context, node, kInputToOutputWeightsTensor); - TfLiteTensor* recurrent_to_input_weights = + const TfLiteTensor* recurrent_to_input_weights = GetOptionalInputTensor(context, node, kRecurrentToInputWeightsTensor); const TfLiteTensor* recurrent_to_forget_weights = GetInput(context, node, kRecurrentToForgetWeightsTensor); @@ -342,14 +342,14 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { const TfLiteTensor* recurrent_to_output_weights = GetInput(context, node, kRecurrentToOutputWeightsTensor); - TfLiteTensor* cell_to_input_weights = + const TfLiteTensor* cell_to_input_weights = GetOptionalInputTensor(context, node, kCellToInputWeightsTensor); - TfLiteTensor* cell_to_forget_weights = + const TfLiteTensor* cell_to_forget_weights = GetOptionalInputTensor(context, node, kCellToForgetWeightsTensor); - TfLiteTensor* cell_to_output_weights = + const TfLiteTensor* cell_to_output_weights = GetOptionalInputTensor(context, node, kCellToOutputWeightsTensor); - TfLiteTensor* input_gate_bias = + const TfLiteTensor* input_gate_bias = GetOptionalInputTensor(context, node, kInputGateBiasTensor); const TfLiteTensor* forget_gate_bias = GetInput(context, node, kForgetGateBiasTensor); @@ -357,9 +357,9 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { const TfLiteTensor* output_gate_bias = GetInput(context, node, kOutputGateBiasTensor); - TfLiteTensor* projection_weights = + const TfLiteTensor* projection_weights = GetOptionalInputTensor(context, node, kProjectionWeightsTensor); - TfLiteTensor* projection_bias = + const TfLiteTensor* projection_bias = GetOptionalInputTensor(context, node, kProjectionBiasTensor); TfLiteTensor* output_state = GetOutput(context, node, kOutputStateTensor); diff --git a/tensorflow/contrib/lite/kernels/pad.cc b/tensorflow/contrib/lite/kernels/pad.cc index b1eb6f76a4..ecac2dd5e3 100644 --- a/tensorflow/contrib/lite/kernels/pad.cc +++ b/tensorflow/contrib/lite/kernels/pad.cc @@ -45,7 +45,7 @@ struct PadContext { output = GetOutput(context, node, 0); dims = NumDimensions(input); } - TfLiteTensor* constant_values; + const TfLiteTensor* constant_values; const TfLiteTensor* input; const TfLiteTensor* paddings; TfLiteTensor* output; diff --git a/tensorflow/contrib/lite/kernels/svdf.cc b/tensorflow/contrib/lite/kernels/svdf.cc index 788812755e..308860c299 100644 --- a/tensorflow/contrib/lite/kernels/svdf.cc +++ b/tensorflow/contrib/lite/kernels/svdf.cc @@ -74,7 +74,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { TF_LITE_ASSERT_EQ(input->dims->data[1], weights_feature->dims->data[1]); TF_LITE_ASSERT_EQ(weights_time->dims->data[0], num_filters); - TfLiteTensor* bias = GetOptionalInputTensor(context, node, kBiasTensor); + const TfLiteTensor* bias = GetOptionalInputTensor(context, node, kBiasTensor); if (bias) { TF_LITE_ASSERT_EQ(bias->dims->data[0], num_units); } @@ -134,7 +134,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { TfLiteTensor* output = GetOutput(context, node, kOutputTensor); TfLiteTensor* scratch = GetTemporary(context, node, /*index=*/0); - TfLiteTensor* bias = GetOptionalInputTensor(context, node, kBiasTensor); + const TfLiteTensor* bias = GetOptionalInputTensor(context, node, kBiasTensor); const int rank = params->rank; const int batch_size = input->dims->data[0]; diff --git a/tensorflow/contrib/lite/kernels/unidirectional_sequence_lstm.cc b/tensorflow/contrib/lite/kernels/unidirectional_sequence_lstm.cc index 46d65ca8f8..1c28123a24 100644 --- a/tensorflow/contrib/lite/kernels/unidirectional_sequence_lstm.cc +++ b/tensorflow/contrib/lite/kernels/unidirectional_sequence_lstm.cc @@ -92,7 +92,7 @@ TfLiteStatus CheckInputTensorDimensions(TfLiteContext* context, TF_LITE_ENSURE(context, params->cell_clip >= 0); TF_LITE_ENSURE(context, params->proj_clip >= 0); - TfLiteTensor* input_to_input_weights = + const TfLiteTensor* input_to_input_weights = GetOptionalInputTensor(context, node, kInputToInputWeightsTensor); if (input_to_input_weights) { TF_LITE_ENSURE_EQ(context, input_to_input_weights->dims->size, 2); @@ -112,7 +112,7 @@ TfLiteStatus CheckInputTensorDimensions(TfLiteContext* context, TF_LITE_ENSURE_EQ(context, input_to_cell_weights->dims->data[0], n_cell); TF_LITE_ENSURE_EQ(context, input_to_cell_weights->dims->data[1], n_input); - TfLiteTensor* recurrent_to_input_weights = + const TfLiteTensor* recurrent_to_input_weights = GetOptionalInputTensor(context, node, kRecurrentToInputWeightsTensor); if (recurrent_to_input_weights) { TF_LITE_ENSURE_EQ(context, recurrent_to_input_weights->dims->size, 2); @@ -146,21 +146,21 @@ TfLiteStatus CheckInputTensorDimensions(TfLiteContext* context, (recurrent_to_input_weights == nullptr)); TF_LITE_ENSURE(context, cifg_weights_all_or_none == true); - TfLiteTensor* cell_to_input_weights = + const TfLiteTensor* cell_to_input_weights = GetOptionalInputTensor(context, node, kCellToInputWeightsTensor); if (cell_to_input_weights) { TF_LITE_ENSURE_EQ(context, cell_to_input_weights->dims->size, 1); TF_LITE_ENSURE_EQ(context, cell_to_input_weights->dims->data[0], n_cell); } - TfLiteTensor* cell_to_forget_weights = + const TfLiteTensor* cell_to_forget_weights = GetOptionalInputTensor(context, node, kCellToForgetWeightsTensor); if (cell_to_forget_weights) { TF_LITE_ENSURE_EQ(context, cell_to_forget_weights->dims->size, 1); TF_LITE_ENSURE_EQ(context, cell_to_forget_weights->dims->data[0], n_cell); } - TfLiteTensor* cell_to_output_weights = + const TfLiteTensor* cell_to_output_weights = GetOptionalInputTensor(context, node, kCellToOutputWeightsTensor); if (cell_to_output_weights) { TF_LITE_ENSURE_EQ(context, cell_to_output_weights->dims->size, 1); @@ -179,7 +179,7 @@ TfLiteStatus CheckInputTensorDimensions(TfLiteContext* context, TF_LITE_ENSURE(context, peephole_weights_all_or_none == true); // Make sure the input gate bias is present only when not a CIFG-LSTM. - TfLiteTensor* input_gate_bias = + const TfLiteTensor* input_gate_bias = GetOptionalInputTensor(context, node, kInputGateBiasTensor); if (use_cifg) { TF_LITE_ENSURE_EQ(context, input_gate_bias, nullptr); @@ -202,7 +202,7 @@ TfLiteStatus CheckInputTensorDimensions(TfLiteContext* context, TF_LITE_ENSURE_EQ(context, output_gate_bias->dims->size, 1); TF_LITE_ENSURE_EQ(context, output_gate_bias->dims->data[0], n_cell); - TfLiteTensor* projection_weights = + const TfLiteTensor* projection_weights = GetOptionalInputTensor(context, node, kProjectionWeightsTensor); if (projection_weights) { TF_LITE_ENSURE_EQ(context, projection_weights->dims->size, 2); @@ -210,7 +210,7 @@ TfLiteStatus CheckInputTensorDimensions(TfLiteContext* context, TF_LITE_ENSURE_EQ(context, projection_weights->dims->data[1], n_cell); } - TfLiteTensor* projection_bias = + const TfLiteTensor* projection_bias = GetOptionalInputTensor(context, node, kProjectionBiasTensor); if (projection_bias) { TF_LITE_ENSURE_EQ(context, projection_bias->dims->size, 1); @@ -300,7 +300,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { output_state->allocation_type = kTfLiteArenaRwPersistent; cell_state->allocation_type = kTfLiteArenaRwPersistent; - TfLiteTensor* input_to_input_weights = + const TfLiteTensor* input_to_input_weights = GetOptionalInputTensor(context, node, kInputToInputWeightsTensor); const bool use_cifg = (input_to_input_weights == nullptr); if (use_cifg) { @@ -326,7 +326,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { auto* params = reinterpret_cast(node->builtin_data); const TfLiteTensor* input = GetInput(context, node, kInputTensor); - TfLiteTensor* input_to_input_weights = + const TfLiteTensor* input_to_input_weights = GetOptionalInputTensor(context, node, kInputToInputWeightsTensor); const TfLiteTensor* input_to_forget_weights = GetInput(context, node, kInputToForgetWeightsTensor); @@ -335,7 +335,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { const TfLiteTensor* input_to_output_weights = GetInput(context, node, kInputToOutputWeightsTensor); - TfLiteTensor* recurrent_to_input_weights = + const TfLiteTensor* recurrent_to_input_weights = GetOptionalInputTensor(context, node, kRecurrentToInputWeightsTensor); const TfLiteTensor* recurrent_to_forget_weights = GetInput(context, node, kRecurrentToForgetWeightsTensor); @@ -344,14 +344,14 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { const TfLiteTensor* recurrent_to_output_weights = GetInput(context, node, kRecurrentToOutputWeightsTensor); - TfLiteTensor* cell_to_input_weights = + const TfLiteTensor* cell_to_input_weights = GetOptionalInputTensor(context, node, kCellToInputWeightsTensor); - TfLiteTensor* cell_to_forget_weights = + const TfLiteTensor* cell_to_forget_weights = GetOptionalInputTensor(context, node, kCellToForgetWeightsTensor); - TfLiteTensor* cell_to_output_weights = + const TfLiteTensor* cell_to_output_weights = GetOptionalInputTensor(context, node, kCellToOutputWeightsTensor); - TfLiteTensor* input_gate_bias = + const TfLiteTensor* input_gate_bias = GetOptionalInputTensor(context, node, kInputGateBiasTensor); const TfLiteTensor* forget_gate_bias = GetInput(context, node, kForgetGateBiasTensor); @@ -359,9 +359,9 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { const TfLiteTensor* output_gate_bias = GetInput(context, node, kOutputGateBiasTensor); - TfLiteTensor* projection_weights = + const TfLiteTensor* projection_weights = GetOptionalInputTensor(context, node, kProjectionWeightsTensor); - TfLiteTensor* projection_bias = + const TfLiteTensor* projection_bias = GetOptionalInputTensor(context, node, kProjectionBiasTensor); TfLiteTensor* output_state = GetOutput(context, node, kOutputStateTensor); -- cgit v1.2.3