Move params to kernels/internal/types.h.

PiperOrigin-RevId: 208877784

1 files changed, 197 insertions, 15 deletions

diff --git a/tensorflow/contrib/lite/kernels/internal/types.h b/tensorflow/contrib/lite/kernels/internal/types.h
index 7b6838db53..204df9ab19 100644
--- a/tensorflow/contrib/lite/kernels/internal/types.h
+++ b/tensorflow/contrib/lite/kernels/internal/types.h
@@ -660,6 +660,19 @@ enum class BroadcastableOpCategory : uint8 {
   kGenericBroadcast,           // Fall-back.
 };
 
+struct MinMax {
+  float min;
+  float max;
+};
+static_assert(sizeof(MinMax) == 8, "");
+
+struct ActivationParams {
+  FusedActivationFunctionType activation_type;
+  // Quantized inference params.
+  int32 activation_min;
+  int32 activation_max;
+};
+
 // For Add, Sub, Mul ops.
 struct ArithmeticParams {
   // Shape dependent / common to data / op types.
@@ -695,29 +708,122 @@ struct ArithmeticParams {
   int broadcast_shape[5];
 };
 
-template <typename T>
-inline void SetActivationParams(T min, T max, ArithmeticParams* params);
+struct ConcatenationParams {
+  int8 axis;
+};
 
-template <>
-inline void SetActivationParams(float min, float max,
-                                ArithmeticParams* params) {
-  params->float_activation_min = min;
-  params->float_activation_max = max;
-}
+struct ComparisonParams {
+  // uint8 inference params.
+  int left_shift;
+  int32 input0_offset;
+  int32 input0_multiplier;
+  int input0_shift;
+  int32 input1_offset;
+  int32 input1_multiplier;
+  int input1_shift;
+  // Shape dependent / common to inference types.
+  bool is_broadcast;
+};
 
-template <>
-inline void SetActivationParams(int32 min, int32 max,
-                                ArithmeticParams* params) {
-  params->quantized_activation_min = min;
-  params->quantized_activation_max = max;
-}
+struct ConvParams {
+  PaddingType padding_type;
+  PaddingValues padding_values;
+  // TODO(starka): This was just "stride", so check that width+height is OK.
+  int8 stride_width;
+  int8 stride_height;
+  int8 dilation_width_factor;
+  int8 dilation_height_factor;
+  // uint8 inference params.
+  // TODO(b/65838351): Use smaller types if appropriate.
+  int32 input_offset;
+  int32 weights_offset;
+  int32 output_offset;
+  int32 output_multiplier;
+  int output_shift;
+  int32 output_activation_min;
+  int32 output_activation_max;
+};
+
+struct DepthToSpaceParams {
+  int16 block_size;
+};
+
+struct DepthwiseParams {
+  PaddingType padding_type;
+  PaddingValues padding_values;
+  int8 stride;
+  int8 depth_multiplier;
+  // uint8 inference params.
+  // TODO(b/65838351): Use smaller types if appropriate.
+  int32 input_offset;
+  int32 weights_offset;
+  int32 output_offset;
+  int32 output_multiplier;
+  int output_shift;
+  int32 output_activation_min;
+  int32 output_activation_max;
+};
+
+struct FakeQuantParams {
+  MinMax minmax;
+  int32 num_bits;
+};
+
+struct FullyConnectedParams {
+  // uint8 inference params.
+  // TODO(b/65838351): Use smaller types if appropriate.
+  int32 input_offset;
+  int32 weights_offset;
+  int32 output_offset;
+  int32 output_multiplier;
+  int output_shift;
+  int32 output_activation_min;
+  int32 output_activation_max;
+  FullyConnectedWeightsFormat weights_format;
+};
+
+struct GatherParams {
+  int8 input_rank;
+  int16 axis;
+};
+
+struct L2NormalizationParams {
+  // uint8 inference params.
+  int32 input_zero_point;
+};
+
+struct LocalResponseNormalizationParams {
+  int32 range;
+  double bias;
+  double alpha;
+  double beta;
+};
+
+struct LogisticParams {
+  // uint8 inference params.
+  int32 input_zero_point;
+  int32 input_range_radius;
+  int32 input_multiplier;
+  int input_left_shift;
+};
+
+struct LstmCellParams {
+  int32 weights_zero_point;
+  int32 accum_multiplier;
+  int accum_shift;
+  int state_integer_bits;
+};
+
+struct MeanParams {
+  int8 axis_count;
+  int16 axis[4];
+};
 
 struct PadParams {
   int8 left_padding_count;
   int32 left_padding[4];
   int8 right_padding_count;
   int32 right_padding[4];
-  // FloatOrInt pad_value;
 };
 
 struct PoolParams {
@@ -736,6 +842,15 @@ struct PoolParams {
   float float_activation_max;
 };
 
+struct ReshapeParams {
+  int8 shape_count;
+  int32 shape[4];
+};
+
+struct ResizeBilinearParams {
+  bool align_corners;
+};
+
 struct SliceParams {
   int8 begin_count;
   int32 begin[4];
@@ -743,6 +858,73 @@ struct SliceParams {
   int32 size[4];
 };
 
+struct SoftmaxParams {
+  // beta is not really used (not a Tensorflow parameter) and not implemented
+  // for LogSoftmax.
+  double beta;
+  // uint8 inference params.  Used even when beta defaults to 1.0.
+  int32 input_beta_multiplier;
+  int32 input_beta_left_shift;
+  // Reverse scaling is only used by LogSoftmax.
+  int32 reverse_scaling_divisor;
+  int32 reverse_scaling_right_shift;
+  int diff_min;
+};
+
+struct SpaceToDepthParams {
+  int16 block_size;
+};
+
+struct SplitParams {
+  // Graphs that split into, say, 2000 nodes are encountered.  The indices in
+  // OperatorEdges are of type uint16.
+  uint16 num_split;
+};
+
+struct SqueezeParams {
+  int8 squeeze_dims_count;
+  int32 squeeze_dims[4];
+};
+
+struct StridedSliceParams {
+  int8 start_indices_count;
+  int16 start_indices[4];
+  int8 stop_indices_count;
+  int16 stop_indices[4];
+  int8 strides_count;
+  int16 strides[4];
+
+  int16 begin_mask;
+  int16 ellipsis_mask;
+  int16 end_mask;
+  int16 new_axis_mask;
+  int16 shrink_axis_mask;
+};
+
+struct TanhParams {
+  int32 input_zero_point;
+  int32 input_range_radius;
+  int32 input_multiplier;
+  int input_left_shift;
+};
+
+template <typename T>
+inline void SetActivationParams(T min, T max, ArithmeticParams* params);
+
+template <>
+inline void SetActivationParams(float min, float max,
+                                ArithmeticParams* params) {
+  params->float_activation_min = min;
+  params->float_activation_max = max;
+}
+
+template <>
+inline void SetActivationParams(int32 min, int32 max,
+                                ArithmeticParams* params) {
+  params->quantized_activation_min = min;
+  params->quantized_activation_max = max;
+}
+
 }  // namespace tflite
 
 #endif  // TENSORFLOW_CONTRIB_LITE_KERNELS_INTERNAL_TYPES_H_