mirror of
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removed tflite-lib
This commit is contained in:
CaCO3
@@ -1,525 +0,0 @@
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/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#ifndef TENSORFLOW_LITE_C_BUILTIN_OP_DATA_H_
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#define TENSORFLOW_LITE_C_BUILTIN_OP_DATA_H_
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#include <stdint.h>
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#include "tensorflow/lite/c/common.h"
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#ifdef __cplusplus
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extern "C" {
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#endif // __cplusplus
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// TfLiteReshapeParams can't have dynamic data so we fix the maximum possible
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// number of dimensions.
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#define TFLITE_RESHAPE_PARAMS_MAX_DIMENSION_COUNT 8
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// TODO(aselle): Consider using "if this then that" for testing.
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// Useful placeholder to put in otherwise empty structs to avoid size warnings.
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typedef struct {
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char dummy;
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} EmptyStructPlaceholder;
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// IMPORTANT: All new members of structs must be added at the end to ensure
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// backwards compatibility.
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// Possible padding types (for convolutions)
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typedef enum {
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kTfLitePaddingUnknown = 0,
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kTfLitePaddingSame,
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kTfLitePaddingValid,
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} TfLitePadding;
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typedef enum {
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kTfLiteMirrorPaddingUnknown = 0,
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kTfLiteMirrorPaddingReflect,
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kTfLiteMirrorPaddingSymmetric,
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} TfLiteMirrorPaddingMode;
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// TODO(b/130259536): We should move this out of builtin_op_data.
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typedef struct {
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int width;
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int height;
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int width_offset;
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int height_offset;
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} TfLitePaddingValues;
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typedef struct {
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TfLiteMirrorPaddingMode mode;
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} TfLiteMirrorPaddingParams;
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// Possible fused activation functions.
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typedef enum {
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kTfLiteActNone = 0,
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kTfLiteActRelu,
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kTfLiteActReluN1To1, // min(max(-1, x), 1)
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kTfLiteActRelu6, // min(max(0, x), 6)
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kTfLiteActTanh,
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kTfLiteActSignBit,
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kTfLiteActSigmoid,
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} TfLiteFusedActivation;
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typedef struct {
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// Parameters for CONV_2D version 1.
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TfLitePadding padding;
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int stride_width;
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int stride_height;
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TfLiteFusedActivation activation;
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// Parameters for CONV_2D version 2.
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// Note: Version 2 supports dilation values not equal to 1.
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int dilation_width_factor;
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int dilation_height_factor;
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} TfLiteConvParams;
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typedef struct {
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TfLitePadding padding;
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int stride_width;
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int stride_height;
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int stride_depth;
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int dilation_width_factor;
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int dilation_height_factor;
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int dilation_depth_factor;
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TfLiteFusedActivation activation;
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} TfLiteConv3DParams;
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typedef TfLiteConv3DParams TfLiteConv3DTransposeParams;
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typedef struct {
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TfLitePadding padding;
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int stride_width;
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int stride_height;
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int filter_width;
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int filter_height;
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TfLiteFusedActivation activation;
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struct {
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TfLitePaddingValues padding;
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} computed;
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} TfLitePoolParams;
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typedef struct {
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// Parameters for DepthwiseConv version 1 or above.
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TfLitePadding padding;
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int stride_width;
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int stride_height;
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// `depth_multiplier` is redundant. It's used by CPU kernels in
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// TensorFlow 2.0 or below, but ignored in versions above.
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//
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// The information can be deduced from the shape of input and the shape of
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// weights. Since the TFLiteConverter toolchain doesn't support partially
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// specified shapes, relying on `depth_multiplier` stops us from supporting
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// graphs with dynamic shape tensors.
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//
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// Note: Some of the delegates (e.g. NNAPI, GPU) are still relying on this
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// field.
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int depth_multiplier;
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TfLiteFusedActivation activation;
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// Parameters for DepthwiseConv version 2 or above.
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int dilation_width_factor;
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int dilation_height_factor;
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} TfLiteDepthwiseConvParams;
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typedef struct {
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int rank;
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TfLiteFusedActivation activation;
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// Parameter for SVDF version 4.
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bool asymmetric_quantize_inputs;
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} TfLiteSVDFParams;
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typedef struct {
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TfLiteFusedActivation activation;
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// Parameter for RNN version 3.
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bool asymmetric_quantize_inputs;
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} TfLiteRNNParams;
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typedef struct {
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bool time_major;
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TfLiteFusedActivation activation;
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// Parameter for Sequence RNN version 3.
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bool asymmetric_quantize_inputs;
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} TfLiteSequenceRNNParams;
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typedef struct {
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bool time_major;
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TfLiteFusedActivation activation;
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bool merge_outputs;
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// Parameter for Bidirectional RNN verison 3.
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bool asymmetric_quantize_inputs;
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} TfLiteBidirectionalSequenceRNNParams;
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typedef enum {
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kTfLiteFullyConnectedWeightsFormatDefault = 0,
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kTfLiteFullyConnectedWeightsFormatShuffled4x16Int8 = 1,
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} TfLiteFullyConnectedWeightsFormat;
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typedef struct {
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// Parameters for FullyConnected version 1 or above.
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TfLiteFusedActivation activation;
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// Parameters for FullyConnected version 2 or above.
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TfLiteFullyConnectedWeightsFormat weights_format;
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// Parameters for FullyConnected version 5 or above.
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// If set to true, then the number of dimensions in the input and the output
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// tensors are the same. Furthermore, all but the last dimension of the input
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// and output shapes will be equal.
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bool keep_num_dims;
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// Parameters for FullyConnected version 7 or above.
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// If set to true and the weights are quantized, then non constant inputs
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// are quantized at evaluation time with asymmetric quantization.
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bool asymmetric_quantize_inputs;
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} TfLiteFullyConnectedParams;
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typedef enum {
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kTfLiteLshProjectionUnknown = 0,
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kTfLiteLshProjectionSparse = 1,
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kTfLiteLshProjectionDense = 2,
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} TfLiteLSHProjectionType;
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typedef struct {
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TfLiteLSHProjectionType type;
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} TfLiteLSHProjectionParams;
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typedef struct {
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float beta;
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} TfLiteSoftmaxParams;
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typedef struct {
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int axis;
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TfLiteFusedActivation activation;
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} TfLiteConcatenationParams;
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typedef struct {
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TfLiteFusedActivation activation;
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// Parameter added for the version 4.
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bool pot_scale_int16;
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} TfLiteAddParams;
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typedef struct {
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EmptyStructPlaceholder placeholder;
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} TfLiteSpaceToBatchNDParams;
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typedef struct {
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EmptyStructPlaceholder placeholder;
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} TfLiteBatchToSpaceNDParams;
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typedef struct {
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bool adj_x;
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bool adj_y;
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// Parameters for BatchMatMul version 4 or above.
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// If set to true and the weights are quantized, then non constant inputs
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// are quantized at evaluation time with asymmetric quantization.
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bool asymmetric_quantize_inputs;
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} TfLiteBatchMatMulParams;
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typedef struct {
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TfLiteFusedActivation activation;
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} TfLiteMulParams;
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typedef struct {
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TfLiteFusedActivation activation;
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// Parameter added for the version 5.
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bool pot_scale_int16;
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} TfLiteSubParams;
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typedef struct {
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TfLiteFusedActivation activation;
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} TfLiteDivParams;
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typedef struct {
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TfLiteFusedActivation activation;
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} TfLiteL2NormParams;
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typedef struct {
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int radius;
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float bias;
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float alpha;
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float beta;
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} TfLiteLocalResponseNormParams;
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typedef enum {
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kTfLiteLSTMFullKernel = 0,
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kTfLiteLSTMBasicKernel
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} TfLiteLSTMKernelType;
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typedef struct {
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// Parameters for LSTM version 1.
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TfLiteFusedActivation activation;
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float cell_clip;
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float proj_clip;
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// Parameters for LSTM version 2.
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// kTfLiteLSTMBasicKernel is only supported in version 2 or above.
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TfLiteLSTMKernelType kernel_type;
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// Parameters for LSTM version 4.
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bool asymmetric_quantize_inputs;
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} TfLiteLSTMParams;
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typedef struct {
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// Parameters needed for the underlying LSTM.
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TfLiteFusedActivation activation;
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float cell_clip;
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float proj_clip;
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// If set to true then the first dimension is time, otherwise batch.
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bool time_major;
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// Parameter for unidirectional sequence RNN version 3.
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bool asymmetric_quantize_inputs;
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} TfLiteUnidirectionalSequenceLSTMParams;
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typedef struct {
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// Parameters supported by version 1:
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// Parameters inherited for the LSTM kernel.
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TfLiteFusedActivation activation;
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float cell_clip;
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float proj_clip;
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// If true, store the outputs of both directions in the first output.
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bool merge_outputs;
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// Parameters supported by version 2:
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// If set to true then the first dimension is time, otherwise batch.
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bool time_major;
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// Parameters supported by version 4:
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// If set to true, then hybrid ops use asymmetric quantization for inputs.
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bool asymmetric_quantize_inputs;
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} TfLiteBidirectionalSequenceLSTMParams;
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typedef struct {
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bool align_corners;
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// half_pixel_centers assumes pixels are of half the actual dimensions, and
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// yields more accurate resizes. Corresponds to the same argument for the
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// original TensorFlow op in TF2.0.
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bool half_pixel_centers;
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} TfLiteResizeBilinearParams;
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typedef struct {
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bool align_corners;
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bool half_pixel_centers;
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} TfLiteResizeNearestNeighborParams;
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typedef struct {
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EmptyStructPlaceholder placeholder;
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} TfLitePadParams;
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typedef struct {
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EmptyStructPlaceholder placeholder;
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} TfLitePadV2Params;
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typedef struct {
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// These fields are only used in old models for backward compatibility.
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// In the current implementation, we use the 2nd input of the op as the shape,
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// and these fields are unused.
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int shape[TFLITE_RESHAPE_PARAMS_MAX_DIMENSION_COUNT];
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int num_dimensions;
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} TfLiteReshapeParams;
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typedef struct {
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int ngram_size;
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int max_skip_size;
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bool include_all_ngrams;
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} TfLiteSkipGramParams;
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typedef struct {
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int block_size;
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} TfLiteSpaceToDepthParams;
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typedef struct {
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int block_size;
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} TfLiteDepthToSpaceParams;
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typedef struct {
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TfLiteType in_data_type;
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TfLiteType out_data_type;
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} TfLiteCastParams;
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typedef enum {
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kTfLiteCombinerTypeSum = 0,
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kTfLiteCombinerTypeMean = 1,
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kTfLiteCombinerTypeSqrtn = 2,
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} TfLiteCombinerType;
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typedef struct {
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TfLiteCombinerType combiner;
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} TfLiteEmbeddingLookupSparseParams;
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typedef struct {
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int axis;
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int batch_dims;
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} TfLiteGatherParams;
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typedef struct {
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EmptyStructPlaceholder placeholder;
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} TfLiteTransposeParams;
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typedef struct {
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bool keep_dims;
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} TfLiteReducerParams;
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typedef struct {
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int num_splits;
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} TfLiteSplitParams;
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typedef struct {
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int num_splits;
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} TfLiteSplitVParams;
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typedef struct {
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// TODO(ahentz): We can't have dynamic data in this struct, at least not yet.
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// For now we will fix the maximum possible number of dimensions.
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int squeeze_dims[8];
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int num_squeeze_dims;
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} TfLiteSqueezeParams;
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typedef struct {
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int begin_mask;
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int end_mask;
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int ellipsis_mask;
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int new_axis_mask;
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int shrink_axis_mask;
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} TfLiteStridedSliceParams;
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typedef struct {
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TfLiteType output_type;
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} TfLiteArgMaxParams;
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typedef struct {
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TfLiteType output_type;
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} TfLiteArgMinParams;
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typedef struct {
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TfLitePadding padding;
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int stride_width;
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int stride_height;
|
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} TfLiteTransposeConvParams;
|
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typedef struct {
|
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bool validate_indices;
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} TfLiteSparseToDenseParams;
|
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typedef struct {
|
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TfLiteType out_type;
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} TfLiteShapeParams;
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typedef struct {
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EmptyStructPlaceholder placeholder;
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} TfLiteRankParams;
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typedef struct {
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// Parameters supported by version 1:
|
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float min;
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float max;
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int num_bits;
|
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|
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// Parameters supported by version 2:
|
||||
bool narrow_range;
|
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} TfLiteFakeQuantParams;
|
||||
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typedef struct {
|
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int values_count;
|
||||
int axis;
|
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} TfLitePackParams;
|
||||
|
||||
typedef struct {
|
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int axis;
|
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} TfLiteOneHotParams;
|
||||
|
||||
typedef struct {
|
||||
int num;
|
||||
int axis;
|
||||
} TfLiteUnpackParams;
|
||||
|
||||
typedef struct {
|
||||
float alpha;
|
||||
} TfLiteLeakyReluParams;
|
||||
|
||||
typedef struct {
|
||||
TfLiteType index_out_type;
|
||||
} TfLiteUniqueParams;
|
||||
|
||||
typedef struct {
|
||||
int seq_dim;
|
||||
int batch_dim;
|
||||
} TfLiteReverseSequenceParams;
|
||||
|
||||
typedef struct {
|
||||
EmptyStructPlaceholder placeholder;
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||||
} TfLiteMatrixDiagParams;
|
||||
|
||||
typedef struct {
|
||||
EmptyStructPlaceholder placeholder;
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||||
} TfLiteMatrixSetDiagParams;
|
||||
|
||||
typedef struct {
|
||||
int then_subgraph_index;
|
||||
int else_subgraph_index;
|
||||
} TfLiteIfParams;
|
||||
|
||||
typedef struct {
|
||||
int cond_subgraph_index;
|
||||
int body_subgraph_index;
|
||||
} TfLiteWhileParams;
|
||||
|
||||
typedef struct {
|
||||
bool exclusive;
|
||||
bool reverse;
|
||||
} TfLiteCumsumParams;
|
||||
|
||||
typedef struct {
|
||||
int init_subgraph_index;
|
||||
} TfLiteCallOnceParams;
|
||||
|
||||
typedef struct {
|
||||
int table_id;
|
||||
TfLiteType key_dtype;
|
||||
TfLiteType value_dtype;
|
||||
} TfLiteHashtableParams;
|
||||
|
||||
typedef struct {
|
||||
const char* container;
|
||||
const char* shared_name;
|
||||
} TfLiteVarHandleParams;
|
||||
|
||||
typedef struct {
|
||||
int seed;
|
||||
int seed2;
|
||||
} TfLiteRandomParams;
|
||||
|
||||
typedef struct {
|
||||
int num_boundaries;
|
||||
// This points to the memory stored in the model (flatbuffer),
|
||||
// and is not owned.
|
||||
const float* boundaries;
|
||||
} TfLiteBucketizeParams;
|
||||
|
||||
typedef struct {
|
||||
bool approximate;
|
||||
} TfLiteGeluParams;
|
||||
|
||||
#ifdef __cplusplus
|
||||
} // extern "C"
|
||||
#endif // __cplusplus
|
||||
|
||||
#endif // TENSORFLOW_LITE_C_BUILTIN_OP_DATA_H_
|
||||
@@ -1,130 +0,0 @@
|
||||
/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
==============================================================================*/
|
||||
|
||||
// This file declares types used by the pure C inference API defined in c_api.h,
|
||||
// some of which are also used in the C++ and C kernel and interpreter APIs.
|
||||
|
||||
#ifndef TENSORFLOW_LITE_C_C_API_TYPES_H_
|
||||
#define TENSORFLOW_LITE_C_C_API_TYPES_H_
|
||||
|
||||
#include <stdint.h>
|
||||
|
||||
#ifdef __cplusplus
|
||||
extern "C" {
|
||||
#endif
|
||||
|
||||
// Define TFL_CAPI_EXPORT macro to export a function properly with a shared
|
||||
// library.
|
||||
#ifdef SWIG
|
||||
#define TFL_CAPI_EXPORT
|
||||
#elif defined(TFL_STATIC_LIBRARY_BUILD)
|
||||
#define TFL_CAPI_EXPORT
|
||||
#else // not definded TFL_STATIC_LIBRARY_BUILD
|
||||
#if defined(_WIN32)
|
||||
#ifdef TFL_COMPILE_LIBRARY
|
||||
#define TFL_CAPI_EXPORT __declspec(dllexport)
|
||||
#else
|
||||
#define TFL_CAPI_EXPORT __declspec(dllimport)
|
||||
#endif // TFL_COMPILE_LIBRARY
|
||||
#else
|
||||
#define TFL_CAPI_EXPORT __attribute__((visibility("default")))
|
||||
#endif // _WIN32
|
||||
#endif // SWIG
|
||||
|
||||
// Note that new error status values may be added in future in order to
|
||||
// indicate more fine-grained internal states, therefore, applications should
|
||||
// not rely on status values being members of the enum.
|
||||
typedef enum TfLiteStatus {
|
||||
kTfLiteOk = 0,
|
||||
|
||||
// Generally referring to an error in the runtime (i.e. interpreter)
|
||||
kTfLiteError = 1,
|
||||
|
||||
// Generally referring to an error from a TfLiteDelegate itself.
|
||||
kTfLiteDelegateError = 2,
|
||||
|
||||
// Generally referring to an error in applying a delegate due to
|
||||
// incompatibility between runtime and delegate, e.g., this error is returned
|
||||
// when trying to apply a TF Lite delegate onto a model graph that's already
|
||||
// immutable.
|
||||
kTfLiteApplicationError = 3,
|
||||
|
||||
// Generally referring to serialized delegate data not being found.
|
||||
// See tflite::delegates::Serialization.
|
||||
kTfLiteDelegateDataNotFound = 4,
|
||||
|
||||
// Generally referring to data-writing issues in delegate serialization.
|
||||
// See tflite::delegates::Serialization.
|
||||
kTfLiteDelegateDataWriteError = 5,
|
||||
|
||||
// Generally referring to data-reading issues in delegate serialization.
|
||||
// See tflite::delegates::Serialization.
|
||||
kTfLiteDelegateDataReadError = 6,
|
||||
|
||||
// Generally referring to issues when the TF Lite model has ops that cannot be
|
||||
// resolved at runtime. This could happen when the specific op is not
|
||||
// registered or built with the TF Lite framework.
|
||||
kTfLiteUnresolvedOps = 7,
|
||||
} TfLiteStatus;
|
||||
|
||||
// Types supported by tensor
|
||||
typedef enum {
|
||||
kTfLiteNoType = 0,
|
||||
kTfLiteFloat32 = 1,
|
||||
kTfLiteInt32 = 2,
|
||||
kTfLiteUInt8 = 3,
|
||||
kTfLiteInt64 = 4,
|
||||
kTfLiteString = 5,
|
||||
kTfLiteBool = 6,
|
||||
kTfLiteInt16 = 7,
|
||||
kTfLiteComplex64 = 8,
|
||||
kTfLiteInt8 = 9,
|
||||
kTfLiteFloat16 = 10,
|
||||
kTfLiteFloat64 = 11,
|
||||
kTfLiteComplex128 = 12,
|
||||
kTfLiteUInt64 = 13,
|
||||
kTfLiteResource = 14,
|
||||
kTfLiteVariant = 15,
|
||||
kTfLiteUInt32 = 16,
|
||||
kTfLiteUInt16 = 17,
|
||||
} TfLiteType;
|
||||
|
||||
// Legacy. Will be deprecated in favor of TfLiteAffineQuantization.
|
||||
// If per-layer quantization is specified this field will still be populated in
|
||||
// addition to TfLiteAffineQuantization.
|
||||
// Parameters for asymmetric quantization. Quantized values can be converted
|
||||
// back to float using:
|
||||
// real_value = scale * (quantized_value - zero_point)
|
||||
typedef struct TfLiteQuantizationParams {
|
||||
float scale;
|
||||
int32_t zero_point;
|
||||
} TfLiteQuantizationParams;
|
||||
|
||||
// --------------------------------------------------------------------------
|
||||
// Opaque types used by c_api.h, c_api_opaque.h and common.h.
|
||||
|
||||
// TfLiteOpaqueContext is an opaque version of TfLiteContext;
|
||||
typedef struct TfLiteOpaqueContext TfLiteOpaqueContext;
|
||||
|
||||
// TfLiteOpaqueNode is an opaque version of TfLiteNode;
|
||||
typedef struct TfLiteOpaqueNode TfLiteOpaqueNode;
|
||||
|
||||
// TfLiteOpaqueTensor is an opaque version of TfLiteTensor;
|
||||
typedef struct TfLiteOpaqueTensor TfLiteOpaqueTensor;
|
||||
|
||||
#ifdef __cplusplus
|
||||
} // extern C
|
||||
#endif
|
||||
#endif // TENSORFLOW_LITE_C_C_API_TYPES_H_
|
||||
Reference in New Issue
Block a user