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Searched refs:kernel_type (Results 1 – 25 of 83) sorted by relevance

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/external/tensorflow/tensorflow/lite/kernels/
Dpooling.cc112 template <KernelType kernel_type>
132 if (kernel_type == kReference) { in AverageEvalFloat()
140 template <KernelType kernel_type>
162 if (kernel_type == kReference) { in AverageEvalQuantizedUint8()
170 template <KernelType kernel_type>
192 if (kernel_type == kReference) { in AverageEvalQuantizedInt8()
200 template <KernelType kernel_type>
219 if (kernel_type == kReference) { in MaxEvalFloat()
227 template <KernelType kernel_type>
248 if (kernel_type == kReference) { in MaxEvalQuantizedUInt8()
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Dquantize.cc46 template <KernelType kernel_type, typename output_type>
52 if (kernel_type == kReference) { in AffineQuantize()
61 template <KernelType kernel_type, typename input_type, typename output_type>
67 if (kernel_type == kReference) { in Requantize()
138 template <KernelType kernel_type>
157 AffineQuantize<kernel_type>(op_params, input_shape, input_data, in Eval()
162 AffineQuantize<kernel_type>(op_params, input_shape, input_data, in Eval()
167 AffineQuantize<kernel_type>(op_params, input_shape, input_data, in Eval()
180 Requantize<kernel_type>(GetTensorData<int16_t>(input), in Eval()
198 Requantize<kernel_type>(input_data, size, data->output_multiplier, in Eval()
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Dstrided_slice.cc165 template <KernelType kernel_type>
174 #define TF_LITE_STRIDED_SLICE(kernel_type, data_type) \ in Eval() argument
175 kernel_type::StridedSlice(op_params, GetTensorShape(op_context.input), \ in Eval()
182 if (kernel_type == kReference) { in Eval()
187 if (kernel_type == kReference) { in Eval()
192 if (kernel_type == kReference) { in Eval()
197 if (kernel_type == kReference) { in Eval()
202 if (kernel_type == kReference) { in Eval()
207 if (kernel_type == kReference) { in Eval()
212 if (kernel_type == kReference) { in Eval()
Dslice.cc138 template <KernelType kernel_type>
178 #define TF_LITE_SLICE(data_type, kernel_type) \ in Eval() argument
190 if (kernel_type == kGenericOptimized) { \ in Eval()
201 TF_LITE_SLICE(float, kernel_type); in Eval()
204 TF_LITE_SLICE(int32_t, kernel_type); in Eval()
207 TF_LITE_SLICE(int64_t, kernel_type); in Eval()
210 TF_LITE_SLICE(int8_t, kernel_type); in Eval()
213 TF_LITE_SLICE(uint8_t, kernel_type); in Eval()
216 TF_LITE_SLICE(bool, kernel_type); in Eval()
219 TF_LITE_SLICE(string, kernel_type); in Eval()
Dconv.cc153 KernelType kernel_type) { in IsIm2ColRequired() argument
174 switch (kernel_type) { in IsIm2ColRequired()
207 KernelType kernel_type) { in AllocateTemporaryTensorsIfRequired() argument
231 IsIm2ColRequired(input, params, filter, data, is_hybrid, kernel_type); in AllocateTemporaryTensorsIfRequired()
290 TfLiteStatus Prepare(KernelType kernel_type, TfLiteContext* context, in Prepare() argument
359 (kernel_type == kMultithreadOptimized) && in Prepare()
365 context, node, is_hybrid, is_hybrid_per_channel, kernel_type)); in Prepare()
538 template <KernelType kernel_type>
540 return Prepare(kernel_type, context, node); in Prepare()
543 template <KernelType kernel_type>
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Dresize_bilinear.cc89 template <KernelType kernel_type>
113 if (kernel_type == kReference) { in Eval()
116 if (kernel_type == kGenericOptimized || kernel_type == kNeonOptimized) { in Eval()
120 if (kernel_type == kReference) { in Eval()
123 if (kernel_type == kGenericOptimized || kernel_type == kNeonOptimized) { in Eval()
Dmul.cc100 template <KernelType kernel_type>
119 if (kernel_type == kReference) { in EvalMul()
133 if (kernel_type == kReference) { in EvalMul()
150 template <KernelType kernel_type>
173 if (kernel_type == kReference) { in EvalQuantized()
188 if (kernel_type == kReference) { in EvalQuantized()
211 if (kernel_type == kReference) { in EvalQuantized()
231 if (kernel_type == kReference) { in EvalQuantized()
246 template <KernelType kernel_type>
256 EvalMul<kernel_type>(context, node, params, data, input1, input2, output); in Eval()
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Ddepth_to_space.cc79 template <KernelType kernel_type>
95 if (kernel_type == kReference) { in Eval()
102 if (kernel_type == kReference) { in Eval()
109 if (kernel_type == kReference) { in Eval()
116 if (kernel_type == kReference) { in Eval()
123 if (kernel_type == kReference) { in Eval()
Dspace_to_depth.cc75 template <KernelType kernel_type>
91 if (kernel_type == kReference) { in Eval()
98 if (kernel_type == kReference) { in Eval()
105 if (kernel_type == kReference) { in Eval()
112 if (kernel_type == kReference) { in Eval()
119 if (kernel_type == kReference) { in Eval()
Dpad.cc122 template <KernelType kernel_type>
163 if (kernel_type == kReference) { in Eval()
169 } else if (kernel_type == kGenericOptimized) { in Eval()
196 if (kernel_type == kReference) { in Eval()
202 } else if (kernel_type == kGenericOptimized) { in Eval()
240 if (kernel_type == kReference) { in Eval()
242 } else if (kernel_type == kGenericOptimized) { in Eval()
251 if (kernel_type == kReference) { in Eval()
253 } else if (kernel_type == kGenericOptimized) { in Eval()
Ddiv.cc100 template <KernelType kernel_type>
116 if (kernel_type == kReference) { in EvalDiv()
130 if (kernel_type == kReference) { in EvalDiv()
147 template <KernelType kernel_type>
169 if (kernel_type == kReference) { in EvalQuantized()
191 template <KernelType kernel_type>
201 EvalDiv<kernel_type>(context, node, params, data, input1, input2, output); in Eval()
204 context, EvalQuantized<kernel_type>(context, node, params, data, input1, in Eval()
Dexp.cc55 template <KernelType kernel_type>
59 #define TF_LITE_EXP(kernel_type, data_type) \ in Eval() argument
60 kernel_type::Exp<data_type>(GetTensorData<data_type>(op_context.input), \ in Eval()
65 if (kernel_type == kReference) { in Eval()
Dfully_connected.cc253 template <KernelType kernel_type>
263 const bool is_pie = kernel_type == kLegacyPie; in Prepare()
382 template <KernelType kernel_type>
397 if (kernel_type == kReference) { in FullyConnectedInt8()
415 template <KernelType kernel_type>
435 template <KernelType kernel_type>
463 if (kernel_type == kReference) { in EvalQuantized()
479 FullyConnectedInt8<kernel_type>( in EvalQuantized()
485 FullyConnectedInt16<kernel_type>(data, input, filter, bias, output); in EvalQuantized()
486 } else if (kernel_type == kReference) { in EvalQuantized()
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Dadd.cc169 template <KernelType kernel_type>
187 if (kernel_type == kReference) { in EvalAdd()
201 if (kernel_type == kReference) { in EvalAdd()
218 template <KernelType kernel_type>
246 if (kernel_type == kReference) { in EvalAddQuantized()
260 if (kernel_type == kReference) { in EvalAddQuantized()
288 if (kernel_type == kReference) { in EvalAddQuantized()
299 template <KernelType kernel_type>
309 EvalAdd<kernel_type>(context, node, params, data, input1, input2, output); in Eval()
313 EvalAddQuantized<kernel_type>(context, node, params, data, in Eval()
Ddepthwise_conv.cc274 template <KernelType kernel_type>
295 if (kernel_type == kReference) { in EvalFloat()
312 template <KernelType kernel_type>
339 if (kernel_type == kReference) { in EvalQuantized()
356 template <KernelType kernel_type>
380 if (kernel_type == kReference) { in EvalQuantizedPerChannel()
401 template <KernelType kernel_type>
443 if (kernel_type == kReference) { in EvalHybridPerChannel()
463 template <KernelType kernel_type, TfLiteType input_type>
479 return EvalFloat<kernel_type>(context, node, params, data, input, in EvalImpl()
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Dspace_to_batch_nd.cc109 template <KernelType kernel_type>
131 if (kernel_type == kReference) { in Eval()
138 if (kernel_type == kReference) { in Eval()
147 if (kernel_type == kReference) { in Eval()
156 if (kernel_type == kReference) { in Eval()
163 if (kernel_type == kReference) { in Eval()
Dbatch_to_space_nd.cc120 template <KernelType kernel_type>
140 if (kernel_type == kReference) { in Eval()
147 if (kernel_type == kReference) { in Eval()
154 if (kernel_type == kReference) { in Eval()
161 if (kernel_type == kReference) { in Eval()
168 if (kernel_type == kReference) { in Eval()
Dtranspose_conv.cc128 template <KernelType kernel_type>
137 if (kernel_type == kGenericOptimized) { in AllocateTemporaryTensorsIfRequired()
148 if (kernel_type == kGenericOptimized) { in AllocateTemporaryTensorsIfRequired()
242 template <KernelType kernel_type>
272 TF_LITE_ENSURE_STATUS(AllocateTemporaryTensorsIfRequired<kernel_type>( in Prepare()
343 template <KernelType kernel_type>
357 switch (kernel_type) { in EvalFloat()
379 template <KernelType kernel_type>
405 switch (kernel_type) { in EvalQuantized()
428 template <KernelType kernel_type>
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Ddequantize.h40 template <KernelType kernel_type>
48 if (kernel_type == kReference) { in DequantizeImpl()
59 if (kernel_type == kReference) { in DequantizeImpl()
70 if (kernel_type == kReference) { in DequantizeImpl()
Dl2norm.cc72 template <KernelType kernel_type>
99 if (kernel_type == kReference) { in Eval()
102 if (kernel_type == kGenericOptimized) { in Eval()
114 if (kernel_type == kReference) { in Eval()
117 if (kernel_type == kGenericOptimized) { in Eval()
Dactivations.cc385 template <KernelType kernel_type>
395 if (kernel_type == kFixedPointOptimized) { in TanhPrepare()
414 if (kernel_type == kGenericOptimized || kernel_type == kReference) { in TanhPrepare()
462 template <KernelType kernel_type>
472 if (kernel_type == kFixedPointOptimized) { in SigmoidPrepare()
501 if (kernel_type == kGenericOptimized || kernel_type == kReference) { in SigmoidPrepare()
697 template <KernelType kernel_type>
705 if (kernel_type == kReference) { in HardSwishEval()
718 if (kernel_type == kReference) { in HardSwishEval()
731 if (kernel_type == kReference) { in HardSwishEval()
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/external/libaom/libaom/test/
Dhiprec_convolve_test_util.cc24 InterpKernel vkernel, int kernel_type = 2) { in generate_kernels() argument
25 if (kernel_type == 0) { in generate_kernels()
32 } else if (kernel_type == 1) { in generate_kernels()
111 for (int kernel_type = 0; kernel_type < 3; kernel_type++) { in RunCheckOutput() local
112 generate_kernels(&rnd_, hkernel, vkernel, kernel_type); in RunCheckOutput()
255 for (int kernel_type = 0; kernel_type < 3; kernel_type++) { in RunCheckOutput() local
256 generate_kernels(&rnd_, hkernel, vkernel, kernel_type); in RunCheckOutput()
/external/tensorflow/tensorflow/cc/gradients/
Dimage_grad_test.cc200 Input translation, const string& kernel_type, bool antialias, in MakeOp() argument
204 ScaleAndTranslate::KernelType(kernel_type) in MakeOp()
213 Input translation, const string& kernel_type, in TestScaleAndTranslate() argument
218 kernel_type, antialias, &x, &y); in TestScaleAndTranslate()
242 for (const std::string& kernel_type : kKernelTypes) { in TEST_F() local
244 kXShape, kOutHeight, kOutWidth, scale, translation, kernel_type, in TEST_F()
274 for (const std::string& kernel_type : kKernelTypes) { in TEST_F() local
276 kXShape, kOutHeight, kOutWidth, scale, translation, kernel_type, in TEST_F()
291 for (const std::string& kernel_type : kKernelTypes) { in TEST_F() local
293 kXShape, kOutHeight, kOutWidth, scale, translation, kernel_type, in TEST_F()
/external/tensorflow/tensorflow/lite/micro/kernels/
Dstrided_slice.cc132 template <KernelType kernel_type>
137 #define TF_LITE_STRIDED_SLICE(kernel_type, data_type) \ in Eval() argument
138 kernel_type::StridedSlice(op_params, GetTensorShape(op_context.input), \ in Eval()
145 if (kernel_type == kReference) { in Eval()
150 if (kernel_type == kReference) { in Eval()
155 if (kernel_type == kReference) { in Eval()
/external/tensorflow/tensorflow/lite/kernels/internal/
Ddepthwiseconv_quantized_test.cc225 DotProduct3x3KernelType kernel_type = in DispatchDepthwiseConvImpl() local
229 ASSERT_NE(kernel_type, DotProduct3x3KernelType::kNone) in DispatchDepthwiseConvImpl()
230 << "Kernel type = " << static_cast<int>(kernel_type); in DispatchDepthwiseConvImpl()
243 DotProduct3x3KernelType kernel_type = in DispatchDepthwiseConvImpl() local
248 kernel_type == DotProduct3x3KernelType::kPlain || in DispatchDepthwiseConvImpl()
249 kernel_type == DotProduct3x3KernelType::kStride2 || in DispatchDepthwiseConvImpl()
250 kernel_type == in DispatchDepthwiseConvImpl()
252 kernel_type == in DispatchDepthwiseConvImpl()
254 << "Kernel type = " << static_cast<int>(kernel_type) in DispatchDepthwiseConvImpl()
277 DotProduct3x3KernelType kernel_type = in DispatchDepthwiseConvImpl() local
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