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/tflite-micro-3.4.0-2.7.6/tensorflow/lite/kernels/internal/reference/
Dtranspose.h57 for (int k = 0; k < N; ++k) { in TransposeImpl() local
58 TFLITE_DCHECK_EQ(input_desc.extents[extended_perm[k]], in TransposeImpl()
59 output_desc.extents[k]); in TransposeImpl()
60 perm_input_desc.extents[k] = input_desc.extents[extended_perm[k]]; in TransposeImpl()
61 perm_input_desc.strides[k] = input_desc.strides[extended_perm[k]]; in TransposeImpl()
Dconcatenation.h61 for (int k = 0; k < outer_size; k++) { in Concatenation() local
64 const Scalar* input_ptr = input_data[i] + k * copy_size; in Concatenation()
113 for (int k = 0; k < outer_size; k++) { in ConcatenationWithScaling() local
116 const uint8_t* input_ptr = input_data[i] + k * copy_size; in ConcatenationWithScaling()
Dbatch_matmul.h96 for (int k = 0; k < accum_depth; ++k) { in BatchMatMul() local
97 total += static_cast<Tout>(lhs_ptr2[accum_depth * i + k]) * in BatchMatMul()
98 static_cast<Tout>(rhs_ptr2[j * accum_depth + k]); in BatchMatMul()
184 for (int k = 0; k < accum_depth; ++k) { in BatchMatMul() local
186 lhs_ptr2[accum_depth * i + k] * rhs_ptr2[j * accum_depth + k]; in BatchMatMul()
253 for (int k = 0; k < accum_depth; ++k) { in BatchMatMul() local
254 AccumT lhs_val = lhs_ptr2[accum_depth * i + k]; in BatchMatMul()
255 AccumT rhs_val = rhs_ptr2[accum_depth * j + k]; in BatchMatMul()
/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/examples/magic_wand/train/
Ddata_augmentation.py34 for k in range(denominator):
36 k][j] = (data[molecule * i + k][j] * (denominator - k) +
37 data[molecule * i + k + 1][j] * k) / denominator
/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/kernels/ethos_u/
Dethosu.cc99 for (int k = 0; k < tensor->dims->size; k++) { in Eval() local
100 byte_size = byte_size * tensor->dims->data[k]; in Eval()
112 for (int k = 0; k < tensor->dims->size; k++) { in Eval() local
113 byte_size = byte_size * tensor->dims->data[k]; in Eval()
/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/kernels/ceva/
Ddepthwise_conv.cc90 for (int k = 0; k < batches; k++) { in EvalFloat() local
95 &input_data[k * input_height * input_width * input_depth], in EvalFloat()
98 &output_data[k * output_height * output_width * output_depth], in EvalFloat()
171 for (int k = 0; k < batches; k++) { in EvalQuantizedPerChannel() local
177 &input_data[k * input_height * input_width * input_depth], in EvalQuantizedPerChannel()
180 &output_data[k * output_height * output_width * output_depth], in EvalQuantizedPerChannel()
Dconv.cc104 for (int k = 0; k < batches; k++) { in EvalQuantizedPerChannel() local
113 &input_data[k * input_height * input_width * input_depth_Dims3], in EvalQuantizedPerChannel()
117 &output_data[k * output_height * output_width * output_depth_Dims3], in EvalQuantizedPerChannel()
184 for (int k = 0; k < batches; k++) { in EvalFloat() local
188 &input_data[k * input_height * input_width * input_depth_Dims3], in EvalFloat()
191 &output_data[k * output_height * output_width * output_depth_Dims3], in EvalFloat()
/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/kernels/
Dpack.cc62 for (int k = 0; k < outer_size; ++k) { in PackImpl() local
63 const T* input_ptr = input_data + copy_size * k; in PackImpl()
64 int loc = k * values_count * copy_size + i * copy_size; in PackImpl()
Dunpack.cc65 for (int k = 0; k < outer_size; ++k) { in UnpackImpl() local
66 T* output_ptr = output_data + copy_size * k; in UnpackImpl()
67 int loc = k * output_count * copy_size + i * copy_size; in UnpackImpl()
Dsplit.cc56 for (int k = 0; k < outer_size; ++k) { in SplitImpl() local
61 T* output_ptr = output_data + k * copy_size; in SplitImpl()
Dsplit_v.cc58 for (int k = 0; k < outer_size; ++k) { in SplitImpl() local
65 T* output_ptr = output_data + k * copy_size; in SplitImpl()
Dsvdf_common.cc316 for (int k = 0; k < input_size; ++k) { in EvalFloatSvdfReference() local
/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/tools/make/targets/
Dceva_makefile.inc50 __internal_data_size=512k \
52 __internal_code_size=256k \
73 -defsym __internal_code_size=0k \
74 -defsym __internal_data_size=512k
Dapollo3evb_makefile.inc111 # - Increase the stack size from 1k to 20k
/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/tools/make/templates/ceva/
Dceva_app_makefile_v18.0.5.tpl20 __internal_data_size=512k \
22 __internal_code_size=256k \
/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/tools/make/templates/ceva_SP500/
Dceva_app_makefile.tpl20 -defsym __internal_code_size=0k \
21 -defsym __internal_data_size=512k \
/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/tools/make/targets/ceva/
DCEVA_BX1_TFLM_18.0.2.ld25 __internal_code_size = DEFINED(__internal_code_size ) ? __internal_code_size : 256k;
27 __internal_data_size = DEFINED(__internal_data_size ) ? __internal_data_size : 512k;
33 __malloc_size = DEFINED(__malloc_size ) ? __malloc_size : 64k;
34 __stack_size = DEFINED(__stack_size ) ? __stack_size : 64k;
DCEVA_BX1_TFLM.ld25 __internal_code_size = DEFINED(__internal_code_size ) ? __internal_code_size : 256k;
27 __internal_data_size = DEFINED(__internal_data_size ) ? __internal_data_size : 512k;
33 __malloc_size = DEFINED(__malloc_size ) ? __malloc_size : 32k;
34 __stack_size = DEFINED(__stack_size ) ? __stack_size : 32k;
DCEVA_BX1_TFLM_18.0.3.ld26 __internal_code_size = DEFINED(__internal_code_size ) ? __internal_code_size : 256k;
28 __internal_data_size = DEFINED(__internal_data_size ) ? __internal_data_size : 512k;
34 __malloc_size = DEFINED(__malloc_size ) ? __malloc_size : 32k;
35 __stack_size = DEFINED(__stack_size ) ? __stack_size : 32k;
DCEVA_BX1_TFLM_18.0.5.ld26 __internal_code_size = DEFINED(__internal_code_size ) ? __internal_code_size : 256k;
28 __internal_data_size = DEFINED(__internal_data_size ) ? __internal_data_size : 512k;
34 __malloc_size = DEFINED(__malloc_size ) ? __malloc_size : 32k;
35 __stack_size = DEFINED(__stack_size ) ? __stack_size : 32k;
DCEVA_SP500_TFLM.ld26 __internal_data_size = DEFINED(__internal_data_size ) ? __internal_data_size : 256k;
32 __malloc_size = DEFINED(__malloc_size ) ? __malloc_size : 16k;
33 __stack_size = DEFINED(__stack_size ) ? __stack_size : 16k;
/tflite-micro-3.4.0-2.7.6/third_party/
Drepo.bzl34 return {ctx.path(v): Label(k) for k, v in link_files.items()}
/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/kernels/cmsis_nn/
Dsvdf.cc192 for (int k = 0; k < input_size; ++k) { in EvalFloatSVDF() local
/tflite-micro-3.4.0-2.7.6/third_party/hexagon/
Dsvdf.cc219 for (int k = 0; k < input_size; ++k) { in EvalFloatSVDF() local
/tflite-micro-3.4.0-2.7.6/tensorflow/lite/micro/kernels/arc_mli/
DREADME.md115 For example, to reduce sizes of arrays placed in DCCM and XCCM to 32k and 8k

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