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Functions873 in github.com/Maratyszcza/NNPACK

⨍ Functions 873◇ Types & classes 270

↓ 2 callersFunctionnnp_relu_input_gradient

src/relu-input-gradient.c:35

↓ 2 callersFunctionnnp_softmax_output

src/softmax-output.c:50

↓ 2 callersFunctionnnp_softmax_output__reference

src/ref/softmax-output.c:49

↓ 2 callersMethodoutputSize

test/testers/winograd.h:44

↓ 2 callersFunctionpool1

* VGG model A pool1 layer: * channels = 64 * input size = 224x224 * implicit padding = 0 * pooling size = 2x2 *

test/models/vgg-a.h:262

↓ 2 callersFunctionpool2

* VGG model A pool2 layer: * channels = 128 * input size = 112x112 * implicit padding = 0 * pooling size = 2x2 *

test/models/vgg-a.h:279

↓ 2 callersFunctionpool3

* VGG model A pool3 layer: * channels = 256 * input size = 56x56 * implicit padding = 0 * pooling size = 2x2 * p

test/models/vgg-a.h:296

↓ 2 callersFunctionpsimd_fft16_dualreal_f32

src/psimd/fft/dualreal.h:56

↓ 2 callersFunctionpsimd_fft4_aos_f32

src/psimd/fft/aos.h:12

↓ 2 callersFunctionpsimd_fft8_aos_f32

src/psimd/fft/aos.h:185

↓ 2 callersFunctionpsimd_fft8_dualreal_f32

src/psimd/fft/dualreal.h:9

↓ 2 callersFunctionpsimd_ifft4_aos_f32

src/psimd/fft/aos.h:125

↓ 2 callersFunctionpsimd_ifft8_aos_f32

src/psimd/fft/aos.h:420

↓ 2 callersFunctionscalar_fft16_dualreal

src/scalar/fft/dualreal.h:51

↓ 2 callersFunctionscalar_fft16_real

src/scalar/fft/real.h:49

↓ 2 callersFunctionscalar_fft4_aos

src/scalar/fft/aos.h:10

↓ 2 callersFunctionscalar_fft8_aos

src/scalar/fft/aos.h:183

↓ 2 callersFunctionscalar_fft8_dualreal

src/scalar/fft/dualreal.h:7

↓ 2 callersFunctionscalar_fft8_real

src/scalar/fft/real.h:7

↓ 2 callersFunctionscalar_ifft4_aos

src/scalar/fft/aos.h:123

↓ 2 callersFunctionscalar_ifft8_aos

src/scalar/fft/aos.h:418

↓ 2 callersFunctionscaled_exp_minus_c

(reg_n, reg_x, reg_y, ymm_scale, ymm_c)

src/x86_64-fma/softmax.py:188

↓ 2 callersFunctionscaled_exp_minus_c__scalar

src/psimd/softmax.c:92

↓ 2 callersFunctionscaled_exp_minus_c__scalar

src/scalar/softmax.c:25

↓ 2 callersFunctionsum_exp_minus_c__psimd

src/psimd/softmax.c:62

↓ 2 callersFunctionsum_exp_minus_c__scalar

src/psimd/softmax.c:54

↓ 2 callersFunctionsum_exp_minus_c__scalar

src/scalar/softmax.c:17

↓ 2 callersFunctionulpf

src/x86_64-fma/exp.c:67

↓ 2 callersFunctionvalidate_relu_arguments

include/nnpack/validation.h:142

↓ 1 callersFunctionaverage

bench/median.c:29

↓ 1 callersFunctionaverage_profile

bench/median.c:33

↓ 1 callersFunctionbenchmark_batch_transform

bench/transform.c:124

↓ 1 callersFunctionbenchmark_convolution

bench/convolution.c:37

↓ 1 callersFunctionbenchmark_fully_connected

bench/fully-connected.c:22

↓ 1 callersFunctionbenchmark_gemm

bench/gemm.c:31

↓ 1 callersFunctionbenchmark_pooling

bench/pooling.c:16

↓ 1 callersFunctionbenchmark_relu

bench/relu.c:23

↓ 1 callersFunctioncompute_direct_convolution_inference

src/convolution-inference.c:953

↓ 1 callersFunctioncompute_fast_convolution_inference

src/convolution-inference.c:470

↓ 1 callersFunctioncompute_fast_convolution_input_gradient

src/convolution-input-gradient.c:238

↓ 1 callersFunctioncompute_fast_convolution_kernel_gradient

src/convolution-kernel-gradient.c:222

↓ 1 callersFunctioncompute_fast_convolution_output

src/convolution-output.c:235

↓ 1 callersFunctioncompute_fully_connected_output

src/fully-connected-output.c:140

↓ 1 callersFunctioncompute_gemm_convolution_inference

src/convolution-inference.c:736

↓ 1 callersFunctionconvolution

(mode, batch_size, input_channels, output_channels, image_size, kernel_size, padding, algorithm, transform_str

benchmark.py:13

↓ 1 callersFunctionfully_connected

(mode, batch_size, input_channels, output_channels, threads=None, verbose=False, use_selldr=False)

benchmark.py:57

↓ 1 callersFunctionget_x86_cpu_info

bench/perf_counter.c:22

↓ 1 callersFunctioninit_static_hwinfo

↓ 1 callersFunctioninit_static_ios_hwinfo

↓ 1 callersFunctioninit_x86_hwinfo

↓ 1 callersFunctioninplace_scaled_exp_minus_c__psimd

src/psimd/softmax.c:98

↓ 1 callersFunctionmain

configure.py:16

↓ 1 callersFunctionneon_grad_reluq_f32

include/nnpack/activations.h:32

↓ 1 callersFunctionnnp_conv1x1_only_2x4__psimd

src/psimd/blas/conv1x1.c:14

↓ 1 callersFunctionnnp_conv1x1_only_2x4__scalar

src/scalar/blas/conv1x1.c:5

↓ 1 callersFunctionnnp_conv1x1_only_4x4__neon

src/neon/blas/conv1x1.c:8

↓ 1 callersFunctionnnp_convolution_input_gradient__reference

src/ref/convolution-input-gradient.c:56

↓ 1 callersFunctionnnp_convolution_kernel_gradient__reference

src/ref/convolution-kernel.c:71

↓ 1 callersFunctionnnp_deinitialize

↓ 1 callersFunctionnnp_fully_connected_output_f16f32__reference

src/ref/fully-connected-output.c:75

↓ 1 callersFunctionnnp_h4gemm_only_3x3__neonhp

src/neon/blas/h4gemm.c:8

↓ 1 callersFunctionnnp_h4gemm_upto_3x3__neonhp

src/neon/blas/h4gemm.c:71

↓ 1 callersFunctionnnp_iwt8x8_3x3_fp16_with_offset__neonhp

src/neon/2d-winograd-8x8-3x3-fp16.c:13

↓ 1 callersFunctionnnp_iwt8x8_3x3_with_offset__neon

src/neon/2d-winograd-8x8-3x3.c:13

↓ 1 callersFunctionnnp_max_pooling_output__reference

src/ref/max-pooling-output.c:51

↓ 1 callersFunctionnnp_owt8x8_3x3__neon

src/neon/2d-winograd-8x8-3x3.c:186

↓ 1 callersFunctionnnp_owt8x8_3x3_fp16__neonhp

src/neon/2d-winograd-8x8-3x3-fp16.c:136

↓ 1 callersFunctionnnp_relu_input_gradient__reference

src/ref/relu-input-gradient.c:29

↓ 1 callersFunctionnnp_s2gemm_only_2x2__scalar

src/scalar/blas/s2gemm.c:5

↓ 1 callersFunctionnnp_s4gemm_only_3x3__neon

src/neon/blas/s4gemm.c:8

↓ 1 callersFunctionnnp_s4gemm_only_3x4__psimd

src/psimd/blas/s4gemm.c:7

↓ 1 callersFunctionnnp_s4gemm_upto_3x3__neon

src/neon/blas/s4gemm.c:67

↓ 1 callersFunctionnnp_sgemm_only_4x3__scalar

src/scalar/blas/sgemm.c:7

↓ 1 callersFunctionnnp_sgemm_only_4x8__psimd

src/psimd/blas/sgemm.c:9

↓ 1 callersFunctionnnp_sgemm_only_6x8__neon

src/neon/blas/sgemm.c:8

↓ 1 callersFunctionoutplace_scaled_exp_minus_c__psimd

src/psimd/softmax.c:125

↓ 1 callersMethodoutputHeight

test/testers/pooling.h:165

↓ 1 callersMethodoutputHeight

test/testers/convolution.h:168

↓ 1 callersMethodoutputWidth

test/testers/pooling.h:171

↓ 1 callersMethodoutputWidth

test/testers/convolution.h:172

↓ 1 callersFunctionparse_options

bench/convolution.c:253

↓ 1 callersFunctionparse_options

bench/ugemm.c:111

↓ 1 callersFunctionparse_options

bench/gemm.c:120

↓ 1 callersFunctionparse_options

bench/pooling.c:85

↓ 1 callersFunctionparse_options

bench/relu.c:96

↓ 1 callersFunctionparse_options

bench/transform.c:359

↓ 1 callersFunctionparse_options

bench/fully-connected.c:126

↓ 1 callersFunctionperf_event_open

bench/perf_counter.c:630

↓ 1 callersFunctionpool4

* VGG model A pool4 layer: * channels = 512 * input size = 28x28 * implicit padding = 0 * pooling size = 2x2 * p

test/models/vgg-a.h:313

↓ 1 callersFunctionpool5

* VGG model A pool5 layer: * channels = 512 * input size = 14x14 * implicit padding = 0 * pooling size = 2x2 * p

test/models/vgg-a.h:330

↓ 1 callersFunctionprofile_batch_fft

bench/transform.c:250

↓ 1 callersFunctionprofile_gemm

bench/ugemm.c:24

↓ 1 callersFunctionpsimd_grad_relu_f32

include/nnpack/activations.h:19

↓ 1 callersFunctionround_up_by_power_of_2

include/nnpack/utils.h:29

↓ 1 callersFunctionselect_algorithm

src/convolution-inference.c:1022

↓ 1 callersFunctionswitch

src/convolution-inference.c:883

↓ 1 callersFunctiontranspose8x3

src/x86_64-fma/winograd/o6x6k3x3.py:329

↓ 1 callersFunctiontranspose8x8

src/x86_64-fma/winograd/o6x6k3x3.py:225

↓ 1 callersFunctionvalidate_pooling_arguments

include/nnpack/validation.h:102

↓ 1 callersFunctionvalidate_softmax_arguments

include/nnpack/validation.h:164

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