| /aosp_15_r20/external/tensorflow/tensorflow/lite/kernels/ |
| H A D | pooling.cc | 38 namespace pooling { namespace
471 static TfLiteRegistration r = {pooling::Init, pooling::Free, in Register_AVERAGE_POOL_REF()
472 pooling::GenericPrepare<pooling::kAverage>, in Register_AVERAGE_POOL_REF()
473 pooling::AverageEval<pooling::kReference>}; in Register_AVERAGE_POOL_REF()
478 static TfLiteRegistration r = {pooling::Init, pooling::Free, in Register_MAX_POOL_REF()
479 pooling::GenericPrepare<pooling::kMax>, in Register_MAX_POOL_REF()
480 pooling::MaxEval<pooling::kReference>}; in Register_MAX_POOL_REF()
485 static TfLiteRegistration r = {pooling::Init, pooling::Free, in Register_L2_POOL_REF()
486 pooling::GenericPrepare<pooling::kL2>, in Register_L2_POOL_REF()
487 pooling::L2Eval<pooling::kReference>}; in Register_L2_POOL_REF()
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| /aosp_15_r20/external/tensorflow/tensorflow/core/api_def/base_api/ |
| H A D | api_def_FractionalAvgPool.pbtxt | 12 output tensor after fractional avg pooling.
18 row pooling sequence, needed to calculate gradient.
24 column pooling sequence, needed to calculate gradient.
32 pooling ratio looks like [1.0, 1.44, 1.73, 1.0]. The first and last elements
33 must be 1.0 because we don't allow pooling on batch and channels
34 dimensions. 1.44 and 1.73 are pooling ratio on height and width dimensions
41 When set to True, generates the pooling sequence in a
50 When set to True, it means when pooling, the values at the boundary
51 of adjacent pooling cells are used by both cells. For example:
57 If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice.
[all …]
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| H A D | api_def_FractionalMaxPool.pbtxt | 12 output tensor after fractional max pooling.
18 row pooling sequence, needed to calculate gradient.
24 column pooling sequence, needed to calculate gradient.
32 pooling ratio looks like [1.0, 1.44, 1.73, 1.0]. The first and last elements
33 must be 1.0 because we don't allow pooling on batch and channels
34 dimensions. 1.44 and 1.73 are pooling ratio on height and width dimensions
41 When set to True, generates the pooling sequence in a
50 When set to True, it means when pooling, the values at the boundary
51 of adjacent pooling cells are used by both cells. For example:
57 If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice.
[all …]
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| H A D | api_def_FractionalAvgPoolGrad.pbtxt | 20 row pooling sequence, form pooling region with
27 column pooling sequence, form pooling region with
40 When set to True, it means when pooling, the values at the boundary
41 of adjacent pooling cells are used by both cells. For example:
47 If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice.
48 The result would be [41/3, 26/3] for fractional avg pooling.
55 out_backprop to those indices that form the same pooling cell. Therefore, we
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| H A D | api_def_FractionalMaxPoolGrad.pbtxt | 26 row pooling sequence, form pooling region with
33 column pooling sequence, form pooling region with
46 When set to True, it means when pooling, the values at the boundary
47 of adjacent pooling cells are used by both cells. For example:
53 If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice.
54 The result would be [20, 16] for fractional max pooling.
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| /aosp_15_r20/external/tensorflow/tensorflow/python/layers/ |
| H A D | pooling.py | 18 from tensorflow.python.keras.legacy_tf_layers import pooling
21 AveragePooling1D = pooling.AveragePooling1D
22 average_pooling1d = pooling.average_pooling1d
23 MaxPooling1D = pooling.MaxPooling1D
24 max_pooling1d = pooling.max_pooling1d
25 AveragePooling2D = pooling.AveragePooling2D
26 average_pooling2d = pooling.average_pooling2d
27 MaxPooling2D = pooling.MaxPooling2D
28 max_pooling2d = pooling.max_pooling2d
29 AveragePooling3D = pooling.AveragePooling3D
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| H A D | layers.py | 57 from tensorflow.python.layers.pooling import AveragePooling1D
58 from tensorflow.python.layers.pooling import MaxPooling1D
59 from tensorflow.python.layers.pooling import AveragePooling2D
60 from tensorflow.python.layers.pooling import MaxPooling2D
61 from tensorflow.python.layers.pooling import AveragePooling3D
62 from tensorflow.python.layers.pooling import MaxPooling3D
64 from tensorflow.python.layers.pooling import average_pooling1d
65 from tensorflow.python.layers.pooling import max_pooling1d
66 from tensorflow.python.layers.pooling import average_pooling2d
67 from tensorflow.python.layers.pooling import max_pooling2d
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| /aosp_15_r20/external/tensorflow/tensorflow/python/keras/layers/ |
| H A D | __init__.py | 108 from tensorflow.python.keras.layers.pooling import MaxPooling1D
109 from tensorflow.python.keras.layers.pooling import MaxPooling2D
110 from tensorflow.python.keras.layers.pooling import MaxPooling3D
111 from tensorflow.python.keras.layers.pooling import AveragePooling1D
112 from tensorflow.python.keras.layers.pooling import AveragePooling2D
113 from tensorflow.python.keras.layers.pooling import AveragePooling3D
114 from tensorflow.python.keras.layers.pooling import GlobalAveragePooling1D
115 from tensorflow.python.keras.layers.pooling import GlobalAveragePooling2D
116 from tensorflow.python.keras.layers.pooling import GlobalAveragePooling3D
117 from tensorflow.python.keras.layers.pooling import GlobalMaxPooling1D
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| /aosp_15_r20/external/ComputeLibrary/src/cpu/kernels/internal/ |
| H A D | CpuPool2dAssemblyWrapperKernel.cpp | 191 … arm_conv::pooling::PoolingType pool_type = (info.pool_type == PoolingType::AVG) ? arm_conv::pooli… in create_arm_pooling()
193 arm_conv::pooling::PoolingWindow window{}; in create_arm_pooling()
197 arm_conv::pooling::PoolingStride stride{}; in create_arm_pooling()
200 …const arm_conv::pooling::PaddingValues padding{ info.pad_stride_info.pad_left(), info.pad_stride_i… in create_arm_pooling()
214 …arm_conv::pooling::PoolingArgs args(&cpu_info, pool_type, window, stride, info.exclude_padding, n_… in create_arm_pooling()
217 auto pooling_kernel_asm = arm_conv::pooling::pooling<Typesrc, Typedst>(args); in create_arm_pooling()
230 … arm_conv::pooling::PoolingType pool_type = (info.pool_type == PoolingType::AVG) ? arm_conv::pooli… in create_arm_pooling_requant()
232 arm_conv::pooling::PoolingWindow window{}; in create_arm_pooling_requant()
236 arm_conv::pooling::PoolingStride stride{}; in create_arm_pooling_requant()
239 …const arm_conv::pooling::PaddingValues padding{ info.pad_stride_info.pad_left(), info.pad_stride_i… in create_arm_pooling_requant()
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| /aosp_15_r20/external/ComputeLibrary/src/ |
| H A D | BUILD.bazel | 205 …"core/NEON/kernels/arm_conv/pooling/kernels/sme_fp16_nhwc_avg_3x3_s1_output2x2_depthfirst/generic.…
206 "core/NEON/kernels/arm_conv/pooling/kernels/sme_fp16_nhwc_avg_generic_depthfirst/generic.cpp",
207 …"core/NEON/kernels/arm_conv/pooling/kernels/sme_fp16_nhwc_max_2x2_s1_output2x2_depthfirst/generic.…
208 "core/NEON/kernels/arm_conv/pooling/kernels/sme_fp16_nhwc_max_generic_depthfirst/generic.cpp",
209 …"core/NEON/kernels/arm_conv/pooling/kernels/sme_fp32_nhwc_avg_3x3_s1_output2x2_depthfirst/generic.…
210 "core/NEON/kernels/arm_conv/pooling/kernels/sme_fp32_nhwc_avg_generic_depthfirst/generic.cpp",
211 …"core/NEON/kernels/arm_conv/pooling/kernels/sme_fp32_nhwc_max_2x2_s1_output2x2_depthfirst/generic.…
212 "core/NEON/kernels/arm_conv/pooling/kernels/sme_fp32_nhwc_max_generic_depthfirst/generic.cpp",
213 "core/NEON/kernels/arm_conv/pooling/kernels/sme_s8_nhwc_avg_generic_depthfirst/generic.cpp",
214 …"core/NEON/kernels/arm_conv/pooling/kernels/sme_s8_nhwc_max_2x2_s1_output2x2_depthfirst/generic.cp…
[all …]
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| H A D | CMakeLists.txt | 184 …core/NEON/kernels/arm_conv/pooling/kernels/sme_fp16_nhwc_avg_3x3_s1_output2x2_depthfirst/generic.c…
185 core/NEON/kernels/arm_conv/pooling/kernels/sme_fp16_nhwc_avg_generic_depthfirst/generic.cpp
186 …core/NEON/kernels/arm_conv/pooling/kernels/sme_fp16_nhwc_max_2x2_s1_output2x2_depthfirst/generic.c…
187 core/NEON/kernels/arm_conv/pooling/kernels/sme_fp16_nhwc_max_generic_depthfirst/generic.cpp
188 …core/NEON/kernels/arm_conv/pooling/kernels/sme_fp32_nhwc_avg_3x3_s1_output2x2_depthfirst/generic.c…
189 core/NEON/kernels/arm_conv/pooling/kernels/sme_fp32_nhwc_avg_generic_depthfirst/generic.cpp
190 …core/NEON/kernels/arm_conv/pooling/kernels/sme_fp32_nhwc_max_2x2_s1_output2x2_depthfirst/generic.c…
191 core/NEON/kernels/arm_conv/pooling/kernels/sme_fp32_nhwc_max_generic_depthfirst/generic.cpp
192 core/NEON/kernels/arm_conv/pooling/kernels/sme_s8_nhwc_avg_generic_depthfirst/generic.cpp
193 core/NEON/kernels/arm_conv/pooling/kernels/sme_s8_nhwc_max_2x2_s1_output2x2_depthfirst/generic.cpp
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| /aosp_15_r20/external/pytorch/aten/src/ATen/native/quantized/cpu/qnnpack/ |
| H A D | CMakeLists.txt | 154 src/average-pooling.c
163 src/global-average-pooling.c
167 src/max-pooling.c
566 add_executable(max-pooling-test test/max-pooling.cc)
567 set_target_properties(max-pooling-test PROPERTIES
571 target_include_directories(max-pooling-test PRIVATE src test)
572 target_link_libraries(max-pooling-test PRIVATE pytorch_qnnpack cpuinfo gtest gtest_main)
573 add_test(max-pooling-test max-pooling-test)
575 add_executable(average-pooling-test test/average-pooling.cc)
576 set_target_properties(average-pooling-test PROPERTIES
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| H A D | buckbuild.bzl | 256 "src/average-pooling.c",
270 "src/global-average-pooling.c",
276 "src/max-pooling.c",
571 "test/average-pooling.cc",
578 "test/global-average-pooling.cc",
582 "test/max-pooling.cc",
603 "average-pooling-operator-tester.h": "test/average-pooling-operator-tester.h",
616 … "global-average-pooling-operator-tester.h": "test/global-average-pooling-operator-tester.h",
622 "max-pooling-operator-tester.h": "test/max-pooling-operator-tester.h",
|
| /aosp_15_r20/external/ComputeLibrary/ |
| H A D | Android.bp | 219 … "src/core/NEON/kernels/arm_conv/pooling/kernels/cpp_nhwc_1x1_stride_any_depthfirst/generic.cpp",
220 "src/core/NEON/kernels/arm_conv/pooling/pooling_fp16.cpp",
221 "src/core/NEON/kernels/arm_conv/pooling/pooling_fp32.cpp",
222 "src/core/NEON/kernels/arm_conv/pooling/pooling_s8.cpp",
223 "src/core/NEON/kernels/arm_conv/pooling/pooling_s8q.cpp",
224 "src/core/NEON/kernels/arm_conv/pooling/pooling_u8.cpp",
225 "src/core/NEON/kernels/arm_conv/pooling/pooling_u8q.cpp",
1037 …"src/core/NEON/kernels/arm_conv/pooling/kernels/a64_fp16_nhwc_avg_3x3_s1_output2x2_depthfirst/gene…
1038 … "src/core/NEON/kernels/arm_conv/pooling/kernels/a64_fp16_nhwc_avg_generic_depthfirst/generic.cpp",
1039 …"src/core/NEON/kernels/arm_conv/pooling/kernels/a64_fp16_nhwc_max_2x2_s1_output2x2_depthfirst/gene…
[all …]
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| /aosp_15_r20/external/armnn/src/backends/backendsCommon/test/ |
| H A D | EndToEndTestImpl.hpp | 202 IConnectableLayer* pooling = net->AddActivationLayer(descriptor); in ImportNonAlignedInputPointerTest() local
206 input->GetOutputSlot(0).Connect(pooling->GetInputSlot(0)); in ImportNonAlignedInputPointerTest()
207 pooling->GetOutputSlot(0).Connect(output->GetInputSlot(0)); in ImportNonAlignedInputPointerTest()
210 pooling->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32)); in ImportNonAlignedInputPointerTest()
270 IConnectableLayer* pooling = net->AddActivationLayer(descriptor); in ExportNonAlignedOutputPointerTest() local
274 input->GetOutputSlot(0).Connect(pooling->GetInputSlot(0)); in ExportNonAlignedOutputPointerTest()
275 pooling->GetOutputSlot(0).Connect(output->GetInputSlot(0)); in ExportNonAlignedOutputPointerTest()
278 pooling->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32)); in ExportNonAlignedOutputPointerTest()
345 IConnectableLayer* pooling = net->AddActivationLayer(descriptor); in ImportAlignedPointerTest() local
349 input->GetOutputSlot(0).Connect(pooling->GetInputSlot(0)); in ImportAlignedPointerTest()
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| /aosp_15_r20/external/armnn/src/armnn/test/ |
| H A D | EndToEndTest.cpp | 33 IConnectableLayer* pooling = net->AddNormalizationLayer(descriptor); variable
37 input->GetOutputSlot(0).Connect(pooling->GetInputSlot(0));
38 pooling->GetOutputSlot(0).Connect(output->GetInputSlot(0));
41 pooling->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 4, 4 }, DataType::Float32));
|
| /aosp_15_r20/external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| H A D | pooling_ops.cc | 206 auto pooling = xla::MaxPool( in Compile() local
213 StatusOr<xla::Shape> result_shape = ctx->builder()->GetShape(pooling); in Compile()
227 pooling = in Compile()
228 xla::Transpose(xla::Reshape(pooling, new_dims), {0, 1, 3, 4, 2}); in Compile()
231 ctx->SetOutput(0, pooling); in Compile()
288 auto pooling = in Compile() local
292 ctx->SetOutput(0, ConvertElementType(pooling, ctx->input_xla_type(0))); in Compile()
390 auto pooling = in Compile() local
393 auto status_or_shape = pooling.builder()->GetShape(pooling); in Compile()
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| /aosp_15_r20/packages/modules/NeuralNetworks/common/types/operations/src/ |
| D | Pooling.cpp | 25 namespace pooling { namespace
94 return pooling::validate(OperationType::AVERAGE_POOL_2D, context); in __anon99b48d8d0102()
97 return pooling::validate(OperationType::L2_POOL_2D, context); in __anon99b48d8d0202()
100 return pooling::validate(OperationType::MAX_POOL_2D, context); in __anon99b48d8d0302()
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| /aosp_15_r20/packages/modules/NeuralNetworks/common/cpu_operations/ |
| D | Pooling.cpp | 42 namespace pooling { namespace
382 NN_REGISTER_OPERATION_DEFAULT_VALIDATION(AVERAGE_POOL_2D, pooling::prepare,
383 pooling::executeAveragePool, .allowZeroSizedInput = true);
384 NN_REGISTER_OPERATION_DEFAULT_VALIDATION(L2_POOL_2D, pooling::prepare, pooling::executeL2Pool,
386 NN_REGISTER_OPERATION_DEFAULT_VALIDATION(MAX_POOL_2D, pooling::prepare, pooling::executeMaxPool,
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| /aosp_15_r20/external/armnn/src/backends/neon/test/ |
| H A D | NeonFallbackTests.cpp | 187 IConnectableLayer* pooling = net->AddPooling2dLayer(desc, "pooling"); variable
192 add->GetOutputSlot(0).Connect(pooling->GetInputSlot(0));
193 pooling->GetOutputSlot(0).Connect(output->GetInputSlot(0));
201 pooling->GetOutputSlot(0).SetTensorInfo(poolingInfo);
467 IConnectableLayer* pooling = net->AddPooling2dLayer(desc, "pooling"); variable
471 input0->GetOutputSlot(0).Connect(pooling->GetInputSlot(0));
473 pooling->GetOutputSlot(0).Connect(add->GetInputSlot(0));
481 pooling->GetOutputSlot(0).SetTensorInfo(poolingInfo);
1018 IConnectableLayer* pooling = net->AddPooling2dLayer(desc, "pooling"); variable
1025 sub->GetOutputSlot(0).Connect(pooling->GetInputSlot(0));
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| /aosp_15_r20/external/armnn/src/backends/cl/test/ |
| H A D | ClFallbackTests.cpp | 306 IConnectableLayer* pooling = net->AddPooling2dLayer(desc, "pooling"); variable
313 sub->GetOutputSlot(0).Connect(pooling->GetInputSlot(0));
314 pooling->GetOutputSlot(0).Connect(output->GetInputSlot(0));
325 pooling->GetOutputSlot(0).SetTensorInfo(poolingInfo);
465 IConnectableLayer* pooling = net->AddPooling2dLayer(desc, "pooling"); variable
472 sub->GetOutputSlot(0).Connect(pooling->GetInputSlot(0));
473 pooling->GetOutputSlot(0).Connect(output->GetInputSlot(0));
484 pooling->GetOutputSlot(0).SetTensorInfo(poolingInfo);
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| /aosp_15_r20/external/tensorflow/tensorflow/python/eager/benchmarks/resnet50/ |
| H A D | resnet50.py | 201 pooling=None, argument
214 self.pooling = pooling
282 if pooling == 'avg':
287 elif pooling == 'max':
|
| /aosp_15_r20/external/tensorflow/tensorflow/security/advisory/ |
| H A D | tfsa-2021-074.md | 1 ## TFSA-2021-074: Division by zero in optimized pooling implementations in TFLite
7 Optimized pooling implementations in TFLite fail to check that the stride
9 …w/tensorflow/blob/3f24ccd932546416ec906a02ddd183b48a1d2c83/tensorflow/lite/kernels/pooling.cc#L90).
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| /aosp_15_r20/external/ComputeLibrary/src/core/CL/cl_kernels/nchw/ |
| H A D | pooling_layer.cl | 68 /** Performs a pooling function of pool size equal to N (NCHW)
72 * @note In case of average pooling the following information must be passed at compile time:
73 * -DPOOL_AVG must be provided otherwise max pooling will be performed.
76 * -DPAD_X and -DPAD_Y which are the pooling paddings in x and y dimension
77 …* @note The initial value for the pooling operation must be passed at compile time using -DINITIAL…
178 // Divide by pool region in case of average pooling
204 // Take square root of the result in L2 pooling
214 /** Performs a MAX pooling of pool size equal to 2, and record max value indices for NCHW.
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| /aosp_15_r20/external/ComputeLibrary/src/core/CL/cl_kernels/nhwc/ |
| H A D | pooling_layer.cl | 46 /** Performs pooling layer of size equal to MxN. This OpenCL kernel can perform the following pooli…
61 …* @note The initial value for the pooling operation must be passed at compile time using -DINITIAL…
124 // Global pooling path
159 // Take square root of the result in L2 pooling
176 /** Performs pooling layer of size equal to 2. This OpenCL kernel can perform the following pooling…
191 …* @note The initial value for the pooling operation must be passed at compile time using -DINITIAL…
320 // Take square root of the result in L2 pooling
|