/external/tensorflow/tensorflow/compiler/tests/ |
D | pooling_ops_test.py | 74 def _VerifyOneTest(self, pool_func, input_sizes, ksize, strides, padding, argument 98 ksize = NHWCToNCHW(ksize) 101 ksize=ksize, 110 def _VerifyValues(self, pool_func, input_sizes, ksize, strides, padding, argument 124 self._VerifyOneTest(pool_func, input_sizes, ksize, strides, padding, 131 ksize=[1, 2, 2, 1], 140 ksize=[1, 2, 2, 1], 157 ksize=[1, 1, 2, 1], 166 ksize=[1, 2, 2, 1], 173 ksize=[1, 2, 2, 1], [all …]
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D | pooling_ops_3d_test.py | 34 def _AvgPoolGrad(inputs, outputs, output_gradients, ksize, strides, padding): argument 39 ksize=ksize, 69 ksize=[1] + window + [1], 194 ksize, argument 209 ksize = [1] + ksize + [1] 220 ksize=ksize, 240 ksize=ksize, 255 ksize=ksize, 271 ksize=ksize, 279 ksize=ksize, [all …]
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | pooling_ops_test.py | 108 def _VerifyOneType(self, pool_func, input_sizes, ksize, strides, padding, argument 139 input_sizes, total_size, pool_func, ksize, strides, 152 ksize = test_util.NHWCToNCHW(ksize) 159 ksize=ksize_placeholder, 166 ksize=ksize, 177 ksize_placeholder: ksize, 185 def _VerifyOneTest(self, pool_func, input_sizes, ksize, strides, padding, argument 207 self._VerifyOneType(pool_func, input_sizes, ksize, strides, padding, 209 self._VerifyOneType(pool_func, input_sizes, ksize, strides, padding, 213 self._VerifyOneType(pool_func, input_sizes, ksize, strides, padding, [all …]
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D | extract_volume_patches_grad_test.py | 90 ksize = 5 95 ksizes=[1, ksize, ksize, ksize, 1],
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D | extract_image_patches_grad_test.py | 112 ksize = 5 116 ksizes=[1, ksize, ksize, 1],
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/external/eigen/unsupported/test/ |
D | cxx11_tensor_image_patch.cpp | 189 int ksize = 2; // Corresponds to the Rows and Cols for tensor.extract_image_patches<>. in test_patch_padding_valid() local 197 …Tensor<float, 5> result = tensor.extract_image_patches(ksize, ksize, stride, stride, 1, 1, PADDING… in test_patch_padding_valid() 200 VERIFY_IS_EQUAL(result.dimension(1), ksize); // kernel rows in test_patch_padding_valid() 201 VERIFY_IS_EQUAL(result.dimension(2), ksize); // kernel cols in test_patch_padding_valid() 212 …Tensor<float, 5, RowMajor> result_row_major = tensor_row_major.extract_image_patches(ksize, ksize,… in test_patch_padding_valid() 223 for (int i = 0; (i+stride+ksize-1) < input_rows; i += stride) { // input rows in test_patch_padding_valid() 224 for (int j = 0; (j+stride+ksize-1) < input_cols; j += stride) { // input cols in test_patch_padding_valid() 226 for (int r = 0; r < ksize; ++r) { // patch rows in test_patch_padding_valid() 227 for (int c = 0; c < ksize; ++c) { // patch cols in test_patch_padding_valid() 265 int ksize = 3; // Corresponds to the Rows and Cols for tensor.extract_image_patches<>. in test_patch_padding_valid_same_value() local [all …]
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/external/tensorflow/tensorflow/core/framework/ |
D | ops_util.cc | 40 Status GetBroadcastSize(const int index, const int in_size, const int ksize, in GetBroadcastSize() argument 49 *bsize = ksize; in GetBroadcastSize() 53 *bsize = ksize + *bindex - pad_size; in GetBroadcastSize() 59 if (*bindex + ksize > in_size) { in GetBroadcastSize() 60 *bsize = std::min((in_size - *bindex), ksize); in GetBroadcastSize()
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/external/tensorflow/tensorflow/python/ops/ |
D | nn_ops.py | 3368 def avg_pool_v2(input, ksize, strides, padding, data_format=None, name=None): # pylint: disable=re… argument 3410 ksize = _get_sequence(ksize, n, channel_index, "ksize") 3422 ksize=ksize, 3430 def avg_pool(value, ksize, strides, padding, data_format="NHWC", argument 3461 ksize = _get_sequence(ksize, 2, channel_index, "ksize") 3466 ksize=ksize, 3474 def avg_pool2d(input, ksize, strides, padding, data_format="NHWC", name=None): # pylint: disable=r… argument 3500 ksize = _get_sequence(ksize, 2, channel_index, "ksize") 3505 ksize=ksize, 3513 def avg_pool1d(input, ksize, strides, padding, data_format="NWC", name=None): # pylint: disable=re… argument [all …]
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D | init_ops.py | 873 def _orthogonal_kernel(self, ksize, cin, cout): argument 889 if ksize == 1: 894 for _ in range(ksize - 2): 898 for i in range(ksize): 899 for j in range(ksize): 902 return self._dict_to_tensor(p, ksize, ksize) 998 def _orthogonal_kernel(self, ksize, cin, cout): argument 1014 if ksize == 1: 1018 for _ in range(ksize - 2): 1021 for i in range(ksize): [all …]
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D | nn_test.py | 1249 ksize = 2 1252 y1 = nn_ops.avg_pool_v2(x, ksize, strides, "SAME") 1253 y2 = nn_ops.avg_pool1d(x, ksize, strides, "SAME") 1259 ksize = 2 1262 y1 = nn_ops.avg_pool_v2(x, ksize, strides, "SAME") 1263 y2 = nn_ops.avg_pool1d(x, ksize, strides, "SAME") 1269 ksize = 2 1272 y1 = nn_ops.avg_pool_v2(x, ksize, strides, "SAME") 1273 y2 = nn_ops.avg_pool(x, ksize, strides, "SAME") 1279 ksize = 2 [all …]
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/external/tensorflow/tensorflow/core/kernels/ |
D | maxpooling_op.cc | 270 std::vector<int32> ksize = ksize_; in Compute() local 275 ksize.resize(tensor_ksize.shape().num_elements()); in Compute() 276 std::copy_n(&value_ksize(0), ksize.size(), ksize.begin()); in Compute() 284 OP_REQUIRES(context, ksize.size() == 4, in Compute() 290 OP_REQUIRES(context, ksize[0] == 1 && stride[0] == 1, in Compute() 294 context, ksize[3] == 1 && stride[3] == 1, in Compute() 298 PoolParameters params{context, ksize, stride, in Compute() 394 std::vector<int32> ksize = ksize_; in Compute() local 399 ksize.resize(tensor_ksize.shape().num_elements()); in Compute() 400 std::copy_n(&value_ksize(0), ksize.size(), ksize.begin()); in Compute() [all …]
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D | mkl_pooling_ops_common.cc | 225 const std::vector<int32>& ksize, in Init() argument 247 Init(context, ksize, stride, padding, data_format); in Init() 253 const std::vector<int32>& ksize, in Init() argument 263 Init(context, ksize, stride, padding, data_format); in Init() 268 const std::vector<int32>& ksize, in Init() argument 273 if (ksize.size() == 4) { in Init() 288 Init(context, ksize, stride, padding, data_format); in Init() 293 const std::vector<int32>& ksize, in Init() argument 299 bool is_pool2d = (ksize.size() == 4); in Init() 303 window_rows = GetTensorDim(ksize, data_format, 'H'); in Init() [all …]
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D | quantized_pooling_ops_test.cc | 39 const int ksize = 2; in TEST_F() local 46 .Attr("ksize", {1, ksize, ksize, 1}) in TEST_F() 84 const int ksize = 2; in TEST_F() local 91 .Attr("ksize", {1, ksize, ksize, 1}) in TEST_F()
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D | mkl_quantized_pooling_ops_test.cc | 65 const int ksize = 2; in TEST_F() local 75 .Attr("ksize", {1, ksize, ksize, 1}) in TEST_F() 134 const int ksize = 2; in TEST_F() local 144 .Attr("ksize", {1, ksize, ksize, 1}) in TEST_F()
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/external/linux-kselftest/tools/testing/selftests/bpf/ |
D | test_get_stack_rawtp.c | 60 int max_len, max_buildid_len, usize, ksize, total_size; in bpf_prog1() local 90 ksize = bpf_get_stack(ctx, raw_data + usize, max_len - usize, 0); in bpf_prog1() 91 if (ksize < 0) in bpf_prog1() 94 total_size = usize + ksize; in bpf_prog1()
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/external/tensorflow/tensorflow/cc/gradients/ |
D | nn_grad_test.cc | 241 const std::vector<int> ksize{1, 2, 2, 1}; in TEST_F() local 243 auto y = MaxPool(scope_, x, ksize, strides, "VALID"); in TEST_F() 254 Tensor ksize = test::AsTensor<int>({1, 2, 2, 1}, {4}); in TEST_F() local 256 auto y = MaxPoolV2(scope_, x, ksize, strides, "VALID"); in TEST_F() 267 const std::vector<int> ksize{1, 3, 3, 3, 1}; in TEST_F() local 269 auto y = MaxPool3D(scope_, x, ksize, strides, "VALID"); in TEST_F() 280 const std::vector<int> ksize{1, 2, 2, 1}; in TEST_F() local 282 auto y = AvgPool(scope_, x, ksize, strides, "SAME"); in TEST_F() 291 const std::vector<int> ksize{1, 3, 3, 3, 1}; in TEST_F() local 293 auto y = AvgPool3D(scope_, x, ksize, strides, "SAME"); in TEST_F()
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D | nn_grad.cc | 246 std::vector<int32> ksize; in MaxPoolGradHelper() local 249 TF_RETURN_IF_ERROR(GetNodeAttr(attrs, "ksize", &ksize)); in MaxPoolGradHelper() 253 scope, op.input(0), op.output(0), grad_inputs[0], ksize, strides, padding, in MaxPoolGradHelper() 281 std::vector<int32> ksize; in MaxPool3DGradHelper() local 286 TF_RETURN_IF_ERROR(GetNodeAttr(attrs, "ksize", &ksize)); in MaxPool3DGradHelper() 292 MaxPool3DGrad(scope, op.input(0), op.output(0), grad_inputs[0], ksize, in MaxPool3DGradHelper() 302 std::vector<int32> ksize; in AvgPoolGradHelper() local 307 TF_RETURN_IF_ERROR(GetNodeAttr(attrs, "ksize", &ksize)); in AvgPoolGradHelper() 313 grad_inputs[0], ksize, strides, padding, in AvgPoolGradHelper() 323 std::vector<int32> ksize; in AvgPool3DGradHelper() local [all …]
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/external/tensorflow/tensorflow/contrib/receptive_field/python/util/ |
D | parse_layer_parameters.py | 190 ksize = node.attr["ksize"] 191 kernel_size_y = ksize.list.i[1] 192 kernel_size_x = ksize.list.i[2] 193 if ksize.list.i[0] != 1: 195 if ksize.list.i[3] != 1:
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/external/tensorflow/tensorflow/core/api_def/base_api/ |
D | api_def_MaxPool3D.pbtxt | 16 name: "ksize" 19 the input tensor. Must have `ksize[0] = ksize[4] = 1`.
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D | api_def_AvgPool3D.pbtxt | 16 name: "ksize" 19 the input tensor. Must have `ksize[0] = ksize[4] = 1`.
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D | api_def_AvgPool3DGrad.pbtxt | 22 name: "ksize" 25 the input tensor. Must have `ksize[0] = ksize[4] = 1`.
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D | api_def_MaxPool3DGrad.pbtxt | 22 name: "ksize" 25 the input tensor. Must have `ksize[0] = ksize[4] = 1`.
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D | api_def_MaxPool3DGradGrad.pbtxt | 28 name: "ksize" 31 the input tensor. Must have `ksize[0] = ksize[4] = 1`.
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/external/tensorflow/tensorflow/lite/testing/nnapi_tflite_zip_tests/ |
D | test_manifest.txt | 17 avg_pool/avg_pool_data_format='NHWC',input_shape=[1,1,1,1],ksize=[1,1,1,1],padding='SAME',strides=[… 18 avg_pool/avg_pool_data_format='NHWC',input_shape=[1,1,1,1],ksize=[1,1,1,1],padding='SAME',strides=[… 19 avg_pool/avg_pool_data_format='NHWC',input_shape=[1,1,1,1],ksize=[1,1,1,1],padding='SAME',strides=[… 20 avg_pool/avg_pool_data_format='NHWC',input_shape=[1,15,14,1],ksize=[1,1,1,1],padding='SAME',strides… 21 avg_pool/avg_pool_data_format='NHWC',input_shape=[1,15,14,1],ksize=[1,1,1,1],padding='SAME',strides… 22 avg_pool/avg_pool_data_format='NHWC',input_shape=[1,15,14,1],ksize=[1,1,1,1],padding='SAME',strides… 23 avg_pool/avg_pool_data_format='NHWC',input_shape=[3,15,14,3],ksize=[1,1,1,1],padding='SAME',strides… 24 avg_pool/avg_pool_data_format='NHWC',input_shape=[3,15,14,3],ksize=[1,1,1,1],padding='SAME',strides… 25 avg_pool/avg_pool_data_format='NHWC',input_shape=[3,15,14,3],ksize=[1,1,1,1],padding='SAME',strides… 26 avg_pool/avg_pool_data_format='NHWC',input_shape=[1,1,1,1],ksize=[1,1,1,1],padding='VALID',strides=… [all …]
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/external/eigen/bench/ |
D | benchmark-blocking-sizes.cpp | 572 for (size_t ksize = minsize; ksize <= maxsize; ksize *= 2) { in run() local 575 for (size_t kblock = minsize; kblock <= ksize; kblock *= 2) { in run() 578 benchmarks.emplace_back(ksize, msize, nsize, kblock, mblock, nblock); in run() 603 for (size_t ksize = minsize; ksize <= maxsize; ksize *= 2) { in run() local 606 benchmarks.emplace_back(ksize, msize, nsize); in run()
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