| /external/tensorflow/tensorflow/compiler/tests/ |
| pooling_ops_test.py | 74 def _VerifyOneTest(self, pool_func, input_sizes, ksize, strides, padding,
81 ksize: The kernel size dimensions
98 ksize = NHWCToNCHW(ksize)
101 ksize=ksize,
110 def _VerifyValues(self, pool_func, input_sizes, ksize, strides, padding,
118 ksize: The kernel size dimensions
124 self._VerifyOneTest(pool_func, input_sizes, ksize, strides, padding,
131 ksize=[1, 2, 2, 1]
[all...] |
| pooling_ops_3d_test.py | 34 def _AvgPoolGrad(inputs, outputs, output_gradients, ksize, strides, padding):
39 ksize=ksize,
69 ksize=[1] + window + [1],
190 def _VerifyGradient(self, pool_func, pool_grad_func, input_sizes, ksize,
198 ksize: The kernel size dimensions
202 ksize = [1] + ksize + [1]
213 ksize=ksize,
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| ops_util.cc | 37 Status GetBroadcastSize(const int index, const int in_size, const int ksize,
46 *bsize = ksize;
50 *bsize = ksize + *bindex - pad_size;
56 if (*bindex + ksize > in_size) {
57 *bsize = std::min((in_size - *bindex), ksize);
|
| mkl_pooling_ops_common.cc | 29 const std::vector<int32>& ksize,
42 Init(context, ksize, stride, padding, data_format);
48 const std::vector<int32>& ksize,
58 Init(context, ksize, stride, padding, data_format);
63 const std::vector<int32>& ksize,
73 Init(context, ksize, stride, padding, data_format);
78 const std::vector<int32>& ksize,
85 window_rows = GetTensorDim(ksize, data_format, 'H');
86 window_cols = GetTensorDim(ksize, data_format, 'W');
87 depth_window = GetTensorDim(ksize, data_format, 'C')
[all...] |
| quantized_pooling_ops_test.cc | 39 const int ksize = 2; local
46 .Attr("ksize", {1, ksize, ksize, 1})
84 const int ksize = 2; local
91 .Attr("ksize", {1, ksize, ksize, 1})
|
| maxpooling_op.cc | 212 OP_REQUIRES_OK(context, context->GetAttr("ksize", &ksize_));
214 errors::InvalidArgument("Sliding window ksize field must "
256 std::vector<int32> ksize = ksize_; variable
261 ksize.resize(tensor_ksize.shape().num_elements());
262 std::copy_n(&value_ksize(0), ksize.size(), ksize.begin());
270 OP_REQUIRES(context, ksize.size() == 4,
271 errors::InvalidArgument("Sliding window ksize field must "
276 OP_REQUIRES(context, ksize[0] == 1 && stride[0] == 1,
280 context, ksize[3] == 1 && stride[3] == 1
380 std::vector<int32> ksize = ksize_; variable
485 std::vector<int32> ksize = ksize_; variable
686 std::vector<int32> ksize = ksize_; variable
824 std::vector<int32> ksize = ksize_; variable
1148 std::vector<int32> ksize = ksize_; variable
[all...] |
| pooling_ops_3d.h | 42 Pool3dParameters(OpKernelContext* context, const std::vector<int32>& ksize,
|
| ops_util.h | 38 Status GetBroadcastSize(const int index, const int in_size, const int ksize,
|
| mkl_pooling_ops_common.h | 85 void Init(OpKernelContext* context, const std::vector<int32>& ksize,
89 void Init(OpKernelContext* context, const std::vector<int32>& ksize,
93 void Init(OpKernelContext* context, const std::vector<int32>& ksize,
100 void Init(OpKernelContext* context, const std::vector<int32>& ksize,
118 OP_REQUIRES_OK(context, context->GetAttr("ksize", &this->ksize_));
120 errors::InvalidArgument("Sliding window ksize field must "
|
| pooling_ops_common.cc | 32 const std::vector<int32>& ksize,
51 window_rows = GetTensorDim(ksize, data_format, 'H');
52 window_cols = GetTensorDim(ksize, data_format, 'W');
53 depth_window = GetTensorDim(ksize, data_format, 'C');
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| pooling_ops_test.py | 95 def _VerifyOneType(self, pool_func, input_sizes, ksize, strides, padding,
103 ksize: The kernel size dimensions
126 input_sizes, total_size, pool_func, ksize, strides)
138 ksize = test_util.NHWCToNCHW(ksize)
145 ksize=ksize_placeholder,
152 ksize=ksize,
163 ksize_placeholder: ksize,
171 def _VerifyOneTest(self, pool_func, input_sizes, ksize, strides, padding
[all...] |
| pooling_ops_3d_test.py | 78 ksize=window,
248 ksize = [1, window[0], window[1], window[2], 1]
253 ksize = test_util.NHWCToNCHW(ksize)
259 ksize=ksize,
|
| /external/eigen/unsupported/test/ |
| cxx11_tensor_image_patch.cpp | 189 int ksize = 2; // Corresponds to the Rows and Cols for tensor.extract_image_patches<>. local
197 Tensor<float, 5> result = tensor.extract_image_patches(ksize, ksize, stride, stride, 1, 1, PADDING_VALID);
200 VERIFY_IS_EQUAL(result.dimension(1), ksize); // kernel rows
201 VERIFY_IS_EQUAL(result.dimension(2), ksize); // kernel cols
212 Tensor<float, 5, RowMajor> result_row_major = tensor_row_major.extract_image_patches(ksize, ksize, stride, stride, 1, 1, PADDING_VALID);
223 for (int i = 0; (i+stride+ksize-1) < input_rows; i += stride) { // input rows
224 for (int j = 0; (j+stride+ksize-1) < input_cols; j += stride) { // input cols
226 for (int r = 0; r < ksize; ++r) { // patch row
265 int ksize = 3; \/\/ Corresponds to the Rows and Cols for tensor.extract_image_patches<>. local
338 int ksize = 2; \/\/ Corresponds to the Rows and Cols for tensor.extract_image_patches<>. local
[all...] |
| /external/opencv/cv/src/ |
| cvfilter.cpp | 108 trow_sz = cvAlign( (max_width + ksize.width - 1)*CV_ELEM_SIZE(src_type), ALIGN );
113 width += ksize.width - 1;
137 _ksize.width == ksize.width && _ksize.height == ksize.height &&
145 ksize = _ksize;
149 anchor.x = ksize.width / 2;
151 anchor.y = ksize.height / 2;
153 max_ky = MAX( anchor.y, ksize.height - anchor.y - 1 );
157 if( ksize.width <= 0 || ksize.height <= 0 |
[all...] |
| cvsmooth.cpp | 131 scale = normalized ? 1./(ksize.width*ksize.height) : 1;
181 s = sum = buf_end + cvAlign((width + ksize.width - 1)*CV_ELEM_SIZE(src_type), ALIGN);
194 int ksize = state->get_kernel_size().width; local
199 width = (width - 1)*cn; ksize *= cn;
204 for( i = 0; i < ksize; i += cn )
209 s += src[i+ksize] - src[i];
220 int ksize = state->get_kernel_size().width; local
225 width = (width - 1)*cn; ksize *= cn;
230 for( i = 0; i < ksize; i += cn
248 int ksize = state->get_kernel_size().height; local
308 int ksize = state->get_kernel_size().height; local
385 int ksize = state->get_kernel_size().height; local
443 int ksize = state->get_kernel_size().height; local
1479 CvSize ksize = { param1, param2 }; local
[all...] |
| _cvimgproc.h | 83 CvMat* icvIPPFilterInit( const CvMat* src, int stripe_size, CvSize ksize );
86 CvSize ksize, CvPoint anchor );
|
| cvderiv.cpp | 388 trow_sz = cvAlign( (max_width + ksize.width - 1)*CV_ELEM_SIZE(src_type), ALIGN );
494 int ksize = _kx->cols + _kx->rows - 1; \
497 int ksize2 = ksize/2, ksize2n = ksize2*cn; \
512 else if( ksize == 3 ) \
519 else if( ksize == 5 ) \
552 int ksize = _kx->cols + _kx->rows - 1, ksize2 = ksize/2; local
557 int shift = ksize - 1, delta = (1 << shift) >> 1;
573 if( ksize == 3 )
607 else if( ksize == 5
694 int ksize = _kx->cols + _kx->rows - 1, ksize2 = ksize\/2; local
[all...] |
| cvmorph.cpp | 235 ksize.width*ksize.height*(2*sizeof(int) + sizeof(uchar*))));
269 for( i = 0; i < ksize.height; i++ )
270 for( j = 0; j < ksize.width; j++ )
468 int ksize = state->get_kernel_size().width; \
473 width *= cn; ksize *= cn; \
475 if( ksize == cn ) \
488 for( j = cn*2; j < ksize; j += cn ) \
502 for( j = cn; j < ksize; j += cn ) \
527 int ksize = state->get_kernel_size().height;
[all...] |
| /external/tensorflow/tensorflow/contrib/receptive_field/python/util/ |
| parse_layer_parameters.py | 177 if not ksize_input_name.endswith("/ksize"):
178 raise ValueError("Kernel size name does not end with '/ksize'")
185 raise ValueError("pool ksize for first dim is not 1")
187 raise ValueError("pool ksize for last dim is not 1")
189 ksize = node.attr["ksize"]
190 kernel_size_y = ksize.list.i[1]
191 kernel_size_x = ksize.list.i[2]
192 if ksize.list.i[0] != 1:
193 raise ValueError("pool ksize for first dim is not 1"
[all...] |
| /external/eigen/bench/ |
| benchmark-blocking-sizes.cpp | 572 for (size_t ksize = minsize; ksize <= maxsize; ksize *= 2) {
575 for (size_t kblock = minsize; kblock <= ksize; kblock *= 2) {
578 benchmarks.emplace_back(ksize, msize, nsize, kblock, mblock, nblock);
603 for (size_t ksize = minsize; ksize <= maxsize; ksize *= 2) {
606 benchmarks.emplace_back(ksize, msize, nsize);
|
| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| pooling_ops.cc | 43 OP_REQUIRES_OK(ctx, ctx->GetAttr("ksize", &ksize_int));
45 errors::InvalidArgument("Sliding window ksize field must "
82 std::vector<int64> ksize = ksize_; variable
88 errors::InvalidArgument("ksize must be a vector, not shape ",
91 errors::InvalidArgument("Sliding window ksize field must "
94 ksize.clear();
95 OP_REQUIRES_OK(ctx, ctx->ConstantInputAsIntVector(1, &ksize));
116 input, InitValue(ctx->builder(), type), *Reduction(ctx, type), ksize,
163 .CompileTimeConstInput("ksize")
180 const std::vector<int64>& ksize, const std::vector<int64>& stride
[all...] |
| /external/tensorflow/tensorflow/cc/gradients/ |
| nn_grad_test.cc | 185 const std::vector<int> ksize{1, 2, 2, 1};
187 auto y = MaxPool(scope_, x, ksize, strides, "VALID");
198 Tensor ksize = test::AsTensor<int>({1, 2, 2, 1}, {4}); local
200 auto y = MaxPoolV2(scope_, x, ksize, strides, "VALID");
|
| nn_grad.cc | 157 std::vector<int32> ksize; local
160 TF_RETURN_IF_ERROR(GetNodeAttr(attrs, "ksize", &ksize));
168 ksize, strides,
|
| /external/python/cpython2/PC/ |
| _subprocess.c | 355 int ksize, vsize, totalsize; local
364 ksize = PyString_GET_SIZE(key);
366 totalsize = (p - PyString_AS_STRING(out)) + ksize + 1 +
374 memcpy(p, PyString_AS_STRING(key), ksize);
375 p += ksize;
|
| /external/icu/icu4c/source/common/ |
| locid.cpp | 301 int32_t ksize = 0; local
367 ksize = (int32_t)uprv_strlen(newKeywords);
368 if ( ksize < 0 || ksize > ULOC_STRING_LIMIT ) {
372 size += ksize + 1;
396 if ( ksize != 0)
|
