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/external/tensorflow/tensorflow/core/kernels/
Deigen_backward_spatial_convolutions_test.cc32 const int input_rows = 3; in TEST() local
37 const int output_rows = input_rows - patch_rows + 1; in TEST()
40 Tensor<float, 3> input_backward(input_depth, input_rows, input_cols); in TEST()
49 input_rows, input_cols, 1); in TEST()
52 EXPECT_EQ(input_backward.dimension(1), input_rows); in TEST()
56 for (int i = 0; i < input_rows; ++i) { in TEST()
81 const int input_rows = 3; in TEST() local
86 const int output_rows = input_rows - patch_rows + 1; in TEST()
89 Tensor<float, 3, RowMajor> input_backward(input_cols, input_rows, in TEST()
101 input_rows, input_cols, 1); in TEST()
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Ddilation_ops_gpu.cu.cc40 const T* filter_ptr, int batch, int input_rows, in DilationKernel() argument
59 if (h_in >= 0 && h_in < input_rows) { in DilationKernel()
65 input_cols * (h_in + input_rows * b))] + in DilationKernel()
81 const T* out_backprop_ptr, int batch, int input_rows, int input_cols, in DilationBackpropInputKernel() argument
103 if (h_in >= 0 && h_in < input_rows) { in DilationBackpropInputKernel()
109 input_cols * (h_in + input_rows * b))] + in DilationBackpropInputKernel()
122 depth * (w_in_max + input_cols * (h_in_max + input_rows * b)), in DilationBackpropInputKernel()
130 const T* out_backprop_ptr, int batch, int input_rows, int input_cols, in DilationBackpropFilterKernel() argument
152 if (h_in >= 0 && h_in < input_rows) { in DilationBackpropFilterKernel()
158 input_cols * (h_in + input_rows * b))] + in DilationBackpropFilterKernel()
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Deigen_pooling_test.cc29 const int input_rows = 5; in TEST() local
37 Tensor<float, 4> input(depth, input_rows, input_cols, num_batches); in TEST()
77 const int input_rows = 5; in TEST() local
85 Tensor<float, 4, RowMajor> input(num_batches, input_cols, input_rows, depth); in TEST()
127 const int input_rows = 5; in TEST() local
137 Tensor<float, 5> input(channels, input_planes, input_rows, input_cols, in TEST()
187 const int input_rows = 5; in TEST() local
197 Tensor<float, 5, RowMajor> input(num_batches, input_cols, input_rows, in TEST()
247 const int input_rows = 5; in TEST() local
257 Tensor<float, 5> input(channels, input_planes, input_rows, input_cols, in TEST()
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Deigen_spatial_convolutions_test.cc31 const int input_rows = 4; in TEST() local
36 const int output_rows = input_rows; in TEST()
39 Tensor<float, 3> input(input_depth, input_rows, input_cols); in TEST()
76 const int input_rows = 4; in TEST() local
81 const int output_rows = input_rows; in TEST()
84 Tensor<float, 3, RowMajor> input(input_cols, input_rows, input_depth); in TEST()
195 const int input_rows = 5; in TEST() local
201 const int output_rows = input_rows - patch_rows + 1; in TEST()
204 Tensor<float, 4> input(input_depth, input_rows, input_cols, num_batches); in TEST()
247 const int input_rows = 5; in TEST() local
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Dmkl_conv_ops.h132 int input_rows = static_cast<int>(input_rows_raw); in GetInputSizeInMklOrder() local
143 mkldnn_sizes[MklDnnDims::Dim_H] = input_rows; in GetInputSizeInMklOrder()
156 int input_rows = static_cast<int>(input_rows_raw); in GetInputSizeInMklOrder() local
168 mkldnn_sizes[MklDnnDims3D::Dim3d_H] = input_rows; in GetInputSizeInMklOrder()
324 int input_planes, input_rows, input_cols; variable
326 input_rows = GetTensorDim(input_shape, data_format_, 'H');
330 input_rows = GetTensorDim(input_shape, data_format_, '1');
407 input_rows, filter_rows, dilation_rows, stride_rows,
418 input_rows, filter_rows, stride_rows,
Ddilation_ops.cc75 const int input_rows = input.dim_size(1); in ParseSizes() local
107 context, GetWindowedOutputSize(input_rows, filter_rows_eff, *stride_rows, in ParseSizes()
169 const int input_rows = input.dimension(1); in operator ()() local
190 if (h_in >= 0 && h_in < input_rows) { in operator ()()
278 const int input_rows = input.dimension(1); in operator ()() local
307 if (h_in >= 0 && h_in < input_rows) { in operator ()()
398 const int input_rows = input.dimension(1); in operator ()() local
427 if (h_in >= 0 && h_in < input_rows) { in operator ()()
Dconv_ops.cc155 const Tensor& filter, int batch, int input_rows, in Run() argument
171 const Tensor& filter, int batch, int input_rows, in Run() argument
186 args.in_rows = input_rows; in Run()
212 const Tensor& filter, int batch, int input_rows, in Run() argument
226 const Tensor& filter, int batch, int input_rows, in Run() argument
238 desc.H = input_rows; in Run()
374 const int input_rows = static_cast<int>(input_rows_raw); in ComputeConv2DDimension() local
411 input_rows, filter_rows, dilation_rows, stride_rows, params.padding, in ComputeConv2DDimension()
418 dimensions->input_rows = input_rows; in ComputeConv2DDimension()
478 << ", input_rows = " << dimensions.input_rows in Compute()
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Deigen_benchmark.h88 Eigen::Index input_rows = input_dims[1]; in SpatialConvolutionBackwardInput() local
108 filter, output_backward, input_rows, input_cols); in SpatialConvolutionBackwardInput()
225 Eigen::Index input_rows = input_dims[1]; in CuboidConvolutionBackwardInput() local
246 filter, output_backward, input_planes, input_rows, input_cols); in CuboidConvolutionBackwardInput()
Dconv_ops_using_gemm.cc495 const int input_rows = static_cast<int>(input_rows_raw); in Compute() local
522 GetWindowedOutputSize(input_rows, filter_rows, stride_rows, in Compute()
538 << ", input_rows = " << input_rows in Compute()
549 conv_functor(context, input.flat<T>().data(), batch, input_rows, input_cols, in Compute()
Ddepthwise_conv_op.cc334 const int32 input_rows = static_cast<int32>(input_rows_raw); in Compute() local
350 GetWindowedOutputSize(input_rows, filter_rows, stride_, in Compute()
378 << " Input: [" << batch << ", " << input_rows << ", " << input_cols in Compute()
414 args.in_rows = input_rows; in Compute()
/external/libopus/src/
Dmapping_matrix.c88 int input_rows, in mapping_matrix_multiply_channel_in_float() argument
98 celt_assert(input_rows <= matrix->cols && output_rows <= matrix->rows); in mapping_matrix_multiply_channel_in_float()
105 for (col = 0; col < input_rows; col++) in mapping_matrix_multiply_channel_in_float()
109 input[MATRIX_INDEX(input_rows, col, i)]; in mapping_matrix_multiply_channel_in_float()
123 int input_rows, in mapping_matrix_multiply_channel_out_float() argument
134 celt_assert(input_rows <= matrix->cols && output_rows <= matrix->rows); in mapping_matrix_multiply_channel_out_float()
141 input_sample = (1/32768.f)*input[input_rows * i]; in mapping_matrix_multiply_channel_out_float()
143 input_sample = input[input_rows * i]; in mapping_matrix_multiply_channel_out_float()
159 int input_rows, in mapping_matrix_multiply_channel_in_short() argument
169 celt_assert(input_rows <= matrix->cols && output_rows <= matrix->rows); in mapping_matrix_multiply_channel_in_short()
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Dmapping_matrix.h68 int input_rows,
79 int input_rows,
89 int input_rows,
100 int input_rows,
/external/tensorflow/tensorflow/compiler/xla/service/cpu/
Druntime_single_threaded_conv2d.cc27 Eigen::half* rhs, int64 input_batch, int64 input_rows, int64 input_cols, in __xla_cpu_runtime_EigenSingleThreadedConvF16() argument
35 Eigen::DefaultDevice(), out, lhs, rhs, input_batch, input_rows, in __xla_cpu_runtime_EigenSingleThreadedConvF16()
45 int64 input_batch, int64 input_rows, int64 input_cols, int64 input_channels, in __xla_cpu_runtime_EigenSingleThreadedConvF32() argument
52 Eigen::DefaultDevice(), out, lhs, rhs, input_batch, input_rows, in __xla_cpu_runtime_EigenSingleThreadedConvF32()
Druntime_conv2d.cc29 int64 input_batch, int64 input_rows, int64 input_cols, int64 input_channels, in __xla_cpu_runtime_EigenConvF32() argument
39 input_rows, input_cols, input_channels, kernel_rows, kernel_cols, in __xla_cpu_runtime_EigenConvF32()
47 Eigen::half* rhs, int64 input_batch, int64 input_rows, int64 input_cols, in __xla_cpu_runtime_EigenConvF16() argument
58 input_rows, input_cols, input_channels, kernel_rows, kernel_cols, in __xla_cpu_runtime_EigenConvF16()
Druntime_conv2d_mkl.cc53 ScalarType* rhs, int64 input_batch, int64 input_rows, in MKLConvImpl() argument
69 ToInt(input_rows), ToInt(input_cols)}; in MKLConvImpl()
154 int64 input_batch, int64 input_rows, int64 input_cols, int64 input_channels, in __xla_cpu_runtime_MKLConvF32() argument
165 run_options_ptr, out, lhs, rhs, input_batch, input_rows, input_cols, in __xla_cpu_runtime_MKLConvF32()
171 MKLConvImpl(nullptr, out, lhs, rhs, input_batch, input_rows, input_cols, in __xla_cpu_runtime_MKLConvF32()
Druntime_single_threaded_conv2d.h27 tensorflow::int64 input_batch, tensorflow::int64 input_rows,
41 tensorflow::int64 input_rows, tensorflow::int64 input_cols,
Druntime_conv2d.h27 tensorflow::int64 input_rows, tensorflow::int64 input_cols,
41 tensorflow::int64 input_batch, tensorflow::int64 input_rows,
Druntime_conv2d_impl.h29 ScalarType* rhs, int64 input_batch, int64 input_rows, in EigenConvImpl() argument
40 input(lhs, input_batch, input_rows, input_cols, input_channels); in EigenConvImpl()
Druntime_conv2d_mkl.h27 tensorflow::int64 input_rows, tensorflow::int64 input_cols,
/external/eigen/unsupported/test/
Dcxx11_tensor_image_patch.cpp186 int input_rows = 3; in test_patch_padding_valid() local
191 Tensor<float, 4> tensor(input_depth, input_rows, input_cols, input_batches); 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()
225 int patchId = i+input_rows*j; in test_patch_padding_valid()
234 … if (row_offset >= 0 && col_offset >= 0 && row_offset < input_rows && col_offset < input_cols) { in test_patch_padding_valid()
262 int input_rows = 5; in test_patch_padding_valid_same_value() local
268 Tensor<float, 4> tensor(input_depth, input_rows, input_cols, input_batches); in test_patch_padding_valid_same_value()
296 for (int i = 0; (i+stride+ksize-1) <= input_rows; i += stride) { // input rows in test_patch_padding_valid_same_value()
298 int patchId = i+input_rows*j; in test_patch_padding_valid_same_value()
307 … if (row_offset >= 0 && col_offset >= 0 && row_offset < input_rows && col_offset < input_cols) { in test_patch_padding_valid_same_value()
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/external/tensorflow/tensorflow/python/kernel_tests/
Dconv_ops_test.py1638 def ConstructAndTestGradient(self, batch, input_rows, input_cols, filter_rows, argument
1642 input_shape = [batch, input_rows, input_cols, in_depth]
1646 output_rows = (input_rows - filter_rows + stride_rows) // stride_rows
1649 output_rows = (input_rows + stride_rows - 1) // stride_rows
1653 output_rows = (input_rows + padding[1][0] + padding[1][1] - filter_rows +
1721 input_rows=5,
1739 input_rows=6,
1757 input_rows=4,
1775 input_rows=6,
1793 input_rows=7,
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Dconv_ops_3d_test.py371 input_planes, input_rows, input_cols = input_shape
374 input_shape = [batch, input_planes, input_rows, input_cols, in_depth]
388 math.ceil((input_rows - filter_rows + 1.0) / strides[2]))
393 output_rows = int(math.ceil(float(input_rows) / strides[2]))
/external/tensorflow/tensorflow/core/kernels/neon/
Dneon_depthwise_conv_op.cc79 const int32 input_rows = input.dim_size(1); in Compute() local
92 GetWindowedOutputSize(input_rows, filter_rows, stride, in Compute()
110 << " Input: [" << batch << ", " << input_rows << ", " << input_cols in Compute()
/external/tensorflow/tensorflow/contrib/factorization/python/ops/
Dwals.py181 input_rows = features[WALSMatrixFactorization.INPUT_ROWS]
281 input_rows,
324 sp_input=input_rows,
353 sp_input=input_rows, transpose_input=False)
/external/libjpeg-turbo/
Djcprepct.c109 expand_bottom_edge(JSAMPARRAY image_data, JDIMENSION num_cols, int input_rows, in expand_bottom_edge() argument
114 for (row = input_rows; row < output_rows; row++) { in expand_bottom_edge()
115 jcopy_sample_rows(image_data, input_rows - 1, image_data, row, 1, in expand_bottom_edge()

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