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Searched refs:filter_rows (Results 1 – 25 of 31) sorted by relevance

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/external/tensorflow/tensorflow/core/util/
Duse_cudnn.cc116 bool ShouldCudnnGroupedConvolutionBeUsed(const int32_t filter_rows, in ShouldCudnnGroupedConvolutionBeUsed() argument
120 return in_depth == out_depth && filter_rows == filter_cols && in ShouldCudnnGroupedConvolutionBeUsed()
121 (filter_rows == 1 || filter_rows == 3 || filter_rows == 5 || in ShouldCudnnGroupedConvolutionBeUsed()
122 filter_rows == 7); in ShouldCudnnGroupedConvolutionBeUsed()
Duse_cudnn.h37 bool ShouldCudnnGroupedConvolutionBeUsed(const int32_t filter_rows,
/external/tensorflow/tensorflow/lite/kernels/internal/optimized/integer_ops/
Dfully_connected.h54 const int filter_rows = filter_shape.Dims(filter_dim_count - 2); in FullyConnectedPerChannel() local
56 TFLITE_DCHECK_EQ(filter_shape.FlatSize(), filter_rows * filter_cols); in FullyConnectedPerChannel()
58 TFLITE_DCHECK_EQ(output_rows, filter_rows); in FullyConnectedPerChannel()
66 lhs_params.rows = filter_rows; in FullyConnectedPerChannel()
82 dst_params.rows = filter_rows; in FullyConnectedPerChannel()
126 const int filter_rows = filter_shape.Dims(filter_dim_count - 2); in FullyConnected() local
128 TFLITE_DCHECK_EQ(filter_shape.FlatSize(), filter_rows * filter_cols); in FullyConnected()
130 TFLITE_DCHECK_EQ(output_rows, filter_rows); in FullyConnected()
138 lhs_params.rows = filter_rows; in FullyConnected()
154 dst_params.rows = filter_rows; in FullyConnected()
Dconv.h86 const int filter_rows = filter_shape.Dims(0); in ConvPerChannel() local
93 TFLITE_DCHECK_EQ(output_rows, filter_rows); in ConvPerChannel()
99 lhs_params.rows = filter_rows; in ConvPerChannel()
/external/tensorflow/tensorflow/core/kernels/
Ddilation_ops_gpu.cu.cc41 int depth, int filter_rows, int filter_cols, int output_rows, in DilationKernel() argument
55 for (int h = 0; h < filter_rows; ++h) { in DilationKernel()
80 int batch, int input_rows, int input_cols, int depth, int filter_rows, in DilationBackpropInputKernel() argument
100 for (int h = 0; h < filter_rows; ++h) { in DilationBackpropInputKernel()
130 int batch, int input_rows, int input_cols, int depth, int filter_rows, in DilationBackpropFilterKernel() argument
150 for (int h = 0; h < filter_rows; ++h) { in DilationBackpropFilterKernel()
190 const int filter_rows = filter.dimension(0); in operator ()() local
202 batch, input_rows, input_cols, depth, filter_rows, filter_cols, in operator ()()
221 const int filter_rows = filter.dimension(0); in operator ()() local
244 input_cols, depth, filter_rows, filter_cols, output_rows, output_cols, in operator ()()
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Ddepthwise_conv_grad_op.cc88 const int64_t filter_rows = filter_shape.dim_size(0); \
130 input_rows, filter_rows, stride_, padding_, \
150 args.filter_rows = filter_rows; \
161 << "]; Filter: [" << filter_rows << ", " << filter_cols << ", " \
201 const int64_t filter_rows = args.filter_rows; in CopyOutputBackpropRegion() local
211 (in_r - filter_rows + pad_rows + stride) / stride); in CopyOutputBackpropRegion()
219 const int64_t filter_spatial_size = args.filter_rows * args.filter_cols; in CopyOutputBackpropRegion()
220 if ((out_r_end - out_r_start + 1) < args.filter_rows || in CopyOutputBackpropRegion()
302 const int64_t filter_spatial_size = args.filter_rows * args.filter_cols; in ComputeBackpropInput()
405 const int64_t filter_spatial_size = args.filter_rows * args.filter_cols; in operator ()()
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Ddepthwise_conv_op.cc97 const int64_t filter_spatial_size = args.filter_rows * args.filter_cols; in Run()
179 const int64_t filter_spatial_size = args.filter_rows * args.filter_cols; in operator ()()
202 const int64_t filter_spatial_size = args.filter_rows * args.filter_cols; in operator ()()
382 const int32_t filter_rows = filter.dim_size(0); in Compute() local
404 input_rows, filter_rows, stride_, padding_, in Compute()
433 filter_rows, filter_cols, in_depth, out_depth))); in Compute()
437 << ", " << in_depth << "]; Filter: [" << filter_rows << ", " in Compute()
455 TensorShape{filter_rows, filter_cols, filter_in_depth, out_depth}; in Compute()
475 args.filter_rows = filter_rows; in Compute()
Ddilation_ops.cc93 const int filter_rows = filter.dim_size(0); in ParseSizes() local
103 filter_rows + (filter_rows - 1) * (*rate_rows - 1); in ParseSizes()
175 const int filter_rows = filter.dimension(0); in operator ()() local
190 for (int h = 0; h < filter_rows; ++h) { in operator ()()
290 const int filter_rows = filter.dimension(0); in operator ()() local
313 for (int h = 0; h < filter_rows; ++h) { in operator ()()
418 const int filter_rows = filter.dimension(0); in operator ()() local
441 for (int h = 0; h < filter_rows; ++h) { in operator ()()
457 if (h_max < filter_rows && w_max < filter_cols) { in operator ()()
Ddeep_conv2d.h73 int filter_rows; member
88 filter_rows(0), in Conv2DArgs()
100 bool CanUseDeepConv2D(int stride_rows, int stride_cols, int filter_rows,
Ddepthwise_conv_op.h31 int filter_rows; member
48 filter_rows(0), in DepthwiseArgs()
145 const int64_t filter_spatial_size = args.filter_rows * args.filter_cols;
219 for (int64_t f_r = 0; f_r < args.filter_rows; ++f_r) {
273 for (int64_t f_r = 0; f_r < args.filter_rows; ++f_r) {
306 for (int64_t f_r = 0; f_r < args.filter_rows; ++f_r) {
Ddepthwise_conv_op_gpu.h61 args.pad_rows < args.filter_rows && args.pad_cols >= 0 &&
63 args.filter_rows * args.filter_cols <=
74 args.pad_rows < args.filter_rows && args.pad_cols >= 0 &&
76 args.filter_rows * args.filter_cols <= args.in_cols * block_height;
97 kKnownFilterHeight < 0 ? args.filter_rows : kKnownFilterHeight;
208 kKnownFilterHeight < 0 ? args.filter_rows : kKnownFilterHeight;
344 kKnownFilterHeight < 0 ? args.filter_rows : kKnownFilterHeight;
499 kKnownFilterHeight < 0 ? args.filter_rows : kKnownFilterHeight;
659 const int tile_height = block_height * 2 + args.filter_rows - 1;
661 const int filter_pixels = args.filter_rows * args.filter_cols;
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Dconv_ops.cc368 int input_cols, int in_depth, int filter_rows, in Run() argument
384 int input_cols, int in_depth, int filter_rows, in Run() argument
391 !CanUseDeepConv2D(stride_rows, stride_cols, filter_rows, filter_cols, in Run()
401 args.filter_rows = filter_rows; in Run()
425 int input_cols, int in_depth, int filter_rows, in Run() argument
439 int input_cols, int in_depth, int filter_rows, in Run() argument
453 desc.R = filter_rows; in Run()
590 const int filter_rows = static_cast<int>(filter.dim_size(0)); in ComputeConv2DDimension() local
626 input_rows, filter_rows, dilation_rows, stride_rows, params.padding, in ComputeConv2DDimension()
636 dimensions->filter_rows = filter_rows; in ComputeConv2DDimension()
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Deigen_benchmark.h126 Eigen::Index filter_rows = filter_dims[0]; in SpatialConvolutionBackwardKernel() local
145 input, output_backward, filter_rows, filter_cols); in SpatialConvolutionBackwardKernel()
261 Eigen::Index filter_rows = filter_dims[0]; in CuboidConvolutionBackwardKernel() local
281 input, output_backward, filter_planes, filter_rows, filter_cols); in CuboidConvolutionBackwardKernel()
Dconv_ops_3d.cc247 const int64_t filter_rows = filter.dim_size(1); in launch() local
261 0, (out_rows - 1) * strides[1] + filter_rows - in_rows); in launch()
269 if (!is_grouped_convolution && filter_planes == 1 && filter_rows == 1 && in launch()
292 filter_rows == in_rows && filter_cols == in_cols && in launch()
421 .set_spatial_dim(DimIndex::Y, filter_rows) in launch()
494 {{filter_planes, filter_rows, filter_cols}}, in launch()
Dconv_ops_using_gemm.cc498 const int filter_rows = static_cast<int>(filter.dim_size(0)); in Compute() local
524 GetWindowedOutputSize(input_rows, filter_rows, stride_rows, in Compute()
541 << ", filter_rows = " << filter_rows in Compute()
552 in_depth, filter.flat<T>().data(), filter_rows, filter_cols, in Compute()
Ddeep_conv2d.cc75 static int64_t GetDirectConvCost(int filter_rows, int filter_cols, int in_depth, in GetDirectConvCost() argument
77 return filter_rows * filter_cols * in_depth * out_depth * out_rows * out_cols; in GetDirectConvCost()
98 bool CanUseDeepConv2D(int stride_rows, int stride_cols, int filter_rows, in CanUseDeepConv2D() argument
103 if (stride_rows > 1 || stride_cols > 1 || filter_rows != 3 || in CanUseDeepConv2D()
120 filter_rows, filter_cols, in_depth, out_depth, out_rows, out_cols); in CanUseDeepConv2D()
302 std::max(int64_t{0}, args.filter_rows - base_filter_rows); in operator ()()
339 if (f_r >= args.filter_rows) continue; in operator ()()
492 const int64_t shard_cost = args.filter_rows * args.filter_cols * in_depth * in operator ()()
971 std::max(int64_t{0}, args.filter_rows - base_filter_rows); in operator ()()
Dnn_ops_test.cc111 int filter_rows, int filter_cols, CONV_OP op, in BM_ConvFloat() argument
133 TF_CHECK_OK(GetWindowedOutputSize(rows, filter_rows, stride, padding, in BM_ConvFloat()
144 static_cast<int64_t>(filter_rows * filter_cols) * in BM_ConvFloat()
151 static_cast<int64_t>(filter_rows * filter_cols) * in BM_ConvFloat()
157 SetConstOp("filter", {filter_rows, filter_cols, in_depth, out_depth}, in BM_ConvFloat()
166 std::vector<int32>({filter_rows, filter_cols, in_depth, out_depth}), in BM_ConvFloat()
521 int filter_rows, int filter_cols, in BM_ConvFloatDepthwise() argument
544 TF_CHECK_OK(GetWindowedOutputSize(rows, filter_rows, stride, padding, in BM_ConvFloatDepthwise()
556 static_cast<int64_t>(filter_rows * filter_cols) * in BM_ConvFloatDepthwise()
567 static_cast<int64_t>(filter_rows * filter_cols) * in BM_ConvFloatDepthwise()
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Dconv_ops.h87 int filter_rows;
Dconv_ops_fused_image_transform.cc797 const int filter_rows = static_cast<int>(filter.dim_size(0)); in Compute() local
825 GetWindowedOutputSize(padded_rows, filter_rows, stride_rows, in Compute()
846 << ", filter_rows = " << filter_rows in Compute()
857 padded_cols, in_depth, filter.flat<T>().data(), filter_rows, in Compute()
Dquantized_conv_ops.cc550 const int64_t filter_rows = filter.dim_size(0); in Compute() local
567 GetWindowedOutputSize(input_rows, filter_rows, stride, in Compute()
588 filter_rows, filter_cols, out_depth, offset_filter, stride, in Compute()
Deigen_spatial_convolutions_test.cc1384 int filter_count, int filter_cols, int filter_rows, in PackRhsHelper() argument
1486 filter_rows, filter_cols, // in PackRhsHelper()
1504 numext::ceil((input_rows_eff - filter_rows + 1.f) / row_strides); in PackRhsHelper()
1512 reshape_dims[0] = input_depth * filter_rows * filter_cols; // patch size in PackRhsHelper()
1582 int filter_count, int filter_cols, int filter_rows, in PackLhsHelper() argument
1589 eigen_assert(block_cols <= input_depth * filter_rows * filter_cols); in PackLhsHelper()
1595 Dimensions filter_dims(filter_count, filter_rows, filter_cols, input_depth); in PackLhsHelper()
1651 reshape_dims[1] = input_depth * filter_rows * filter_cols; in PackLhsHelper()
1710 const Index max_col = filter_rows * filter_cols * input_depth; in PackLhsHelper()
1739 "filter: count=", filter_count, " dims=", filter_rows, "x", filter_cols, in PackLhsHelper()
/external/tensorflow/tensorflow/core/kernels/mkl/
Dmkl_conv_ops.h212 int filter_rows = in GetFilterSizeInMklOrder() local
236 filter_sizes[MKL_GROUP_FILTER_DIM_H] = filter_rows; in GetFilterSizeInMklOrder()
245 filter_sizes[MKL_GROUP_FILTER_DIM_H] = filter_rows; in GetFilterSizeInMklOrder()
252 filter_sizes[MklDnnDims::Dim_H] = filter_rows; in GetFilterSizeInMklOrder()
265 int filter_rows = in GetFilterSizeInMklOrder() local
280 filter_sizes[MklDnnDims3D::Dim3d_H] = filter_rows; in GetFilterSizeInMklOrder()
375 int filter_planes, filter_rows, filter_cols; variable
377 filter_rows = filter_shape.dim_size(TF_2DFILTER_DIM_H);
381 filter_rows = filter_shape.dim_size(TF_3DFILTER_DIM_H);
441 input_rows, filter_rows, dilation_rows, stride_rows,
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/external/tensorflow/tensorflow/python/kernel_tests/nn_ops/
Dconv_ops_test.py870 filter_rows=3,
892 filter_rows=3,
1883 filter_rows, argument
1897 filter_shape = [filter_rows, filter_cols, in_depth // num_groups, out_depth]
1900 output_rows = (input_rows - filter_rows + stride_rows) // stride_rows
1907 output_rows = (input_rows + padding[1][0] + padding[1][1] - filter_rows +
1977 filter_rows=3,
1995 filter_rows=2,
2013 filter_rows=3,
2031 filter_rows=2,
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Dconv_ops_3d_test.py475 filter_planes, filter_rows, filter_cols = filter_shape
479 filter_planes, filter_rows, filter_cols, in_depth, out_depth
491 math.ceil((input_rows - filter_rows + 1.0) / strides[2]))
/external/tensorflow/tensorflow/core/grappler/costs/
Dutils_test.cc68 int filter_rows = 3; in TEST() local
83 CreateConstOp("filter", {filter_rows, filter_cols, in_depth, out_depth}, in TEST()
98 std::vector<int32>({filter_rows, filter_cols, in_depth, out_depth}), in TEST()

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