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Searched refs:filter_cols (Results 1 – 25 of 32) sorted by relevance

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/external/tensorflow/tensorflow/core/kernels/
Ddilation_ops_gpu.cu.cc42 int filter_cols, int output_rows, in DilationKernel() argument
60 for (int w = 0; w < filter_cols; ++w) { in DilationKernel()
66 filter_ptr[d + depth * (w + filter_cols * h)]; in DilationKernel()
82 int depth, int filter_rows, int filter_cols, int output_rows, in DilationBackpropInputKernel() argument
104 for (int w = 0; w < filter_cols; ++w) { in DilationBackpropInputKernel()
110 filter_ptr[d + depth * (w + filter_cols * h)]; in DilationBackpropInputKernel()
131 int depth, int filter_rows, int filter_cols, int output_rows, in DilationBackpropFilterKernel() argument
153 for (int w = 0; w < filter_cols; ++w) { in DilationBackpropFilterKernel()
159 filter_ptr[d + depth * (w + filter_cols * h)]; in DilationBackpropFilterKernel()
170 filter_backprop_ptr + d + depth * (w_max + filter_cols * h_max), in DilationBackpropFilterKernel()
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Ddepthwise_conv_grad_op.cc83 const int64 filter_cols = filter_shape.dim_size(1); \
120 GetWindowedOutputSize(input_cols, filter_cols, stride, \
138 args.filter_cols = filter_cols; \
148 << "]; Filter: [" << filter_rows << ", " << filter_cols << ", " \
189 const int64 filter_cols = args.filter_cols; in CopyOutputBackpropRegion() local
200 static_cast<int64>(0), (in_c - filter_cols + pad_cols + stride) / stride); in CopyOutputBackpropRegion()
204 const int64 filter_spatial_size = args.filter_rows * args.filter_cols; in CopyOutputBackpropRegion()
206 (out_c_end - out_c_start + 1) < args.filter_cols) { in CopyOutputBackpropRegion()
221 (f_r * filter_cols + f_c) * padded_filter_inner_dim_size; in CopyOutputBackpropRegion()
287 const int64 filter_spatial_size = args.filter_rows * args.filter_cols; in ComputeBackpropInput()
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Ddepthwise_conv_op.cc90 const int64 filter_spatial_size = args.filter_rows * args.filter_cols; in Run()
171 const int64 filter_spatial_size = args.filter_rows * args.filter_cols; in operator ()()
194 const int64 filter_spatial_size = args.filter_rows * args.filter_cols; in operator ()()
343 const int32 filter_cols = filter.dim_size(1); in Compute() local
353 GetWindowedOutputSize(input_cols, filter_cols, stride_, in Compute()
380 << filter_cols << ", " << in_depth << ", " << depth_multiplier in Compute()
397 TensorShape{filter_rows, filter_cols, filter_in_depth, out_depth}; in Compute()
418 args.filter_cols = filter_cols; in Compute()
Ddeep_conv2d.h74 int filter_cols; member
89 filter_cols(0), in Conv2DArgs()
101 int filter_cols, int in_depth, int out_depth,
Dmkl_conv_ops.h216 int filter_cols = in GetFilterSizeInMklOrder() local
233 mkldnn_sizes[MKL_GROUP_FILTER_DIM_W] = filter_cols; in GetFilterSizeInMklOrder()
241 mkldnn_sizes[MklDnnDims::Dim_W] = filter_cols; in GetFilterSizeInMklOrder()
256 int filter_cols = in GetFilterSizeInMklOrder() local
270 mkldnn_sizes[MklDnnDims3D::Dim3d_W] = filter_cols; in GetFilterSizeInMklOrder()
343 int filter_planes, filter_rows, filter_cols; variable
346 filter_cols = filter_shape.dim_size(TF_2DFILTER_DIM_W);
350 filter_cols = filter_shape.dim_size(TF_3DFILTER_DIM_W);
411 input_cols, filter_cols, dilation_cols, stride_cols,
421 input_cols, filter_cols, stride_cols,
Ddilation_ops.cc93 const int filter_cols = filter.dim_size(1); in ParseSizes() local
104 filter_cols + (filter_cols - 1) * (*rate_cols - 1); in ParseSizes()
174 const int filter_cols = filter.dimension(1); in operator ()() local
191 for (int w = 0; w < filter_cols; ++w) { in operator ()()
283 const int filter_cols = filter.dimension(1); in operator ()() local
308 for (int w = 0; w < filter_cols; ++w) { in operator ()()
403 const int filter_cols = filter.dimension(1); in operator ()() local
428 for (int w = 0; w < filter_cols; ++w) { in operator ()()
Dconv_ops.cc157 int filter_cols, int pad_rows, int pad_cols, int out_rows, in Run() argument
173 int filter_cols, int pad_rows, int pad_cols, int out_rows, in Run() argument
179 !CanUseDeepConv2D(stride_rows, stride_cols, filter_rows, filter_cols, in Run()
190 args.filter_cols = filter_cols; in Run()
214 int filter_cols, int pad_rows, int pad_cols, int out_rows, in Run() argument
228 int filter_cols, int pad_rows, int pad_cols, int out_rows, in Run() argument
242 desc.S = filter_cols; in Run()
383 const int filter_cols = static_cast<int>(filter.dim_size(1)); in ComputeConv2DDimension() local
414 input_cols, filter_cols, dilation_cols, stride_cols, params.padding, in ComputeConv2DDimension()
422 dimensions->filter_cols = filter_cols; in ComputeConv2DDimension()
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Ddepthwise_conv_op_gpu.h50 args.pad_cols < args.filter_cols && in CanLaunchDepthwiseConv2dGPUSmall()
51 args.filter_rows * args.filter_cols <= in CanLaunchDepthwiseConv2dGPUSmall()
63 args.pad_cols < args.filter_cols && block_height <= args.in_rows && in CanLaunchDepthwiseConv2dBackpropFilterGPUSmall()
64 args.filter_rows * args.filter_cols <= args.in_cols * block_height; in CanLaunchDepthwiseConv2dBackpropFilterGPUSmall()
84 kKnownFilterWidth < 0 ? args.filter_cols : kKnownFilterWidth; in DepthwiseConv2dGPUKernelNHWC()
191 kKnownFilterWidth < 0 ? args.filter_cols : kKnownFilterWidth; in DepthwiseConv2dGPUKernelNHWCSmall()
324 kKnownFilterWidth < 0 ? args.filter_cols : kKnownFilterWidth; in DepthwiseConv2dGPUKernelNCHW()
475 kKnownFilterWidth < 0 ? args.filter_cols : kKnownFilterWidth; in DepthwiseConv2dGPUKernelNCHWSmall()
631 const int tile_width = args.in_cols + args.filter_cols - 1; in LaunchDepthwiseConv2dGPUSmall()
634 const int filter_pixels = args.filter_rows * args.filter_cols; in LaunchDepthwiseConv2dGPUSmall()
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Ddepthwise_conv_op.h32 int filter_cols; member
49 filter_cols(0), in DepthwiseArgs()
145 const int64 filter_spatial_size = args.filter_rows * args.filter_cols;
227 for (int64 f_c = 0; f_c < args.filter_cols; ++f_c) {
Dconv_ops_3d.cc221 const int64 filter_cols = filter.dim_size(2); in launch() local
235 0, (out_cols - 1) * strides[2] + filter_cols - in_cols); in launch()
239 if (filter_planes == 1 && filter_rows == 1 && filter_cols == 1 && in launch()
267 filter_cols == in_cols && padding == Padding::VALID && in launch()
366 filter_desc.set_spatial_dim(DimIndex::X, filter_cols) in launch()
386 filter_rows, filter_cols}), in launch()
423 {{filter_planes, filter_rows, filter_cols}}, in launch()
Deigen_benchmark.h130 Eigen::Index filter_cols = filter_dims[1]; in SpatialConvolutionBackwardKernel() local
149 input, output_backward, filter_rows, filter_cols); in SpatialConvolutionBackwardKernel()
269 Eigen::Index filter_cols = filter_dims[1]; in CuboidConvolutionBackwardKernel() local
289 input, output_backward, filter_planes, filter_rows, filter_cols); in CuboidConvolutionBackwardKernel()
Ddeep_conv2d.cc74 static int64 GetDirectConvCost(int filter_rows, int filter_cols, int in_depth, in GetDirectConvCost() argument
76 return filter_rows * filter_cols * in_depth * out_depth * out_rows * out_cols; in GetDirectConvCost()
98 int filter_cols, int in_depth, int out_depth, in CanUseDeepConv2D() argument
103 filter_cols != 3) { in CanUseDeepConv2D()
119 filter_rows, filter_cols, in_depth, out_depth, out_rows, out_cols); in CanUseDeepConv2D()
301 std::max(int64{0}, args.filter_cols - base_filter_cols); in operator ()()
338 if (f_c >= args.filter_cols) continue; in operator ()()
342 (args.in_depth * (f_r * args.filter_cols + f_c)) + in operator ()()
483 const int64 shard_cost = args.filter_rows * args.filter_cols * in_depth * in operator ()()
961 std::max(int64{0}, args.filter_cols - base_filter_rows); in operator ()()
Dconv_ops_using_gemm.cc506 const int filter_cols = static_cast<int>(filter.dim_size(1)); in Compute() local
525 GetWindowedOutputSize(input_cols, filter_cols, stride_cols, in Compute()
537 << ", filter_cols = " << filter_cols in Compute()
550 in_depth, filter.flat<T>().data(), filter_rows, filter_cols, in Compute()
Dnn_ops_test.cc106 int out_depth, int filter_rows, int filter_cols, in BM_ConvFloat() argument
129 TF_CHECK_OK(GetWindowedOutputSize(cols, filter_cols, stride, padding, in BM_ConvFloat()
138 static_cast<int64>(filter_rows * filter_cols) * in BM_ConvFloat()
145 static_cast<int64>(filter_rows * filter_cols) * in BM_ConvFloat()
151 SetConstOp("filter", {filter_rows, filter_cols, in_depth, out_depth}, in BM_ConvFloat()
160 std::vector<int32>({filter_rows, filter_cols, in_depth, out_depth}), in BM_ConvFloat()
501 int filter_cols, DEPTHWISE_CONV_OP op, in BM_ConvFloatDepthwise() argument
523 TF_CHECK_OK(GetWindowedOutputSize(cols, filter_cols, stride, padding, in BM_ConvFloatDepthwise()
533 static_cast<int64>(filter_rows * filter_cols) * in BM_ConvFloatDepthwise()
544 static_cast<int64>(filter_rows * filter_cols) * in BM_ConvFloatDepthwise()
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Dquantized_conv_ops.cc530 const int64 filter_cols = filter.dim_size(1); in Compute() local
545 GetWindowedOutputSize(input_cols, filter_cols, stride, in Compute()
563 filter_rows, filter_cols, out_depth, offset_filter, stride, in Compute()
Dconv_ops_fused_image_transform.cc810 const int filter_cols = static_cast<int>(filter.dim_size(1)); in Compute() local
830 GetWindowedOutputSize(padded_cols, filter_cols, stride_cols, in Compute()
845 << ", filter_cols = " << filter_cols in Compute()
860 filter_cols, out_depth, stride_rows, stride_cols, padding_, in Compute()
Dconv_ops.h88 int filter_cols;
Deigen_spatial_convolutions_test.cc1383 int filter_count, int filter_cols, int filter_rows, in PackRhsHelper() argument
1480 filter_rows, filter_cols, // in PackRhsHelper()
1491 reshape_dims[0] = input_depth * filter_rows * filter_cols; // patch size in PackRhsHelper()
1556 int filter_count, int filter_cols, int filter_rows, in PackLhsHelper() argument
1563 eigen_assert(block_cols <= input_depth * filter_rows * filter_cols); in PackLhsHelper()
1572 Dimensions filter_dims(filter_count, filter_rows, filter_cols, input_depth); in PackLhsHelper()
1628 reshape_dims[1] = input_depth * filter_rows * filter_cols; in PackLhsHelper()
1683 const Index max_col = filter_rows * filter_cols * input_depth; in PackLhsHelper()
1714 "filter: count=", filter_count, " dims=", filter_rows, "x", filter_cols, in PackLhsHelper()
/external/tensorflow/tensorflow/python/kernel_tests/
Dconv_ops_test.py1639 filter_cols, in_depth, out_depth, stride_rows, argument
1643 filter_shape = [filter_rows, filter_cols, in_depth, out_depth]
1647 output_cols = (input_cols - filter_cols + stride_cols) // stride_cols
1655 output_cols = (input_cols + padding[2][0] + padding[2][1] - filter_cols +
1724 filter_cols=3,
1742 filter_cols=2,
1760 filter_cols=3,
1778 filter_cols=2,
1796 filter_cols=3,
1814 filter_cols=4,
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Dconv_ops_3d_test.py372 filter_planes, filter_rows, filter_cols = filter_shape
376 filter_planes, filter_rows, filter_cols, in_depth, out_depth
390 math.ceil((input_cols - filter_cols + 1.0) / strides[3]))
/external/tensorflow/tensorflow/python/framework/
Dcommon_shapes.py208 filter_cols = filter_shape[1]
226 filter_cols, stride_r, stride_c,
267 filter_cols = filter_shape[1]
287 filter_cols, stride, stride,
332 filter_cols = depthwise_filter_shape[1]
350 filter_cols, stride, stride,
/external/tensorflow/tensorflow/core/kernels/neon/
Dneon_depthwise_conv_op.cc83 const int32 filter_cols = filter.dim_size(1); in Compute() local
95 GetWindowedOutputSize(input_cols, filter_cols, stride, in Compute()
112 << filter_cols << ", " << in_depth << ", " << depth_multiplier in Compute()
/external/tensorflow/tensorflow/contrib/fused_conv/kernels/
Dfused_conv2d_bias_activation_op.cc204 const int32 filter_cols = GetFilterDim(filter, filter_format_, 'W'); in Compute() local
215 OP_REQUIRES_OK(context, GetWindowedOutputSize(conv_input_cols, filter_cols, in Compute()
226 << ", filter_cols = " << filter_cols in Compute()
480 const int filter_cols = GetFilterDim(filter_param, filter_format, 'W'); in launch() local
498 0, (output_cols - 1) * col_stride + filter_cols - conv_input_cols); in launch()
505 AdjustPaddingForCudnn(padding_cols, is_int8x4, filter_cols, &padding_cols, in launch()
589 .set_input_filter_width(filter_cols) in launch()
669 {{filter_rows, filter_cols}}, in launch()
/external/tensorflow/tensorflow/core/grappler/costs/
Dutils_test.cc69 int filter_cols = 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()
/external/tensorflow/tensorflow/contrib/lite/kernels/internal/optimized/
Doptimized_ops.h1185 const int filter_cols = filter_shape.Dims(filter_dim_count - 1); in FullyConnected() local
1186 TFLITE_DCHECK_EQ(filter_shape.FlatSize(), filter_rows * filter_cols); in FullyConnected()
1192 filter_data, output_rows, filter_cols, filter_cols); in FullyConnected()
1194 input_data, filter_cols, batches, filter_cols); in FullyConnected()
2245 const int filter_cols = FlatSizeSkipDim(filter_shape, 0); in HybridConv() local
2252 const int gemm_input_cols = filter_cols; in HybridConv()
2275 filter_data, filter_rows, filter_cols, gemm_input_data, in HybridConv()
2425 const int filter_cols = in Conv() local
2434 TFLITE_DCHECK_EQ(filter_cols, gemm_input_rows); in Conv()
2437 filter_data, filter_rows, filter_cols); in Conv()
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