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Searched refs:in_depth (Results 1 – 25 of 47) sorted by relevance

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/external/tensorflow/tensorflow/core/kernels/
Ddeep_conv2d.cc49 int out_tile_rows, int out_tile_cols, int in_depth, in GetDeepConvCost() argument
54 input_tile_spatial_size * input_tile_spatial_size * in_depth; in GetDeepConvCost()
57 const int64 product_cost = input_tile_spatial_size * in_depth * out_depth; in GetDeepConvCost()
74 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
117 t.output_shape().cols, in_depth, out_depth, out_rows, out_cols); in CanUseDeepConv2D()
119 filter_rows, filter_cols, in_depth, out_depth, out_rows, out_cols); in CanUseDeepConv2D()
146 const int64 vectorized_size = args.in_depth / kPacketSize; in operator ()()
147 const int64 scalar_size = args.in_depth % kPacketSize; in operator ()()
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Ddepthwise_conv_op_gpu.h93 const int in_depth = args.in_depth;
139 in_depth * (in_col + in_width * (in_row + input_offset_temp));
143 (in_channel + in_depth * (filter_col + filter_offset_temp));
162 in_depth * (in_col + in_width * (in_row + input_offset_temp));
166 (in_channel + in_depth * (filter_col + filter_offset_temp));
204 const int in_depth = args.in_depth;
219 const int in_row_size = in_width * in_depth;
230 const int batch_blocks = (in_depth + kBlockDepth - 1) / kBlockDepth;
250 const int tensor_idx = thread_pix * in_depth + thread_depth;
260 const int max_channel = in_depth - thread_depth;
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Ddepthwise_conv_op.h30 int in_depth; member
47 in_depth(0), in DepthwiseArgs()
201 (args.in_depth / kPacketSize) * kPacketSize;
202 const int64 input_scalar_size = args.in_depth - input_vectorized_size;
227 input + (in_r * args.in_cols + in_c) * args.in_depth;
228 int64 limit = args.in_depth;
246 for (int64 d = limit; d < args.in_depth; d++) {
281 input + (in_r * args.in_cols + in_c) * args.in_depth;
283 for (int64 d = 0; d < args.in_depth; d++) {
314 input + (in_r * args.in_cols + in_c) * args.in_depth;
Dconv_ops_benchmark_test.cc76 static Conv2DGraph Conv2D(int batch, int height, int width, int in_depth, in Conv2D() argument
82 ? MakeRandomTensor<T>({batch, height, width, in_depth}) in Conv2D()
83 : MakeRandomTensor<T>({batch, in_depth, height, width}); in Conv2D()
87 MakeRandomTensor<T>({filter_w, filter_h, in_depth, out_depth}); in Conv2D()
108 int batch, int height, int width, int in_depth, int filter_w, int filter_h, in Conv2DWithBias() argument
110 Conv2DGraph conv_graph = Conv2D<T>(batch, height, width, in_depth, filter_w, in Conv2DWithBias()
134 int batch, int height, int width, int in_depth, int filter_w, int filter_h, in Conv2DWithBiasAndActivation() argument
138 Conv2DWithBias<T>(batch, height, width, in_depth, filter_w, filter_h, in Conv2DWithBiasAndActivation()
157 int batch, int height, int width, int in_depth, int filter_w, int filter_h, in Conv2DWithBatchNorm() argument
159 Conv2DGraph conv_graph = Conv2D<T>(batch, height, width, in_depth, filter_w, in Conv2DWithBatchNorm()
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Ddepthwise_conv_grad_op.cc103 const int64 in_depth = GetTensorDim(input_shape, data_format_, 'C'); \
104 OP_REQUIRES(context, in_depth == filter_shape.dim_size(2), \
116 context, (depth_multiplier * in_depth) == out_depth, \
148 args.in_depth = in_depth; \
159 << input_rows << ", " << input_cols << ", " << in_depth \
161 << in_depth << ", " << depth_multiplier << "]; stride = " << stride \
296 const int64 in_depth = args.in_depth; in ComputeBackpropInput() local
306 const int64 base_output_index = (in_r * args.in_cols + in_c) * in_depth; in ComputeBackpropInput()
363 for (int64 d = 0; d < in_depth; ++d) { in ComputeBackpropInput()
422 args.in_rows * args.in_cols * args.in_depth; in operator ()()
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Ddepthwise_conv_op.cc196 args.in_rows * args.in_cols * args.in_depth; in operator ()()
343 const int64 in_depth = GetTensorDim(input, data_format_, 'C'); in Compute() local
344 OP_REQUIRES(context, in_depth == filter.dim_size(2), in Compute()
346 "input and filter must have the same depth: ", in_depth, in Compute()
353 const int32 out_depth = in_depth * depth_multiplier; in Compute()
409 (in_depth == 1 || in Compute()
413 /*in_depth=*/in_depth, in Compute()
418 << ", " << in_depth << "]; Filter: [" << filter_rows << ", " in Compute()
419 << filter_cols << ", " << in_depth << ", " << depth_multiplier in Compute()
455 args.in_depth = in_depth; in Compute()
Ddeep_conv2d.h72 int in_depth; member
87 in_depth(0), in Conv2DArgs()
101 int filter_cols, int in_depth, int out_depth,
Dconv_ops.cc158 const int64 in_depth = GetTensorDim(input, data_format, 'C'); in operator ()() local
159 OP_REQUIRES(ctx, in_depth == filter.dim_size(2), in operator ()()
164 in_depth, " does not match the filter input depth of ", in operator ()()
196 const int64 in_depth = GetTensorDim(input, data_format, 'C'); in operator ()() local
197 OP_REQUIRES(ctx, in_depth == filter.dim_size(2), in operator ()()
202 in_depth, " does not match the filter input depth of ", in operator ()()
223 int input_cols, int in_depth, int filter_rows, in Run() argument
239 int input_cols, int in_depth, int filter_rows, in Run() argument
247 in_depth, out_depth, out_rows, out_cols)) { in Run()
255 args.in_depth = in_depth; in Run()
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Deigen_spatial_convolutions_test.cc669 const int in_depth = 5; in TEST() local
678 const int out_depth = in_depth; in TEST()
682 Tensor<float, 4> input(in_channels, in_depth, in_rows, in_cols); in TEST()
711 c - off_c + k >= 0 && p - off_p + i < in_depth && in TEST()
730 const int in_depth = 5; in TEST() local
739 const int out_depth = in_depth; in TEST()
743 Tensor<float, 4, RowMajor> input(in_cols, in_rows, in_depth, in_channels); in TEST()
773 c - off_c + k >= 0 && p - off_p + i < in_depth && in TEST()
792 const int in_depth = 5; in TEST() local
805 Tensor<float, 4> input(in_channels, in_depth, in_rows, in_cols); in TEST()
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Dconv_grad_filter_ops_benchmark_test.cc41 int in_depth, int filter_h, int filter_w, in Conv2DBackpropFilter() argument
47 ? MakeRandomTensor<T>({batch, height, width, in_depth}) in Conv2DBackpropFilter()
48 : MakeRandomTensor<T>({batch, in_depth, height, width}); in Conv2DBackpropFilter()
50 MakeRandomTensor<T>({filter_h, filter_w, in_depth, out_depth}); in Conv2DBackpropFilter()
72 filter_dims_t.flat<int32>()(2) = in_depth; in Conv2DBackpropFilter()
Dconv_ops_3d.cc139 const int64 in_depth = GetTensorDim(input, data_format_, 'C'); in Compute() local
145 OP_REQUIRES(context, in_depth % filter_depth == 0, in Compute()
148 in_depth, " vs ", filter_depth)); in Compute()
226 const int64 in_depth = GetTensorDim(input, data_format, 'C'); in launch() local
248 bool is_grouped_convolution = filter_depth != in_depth; in launch()
257 const uint64 k = in_depth; in launch()
284 const uint64 k = in_planes * in_rows * in_cols * in_depth; in launch()
324 in_depth); in launch()
358 FORMAT_NCHW, in_batch, {{in_planes, in_rows, in_cols}}, in_depth); in launch()
359 if (in_depth > 1) { in launch()
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Dconv_grad_ops_3d.cc388 dims.spatial_dims[2].filter_size * dims.in_depth; in Compute()
463 dims.spatial_dims[2].input_size * dims.in_depth; in Compute()
502 Col2im<T>(col_buffer_data, dims.in_depth, in Compute()
555 Col2im<T>(im2col_buf, dims.in_depth, in Compute()
856 dims.spatial_dims[2].filter_size * dims.in_depth; in Compute()
925 dims.spatial_dims[2].input_size * dims.in_depth; in Compute()
968 Im2col<T>(input_data_shard, dims.in_depth, in Compute()
1180 bool is_grouped_convolution = filter_shape.dim_size(3) != dims.in_depth; in Compute()
1189 const uint64 n = dims.in_depth; in Compute()
1219 dims.input_size(2) * dims.in_depth; in Compute()
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Dconv_grad_input_ops_benchmark_test.cc40 int in_depth, int filter_h, int filter_w, in Conv2DBackpropInput() argument
46 ? MakeRandomTensor<T>({batch, height, width, in_depth}) in Conv2DBackpropInput()
47 : MakeRandomTensor<T>({batch, in_depth, height, width}); in Conv2DBackpropInput()
49 MakeRandomTensor<T>({filter_w, filter_h, in_depth, out_depth}); in Conv2DBackpropInput()
/external/tensorflow/tensorflow/lite/kernels/internal/optimized/
Dim2col_utils.h32 int in_depth, int single_buffer_length, in ExtractPatchIntoBufferColumn() argument
39 const int kwidth_times_indepth = kwidth * in_depth; in ExtractPatchIntoBufferColumn()
40 const int inwidth_times_indepth = in_width * in_depth; in ExtractPatchIntoBufferColumn()
54 std::min(kwidth - w_offset, in_width - iw_start) * in_depth; in ExtractPatchIntoBufferColumn()
57 output_row_offset + (h_offset * kwidth + w_offset) * in_depth; in ExtractPatchIntoBufferColumn()
66 ((kwidth - (left_padding + right_padding)) * in_depth)); in ExtractPatchIntoBufferColumn()
71 const int top_row_elements = (top_padding * kwidth * in_depth); in ExtractPatchIntoBufferColumn()
88 const int left_start = (out_offset - (left_padding * in_depth)); in ExtractPatchIntoBufferColumn()
90 (left_padding * in_depth * sizeof(T))); in ExtractPatchIntoBufferColumn()
97 (right_padding * in_depth * sizeof(T))); in ExtractPatchIntoBufferColumn()
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/external/tensorflow/tensorflow/python/kernel_tests/
Dconv_ops_3d_test.py464 self, batch, input_shape, filter_shape, in_depth, out_depth, stride, argument
470 input_shape = [batch, input_planes, input_rows, input_cols, in_depth]
472 filter_planes, filter_rows, filter_cols, in_depth, out_depth
567 in_depth=2,
579 in_depth=2,
591 in_depth=2,
603 in_depth=2,
615 in_depth=2,
627 in_depth=2,
639 in_depth=2,
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Dconv_ops_test.py862 in_depth=4,
884 in_depth=4,
1856 in_depth, argument
1866 assert in_depth % num_groups == 0 and out_depth % num_groups == 0
1867 input_shape = [batch, input_rows, input_cols, in_depth]
1868 filter_shape = [filter_rows, filter_cols, in_depth // num_groups, out_depth]
1950 in_depth=2,
1968 in_depth=2,
1986 in_depth=2,
2004 in_depth=2,
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/external/tensorflow/tensorflow/core/kernels/neon/
Dneon_depthwise_conv_op.cc73 const int32 in_depth = input.dim_size(3); in Compute() local
74 OP_REQUIRES(context, in_depth == filter.dim_size(2), in Compute()
76 "input and filter must have the same depth: ", in_depth, in Compute()
86 const int32 out_depth = in_depth * depth_multiplier; in Compute()
111 << ", " << in_depth << "]; Filter: [" << filter_rows << ", " in Compute()
112 << filter_cols << ", " << in_depth << ", " << depth_multiplier in Compute()
/external/tensorflow/tensorflow/lite/kernels/
Dpadding.h83 int in_height, int in_width, int in_depth, int filter_height, in ComputePadding3DValues() argument
90 *out_depth = ComputeOutSize(padding, in_depth, filter_depth, stride_depth, in ComputePadding3DValues()
96 ComputePaddingWithOffset(stride_depth, dilation_rate_depth, in_depth, in ComputePadding3DValues()
/external/tensorflow/tensorflow/compiler/tf2xla/kernels/
Dconv_op_helpers.cc215 in_depth = input_shape.dimensions(feature_dim); in MakeXlaForwardConvOp() local
218 if (in_depth % filter_in_depth != 0) { in MakeXlaForwardConvOp()
220 "Depth of input must be a multiple of depth of filter: ", in_depth, in MakeXlaForwardConvOp()
223 int64 feature_group_count = in_depth / filter_in_depth; in MakeXlaForwardConvOp()
281 /*feature_group_count=*/attrs.depthwise ? in_depth in MakeXlaForwardConvOp()
289 /*feature_group_count=*/attrs.depthwise ? in_depth : feature_group_count, in MakeXlaForwardConvOp()
308 int64 in_depth = input_shape.dimensions(feature_dim), in MakeXlaBackpropInputConvOp() local
311 attrs.depthwise ? filter_in_depth : in_depth / filter_in_depth; in MakeXlaBackpropInputConvOp()
432 int64 in_depth = input_shape.dimensions(c_dim), in MakeXlaBackpropFilterConvOp() local
435 attrs.depthwise ? filter_in_depth : in_depth / filter_in_depth; in MakeXlaBackpropFilterConvOp()
/external/tensorflow/tensorflow/core/api_def/base_api/
Dapi_def_Conv3D.pbtxt6 Shape `[batch, in_depth, in_height, in_width, in_channels]`.
34 [batch, in_depth, in_height, in_width, in_channels].
36 [batch, in_channels, in_depth, in_height, in_width].
Dapi_def_MaxPool3D.pbtxt40 [batch, in_depth, in_height, in_width, in_channels].
42 [batch, in_channels, in_depth, in_height, in_width].
Dapi_def_MaxPool3DGrad.pbtxt46 [batch, in_depth, in_height, in_width, in_channels].
48 [batch, in_channels, in_depth, in_height, in_width].
Dapi_def_AvgPool3DGrad.pbtxt46 [batch, in_depth, in_height, in_width, in_channels].
48 [batch, in_channels, in_depth, in_height, in_width].
/external/tensorflow/tensorflow/core/util/
Duse_cudnn.cc74 const int32 filter_cols, const int32 in_depth, in IsCudnnSupportedFilterSize() argument
76 return in_depth == out_depth && filter_rows == filter_cols && in IsCudnnSupportedFilterSize()
/external/tensorflow/tensorflow/core/grappler/costs/
Dutils_test.cc72 int in_depth = 3; in TEST() local
80 CreateConstOp("input", {batch, rows, cols, in_depth}, input); in TEST()
83 CreateConstOp("filter", {filter_rows, filter_cols, in_depth, out_depth}, in TEST()
92 std::vector<int32>({batch, rows, cols, in_depth}), in TEST()
98 std::vector<int32>({filter_rows, filter_cols, in_depth, out_depth}), in TEST()

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