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    Searched defs:data_channels (Results 1 - 2 of 2) sorted by null

  /external/tensorflow/tensorflow/contrib/resampler/kernels/
resampler_ops.cc 44 const int data_channels, const int num_sampling_points) {
46 const int data_batch_stride = data_height * data_width * data_channels;
47 const int output_batch_stride = num_sampling_points * data_channels;
59 output[batch_id * output_batch_stride + sample_id * data_channels +
68 data_channels * (y * data_width + x) + chan]
93 for (int chan = 0; chan < data_channels; ++chan) {
103 for (int chan = 0; chan < data_channels; ++chan) {
116 static_cast<int64>(num_sampling_points) * data_channels * 1000;
140 "data_width, data_channels], but is: ",
162 const int data_channels = data_shape.dim_size(3) variable
351 const int data_channels = data_shape.dim_size(3); variable
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  /external/tensorflow/tensorflow/compiler/tf2xla/kernels/
resampler_ops.cc 135 // tensor of dimension [batch, dim_0, ... dim_n, 4, data_channels].
139 int64 data_channels, int warp_dims) {
143 // data_channels], the offset dimensions for Gather is the last 3 dimensions.
157 // Output dimensions are [batch, dim_0, ... dim_n, 2, 2, data_channels].
159 /*slice_sizes=*/{1, 2, 2, data_channels});
165 // resulting tensor of dimension: [batch, dim_0, ...dim_n, 2, 2, data_channels].
173 // data_channels], the update window dimensions is the last 3 dimensions.
251 int64 last_warp_dim, int64 data_channels,
271 weights_with_channels_dims.push_back(data_channels);
327 /*limit_indices=*/{batch_size, width + 1, height + 1, data_channels},
492 const int64 data_channels = data_shape.dim_size(3); variable
613 const int64 data_channels = data_shape_tf.dim_size(3); variable
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