Lines Matching refs:CHANNELS
115 const int channels = images.dimension(3);
118 ASSERT_EQ(channels, output.dimension(3));
138 for (int64 c = 0; c < channels; ++c) {
160 const int target_width, int channels) {
162 << channels << " to " << target_height << "x" << target_width
163 << "x" << channels;
165 TensorShape({batch_size, in_height, in_width, channels}));
173 TensorShape({batch_size, target_height, target_width, channels})));
185 void RunManyRandomTests(int channels) {
192 channels);
228 RunRandomTest(2, 141, 186, 299, 299, 1 /* channels */);
229 RunRandomTest(2, 141, 186, 299, 299, 3 /* channels */);
233 RunRandomTest(2, 183, 229, 299, 299, 1 /* channels */);
234 RunRandomTest(2, 183, 229, 299, 299, 3 /* channels */);
238 RunRandomTest(2, 749, 603, 299, 299, 1 /* channels */);
239 RunRandomTest(2, 749, 603, 299, 299, 3 /* channels */);
254 static Graph* ResizeBicubic(int batch_size, int size, int channels,
257 Tensor input(DT_FLOAT, TensorShape({batch_size, size, size, channels}));
268 #define BM_ResizeBicubicDev(BATCH, SIZE, CHANNELS) \
269 static void BM_ResizeBicubic##_##BATCH##_##SIZE##_##CHANNELS(int iters) { \
271 CHANNELS); \
272 test::Benchmark("cpu", ResizeBicubic(BATCH, SIZE, CHANNELS)).Run(iters); \
274 BENCHMARK(BM_ResizeBicubic##_##BATCH##_##SIZE##_##CHANNELS);
289 #define BM_ResizeBicubicExpand(BATCH, SIZE, CHANNELS) \
290 static void BM_ResizeBicubicExpand##_##BATCH##_##SIZE##_##CHANNELS( \
293 CHANNELS * 8 * 8); \
294 test::Benchmark("cpu", ResizeBicubic(BATCH, SIZE, CHANNELS, 8, 8)) \
297 BENCHMARK(BM_ResizeBicubicExpand##_##BATCH##_##SIZE##_##CHANNELS);
