提交 735e7a46 编写于 作者: T Tensor Tang

Merge branch 'develop-paddle' into 'develop'

revise cxx_api_bin.cc for mobilenetv1

See merge request paddlepaddle/paddlelitearmbackend!4
......@@ -32,9 +32,9 @@ void Run(const char* model_dir) {
valid_places);
auto* input_tensor = predictor.GetInput(0);
input_tensor->Resize(DDim(std::vector<DDim::value_type>({100, 100})));
input_tensor->Resize(DDim(std::vector<DDim::value_type>({3, 224, 224})));
auto* data = input_tensor->mutable_data<float>();
for (int i = 0; i < 100 * 100; i++) {
for (int i = 0; i < 3 * 224 * 224; i++) {
data[i] = i;
}
......@@ -65,6 +65,14 @@ USE_LITE_OP(feed);
USE_LITE_OP(fetch);
USE_LITE_OP(io_copy);
USE_LITE_OP(con2d);
USE_LITE_OP(batch_norm);
USE_LITE_OP(relu);
USE_LITE_OP(depthwise_conv2d);
USE_LITE_OP(pool2d);
USE_LITE_OP(elementwise_add);
USE_LITE_OP(softmax);
USE_LITE_KERNEL(feed, kHost, kAny, kAny, def);
USE_LITE_KERNEL(fetch, kHost, kAny, kAny, def);
......@@ -72,7 +80,15 @@ USE_LITE_KERNEL(fetch, kHost, kAny, kAny, def);
USE_LITE_KERNEL(fc, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(mul, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(scale, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(con2d, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(batch_norm, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(relu, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(depthwise_con2d, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(pool2d, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(elementwise_add, kARM, kFloat, kNCHW, def);
USE_LITE_KERNEL(softmax, kARM, kFloat, kNCHW, def);
// USE_LITE_KERNEL(feed, kARM, kAny, kAny, def);
// USE_LITE_KERNEL(fetch, kARM, kAny, kAny, def);
#endif // LITE_WITH_ARM
......
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