File not found conv1_weights.npy in Example graph_resnet50.cpp in computeLibrary

[RavikumarLav]

Output of 'strings libarm_compute.so | grep arm_compute_version':
->V24.02.1
Platform:
->Neon
Operating System:
->Linux

File not found conv1_weights.npy in Example graph_resnet50.cpp in computeLibrary.

Hello
I am trying test graph_resnet50.cpp on arm a78 core but getting failed at convolution layer file conv1_weights.npy not found
<< ConvolutionLayer(
7U, 7U, 64U,
get_weights_accessor(data_path, "/cnn_data/resnet50_model/conv1_weights.npy", weights_layout),
std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr), PadStrideInfo(2, 2, 3, 3))
.set_name("conv1/convolution")
<< BatchNormalizationLayer(
get_weights_accessor(data_path, "/cnn_data/resnet50_model/conv1_BatchNorm_moving_mean.npy"),
get_weights_accessor(data_path, "/cnn_data/resnet50_model/conv1_BatchNorm_moving_variance.npy"),
get_weights_accessor(data_path, "/cnn_data/resnet50_model/conv1_BatchNorm_gamma.npy"),
get_weights_accessor(data_path, "/cnn_data/resnet50_model/conv1_BatchNorm_beta.npy"),
0.0000100099996416f)
.set_name("conv1/BatchNorm")

I am not able find these files in repo please let us know Where we can get these weights in the git repo to test above example.
Problem description:

[morgolock]

Hi @RavikumarLav

The best way to run models is be to use ArmNN's ExecuteNetwork. You can download the resnet50 tflite model and run it with ArmNN.

For more information about this please have a look at #1077 (comment)

Hope this helps