AssertionError: Invalid arch fbnet_a, supported arch dict_keys([])

[arane03]

I am trying to load a pretrained model fbnet_a following your example code:

from mobile_cv.model_zoo.models.fbnet_v2 import fbnet
model_a = fbnet('fbnet_a', pretrained=True)
model_a.eval()

Not only is it saying that the model name does not exist, it apparently says that no such models exist, which is very odd.
Specifically, the Assertion Error:

File "/Users/aadirane/miniforge3/envs/myproj/lib/python3.11/site-packages/mobile_cv/model_zoo/models/fbnet_v2.py", line 358, in _load_pretrained_weight
    arch_name in PRETRAINED_MODELS
AssertionError: Invalid arch fbnet_a, supported arch dict_keys([])

Interestingly, when trying out your original example dmasking_l3 the same error is thrown but in this case PRETRAINED_MODELS is nonempty, and contains fbnet_a:

AssertionError: Invalid arch name dmasking_l3, available names: dict_keys(['default', 'default_i8f', 'eff_0', 'eff_1', 'eff_2', 'eff_3', 'eff_4', 'eff_5', 'eff_6', 'eff_7', 'eff_8', 'eff_l2', 'eff_lite_0', 'eff_lite_1', 'eff_lite_2', 'eff_lite_3', 'eff_lite_4', 'eff_v2_s', 'eff_v2_m', 'eff_v2_l', 'eff_v2_xl', 'eff_v2_b0', 'eff_v2_b1', 'eff_v2_b2', 'eff_v2_b3', 'fbnet_a', 'fbnet_b', 'fbnet_c', 'fbnet_96', 'fbnet_a_i8f', 'fbnet_b_i8f', 'fbnet_c_i8f', 'fbnet_96_i8f', 'FBNetV2_F0', 'FBNetV2_F1', 'FBNetV2_F2', 'FBNetV2_F3', 'FBNetV2_F4', 'FBNetV2_L1', 'FBNetV2_L2', 'FBNetV3_A0', 'FBNetV3_A', 'FBNetV3_B', 'FBNetV3_C', 'FBNetV3_D', 'FBNetV3_E', 'FBNetV3_F', 'FBNetV3_G', 'FBNetV3_20G', 'FBNetV3_A0_i8f', 'FBNetV3_A_i8f', 'FBNetV3_B_i8f', 'FBNetV3_C_i8f', 'FBNetV3_D_i8f', 'FBNetV3_E_i8f', 'FBNetV3_F_i8f', 'FBNetV3_G_i8f', 'FBNetV3_20G_i8f', 'FBNetV3_A_GPU', 'FBNetV3_B_GPU', 'FBNetV3_C_GPU', 'FBNetV3_D_GPU', 'FBNetV3_E_GPU', 'FBNetV3_F_GPU', 'FBNetV3_G_GPU', 'FBNetV3_A_GPU_i8f', 'FBNetV3_B_GPU_i8f', 'FBNetV3_C_GPU_i8f', 'FBNetV3_D_GPU_i8f', 'FBNetV3_E_GPU_i8f', 'FBNetV3_F_GPU_i8f', 'FBNetV3_G_GPU_i8f', 'mnv2', 'mnv3', 'mnv3_small', 'mnv2_i8f', 'mnv3_i8f', 'mnv3_small_i8f', 'MobileOne-S0-Train', 'MobileOne-S0-Deploy', 'MobileOne-S1-Train', 'MobileOne-S1-Deploy', 'MobileOne-S2-Train', 'MobileOne-S2-Deploy', 'MobileOne-S3-Train', 'MobileOne-S3-Deploy', 'MobileOne-S4-Train', 'MobileOne-S4-Deploy', 'RegNet_IB_700M', 'RegNetX_200M', 'RegNetX_400M', 'RegNetX_600M', 'RegNetX_800M', 'RegNetX_1.6G', 'RegNetX_3.2G', 'RegNetX_4.0G', 'RegNetX_6.4G', 'RegNetX_8.0G', 'RegNetX_12G', 'RegNetX_16G', 'RegNetX_32G', 'RegNetY_200M', 'RegNetY_400M', 'RegNetY_600M', 'RegNetY_800M', 'RegNetY_1.6G', 'RegNetY_3.2G', 'RegNetY_4.0G', 'RegNetY_6.4G', 'RegNetY_8.0G', 'RegNetY_12G', 'RegNetY_16G', 'RegNetY_32G', 'ResNet18', 'ResNet34', 'ResNet50', 'ResNet101', 'ResNet152'])