http://tracking.discuss.tvm.ai/tracking/click?d=MTn5ZLDyVKquL4zkljbnh1jQ0_k2wmyJDbp2W0Fkd1ZlhSeI8lGqOR3gbeYqLMFv_cfrr6nlwBsYBcZ3Mg1xLQFFxE8PZ7eRjzzHOol3vVG_MndGLeWtKPEBhVB7tgCPY5FmNzWbep-uci54bBlBPv5wmu6iKX_jxjLnSdqyYahS2gZRHiYtUZId12CRm_CXzgsxHnCMWZrgEJR6fx0k-qq7HO8OeeKP852_miahQPFQRl5Q3ldHRO4Dx3-q9-AIVw2
IIUC, this means, that only models, which have a unique layer in the architecture can be efficiently run with VTA? This unique layer should also be one of the last layers, to offload as much as possible on the FPGA. So if I have a model with the structure¹ ``` nn.conv2d nn.leaky_relu nn.max_pool2d ... nn.conv2d nn.leaky_relu nn.max_pool2d nn.conv2d ``` I won't be able to use graph_pack on this model, since I can't specify a (good) `stop_name` for this network. Which then means, that I can't offload this model to VTA. If that's the case this restricts the usability of VTA to only pretty specific models. Is there already a plan how to address this challenge? cc @thierry, since you are the author of this code. --- ¹ This is the (simplified) structure of TinyYOLO from [Tensornets](http://tracking.discuss.tvm.ai/tracking/click?d=MTn5ZLDyVKquL4zkljbnh2if3iJXsUQXD1pcylhfWTOPQ-F1Y0jZ5r5S1hU5FGOUd6NwJtIo6oEYzg37hZV2mS_74po6HDbRAXMSi3FpMd3VjVrEMTodN89JhHOWeEQFDHBB8SoSK63yg5Og0eAlGmz3CoF23ypRVptWEhI-YKNiadLTgBVWkOX-R8jv8OkbJZc-xDDdaTBErc_6m_z3e6YgAwUwHtaflwtu2jUMFVotCPTls0DMvtijAEOGeDOQqA2) --- [Visit Topic](http://tracking.discuss.tvm.ai/tracking/click?d=09d7fXZTi1UA4ER5iKjGBqRStLPcBDL5DpZUPA0eAC9IkLTdj7I1V-lOkgg7Aw6l9VZsLRlF6xoRZN_uLOa7StuEzk_GgIY25pOGlybbVh5wEhgssuAY8FvmPOjTBCurGFEPzd38XHkyW0rqYwat_cCT6efS35MlyjzB__Jii9DxHlXWDanITgAqZjIDKAuCtQ2) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](http://tracking.discuss.tvm.ai/tracking/click?d=7cFgOaAA4XIBVlVKt_oyC07uihTjg4Q6cjeBRNRTiPo9TgkKm5n39xudndLoa0kWTdcAB5-ouRvl5yuiHHGPg5ExD53M8pOe0DcX-tdEDdqYqpW1krFt03Iun-tq3bzUd8OzbM77a9zOKi0pzlnWgsecvO4jEj1LgDDXWVYy7xY87XCDN_HtpuYaFMrUubG1nqBrtpeG-J1-upBZ0hLdXZfK8GspMk1DKZxxxUHaasUi0). Tianqi Chen, UW, Seattle, WA, 98105, United States http://tracking.discuss.tvm.ai/tracking/unsubscribe?msgid=Ms-4ZSYrZhsN-H9SS5jwMg2
