96da2cacf837a9b84ecdeafb50dfb4a93b402f33,deeplabcut/pose_estimation_tensorflow/train.py,,train,#Any#Any#Any#Any#Any#Any#Any#,143

Before Change

        cfg.dataset_type == "scalecrop"
        or cfg.dataset_type == "tensorpack"
        or cfg.dataset_type == "deterministic"
    ) and cfg["batch_size"] != 1:
        print(
            "Switching batchsize to 1, as the tensorpack/ scalecrop/ deterministic loader does not support batches >1. Use imgaug/default loader for larger batch sizes."
        )
        cfg["batch_size"] = 1  // in case this was edited for analysis.-

After Change

    for it in range(max_iter + 1):
        if "efficientnet" in cfg.net_type:
            dict={tstep: it}
            current_lr = sess.run(learning_rate,feed_dict=dict)
        else:
            current_lr = lr_gen.get_lr(it)
            dict={learning_rate: current_lr}

Instances