1 path: "tensorflow.losses" 2 tf_module { 3 member { 4 name: "Reduction" 5 mtype: "<type \'type\'>" 6 } 7 member_method { 8 name: "absolute_difference" 9 argspec: "args=[\'labels\', \'predictions\', \'weights\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], " 10 } 11 member_method { 12 name: "add_loss" 13 argspec: "args=[\'loss\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'losses\'], " 14 } 15 member_method { 16 name: "compute_weighted_loss" 17 argspec: "args=[\'losses\', \'weights\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], " 18 } 19 member_method { 20 name: "cosine_distance" 21 argspec: "args=[\'labels\', \'predictions\', \'axis\', \'weights\', \'scope\', \'loss_collection\', \'reduction\', \'dim\'], varargs=None, keywords=None, defaults=[\'None\', \'1.0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\', \'None\'], " 22 } 23 member_method { 24 name: "get_losses" 25 argspec: "args=[\'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'None\', \'losses\'], " 26 } 27 member_method { 28 name: "get_regularization_loss" 29 argspec: "args=[\'scope\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'total_regularization_loss\'], " 30 } 31 member_method { 32 name: "get_regularization_losses" 33 argspec: "args=[\'scope\'], varargs=None, keywords=None, defaults=[\'None\'], " 34 } 35 member_method { 36 name: "get_total_loss" 37 argspec: "args=[\'add_regularization_losses\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'total_loss\'], " 38 } 39 member_method { 40 name: "hinge_loss" 41 argspec: "args=[\'labels\', \'logits\', \'weights\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], " 42 } 43 member_method { 44 name: "huber_loss" 45 argspec: "args=[\'labels\', \'predictions\', \'weights\', \'delta\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'1.0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], " 46 } 47 member_method { 48 name: "log_loss" 49 argspec: "args=[\'labels\', \'predictions\', \'weights\', \'epsilon\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'1e-07\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], " 50 } 51 member_method { 52 name: "mean_pairwise_squared_error" 53 argspec: "args=[\'labels\', \'predictions\', \'weights\', \'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\'], " 54 } 55 member_method { 56 name: "mean_squared_error" 57 argspec: "args=[\'labels\', \'predictions\', \'weights\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], " 58 } 59 member_method { 60 name: "sigmoid_cross_entropy" 61 argspec: "args=[\'multi_class_labels\', \'logits\', \'weights\', \'label_smoothing\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], " 62 } 63 member_method { 64 name: "softmax_cross_entropy" 65 argspec: "args=[\'onehot_labels\', \'logits\', \'weights\', \'label_smoothing\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], " 66 } 67 member_method { 68 name: "sparse_softmax_cross_entropy" 69 argspec: "args=[\'labels\', \'logits\', \'weights\', \'scope\', \'loss_collection\', \'reduction\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\', \'weighted_sum_by_nonzero_weights\'], " 70 } 71 } 72
