From b33aa5af14d4ee528bc5b887798e664e0c460f7e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Micha=C5=82=20Filipiuk?= Date: Sun, 6 Jan 2019 10:36:16 +0100 Subject: [PATCH] Solved deprecated warnings and errors: size_average and reduce are now deprecated (https://discuss.pytorch.org/t/userwarning-size-average-and-reduce-args-will-be-deprecated-please-use-reduction-sum-instead/24629) Getting value of 0-tensor fixed to .item() instead of [0] Minor spelling fixed --- reco_encoder/model/model.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/reco_encoder/model/model.py b/reco_encoder/model/model.py index 339a32b..c40552b 100644 --- a/reco_encoder/model/model.py +++ b/reco_encoder/model/model.py @@ -28,11 +28,11 @@ def activation(input, kind): else: raise ValueError('Unknown non-linearity type') -def MSEloss(inputs, targets, size_avarage=False): +def MSEloss(inputs, targets, size_average=False): mask = targets != 0 num_ratings = torch.sum(mask.float()) - criterion = nn.MSELoss(size_average=size_avarage) - return criterion(inputs * mask.float(), targets), Variable(torch.Tensor([1.0])) if size_avarage else num_ratings + criterion = nn.MSELoss(reduction='sum' if not size_average else 'mean') + return criterion(inputs * mask.float(), targets), Variable(torch.Tensor([1.0])) if size_average else num_ratings class AutoEncoder(nn.Module): def __init__(self, layer_sizes, nl_type='selu', is_constrained=True, dp_drop_prob=0.0, last_layer_activations=True): @@ -57,7 +57,7 @@ def __init__(self, layer_sizes, nl_type='selu', is_constrained=True, dp_drop_pro self.encode_w = nn.ParameterList( [nn.Parameter(torch.rand(layer_sizes[i + 1], layer_sizes[i])) for i in range(len(layer_sizes) - 1)]) for ind, w in enumerate(self.encode_w): - weight_init.xavier_uniform(w) + weight_init.xavier_uniform_(w) self.encode_b = nn.ParameterList( [nn.Parameter(torch.zeros(layer_sizes[i + 1])) for i in range(len(layer_sizes) - 1)])