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Hi, is it possible to make a batch containing M speaker and N utterances for each speaker?
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Add two-line code to improve performance slightly. Just name it as **Harder** Example Mining :)
Change $L = max(min(D_{an}) - max(D_{ap}) + m, 0)$ to $L = max(0.8*min(D_{an}) - 1.2*max(D_{ap}) + m,…
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```
# Compute pairwise distance, replace by the official when merged
dist = torch.pow(inputs, 2).sum(dim=1, keepdim=True).expand(n, n)
dist = dist + dist.t()
dist.addmm_(…
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triplwtloss is giving dimension error. Please help me to fix this error.
File "main.py", line 50, in train
loss = self.loss(outputs, labels)
File "/usr/local/lib/python3.7/dist-packages/t…
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Actually, I am trying to implement the same model but my dataset is very big. So, can you help me with the batch-wise training of the same.
ghost updated
5 years ago
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Traceback (most recent call last):
File "keras_server.py", line 353, in
load_FRmodel()
File "keras_server.py", line 94, in load_FRmodel
model = load_model('models/model.h5', custom_ob…
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Training using google/mt5-base as the base model with fp16 and the triplet loss on all-nli data (following the [ example with trainer](https://www.sbert.net/docs/sentence_transformer/training_overview…
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So we have a (shared) embedding network that receives 1 input and outputs 1 embedding. We then build a triplet loss network around it that takes 3 inputs and outputs the loss which we train to minimiz…
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#VCIP2017
URL: https://arxiv.org/pdf/1710.11445.pdf
Keyword: DeepHashing, TripleNet, Loss Function
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First of all, the work is very instructive, thank you! As a novice to scene graph generation, my current research requires methods to extract information from images using scene graph generation. So I…