Viewed29k times 143 I am reading through the documentation of PyTorch and found an example where they write gradients = torch.FloatTensor([0.1, 1.0, 0.0001]) y.backward(gradients) print(x.grad) where x was an initial variable, from which y was constructed (a 3-vector). The question is,...
policy._debug_vars() tuples = policy._get_loss_inputs_dict( batch, shuffle=self.shuffle_sequences) data_keys = [ph for _, ph in policy._loss_inputs] if policy._state_inputs: state_keys = policy._state_inputs + [policy._seq_lens] else: state_keys = [] num_loaded_tuples[poli...
然后通过 cell input activation vector(通过 tanh 计算出来的部分)与 input gate(第二个 sigmoid)的乘积获得当前步骤的 cell 更新 这部输出的 cell state 为前一步被 forget gate 削弱后的 cell state + 当前步骤被 input gate 削弱以后的 cell update 而 的更新更接近传统 RNN 的结构,因此会有 VG 的困扰。...
self.word_embeddings = nn.Embedding(vocab_size, embedding_dim)# The LSTM takes word embeddings as inputs, and outputs hidden states# with dimensionality hidden_dim.self.lstm = nn.LSTM(embedding_dim, hidden_dim, dropout=dropout, bidirectional=directions ==2)# The linear layer that ...
In this post I look at the popular gradient boosting algorithm XGBoost and show how to apply CUDA and parallel algorithms to greatly decrease training times in decision tree algorithms. I originally described this approach in myMSc thesisand it has since evolved to become a core part of the op...
Usediffor a custom algorithm to compute multiple numerical derivatives, rather than callinggradientmultiple times. Algorithms gradientcalculates thecentral differencefor interior data points. For example, consider a matrix with unit-spaced data,A, that has horizontal gradientG = gradient(A). The interio...
\begin{equation} \theta = \theta - (N \times \eta) \frac{1}{N} \sum_{i=1}^N \frac{\partial L_i}{\partial \theta} \tag{4} \end{equation} 故learning_rate = learning_rate * gradient_accumulation_steps 两者效果抵消了,因此等价于 ...
Sections were washed three times in PBS for 10 min at room temperature and incubated in an Alexa 488-conjugated goat anti-rabbit secondary antibody solution (1:250) in PBS for 1 h at room temperature. Finally, sections were washed six times in PBS for 5 min at room temperature and...
Viewed 37k times Part of Mobile Development Collective 33 I have been trying to produce a basic radial gradient background, but without success. I managed to get a linear gradient working as shown with the code below, but I have no idea how to make it radial with different colours - ...
令 X\in \mathbb{R}^{N\times d} and y\in \mathbb{R}^{N} 为 a training data with N data samples. Suppose we use a feature map \phi: \mathbb{R}^{d}\rightarrow \mathbb{R}^{m} to project each input x i…