State Space Models(S4):这些模型已经显示出很好的特性。它们提供了一种平衡,比rnn更有效地捕获远程依赖关系,同时比transformer更高效地使用内存。 Mamba 选择性状态空间:Mamba建立在状态空间模型的概念之上,但引入了一个新的变化。它利用选择性状态空间,支持跨长序列更高效和有效地捕获相关信息。 线性时间复杂度:与Tra...
y_test = torch.tensor(y_test, dtype=torch.float32).view(-1,1)# Define the modelclassSimpleNN(nn.Module):def__init__(self, input_dim):super(SimpleNN, self).__init__()self.fc1 = nn.Linear(input_dim,64)self.fc2 = nn.Li...
The Capitalized one, Tensor, **receive dimension/ shape without '[]' or '()' ** and initialize by randomizing. when the parameters are sent in with a[]or(), it is equivalent to the lowered tensor. torch.FloatTensor([2,3.2]) Out[26]: tensor([2.0000, 3.2000]) torch.FloatTensor((2,...
x=torch.rand(20,1)*10# xdata(tensor),shape=(20,1)y=2*x+(5+torch.randn(20,1))# ydata(tensor),shape=(20,1)# Build Linear Regression Parameters # Initialize w and b,where w is initialized to a normal distribution and b is initialized to0# Automatic differentiation is required,soset...
# Initialize bias to a small constant valuenn.init.constant_(self.out_proj.bias, 1.0) self.S6 = S6(seq_len, 2*d_model, state_size, device) # Add 1D convolution with kernel size 3self.conv = nn.Conv1d(seq_len, seq_len, kernel_...
defpad_sequences_3d(sequences,max_len=None,pad_value=0): # Assuming sequences is a tensor of shape (batch_size, seq_len, feature_size) batch_size, seq_len,feature_size=sequences.shape ifmax_lenisNone:max_len=seq_len+1 # Initialize padded_sequences with the pad_valuepadded_sequences...
_tensor.py classTensor(torch._C._TensorBase): 方法: def backward(self, gradient=None, retain_graph=None, create_graph=False, inputs=None): def register_hook(self, hook): def reinforce(self, reward): def is_shared(self): def share_memory_(self): ...
[ first_counter , second_counter , some_value ])with tf . Session () as sess :sess . run ( tf . global_variables_initializer ())counter_1_res , counter_2_res = sess . run ([ c1 , c2 ])first_counter = torch . Tensor ([...
NestedTensors 处理输入为批量可变长度序列的情况,无需将每个序列填充到批量中的最大长度。有关 NestedTensors 的更多信息,请参阅 torch.nested 和NestedTensors 教程。 代码语言:javascript 代码运行次数:0 运行 复制 import random def generate_rand_batch( batch_size, max_sequence_len, embed_dimension, pad_...
Initializes internal Module state,shared by both nn.Module and ScriptModule.""" torch._C._log_api_usage_once("python.nn_module")self.training=True # 控制 training/testing 状态 self._parameters=OrderedDict()# 在训练过程中会随着BP而更新的参数 ...