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| __init__ (self, ent_tot, rel_tot, dim=100, margin=None, epsilon=None) |
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| forward (self, data) |
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| regularization (self, data) |
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| l3_regularization (self) |
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| predict (self, data) |
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| load_checkpoint (self, path) |
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| save_checkpoint (self, path) |
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| load_parameters (self, path) |
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| save_parameters (self, path) |
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| get_parameters (self, mode="numpy", param_dict=None) |
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| set_parameters (self, parameters) |
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| dim = dim |
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| margin = margin |
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| epsilon = epsilon |
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| ent_embeddings = nn.Embedding(self.ent_tot, self.dim) |
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| rel_embeddings = nn.Embedding(self.rel_tot, self.dim) |
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| embedding_range |
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| ent_tot = ent_tot |
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| rel_tot = rel_tot |
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| zero_const = nn.Parameter(torch.Tensor([0])) |
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| pi_const = nn.Parameter(torch.Tensor([3.14159265358979323846])) |
|
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| _conj (self, tensor) |
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| _real (self, tensor) |
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| _imag (self, tensor) |
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| _mul (self, real_1, imag_1, real_2, imag_2) |
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| _ccorr (self, a, b) |
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| _calc (self, h, t, r, mode) |
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◆ __init__()
OpenKE.module.model.HolE.HolE.__init__ |
( |
| self, |
|
|
| ent_tot, |
|
|
| rel_tot, |
|
|
| dim = 100, |
|
|
| margin = None, |
|
|
| epsilon = None ) |
◆ forward()
OpenKE.module.model.HolE.HolE.forward |
( |
| self, |
|
|
| data ) |
◆ predict()
OpenKE.module.model.HolE.HolE.predict |
( |
| self, |
|
|
| data ) |
◆ embedding_range
OpenKE.module.model.HolE.HolE.embedding_range |
Initial value:= nn.Parameter(
torch.Tensor([(self.margin + self.epsilon) / self.dim]),
requires_grad=False,
)
The documentation for this class was generated from the following file:
- seed_embeddings/OpenKE/module/model/HolE.py