| from transformers import PretrainedConfig | |
| class FelaPdmConfig(PretrainedConfig): | |
| model_type = "fela-pdm" | |
| def __init__( | |
| self, | |
| variant="cmapss_FD001", | |
| task="rul", | |
| in_channels=14, | |
| patch=1, | |
| n_embd=64, | |
| n_layer=4, | |
| n_head=4, | |
| fno_modes=32, | |
| gla_chunk=32, | |
| ffn_hidden=128, | |
| dropout=0.0, | |
| use_gdn=False, | |
| gdn_every=4, | |
| n_classes=0, | |
| rul_head=True, | |
| seq_len=30, | |
| default_variant=None, | |
| variants=None, | |
| **kwargs, | |
| ): | |
| if isinstance(variants, dict): | |
| name = variant or default_variant | |
| if name in variants: | |
| v = variants[name] | |
| task = v.get("task", task) | |
| in_channels = v.get("in_channels", in_channels) | |
| patch = v.get("patch", patch) | |
| n_embd = v.get("n_embd", n_embd) | |
| n_layer = v.get("n_layer", n_layer) | |
| n_head = v.get("n_head", n_head) | |
| fno_modes = v.get("fno_modes", fno_modes) | |
| gla_chunk = v.get("gla_chunk", gla_chunk) | |
| ffn_hidden = v.get("ffn_hidden", ffn_hidden) | |
| dropout = v.get("dropout", dropout) | |
| use_gdn = v.get("use_gdn", use_gdn) | |
| gdn_every = v.get("gdn_every", gdn_every) | |
| n_classes = v.get("n_classes", n_classes) | |
| rul_head = v.get("rul_head", rul_head) | |
| seq_len = v.get("seq_len", seq_len) | |
| self.variant = variant | |
| self.task = task | |
| self.in_channels = in_channels | |
| self.patch = patch | |
| self.n_embd = n_embd | |
| self.n_layer = n_layer | |
| self.n_head = n_head | |
| self.fno_modes = fno_modes | |
| self.gla_chunk = gla_chunk | |
| self.ffn_hidden = ffn_hidden | |
| self.dropout = dropout | |
| self.use_gdn = use_gdn | |
| self.gdn_every = gdn_every | |
| self.n_classes = n_classes | |
| self.rul_head = rul_head | |
| self.seq_len = seq_len | |
| if default_variant is not None: | |
| self.default_variant = default_variant | |
| if variants is not None: | |
| self.variants = variants | |
| super().__init__(**kwargs) | |