isaacmg
isaacmg
/ crossformer.json
Created
January 16, 2024 04:39
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| { | |
| "model_name": "Crossformer", | |
| "use_decoder": true, | |
| "model_type": "PyTorch", | |
| "model_params": { | |
| "n_time_series": 4, | |
| "forecast_history":6, | |
| "forecast_length": 4, | |
| "seg_len": 6 | |
| }, |
isaacmg
/ example.yaml
Created
February 5, 2021 18:27
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| wandb_version: 1 | |
| GCS: | |
| desc: null | |
| value: true | |
| _wandb: | |
| desc: null | |
| value: | |
| cli_version: 0.10.17 | |
| framework: torch |
isaacmg
/ model_xc_stash.py
Created
August 9, 2020 23:02
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| import torch | |
| class TransformerXCBasic(torch.nn.Module): | |
| """ Transformer model """ | |
| def __init__(self, n_time_series, out_seq_len, device, d_model=128, dropout=.5, n_head=8): | |
| super(TransformerXCBasic, self).__init__() | |
| self.input_dim = n_time_series | |
| self.n_head = n_head |
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| model = model_class.from_pretrained(self.args.model_path, | |
| config=config, | |
| # SpERT model parameters | |
| cls_token=self._tokenizer.convert_tokens_to_ids('[CLS]'), | |
| relation_types=input_reader.relation_type_count - 1, | |
| entity_types=input_reader.entity_type_count, | |
| max_pairs=self.args.max_pairs, | |
| prop_drop=self.args.prop_drop, | |
| size_embedding=self.args.size_embedding, | |
| freeze_transformer=self.args.freeze_transformer) |
isaacmg
/ defining_columns.py
Created
April 14, 2020 02:19
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| _column_definition = [ | |
| ('id', DataTypes.REAL_VALUED, InputTypes.ID), | |
| ('hours_from_start', DataTypes.REAL_VALUED, InputTypes.TIME), | |
| ('power_usage', DataTypes.REAL_VALUED, InputTypes.TARGET), | |
| ('hour', DataTypes.REAL_VALUED, InputTypes.KNOWN_INPUT), | |
| ('day_of_week', DataTypes.REAL_VALUED, InputTypes.KNOWN_INPUT), | |
| ('hours_from_start', DataTypes.REAL_VALUED, InputTypes.KNOWN_INPUT), | |
| ('categorical_id', DataTypes.CATEGORICAL, InputTypes.STATIC_INPUT), | |
| ] |
isaacmg
/ ade_eval.conf
Last active
April 5, 2020 18:52
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| label = conll04_eval | |
| model_type = spert | |
| model_path = data/models/ade | |
| tokenizer_path = data/models/ade | |
| dataset_path = data/datasets/ade/ade_split_0_test.json | |
| types_path = data/datasets/ade/ade_types.json | |
| eval_batch_size = 1 | |
| rel_filter_threshold = 0.4 | |
| size_embedding = 25 | |
| prop_drop = 0.1 |
isaacmg
/ eval_ade.conf
Created
April 5, 2020 18:50
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| label = ade_eval | |
| model_type = spert | |
| model_path = data/models/ade | |
| tokenizer_path = data/models/ade | |
| dataset_path = data/datasets/conll04/conll04_test.json | |
| types_path = data/datasets/conll04/conll04_types.json | |
| eval_batch_size = 1 | |
| rel_filter_threshold = 0.4 | |
| size_embedding = 25 | |
| prop_drop = 0.1 |
isaacmg
/ train_epoch_loop.py
Last active
February 11, 2020 18:03
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| def train_epoch_loop(data_loader:DataLoader, opt:torch.optim, model:PyTorchForecast, takes_target:bool, forward_params={}) | |
| i = 0 | |
| running_loss = 0.0 | |
| for src, trg in data_loader: | |
| opt.zero_grad() | |
| # Convert to CPU/GPU/TPU | |
| src = src.to(model.device) | |
| trg = trg.to(model.device) | |
| # TODO figure how to avoid | |
| if takes_target: |
isaacmg
/ Dockerfile
Last active
February 10, 2020 21:20
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| FROM pytorch/pytorch:1.4-cuda10.1-cudnn7-devel | |
| COPY requirements.txt /tmp/ | |
| RUN pip install -r /tmp/requirements.txt | |
| ARG url | |
| RUN git clone -n https://github.com/example/example_repo | |
| RUN git checkout 543231 |
isaacmg
/ meta_model.py
Created
February 10, 2020 19:06
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| @TrainerBase.register('metatrainer') | |
| class MetaTrainer(Trainer): | |
| def __init__(self, | |
| model: Model, | |
| meta_model: MetaModel, | |
| optimizer: torch.optim.Optimizer, | |
| iterator: DataIterator, | |
| train_datasets: List[Iterable[Instance]], | |
| validation_datasets: Optional[Iterable[Instance]] = None, |
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