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https://github.com/amazon-science/chronos-forecasting
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15ffe8835d
*Issue #, if available:* *Description of changes:* This PR adds the Chronos-2 model. * Chronos-2 modeling and pipeline code, including tests. * Updated `pyproject.toml`. Merge `training` and `evaluation` extras into a single `dev` extra. This stuff is only relevant for the Chronos models. * Added `predict_fev` to `BaseChronosPipeline`. * Changes to `InstanceNorm` for Chronos-Bolt to make it general and compatible with Chronos-2. * Minor renaming and polishing in the inference code for Chronos and Chronos-Bolt. By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice. --------- Co-authored-by: Oleksandr Shchur <oleks.shchur@gmail.com>
57 lines
1 KiB
JSON
57 lines
1 KiB
JSON
{
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"architectures": [
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"Chronos2Model"
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],
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"chronos_config": {
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"context_length": 8192,
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"input_patch_size": 16,
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"input_patch_stride": 16,
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"max_output_patches": 64,
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"output_patch_size": 16,
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"quantiles": [
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0.01,
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0.05,
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0.1,
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0.15,
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0.2,
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0.25,
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0.3,
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0.35,
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0.4,
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0.45,
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0.5,
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0.55,
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0.6,
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0.65,
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0.7,
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0.75,
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0.8,
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0.85,
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0.9,
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0.95,
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0.99
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],
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"time_encoding_scale": 8192,
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"use_arcsinh": true,
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"use_reg_token": true
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},
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"chronos_pipeline_class": "Chronos2Pipeline",
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"d_ff": 8,
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"d_kv": 4,
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"d_model": 6,
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"dense_act_fn": "relu",
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"dropout_rate": 0.1,
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"feed_forward_proj": "relu",
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"initializer_factor": 0.05,
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"is_gated_act": false,
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"layer_norm_epsilon": 1e-06,
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"model_type": "t5",
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"num_heads": 4,
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"num_layers": 2,
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"pad_token_id": 0,
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"reg_token_id": 1,
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"rope_theta": 10000.0,
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"torch_dtype": "float32",
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"transformers_version": "4.54.1",
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"vocab_size": 2
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}
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