first commit

.gitmodules

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+[submodule "submodules/uni2ts"]
+	path = submodules/uni2ts
+	url = https://github.com/SalesforceAIResearch/uni2ts.git
+[submodule "submodules/lag_llama"]
+	path = submodules/lag_llama
+	url = https://github.com/time-series-foundation-models/lag-llama.git
+[submodule "submodules/timesfm"]
+	path = submodules/timesfm
+	url = https://github.com/google-research/timesfm.git
+[submodule "submodules/tsfm"]
+	path = submodules/tsfm
+	url = https://github.com/ibm-granite/granite-tsfm.git

CODE_OF_CONDUCT.md

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+# Microsoft Open Source Code of Conduct
+
+This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
+
+Resources:
+
+- [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/)
+- [Microsoft Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/)
+- Contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with questions or concerns

LICENSE

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+    MIT License
+
+    Copyright (c) Microsoft Corporation.
+
+    Permission is hereby granted, free of charge, to any person obtaining a copy
+    of this software and associated documentation files (the "Software"), to deal
+    in the Software without restriction, including without limitation the rights
+    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+    copies of the Software, and to permit persons to whom the Software is
+    furnished to do so, subject to the following conditions:
+
+    The above copyright notice and this permission notice shall be included in all
+    copies or substantial portions of the Software.
+
+    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+    SOFTWARE

SECURITY.md

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+<!-- BEGIN MICROSOFT SECURITY.MD V0.0.9 BLOCK -->
+
+## Security
+
+Microsoft takes the security of our software products and services seriously, which includes all source code repositories managed through our GitHub organizations, which include [Microsoft](https://github.com/Microsoft), [Azure](https://github.com/Azure), [DotNet](https://github.com/dotnet), [AspNet](https://github.com/aspnet) and [Xamarin](https://github.com/xamarin).
+
+If you believe you have found a security vulnerability in any Microsoft-owned repository that meets [Microsoft's definition of a security vulnerability](https://aka.ms/security.md/definition), please report it to us as described below.
+
+## Reporting Security Issues
+
+**Please do not report security vulnerabilities through public GitHub issues.**
+
+Instead, please report them to the Microsoft Security Response Center (MSRC) at [https://msrc.microsoft.com/create-report](https://aka.ms/security.md/msrc/create-report).
+
+If you prefer to submit without logging in, send email to [secure@microsoft.com](mailto:secure@microsoft.com).  If possible, encrypt your message with our PGP key; please download it from the [Microsoft Security Response Center PGP Key page](https://aka.ms/security.md/msrc/pgp).
+
+You should receive a response within 24 hours. If for some reason you do not, please follow up via email to ensure we received your original message. Additional information can be found at [microsoft.com/msrc](https://www.microsoft.com/msrc). 
+
+Please include the requested information listed below (as much as you can provide) to help us better understand the nature and scope of the possible issue:
+
+  * Type of issue (e.g. buffer overflow, SQL injection, cross-site scripting, etc.)
+  * Full paths of source file(s) related to the manifestation of the issue
+  * The location of the affected source code (tag/branch/commit or direct URL)
+  * Any special configuration required to reproduce the issue
+  * Step-by-step instructions to reproduce the issue
+  * Proof-of-concept or exploit code (if possible)
+  * Impact of the issue, including how an attacker might exploit the issue
+
+This information will help us triage your report more quickly.
+
+If you are reporting for a bug bounty, more complete reports can contribute to a higher bounty award. Please visit our [Microsoft Bug Bounty Program](https://aka.ms/security.md/msrc/bounty) page for more details about our active programs.
+
+## Preferred Languages
+
+We prefer all communications to be in English.
+
+## Policy
+
+Microsoft follows the principle of [Coordinated Vulnerability Disclosure](https://aka.ms/security.md/cvd).
+
+<!-- END MICROSOFT SECURITY.MD BLOCK -->

config/default/autoformer.yaml

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+# lightning==2.3.0.dev0
+seed_everything: 0
+trainer:
+  accelerator: gpu
+  devices: 1
+  strategy: auto
+  max_epochs: 50
+  use_distributed_sampler: false
+  limit_train_batches: 100
+  log_every_n_steps: 1
+  default_root_dir: ./results
+  accumulate_grad_batches: 1
+  # num_sanity_val_steps: 0
+  # gradient_clip_algorithm: 'norm'
+model:
+  forecaster:
+    class_path: probts.model.forecaster.point_forecaster.Autoformer
+    init_args:
+      moving_avg: 25
+      factor: 1
+      n_heads: 8
+      activation: 'gelu'
+      e_layers: 2
+      d_layers: 1
+      output_attention: false
+      d_ff: 512
+      f_hidden_size: 512
+      embed: 'timeF'
+      use_lags: false
+      use_feat_idx_emb: false
+      use_time_feat: true
+      feat_idx_emb_dim: 1
+  num_samples: 1
+  learning_rate: 1e-3
+  quantiles_num: 20
+data:
+  data_manager:
+    class_path: probts.data.data_manager.DataManager
+    init_args:
+      dataset: solar_nips
+      split_val: true
+      scaler: standard # none, standard, scaling
+  batch_size: 32
+  test_batch_size: 32
+  num_workers: 8

config/default/csdi.yaml

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+# lightning==2.3.0.dev0
+seed_everything: 1
+trainer:
+  accelerator: gpu
+  devices: 1
+  strategy: auto
+  max_epochs: 50
+  use_distributed_sampler: false
+  limit_train_batches: 800
+  log_every_n_steps: 1
+  check_val_every_n_epoch: 2
+  default_root_dir: ./results
+  accumulate_grad_batches: 8
+model:
+  forecaster:
+    class_path: probts.model.forecaster.prob_forecaster.CSDI
+    init_args:
+      emb_time_dim: 128
+      emb_feature_dim: 16
+      channels: 64
+      n_layers: 4
+      num_heads: 8
+      num_steps: 50
+      diffusion_embedding_dim: 128
+      beta_start: 0.001
+      beta_end: 0.5
+      sample_size: 64
+      linear_trans: false
+      use_lags: false
+      use_feat_idx_emb: false
+      use_time_feat: false
+      feat_idx_emb_dim: 1
+  num_samples: 100
+  learning_rate: 0.001
+  quantiles_num: 20
+data:
+  data_manager:
+    class_path: probts.data.data_manager.DataManager
+    init_args:
+      dataset: solar_nips
+      split_val: true
+      scaler: standard # identity, standard, temporal
+  batch_size: 4
+  test_batch_size: 4
+  num_workers: 8

config/default/dlinear.yaml

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+# lightning==2.3.0.dev0
+seed_everything: 1
+trainer:
+  accelerator: gpu
+  devices: 1
+  strategy: auto
+  max_epochs: 50
+  use_distributed_sampler: false
+  limit_train_batches: 100
+  log_every_n_steps: 1
+  default_root_dir: ./results
+model:
+  forecaster:
+    class_path: probts.model.forecaster.point_forecaster.DLinear
+    init_args:
+      individual: false
+      kernel_size: 3
+      use_lags: true
+      use_feat_idx_emb: true
+      use_time_feat: true
+  learning_rate: 0.01
+  quantiles_num: 20
+data:
+  data_manager:
+    class_path: probts.data.data_manager.DataManager
+    init_args:
+      dataset: solar_nips
+      split_val: true
+      scaler: standard # identity, standard, temporal
+  batch_size: 32
+  test_batch_size: 32
+  num_workers: 8

config/default/gru.yaml

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+# lightning==2.3.0.dev0
+seed_everything: 1
+trainer:
+  accelerator: gpu
+  devices: 1
+  strategy: auto
+  max_epochs: 50
+  use_distributed_sampler: false
+  limit_train_batches: 100
+  log_every_n_steps: 1
+  default_root_dir: ./results
+model:
+  forecaster:
+    class_path: probts.model.forecaster.point_forecaster.GRUForecaster
+    init_args:
+      f_hidden_size: 40
+      num_layers: 2
+      dropout: 0.1
+      use_lags: true
+      use_feat_idx_emb: true
+      use_time_feat: true
+      feat_idx_emb_dim: 1
+  learning_rate: 0.001
+  quantiles_num: 20
+data:
+  data_manager:
+    class_path: probts.data.data_manager.DataManager
+    init_args:
+      dataset: solar_nips
+      split_val: true
+      scaler: standard # identity, standard, temporal
+  batch_size: 64
+  test_batch_size: 64
+  num_workers: 8

config/default/gru_maf.yaml

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+# lightning==2.3.0.dev0
+seed_everything: 1
+trainer:
+  accelerator: gpu
+  devices: 1
+  strategy: auto
+  max_epochs: 1
+  use_distributed_sampler: false
+  limit_train_batches: 100
+  log_every_n_steps: 1
+  default_root_dir: ./results
+model:
+  forecaster:
+    class_path: probts.model.forecaster.prob_forecaster.GRU_MAF
+    init_args:
+      enc_num_layers: 2
+      enc_hidden_size: 40
+      enc_dropout: 0.1
+      n_blocks: 4
+      hidden_size: 100
+      n_hidden: 2
+      batch_norm: false
+      conditional_length: 200
+      dequantize: true
+      use_lags: true
+      use_feat_idx_emb: true
+      use_time_feat: true
+      feat_idx_emb_dim: 1
+      use_scaling: true
+  num_samples: 100
+  learning_rate: 0.001
+  quantiles_num: 20
+data:
+  data_manager:
+    class_path: probts.data.data_manager.DataManager
+    init_args:
+      dataset: solar_nips
+      scaler: identity # identity, standard, temporal
+      split_val: true
+  batch_size: 64
+  test_batch_size: 64
+  num_workers: 8

config/default/gru_nvp.yaml

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+# lightning==2.3.0.dev0
+seed_everything: 1
+trainer:
+  accelerator: gpu
+  devices: 1
+  strategy: auto
+  max_epochs: 7
+  use_distributed_sampler: false
+  limit_train_batches: 100
+  log_every_n_steps: 1
+  default_root_dir: ./results
+model:
+  forecaster:
+    class_path: probts.model.forecaster.prob_forecaster.GRU_NVP
+    init_args:
+      enc_hidden_size: 40
+      enc_num_layers: 2
+      enc_dropout: 0.1
+      n_blocks: 4
+      hidden_size: 100
+      n_hidden: 2
+      batch_norm: true
+      conditional_length: 200
+      dequantize: true
+      use_lags: true
+      use_feat_idx_emb: true
+      use_time_feat: true
+      feat_idx_emb_dim: 1
+      use_scaling: true
+  num_samples: 100
+  learning_rate: 0.001
+  quantiles_num: 20
+data:
+  data_manager:
+    class_path: probts.data.data_manager.DataManager
+    init_args:
+      dataset: solar_nips
+      split_val: true
+      scaler: identity # identity, standard, temporal
+  batch_size: 64
+  test_batch_size: 64
+  num_workers: 8

config/default/itransformer.yaml

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+# lightning==2.3.0.dev0
+seed_everything: 0
+trainer:
+  accelerator: gpu
+  devices: 1
+  strategy: auto
+  max_epochs: 50
+  use_distributed_sampler: false
+  limit_train_batches: 100
+  log_every_n_steps: 1
+  default_root_dir: ./results
+  accumulate_grad_batches: 1
+model:
+  forecaster:
+    class_path: probts.model.forecaster.point_forecaster.iTransformer
+    init_args:
+      factor: 1
+      n_heads: 8
+      activation: 'gelu'
+      e_layers: 2
+      output_attention: false
+      f_hidden_size: 256
+      d_ff: 256
+      label_len: 48
+      use_lags: false
+      use_feat_idx_emb: false
+      use_time_feat: false
+      feat_idx_emb_dim: 1
+  num_samples: 1
+  learning_rate: 1e-4
+  quantiles_num: 20
+data:
+  data_manager:
+    class_path: probts.data.data_manager.DataManager
+    init_args:
+      dataset: solar_nips
+      split_val: true
+      scaler: standard # none, standard, scaling
+  batch_size: 32
+  test_batch_size: 32
+  num_workers: 8