azureml-contrib-automl-dnn-forecasting

View on PyPIReverse Dependencies (0)

1.58.0 azureml_contrib_automl_dnn_forecasting-1.58.0-py3-none-any.whl

Wheel Details

Project: azureml-contrib-automl-dnn-forecasting
Version: 1.58.0
Filename: azureml_contrib_automl_dnn_forecasting-1.58.0-py3-none-any.whl
Download: [link]
Size: 269688
MD5: a43f4ae8a27c8dbe39bb0a6bb225f9f1
SHA256: 74d41c85516be63b9caff58a13c1851790f47ce899965436c9a3ce3989377cb6
Uploaded: 2024-10-16 17:44:02 +0000

dist-info

METADATA

Metadata-Version: 2.1
Name: azureml-contrib-automl-dnn-forecasting
Version: 1.58.0
Summary: Azure Automated Machine Learning DNN package for timeseries forecasting.
Author: Microsoft Corp
Home-Page: https://docs.microsoft.com/python/api/overview/azure/ml/?view=azure-ml-py
License: Proprietary https://aka.ms/azureml-preview-sdk-license
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.8,<4.0
Requires-Dist: azureml-core (~=1.58.0)
Requires-Dist: azureml-automl-core (~=1.58.0)
Requires-Dist: azureml-automl-runtime (~=1.58.0)
Requires-Dist: azureml-train-automl-client (~=1.58.0)
Requires-Dist: azureml-train-automl-runtime (~=1.58.0)
Requires-Dist: azureml-dataset-runtime[pandas] (~=1.58.0)
Requires-Dist: GitPython (>=3.1.37)
Requires-Dist: overrides (~=6.1.0)
Requires-Dist: pandas (==1.5.3)
Requires-Dist: tensorboard (<=2.11.0,>=2.4.1)
Requires-Dist: torch (==2.2.2)
Requires-Dist: tqdm (<=5.0.0,>=4.32.1)
Requires-Dist: mlflow-skinny (<=2.9.2)
Requires-Dist: numpy (<=1.21.6,>=1.16.0); python_version < "3.8"
Requires-Dist: numpy (<=1.23.5,>=1.16.0); python_version >= "3.8"
Description-Content-Type: text/x-rst
License-File: LICENSE.txt
[Description omitted; length: 93 characters]

WHEEL

Wheel-Version: 1.0
Generator: setuptools (75.2.0)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
Deep4Cast/deep4cast/__init__.py sha256=JSkhzHJTvCJ22GpmOIpRwhk9oEHzDCg8wRRaJnvpc-c 53
Deep4Cast/deep4cast/custom_layers.py sha256=ndclFwYf_QljxLs5SQqQkOKIyLbcISA7IIWXuhyHfaA 3089
Deep4Cast/deep4cast/datasets.py sha256=UFo0Wzw460NOVIgcpGZi6h5e-Wmwenp9KNchWcy874k 3526
Deep4Cast/deep4cast/forecasters.py sha256=sG92uj4qnADwt9m_0qwQevgRCkCcKLcQOXvNWtmy1gU 8193
Deep4Cast/deep4cast/metrics.py sha256=0gJYUfWILbhX6AxmgpsB0ARK40G_k-_TlG_CYYAumZQ 12309
Deep4Cast/deep4cast/models.py sha256=OET_BBGLWcytkQhbCAKyVIA5-VdQmE5AyDDt_BrWXUU 7515
Deep4Cast/deep4cast/transforms.py sha256=5to7Ms-GasSNknqQo0dmU4XSAqY7ORFYY0-6RXWKUw4 8990
azureml/contrib/__init__.py sha256=n0xtZ3iWcoVg5Qognsb7InYAUVAK8s3iaVeHB5GOaNA 251
azureml/contrib/automl/__init__.py sha256=vYHjNxCPkvORKum5MXpLaI_2DbXFT_j3pZqPVkAC8UI 329
azureml/contrib/automl/dnn/__init__.py sha256=vYHjNxCPkvORKum5MXpLaI_2DbXFT_j3pZqPVkAC8UI 329
azureml/contrib/automl/dnn/forecasting/__init__.py sha256=S8CcT1ygHHJq2c-1cDA-EF5ZRy0l8tFafwWcZjs3bIM 743
azureml/contrib/automl/dnn/forecasting/constants.py sha256=GvCZY3z7dVef6H3wT4N9wDqhh2zP1XTwk6DMoOY8glM 7714
azureml/contrib/automl/dnn/forecasting/types.py sha256=JsbRO2R7QLQowkFHTNl2eJxgJAa-wy4h8C2DN7CSMTI 442
azureml/contrib/automl/dnn/forecasting/_distributed/__init__.py sha256=12RznPXQBuIuJmQ8nvxrwZGCkZySivJ7AbWKI0XY-Yw 267
azureml/contrib/automl/dnn/forecasting/_distributed/_data_for_inference.py sha256=yW5rFMb51QwkE-zmtNSOK-LM6Dr7CACAdrhpnBSw2VE 3824
azureml/contrib/automl/dnn/forecasting/_distributed/_distributed_util.py sha256=V0eAEBp4OzZ7uBvnUr5j8vluoxg5-MGRwsUe6T6yfxQ 12044
azureml/contrib/automl/dnn/forecasting/_distributed/_grain_summary.py sha256=MpUkPz-mLqgxf794SndBycjpsCY4s9fPgFiUaTjasMc 3457
azureml/contrib/automl/dnn/forecasting/_distributed/_shard_summary.py sha256=hGTAhryNcHIDr-z4pJMfhZTMVWJYW3eA9Hh5_yqGyfY 2920
azureml/contrib/automl/dnn/forecasting/_distributed/_metrics/__init__.py sha256=9-yQUWRyxUe7xX7aOAAUNh5LHVg5ktb_Dm8eb060_hY 263
azureml/contrib/automl/dnn/forecasting/_distributed/_metrics/_explained_variance.py sha256=81HrAr2uYAPYPNMCROj0KGvBWOblyKv5M7wP2q-vTnY 3057
azureml/contrib/automl/dnn/forecasting/_distributed/_metrics/_mae.py sha256=3gU9nXchFLjIG6bFA2Qe9wbAdBRUvzWiPlA7xFCNHF8 2206
azureml/contrib/automl/dnn/forecasting/_distributed/_metrics/_mape.py sha256=uzjynvB0fGgcpi_x2OZnw9GQW7RffLkouns8WaWD2NY 2399
azureml/contrib/automl/dnn/forecasting/_distributed/_metrics/_metric_util.py sha256=bndifw83OjY1rvhuBO1feFdXsWO1hY-mP9rOHQzHMVU 1040
azureml/contrib/automl/dnn/forecasting/_distributed/_metrics/_nmae.py sha256=bKBPIr2_iBAQ__XFG91DeOKFE_Dtv6YR62Wt1KnWlAA 3920
azureml/contrib/automl/dnn/forecasting/_distributed/_metrics/_nrmse.py sha256=gOgdm8sTl6YyJWrZf3bdVOl3Hi70dhvkef2ScPPY6N4 3851
azureml/contrib/automl/dnn/forecasting/_distributed/_metrics/_nrmsle.py sha256=jZvGzHYpxZIfVNZKIp3cdhxNaB4qdtiRXO2v93nFD24 4462
azureml/contrib/automl/dnn/forecasting/_distributed/_metrics/_r2_score.py sha256=-sbiyWUTJTtL86-BabggZk3qPR4uMjmNX2YsMVOX_KA 2727
azureml/contrib/automl/dnn/forecasting/_distributed/_metrics/_rmse.py sha256=9-VdU-fO_nT_UFNRLeO_QFrUqv-Ee1vk9m7hJUip2RI 2171
azureml/contrib/automl/dnn/forecasting/_distributed/_metrics/_rmsle.py sha256=cVG3pdl7CrFsIpT8SrKWk_jVOWI4mPqBXN_KU4tFc-Y 2472
azureml/contrib/automl/dnn/forecasting/_distributed/_metrics/_supported_metrics.py sha256=Hvo9DRKbkNgpvbRP73WpKByY8rRireg4YecyKrYPCew 2624
azureml/contrib/automl/dnn/forecasting/_distributed/_sharding/__init__.py sha256=_iJCCs4wu1P_35tkvQkCoU9njOvfAuMHslp7q91nbT8 799
azureml/contrib/automl/dnn/forecasting/_distributed/_sharding/_download_shards.py sha256=_rRctHIBzGeZ5O7EuGiP3OfR0agvBKecFncFD6h3Yek 8224
azureml/contrib/automl/dnn/forecasting/_distributed/_sharding/_equal_samples_sharding_strategy.py sha256=ufzh5uM8ukBxJIUWe5oheaEhgG0P8Ez6MTzxCpb72Gs 11290
azureml/contrib/automl/dnn/forecasting/_distributed/_sharding/_sharding_strategy_base.py sha256=rYFSb4iuDDOrvSXPVF4cGudt9IrCzWveuZmtFdS3CZg 2734
azureml/contrib/automl/dnn/forecasting/_distributed/_sharding/_sharding_strategy_selector.py sha256=BiTCh1BRVTc2zrGhcfj5yKRweA_lE8yNOKnab5sxjgI 2678
azureml/contrib/automl/dnn/forecasting/callbacks/__init__.py sha256=KG4MGpbeCq8ZWoYOWuKfanfVq--aRSRvAXRWeII9EhM 252
azureml/contrib/automl/dnn/forecasting/callbacks/_all_rank_callback.py sha256=ptNeeCjj-aeBUYKiwFrRL001UH0-C6Vw6YHtY-h1OGM 578
azureml/contrib/automl/dnn/forecasting/callbacks/_global_loss_callback.py sha256=ob8zD2hBbkZRHVsoM94ugsrnHIKvO2p2CW2r6LKLkY0 1802
azureml/contrib/automl/dnn/forecasting/callbacks/_horovod_callback.py sha256=lSswcKIWat9hq0ZRKfcpSXce_vLLc1_VY1wPmoZ4jnQ 2482
azureml/contrib/automl/dnn/forecasting/callbacks/_run_update_base.py sha256=ctgzlPSJEic76trk6Kru81e5bRV3HQ5xl8k28K3wzTA 15036
azureml/contrib/automl/dnn/forecasting/callbacks/_run_update_distributed.py sha256=kOug4CFcO50qylWDovv7pjowhFynSJ9lliZa_yJLL3U 4577
azureml/contrib/automl/dnn/forecasting/callbacks/run_update.py sha256=00Z6XJ2BJXkYf8c8WtcZwLtqzFjami9eIWSjhFV4Ieg 10225
azureml/contrib/automl/dnn/forecasting/datasets/__init__.py sha256=Wo58j5a4s9kmbb8kTJXU39V_EyoPm7bkOYGX-iaRx94 251
azureml/contrib/automl/dnn/forecasting/datasets/_timeseries_dataset_config.py sha256=GyGw7ehjdUm9zasK8IyEA7FObLJ5n1ZeueX-835cxj8 17474
azureml/contrib/automl/dnn/forecasting/datasets/_timeseries_numpy_dataset.py sha256=0dm4yRbnaakpNVGpff08hTlEccvaWZ0nOxZwRpvSWb4 7196
azureml/contrib/automl/dnn/forecasting/datasets/eval_timeseries_datasets.py sha256=G8PJ9FFFHRJ7mUzjsgqzUcJ9kVl-NWYImUy1WWYZ1Vw 14846
azureml/contrib/automl/dnn/forecasting/datasets/timeseries_datasets.py sha256=xMpVe8UNU-WPz1hr9Wrmrt9nlIGRuW3P389OV9Aiu7E 62258
azureml/contrib/automl/dnn/forecasting/datasets/timeseries_datasets_utils.py sha256=Wjf68p2RMzdXvZO3B9ZLugjjqB-XIoI8WhptpfGg9x0 13138
azureml/contrib/automl/dnn/forecasting/datasets/timeseries_inference_datasets.py sha256=ZUMDRJP-dQVxkUJUncNt29_rQneJyB5mfJq1dxHWggI 8649
azureml/contrib/automl/dnn/forecasting/forecasters/__init__.py sha256=g1DqLDKWrMZn1cY2Z5e34SqcpxHOdMXALsbGS0MaALg 254
azureml/contrib/automl/dnn/forecasting/forecasters/deepar.py sha256=uLG7bgnt18a9d1N4Qv4lXxM8IqdIuNzICSPl1uhGVro 7608
azureml/contrib/automl/dnn/forecasting/metrics/__init__.py sha256=CgEoNijX5hDBzRAhKfyd64btoqESZ6CF5pdUYXRXPMo 251
azureml/contrib/automl/dnn/forecasting/metrics/metrics.py sha256=Xd39lmBR9fSQosLeas30CO34IpnA0km8bQXEj6PIeSI 9216
azureml/contrib/automl/dnn/forecasting/metrics/primary_metrics.py sha256=2rSsVtybIzHaxb_ebTYDrDzNviy1asjhVkUBT20G0D8 4919
azureml/contrib/automl/dnn/forecasting/models/__init__.py sha256=5U8rUbjVMCZsstF92Q9MarNzPs1b7mNRN7qw2YieSxs 250
azureml/contrib/automl/dnn/forecasting/models/base_model.py sha256=JOBFV7K76CFngxL4f1jA8zfiCkL0A_lTl1vcmgVESts 640
azureml/contrib/automl/dnn/forecasting/models/deepar.py sha256=-LUk9flLZdRdfSVRCPe8k3dlTikBWZRv7YkQ2Ixdl-c 10060
azureml/contrib/automl/dnn/forecasting/wrapper/__init__.py sha256=FFG8OV5nH1HsexZAEqSaWmf0-BEaxBpsCUlAA6zTWoQ 251
azureml/contrib/automl/dnn/forecasting/wrapper/_distributed_helper.py sha256=TbvAx4LGP9QRHCRu6U-vYYu6aBM1YQbEARp7SO70D54 8309
azureml/contrib/automl/dnn/forecasting/wrapper/_wrapper_util.py sha256=11X2kyexKWo301IaeeExSGO1Vl_J7oyLehHaxCsARUU 10927
azureml/contrib/automl/dnn/forecasting/wrapper/deep4cast_wrapper.py sha256=bmgL9baTaZVPm8sy1FElfAMOCWkP1SRdA-Ds0UdOAo8 4725
azureml/contrib/automl/dnn/forecasting/wrapper/forecast_tcn_wrapper.py sha256=4VNXkp58l9ahnXIQzMNo40XiQrfxntY-7CAXZGPSn6s 58062
azureml/contrib/automl/dnn/forecasting/wrapper/forecast_wrapper.py sha256=k7-TxRlLE2HMg2Gz3T_rfjddwxmUoTxUvVp7ykta39M 44717
azureml/contrib/automl/dnn/forecasting/wrapper/tcn_model_utl.py sha256=oZnrpdmm0fySurXz3PdNTf5R1gZxZNGOhg_7P2ZxVl4 13482
azureml/contrib/automl/dnn/forecasting/wrapper/dispatched/__init__.py sha256=YVnWX_LJBdDNVZD-WNYUsJ8sS2tiF4ubW22j6INnXuo 261
azureml/contrib/automl/dnn/forecasting/wrapper/dispatched/invoker/__init__.py sha256=CaZmzcANnqNhJA2R6Yz2X4-qbB50Qm9_UJh-CIZ4cVg 327
azureml/contrib/automl/dnn/forecasting/wrapper/dispatched/invoker/runner.py sha256=A8dUET96-uFIke4i-G3PdnnQQb8TttWU-4Qf5Bc2_HA 18781
forecast/examples/train.py sha256=DZIKyf9TPggNK5SH5yF6lgv6ojbt01WoajVkxWww9vI 12341
forecast/forecast/__init__.py sha256=ePtXm4IfD4wrfEEtRtIMi5QbW2K6UtUr75_dDzGKZLo 88
forecast/forecast/forecaster.py sha256=bvjjcauyyS6Kv5DzzG25cJN2lzmq7_fOENLJ-Kantv4 33381
forecast/forecast/losses.py sha256=V9oIaZA89WIcIERiJtpE89g2hb3jFQRuQqIWGZUzJC8 3042
forecast/forecast/utils.py sha256=d-9R67Sd1CxQTbJ2_tnPq7vHXn8c24s16qe0-jrPOT8 3161
forecast/forecast/callbacks/__init__.py sha256=zRhwlKeXf8lQdlqI_oUQUmgQVwr4utgp4X1yAxtpTXc 603
forecast/forecast/callbacks/callback.py sha256=GHv2ZLqphyXRNRIPDMmvucXScOKw63JqHKJTXpa2cAk 14494
forecast/forecast/callbacks/optimizer.py sha256=kzNlpEvI3e3SH7bC2wL2ERrr1NXACwVlxkVC9PtVJK4 13309
forecast/forecast/callbacks/serialization.py sha256=cY6qza3Pb8eHoRkJZVUj4yc2DTJrMtu7cAv7VoN0rJc 4649
forecast/forecast/callbacks/tensorboard.py sha256=FLvV7AU3YuoMT3WzSXYeZH8Gzx2LLCtRn2BHCE-jV10 5374
forecast/forecast/callbacks/utils.py sha256=66He6BbHILkEadn2Y3m2mZctQOptnH8edBAEwOhheT4 456
forecast/forecast/data/__init__.py sha256=MxkoSuc_WKqC1DRiUVsU2CgRqxFUO-P03JzmiLPIKhI 732
forecast/forecast/data/dataset.py sha256=amaQKm_YQ9558NBh_ALCqNdCW3sR3hNstKIuHU7mzgs 14823
forecast/forecast/data/date_featurizers.py sha256=fiYGbLHEOLtqVybQx-c7-fofMPflrOekNdsSKibXi5E 10898
forecast/forecast/data/transforms.py sha256=3vrh0KFNaMLvWJZF9RUfussndkyQoQFOKQlqnzy48ng 26875
forecast/forecast/data/utils.py sha256=DN4cz4ws6qZqE-Ts4i8r771lF0DrX13fki8v_qINo-Q 7042
forecast/forecast/data/batch_transforms/__init__.py sha256=4dcGAB7wAwZB2bdGvvRJeGOBQCxuZTfS9eJrn1iTLQA 455
forecast/forecast/data/batch_transforms/batch_transforms.py sha256=K8D1eEMZfgi0yYp6AswUdJzsPl3qAYZhBOehM-dJBPI 8258
forecast/forecast/data/batch_transforms/common.py sha256=v4kfPJpJ6hh2XTAZbqB17OskUXo97BoRrVvEmWlL2bI 1007
forecast/forecast/data/batch_transforms/feature_transform.py sha256=B_-FP9eoZFqcAIGaFXOU_87QwLKo_AmkmCMGdwZDm9A 8570
forecast/forecast/data/batch_transforms/normalizer.py sha256=SmnQJeZtP8ISQ0i8_Wbu7o7wvwnKyjZzc8spu40AB9g 11965
forecast/forecast/data/batch_transforms/one_hot.py sha256=WSFR4_VzkGZR5unZSIP3dey_AyiDz1iP5Tk-doTzybo 7144
forecast/forecast/data/batch_transforms/subtract_offset.py sha256=2csrNE7NG28fUL_guSfunX2z1Qn_aWOWwX16EhhFL7c 4973
forecast/forecast/data/sources/__init__.py sha256=WO9eHXtaNqp88s8FoKG4OJhDn_ILBiEEK8hrAKIWWUQ 545
forecast/forecast/data/sources/data_source.py sha256=UTj38UxvabwJ4q9GWrwEKn2t6n6lTV1P8U_byYWXHsQ 3290
forecast/forecast/data/sources/utils.py sha256=JqhRIv0w-lwkcQejz9x8-mnOYoC2UMbwPy7vOFORBbg 1246
forecast/forecast/data/sources/GEFCom14/__init__.py sha256=4WHjNWbcfcX64WqngxpcYlXgF4aq1K6ODj9XGW_Lb_g 112
forecast/forecast/data/sources/GEFCom14/data_source.py sha256=N3izXZOMpCNpTsGIOFt2WHbUiIVbWUw0GKSORBQfYLY 10435
forecast/forecast/data/sources/electricity/__init__.py sha256=8L1IaW_JrHlOEbR1YgBhFTt--UWcVMHv6SXAr7Bctb4 184
forecast/forecast/data/sources/electricity/data_source.py sha256=uHqqyr8EyAYLhpKiQg3Ffi62zaHuKkDaZ0zt3KIPgYI 10775
forecast/forecast/data/sources/github/__init__.py sha256=vImN7xq8djxW8OiGSujtV8Yo_hwKbw3eeecscg5fDnY 140
forecast/forecast/data/sources/github/data_source.py sha256=Q4Yix0wE8KuCMT0qXUeh5Sw4KVR2gDybpd_KzhzSET4 8617
forecast/forecast/data/sources/m5/__init__.py sha256=wj0qW5CCf-y2tuJEqctN82yQe5vtU-2fo61tfT-3g2c 108
forecast/forecast/data/sources/m5/data_source.py sha256=TuZN6qI_5ug461GQXekErdmU3GA3hMzBOitKppY_AS8 21312
forecast/forecast/data/sources/parts/__init__.py sha256=sZvtz8LKy2Dtz5uSN9JOGdZK-F7TcTmKb-Pgiyewedw 114
forecast/forecast/data/sources/parts/data_source.py sha256=uoaHqo4BNHaw-rzmk7BXm-cwPKzNSkVQp2zCCPGyJxA 8500
forecast/forecast/distributed/__init__.py sha256=aA95QzIXEcAQqxTFefinCE8B9kBjOZZn2F_FY7pBZI4 209
forecast/forecast/distributed/base.py sha256=BqMtxROkt_fNUs4Ma2LDtYgkOmXuTT7PEdK-ieKl0TM 1226
forecast/forecast/distributed/horovod.py sha256=aZeE_3urPIgxsnDFzohtoZrNxxK_XLV3gmTCo1DBCA0 8851
forecast/forecast/distributed/single_process.py sha256=e2ZpTfE6Xuz6XcemW9qYqOYILrzWpP5tgQinfSCioF8 1079
forecast/forecast/metrics/__init__.py sha256=EpPWLXZUJeK7wImh2_mapgMCZS-_CSubN8iCdmK75L0 264
forecast/forecast/metrics/functional.py sha256=rDSflOj-K4C4-3EXJL8R6bQsPpLozskPWBvcyBqE_Wk 5293
forecast/forecast/metrics/metric.py sha256=RMeiX0lR_gQv9fOnqOTvFQqwn2it3w0226mgdqxx3GU 2612
forecast/forecast/metrics/optimizer.py sha256=NinEkbHXcrAzufcflbfdiml5Bka-0-tYZISz8JjJmEo 1020
forecast/forecast/metrics/performance.py sha256=-KYUC1CMkVPZ4YNMudC2naGBFwDG_iZnmIaESXPqpAo 1997
forecast/forecast/models/__init__.py sha256=XxTc2xLGrXqYTm3y20-o_uwEQlPGa595oKEpRSdfeCs 156
forecast/forecast/models/model.py sha256=s1_6XA4RRAmFpEKANPhkG4fi44yvyGqdadPEces06nE 6960
forecast/forecast/models/backbone/__init__.py sha256=8iB_kSqeZtNRZd7w11YBDBqxsJC7NqfBRHwQxatA4Xw 572
forecast/forecast/models/backbone/base.py sha256=Ye2joEmLSoapjd91Bq6PESt0TPdkM-uTjvqpy6zfrU0 2695
forecast/forecast/models/backbone/lstm.py sha256=bNHgQI7vw8GywwuaYijxBg7Qgnk4jh89-JxYOIcNjCU 6618
forecast/forecast/models/backbone/repeated_cell.py sha256=CsGR7q014H9FjlFXEZ8sXOh4Gl8l6wdITKG1dDbXW4M 9986
forecast/forecast/models/backbone/cell/__init__.py sha256=-mgDeXWuVTd1lPlPzNWc-RBnt4OwwRgGl7c7164WLyc 250
forecast/forecast/models/backbone/cell/base.py sha256=dgZcAPMxnkN4uG9yELGHk0k34PR6gvxFaPYvc5nVrr0 5467
forecast/forecast/models/backbone/cell/residual_tcn_cell.py sha256=7F6Du4r-05CrBMuGDLVAarHpeslzubHYNGRAmNhsekY 8159
forecast/forecast/models/canned/__init__.py sha256=j6NpCAsXtrsZYrdIUrNlJYNSEhQN4Sg6VfghkzOD6l0 369
forecast/forecast/models/canned/lstm_quantile_forecaster.py sha256=pLQHawFqKCuhGKJnhQfHKiaXhjmc1M5i7Xct6llXNPM 2392
forecast/forecast/models/canned/tcn_gaussian_forecaster.py sha256=LYW9MB67SXU4sns7qrCpGA4_poOwzVni73A3Cm64eRo 3081
forecast/forecast/models/canned/tcn_quantile_forecaster.py sha256=q0qMs1GZX5qKKtIoGFCNgD_KPyc-I_rIZZVm2fSwi0w 5946
forecast/forecast/models/common/__init__.py sha256=tRUnl3p1xn98wH4xSIVaAQE7BbfDIn4cNKm9gFdETyE 199
forecast/forecast/models/common/component.py sha256=WPWpm50E_0wNOoghX-mEtG6Urc7zmXL8ojhQTSyMIKo 1876
forecast/forecast/models/common/exceptions.py sha256=9ZKrY8yiNHCzWCfPVST-AstMaI8rtrki2stRu9Rp0Uk 316
forecast/forecast/models/common/module.py sha256=GtrVKkeZgo9Q7CqggO0Y8zU0_yNJXlVPiXWErRdjcV8 2680
forecast/forecast/models/common/ops.py sha256=DKuElK8u7zQa2WPagn-4pISf0Pbn74cKliBDd1K6GNw 4722
forecast/forecast/models/forecast_head/__init__.py sha256=9OyWRAoME-OqC4EhNsmMXz0CveWtpcWpSRagnk8qgP8 539
forecast/forecast/models/forecast_head/base.py sha256=1x1hfU9a3-5BlOKEeuAKt98yXyYaLkrw4ObSMi9pw4E 2424
forecast/forecast/models/forecast_head/strictly_positive_scalar.py sha256=0px5YgmqVj-PiFuTmFOmDZ3jUZUL-g9zOl3HTOFiIL4 3238
forecast/forecast/models/forecast_head/unbounded_scalar.py sha256=GLQuFuMzgQkLii_-JNIeWNnODBj6_Lfn3QsGEj-mgWk 3044
forecast/forecast/models/premix/__init__.py sha256=pK-RpfXSO93LGF4KwWsVre94Fo8ucFi6G6jA9559Pvk 663
forecast/forecast/models/premix/base.py sha256=XjBQ-bKEjvNXJ7ucID2w_tAqbTx0cG9O3hiKIkd-xvU 2328
forecast/forecast/models/premix/conv.py sha256=IKduaz1pPIuvrSpdvXbnwwDeJO83vbyKYkaM5BKjiuI 4723
forecast/forecast/models/premix/embedding.py sha256=-GdvpBuun4SVD62PF9GV9lc0SPcPiHKHGQsqydvDcgo 6146
forecast/forecast/models/premix/future_concat.py sha256=OW87tiIB8IohMcU_jebBVbaHEn2aTkhUmMmZP2CFPBE 3217
forecast/forecast/models/premix/identity.py sha256=ogD6IAJ5spzuUV93pRhJY9K9gu6dUpzaBNfnI_q7k_o 1809
forecast/forecast/models/premix/mixer.py sha256=NKC3Sc362zU2GorwWhyeZvf6oWU72IhMLDyh9pvU6UE 4551
forecast/tests/callbacks/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
forecast/tests/callbacks/test_metric.py sha256=ERqPMWjoUrEmqlsBsZEWa65tvMKfAj18rgsPLaIS6jA 1341
forecast/tests/data/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
forecast/tests/data/test_dataset.py sha256=8VUWIEltmAIxu1o24hXGP-LBP73rTwbbmYNpf_POGo8 7330
forecast/tests/data/test_date_featurizers.py sha256=nlk-Kas5acTu66Sj778-GqZnR8qVtmuEranhi6epzls 2192
forecast/tests/data/test_onehot.py sha256=kPG5gp_cKbELpIpF7J892K1XsRXQDw9gUdmWmaYPl44 1325
forecast/tests/data/batch_transforms/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
forecast/tests/data/batch_transforms/test_batch_transform.py sha256=CQxmqWO6YzBmK_kmktssFoWquDpZ2we1uCm_icllBiw 14407
forecast/tests/data/batch_transforms/test_feature_transform.py sha256=qYDgqAGjo480xjMStQb8o2JTT2rQ6Lt4borJsz-8HKg 10318
forecast/tests/data/batch_transforms/test_normalizer.py sha256=tuDX9g8mxX4UH7yBPYPF8tZh_gsyPgaT5El3sFpbLHE 10138
forecast/tests/data/batch_transforms/test_one_hot.py sha256=eL5d3UpDsBMmxoijHHEgkqL7Wuh6oklv_r9vfyeZMqc 3052
forecast/tests/data/batch_transforms/test_subtract_offset.py sha256=odwYLnpLePi8YYwe5TVZk-ZfZbKqEN3CLzWZ4AeaP64 3665
forecast/tests/data/sources/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
forecast/tests/data/sources/test_data_source.py sha256=6vZiekYl5XZx38oUCieVDRR8Qs5Tw-rxGrF2tKXzM58 1706
forecast/tests/data/sources/test_github.py sha256=8EhRrjQRREJZHWtNfFcEq3GmbnFv7Cou1alFD8Vwkn8 636
forecast/tests/metrics/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
forecast/tests/models/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
forecast/tests/models/backbone/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
forecast/tests/models/backbone/cell/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
forecast/tests/models/forecast_head/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
forecast/tests/models/premix/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
forecast/tests/models/premix/test_conv.py sha256=HKcRLspYam12w_nW99qqcNP3AJ-JsFQ6O2fnEH_g5Co 3502
forecast/tests/models/premix/test_identity.py sha256=0RqVYvhkAA_-69hqgMXv-9OlU5PMU5blEvHzk_JEL90 1424
azureml_contrib_automl_dnn_forecasting-1.58.0.dist-info/LICENSE.txt sha256=FOfkEEz4uS7g278F9Rq12rqKF3lLyBUZhVpLetuZrTg 1021
azureml_contrib_automl_dnn_forecasting-1.58.0.dist-info/METADATA sha256=GGnLjd0Bi5SBmXFP97J6-PXtPFfo3ePMM-_9JJCr3aA 1570
azureml_contrib_automl_dnn_forecasting-1.58.0.dist-info/WHEEL sha256=OVMc5UfuAQiSplgO0_WdW7vXVGAt9Hdd6qtN4HotdyA 91
azureml_contrib_automl_dnn_forecasting-1.58.0.dist-info/top_level.txt sha256=33ea4iN8NQlStNGMXmaNrk2bFVU86zHWH3E-3usBfN0 27
azureml_contrib_automl_dnn_forecasting-1.58.0.dist-info/RECORD

top_level.txt

Deep4Cast
azureml
forecast