Pierrick Bruneau pbruneau
pbruneau
/ tensorflow2_keras_mnist_runner.py
Last active
November 26, 2020 08:50
Adaptation of tensorflow2_keras_mnist in order to train an ensemble with repeated horovod.run() calls
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| # Copyright 2019 Uber Technologies, Inc. All Rights Reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, |
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| # Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"). | |
| # You may not use this file except in compliance with the License. | |
| # A copy of the License is located at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # or in the "license" file accompanying this file. This file is distributed | |
| # on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either |
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| import numpy as np | |
| import pandas as pd | |
| # uncomment to deactivate progress bar | |
| #from gluonts.env import env | |
| #env._push(use_tqdm=False) | |
| from gluonts.dataset.common import ListDataset | |
| from gluonts.dataset.field_names import FieldName | |
| from gluonts.model.deepar import DeepAREstimator |
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| from datetime import datetime | |
| import pandas as pd | |
| import cudf | |
| import numpy as np | |
| start = pd.Timestamp(datetime.strptime('2021-03-12 00:00+0000', '%Y-%m-%d %H:%M%z')) | |
| end = pd.Timestamp(datetime.strptime('2021-03-12 11:00+0000', '%Y-%m-%d %H:%M%z')) | |
| timestamps = pd.date_range(start, end, freq='1H') | |
| value = np.random.normal(size=12) | |
| df = pd.DataFrame(value, index=timestamps, columns=['value']) |
pbruneau
/ keras_pipeline_trial.py
Created
September 8, 2021 08:21
Trial of a DALIDataset with external input for Keras
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| import glob | |
| import numpy as np | |
| import cupy as cp | |
| import imageio | |
| from random import shuffle | |
| from nvidia.dali import Pipeline | |
| import nvidia.dali.fn as fn | |
| import nvidia.dali.plugin.tf as dali_tf | |
| import tensorflow as tf |
pbruneau
/ keras_pipeline_trial_fixed.py
Created
September 8, 2021 12:48
Trial of a DALIDataset with external input for Keras
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| import glob | |
| import numpy as np | |
| import cupy as cp | |
| import imageio | |
| from random import shuffle | |
| from nvidia.dali import Pipeline | |
| import nvidia.dali.fn as fn | |
| import nvidia.dali.plugin.tf as dali_tf | |
| import tensorflow as tf |
pbruneau
/ keras_pipeline_trial_withlabels.py
Created
September 8, 2021 15:55
Trial of a DALIDataset with external input for Keras
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| import glob | |
| import numpy as np | |
| import cupy as cp | |
| import imageio | |
| from random import shuffle | |
| from nvidia.dali import Pipeline | |
| import nvidia.dali.fn as fn | |
| import nvidia.dali.plugin.tf as dali_tf | |
| import tensorflow as tf |
pbruneau
/ create_predictor_error.py
Created
September 22, 2021 14:34
Code triggering Estimator.create_predictor error
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| from gluonts.dataset.repository.datasets import get_dataset | |
| from gluonts.model.simple_feedforward import SimpleFeedForwardEstimator | |
| from gluonts.model.deepar import DeepAREstimator | |
| from gluonts.mx.distribution.gaussian import GaussianOutput | |
| from gluonts.mx import Trainer | |
| from gluonts.mx.trainer.callback import TrainingHistory | |
| from gluonts.evaluation import Evaluator | |
| from gluonts.dataset.common import Dataset | |
| from gluonts.mx import copy_parameters | |
| from gluonts.model.predictor import Predictor |
pbruneau
/ code_predictor_fixed.py
Created
September 23, 2021 10:34
Fixing Estimator.create_predictor error
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| from gluonts.dataset.repository.datasets import get_dataset | |
| from gluonts.model.simple_feedforward import SimpleFeedForwardEstimator | |
| from gluonts.model.deepar import DeepAREstimator | |
| from gluonts.mx.distribution.gaussian import GaussianOutput | |
| from gluonts.mx import Trainer | |
| from gluonts.mx.trainer.callback import TrainingHistory | |
| from gluonts.evaluation import Evaluator | |
| from gluonts.dataset.common import Dataset | |
| from gluonts.mx import copy_parameters | |
| from gluonts.model.predictor import Predictor |
pbruneau
/ cudf_multiindex_updated.py
Last active
November 2, 2021 13:49
cudf with pandas MultiIndex
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| from datetime import datetime | |
| import pandas as pd | |
| import cudf | |
| import numpy as np | |
| start = pd.Timestamp(datetime.strptime('2021-03-12 00:00+0000', '%Y-%m-%d %H:%M%z')) | |
| end = pd.Timestamp(datetime.strptime('2021-03-12 11:00+0000', '%Y-%m-%d %H:%M%z')) | |
| timestamps = pd.date_range(start, end, freq='1H') | |
| value = np.random.normal(size=12) | |
| df = pd.DataFrame(value, index=timestamps, columns=['value']) |
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