Minor Unix file formatting fixes (#90)

Signed-off-by: Abolfazl Shahbazi <abolfazl.shahbazi@intel.com>
intel · Aug 19, 2021 · 9ece6ea · 9ece6ea
1 parent 84e046e
commit 9ece6ea
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diff --git a/dockerfiles/ml/scikit-learn/rcv1_svm/Dockerfile b/dockerfiles/ml/scikit-learn/rcv1_svm/Dockerfile
@@ -1,59 +1,59 @@
-# Copyright (c) 2020 Intel Corporation
-#
-# 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,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ============================================================================
-#
-# THIS IS A GENERATED DOCKERFILE.
-#
-# This file was assembled from multiple pieces, whose use is documented
-# throughout. Please refer to the TensorFlow dockerfiles documentation
-# for more information.
-
-FROM ubuntu:18.04
-
-RUN apt-get update --yes \
-    && apt-get install wget --yes && \
-    rm -rf /var/lib/apt/lists/*
-
-ENV USE_DAAL4PY_SKLEARN=YES
-ENV USER modin
-ENV UID 1000
-ENV HOME /home/$USER
-
-RUN adduser --disabled-password \
-    --gecos "Non-root user" \
-    --uid $UID \
-    --home $HOME \
-    $USER
-
-ENV CONDA_DIR ${HOME}/miniconda
-
-SHELL ["/bin/bash", "--login", "-c"]
-
-RUN wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda3.sh && \
-    bash /tmp/miniconda3.sh -b -p "${CONDA_DIR}" -f -u && \
-    "${CONDA_DIR}/bin/conda" init bash && \
-    rm -f /tmp/miniconda3.sh && \
-    echo ". '${CONDA_DIR}/etc/profile.d/conda.sh'" >> "${HOME}/.profile"
-
-RUN conda update -n base -c defaults conda -y && \
-    conda create --name intel_sklearn --yes -c intel python=3.7 scikit-learn
-
-COPY rcv1_svm.py "${HOME}/rcv1_svm.py"
-COPY rcv1_loader.py "${HOME}/rcv1_loader.py"
-
-RUN conda activate intel_sklearn && python ${HOME}/rcv1_loader.py
-
-ENTRYPOINT ["/bin/bash", "--login", "-c", "conda run \"$@\"", "/bin/bash", "-n", "intel_sklearn", "/usr/bin/env", "--"]
-
-CMD ["python", "${HOME}/rcv1_svm.py"]
+# Copyright (c) 2020 Intel Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+#
+# THIS IS A GENERATED DOCKERFILE.
+#
+# This file was assembled from multiple pieces, whose use is documented
+# throughout. Please refer to the TensorFlow dockerfiles documentation
+# for more information.
+
+FROM ubuntu:18.04
+
+RUN apt-get update --yes \
+    && apt-get install wget --yes && \
+    rm -rf /var/lib/apt/lists/*
+
+ENV USE_DAAL4PY_SKLEARN=YES
+ENV USER modin
+ENV UID 1000
+ENV HOME /home/$USER
+
+RUN adduser --disabled-password \
+    --gecos "Non-root user" \
+    --uid $UID \
+    --home $HOME \
+    $USER
+
+ENV CONDA_DIR ${HOME}/miniconda
+
+SHELL ["/bin/bash", "--login", "-c"]
+
+RUN wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda3.sh && \
+    bash /tmp/miniconda3.sh -b -p "${CONDA_DIR}" -f -u && \
+    "${CONDA_DIR}/bin/conda" init bash && \
+    rm -f /tmp/miniconda3.sh && \
+    echo ". '${CONDA_DIR}/etc/profile.d/conda.sh'" >> "${HOME}/.profile"
+
+RUN conda update -n base -c defaults conda -y && \
+    conda create --name intel_sklearn --yes -c intel python=3.7 scikit-learn
+
+COPY rcv1_svm.py "${HOME}/rcv1_svm.py"
+COPY rcv1_loader.py "${HOME}/rcv1_loader.py"
+
+RUN conda activate intel_sklearn && python ${HOME}/rcv1_loader.py
+
+ENTRYPOINT ["/bin/bash", "--login", "-c", "conda run \"$@\"", "/bin/bash", "-n", "intel_sklearn", "/usr/bin/env", "--"]
+
+CMD ["python", "${HOME}/rcv1_svm.py"]
diff --git a/dockerfiles/ml/scikit-learn/rcv1_svm/rcv1_loader.py b/dockerfiles/ml/scikit-learn/rcv1_svm/rcv1_loader.py
@@ -1,23 +1,23 @@
-# Copyright (c) 2020 Intel Corporation
-#
-# 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,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ============================================================================
-#
-# THIS IS A GENERATED DOCKERFILE.
-#
-# This file was assembled from multiple pieces, whose use is documented
-# throughout. Please refer to the TensorFlow dockerfiles documentation
-# for more information.
-
-from sklearn.datasets import fetch_rcv1
-rcv1 = fetch_rcv1()
+# Copyright (c) 2020 Intel Corporation
+#
+# 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,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+#
+# THIS IS A GENERATED DOCKERFILE.
+#
+# This file was assembled from multiple pieces, whose use is documented
+# throughout. Please refer to the TensorFlow dockerfiles documentation
+# for more information.
+
+from sklearn.datasets import fetch_rcv1
+rcv1 = fetch_rcv1()
diff --git a/dockerfiles/ml/scikit-learn/rcv1_svm/rcv1_svm.py b/dockerfiles/ml/scikit-learn/rcv1_svm/rcv1_svm.py
@@ -1,86 +1,86 @@
-# Copyright (c) 2020 Intel Corporation
-#
-# 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,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ============================================================================
-#
-# THIS IS A GENERATED DOCKERFILE.
-#
-# This file was assembled from multiple pieces, whose use is documented
-# throughout. Please refer to the TensorFlow dockerfiles documentation
-# for more information.
-
-from sklearn.metrics import accuracy_score, f1_score
-from sklearn.multiclass import OneVsRestClassifier
-from sklearn.model_selection import train_test_split
-from sklearn.datasets import fetch_rcv1
-import timeit
-import os
-
-t0 = timeit.default_timer()
-
-rcv1 = fetch_rcv1()
-
-rcv1_data = rcv1.data
-rcv1_target = rcv1.target
-
-t1 = timeit.default_timer()
-time_load = t1 - t0
-
-t0 = timeit.default_timer()
-
-x_train, x_test, y_train, y_test = train_test_split(
-    rcv1_data, rcv1_target, test_size=0.05, random_state=42)
-
-from daal4py.sklearn import patch_sklearn
-patch_sklearn()
-
-from sklearn.svm import SVC
-
-t1 = timeit.default_timer()
-time_train_test_split = t1 - t0
-
-print('[Data] train: {} test: {}'.format(x_train.shape, x_test.shape))
-print('[Target] train: {} test: {}'.format(y_train.shape, y_test.shape))
-
-
-print('[Time] Load time {} sec'.format(time_load))
-print('[Time] train_test_split time {} sec'.format(time_train_test_split))
-
-t0 = timeit.default_timer()
-
-clf = SVC(C=100.0, kernel='rbf', cache_size=8*1024)
-svm = OneVsRestClassifier(clf, n_jobs=4)
-svm.fit(x_train, y_train)
-
-t1 = timeit.default_timer()
-time_fit_train_run = t1 - t0
-
-print('[Time] Fit time {} sec'.format(time_fit_train_run))
-
-t0 = timeit.default_timer()
-svm_prediction = svm.predict(x_test)
-t1 = timeit.default_timer()
-time_predict_test_run = t1 - t0
-
-print('[Time] Predict time {} sec'.format(time_predict_test_run))
-
-t0 = timeit.default_timer()
-print('Accuracy score is {}'.format(accuracy_score(y_test, svm_prediction)))
-print('F1 samples score is {}'.format(
-    f1_score(y_test, svm_prediction, average='samples')))
-print('F1 micro score is {}'.format(
-    f1_score(y_test, svm_prediction, average='micro')))
-t1 = timeit.default_timer()
-time_metric_run = t1 - t0
-
-print('[Time] Metric time {} sec'.format(time_metric_run))
+# Copyright (c) 2020 Intel Corporation
+#
+# 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,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+#
+# THIS IS A GENERATED DOCKERFILE.
+#
+# This file was assembled from multiple pieces, whose use is documented
+# throughout. Please refer to the TensorFlow dockerfiles documentation
+# for more information.
+
+from sklearn.metrics import accuracy_score, f1_score
+from sklearn.multiclass import OneVsRestClassifier
+from sklearn.model_selection import train_test_split
+from sklearn.datasets import fetch_rcv1
+import timeit
+import os
+
+t0 = timeit.default_timer()
+
+rcv1 = fetch_rcv1()
+
+rcv1_data = rcv1.data
+rcv1_target = rcv1.target
+
+t1 = timeit.default_timer()
+time_load = t1 - t0
+
+t0 = timeit.default_timer()
+
+x_train, x_test, y_train, y_test = train_test_split(
+    rcv1_data, rcv1_target, test_size=0.05, random_state=42)
+
+from daal4py.sklearn import patch_sklearn
+patch_sklearn()
+
+from sklearn.svm import SVC
+
+t1 = timeit.default_timer()
+time_train_test_split = t1 - t0
+
+print('[Data] train: {} test: {}'.format(x_train.shape, x_test.shape))
+print('[Target] train: {} test: {}'.format(y_train.shape, y_test.shape))
+
+
+print('[Time] Load time {} sec'.format(time_load))
+print('[Time] train_test_split time {} sec'.format(time_train_test_split))
+
+t0 = timeit.default_timer()
+
+clf = SVC(C=100.0, kernel='rbf', cache_size=8*1024)
+svm = OneVsRestClassifier(clf, n_jobs=4)
+svm.fit(x_train, y_train)
+
+t1 = timeit.default_timer()
+time_fit_train_run = t1 - t0
+
+print('[Time] Fit time {} sec'.format(time_fit_train_run))
+
+t0 = timeit.default_timer()
+svm_prediction = svm.predict(x_test)
+t1 = timeit.default_timer()
+time_predict_test_run = t1 - t0
+
+print('[Time] Predict time {} sec'.format(time_predict_test_run))
+
+t0 = timeit.default_timer()
+print('Accuracy score is {}'.format(accuracy_score(y_test, svm_prediction)))
+print('F1 samples score is {}'.format(
+    f1_score(y_test, svm_prediction, average='samples')))
+print('F1 micro score is {}'.format(
+    f1_score(y_test, svm_prediction, average='micro')))
+t1 = timeit.default_timer()
+time_metric_run = t1 - t0
+
+print('[Time] Metric time {} sec'.format(time_metric_run))