repo_name stringlengths 8 75 | hexsha stringlengths 40 40 | code stringlengths 447 163k | apis list | file_path stringlengths 7 127 | api_extract stringlengths 346 104k |
|---|---|---|---|---|---|
Bertinus/IRM-games | e8a94e9647d1ea7211236bbd3f4ed16b1e8207b6 | import tensorflow as tf
import torch
import numpy as np
import matplotlib.pyplot as plt
from sklearn.utils import shuffle
from tqdm import tqdm_notebook as tqdm
tf.compat.v1.enable_eager_execution()
class AbstractIrmGame:
""" Abstract class for IRM games. """
def __init__(self, models, optimizers, extra_gra... | [
"matplotlib.pyplot.legend",
"tensorflow.zeros",
"torch.zeros",
"tensorflow.reduce_sum",
"tensorflow.compat.v1.enable_eager_execution",
"matplotlib.pyplot.plot",
"numpy.concatenate",
"numpy.mean",
"torch.no_grad",
"tensorflow.where",
"numpy.where",
"torch.nn.CrossEntropyLoss",
"torch.tensor",... | IRM_methods.py | [(8, 'tensorflow.compat.v1.enable_eager_execution', 'tf.compat.v1.enable_eager_execution', ([], {}), True, 'import tensorflow as tf\n'), (27, 'tensorflow.keras.losses.SparseCategoricalCrossentropy', 'tf.keras.losses.SparseCategoricalCrossentropy', ([], {'from_logits': '(True)'}), True, 'import tensorflow as tf\n'), (28... |
paulokuong/fourthbrain_capstone | db4f76bfc5fd7b1ecc355282f37a87a06f62aa47 | import pandas as pd
import numpy as np
import seaborn as sns
from datetime import datetime
import os
import time
from sklearn.inspection import permutation_importance
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeClassifier... | [
"pandas.Series",
"sklearn.ensemble.RandomForestClassifier",
"numpy.abs",
"sklearn.inspection.permutation_importance",
"sklearn.model_selection.train_test_split",
"pandas.DataFrame",
"numpy.full",
"tensorflow.keras.backend.clear_session",
"pandas.unique",
"pandas.read_json",
"tensorflow.optimizer... | presentation/groupby_user_conversion.py | [(50, 'numpy.full', 'np.full', (['(cor.shape[0],)', '(True)'], {'dtype': 'bool'}), True, 'import numpy as np\n'), (78, 'sklearn.ensemble.RandomForestClassifier', 'RandomForestClassifier', ([], {'random_state': 'random_state'}), False, 'from sklearn.ensemble import RandomForestClassifier\n'), (80, 'time.time', 'time.tim... |
fdibaldassarre/waifu2x-tensorflow | aa170c306d655047a7d6b13f588d13b6bdd28736 | #!/usr/bin/env python3
import json
import os
from PIL import Image
import numpy as np
import tensorflow as tf
from tensorflow.keras import Sequential
from tensorflow.keras import layers
from src.Places import MODELS_FOLDER
OP_SCALE = 'scale'
OP_NOISE = 'noise'
OP_NOISE_SCALE = 'noise_scale'
LEAKY_ALPHA = tf.const... | [
"tensorflow.multiply",
"numpy.maximum",
"tensorflow.constant",
"numpy.expand_dims",
"tensorflow.greater",
"numpy.asarray",
"tensorflow.keras.Sequential",
"numpy.round"
] | src/Waifu2x.py | [(19, 'tensorflow.constant', 'tf.constant', (['(0.1)'], {}), True, 'import tensorflow as tf\n'), (29, 'PIL.Image.fromarray', 'Image.fromarray', (['data'], {}), False, 'from PIL import Image\n'), (35, 'numpy.asarray', 'np.asarray', (["config['bias']"], {'dtype': 'np.float32'}), True, 'import numpy as np\n'), (62, 'PIL.I... |
dathudeptrai/rfcx-kaggle | e0d4705cd27c02142f3b2cac42083d6569a90863 | # Copyright 2015 The TensorFlow Authors. 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 applica... | [
"tensorflow.python.keras.applications.imagenet_utils.decode_predictions",
"tensorflow.python.keras.backend.image_data_format",
"tensorflow.python.keras.utils.data_utils.get_file",
"tensorflow.python.keras.layers.VersionAwareLayers",
"tensorflow.python.util.tf_export.keras_export",
"tensorflow.python.keras... | backbones/inceptionv3.py | [(42, 'tensorflow.python.keras.layers.VersionAwareLayers', 'VersionAwareLayers', ([], {}), False, 'from tensorflow.python.keras.layers import VersionAwareLayers\n'), (45, 'tensorflow.python.util.tf_export.keras_export', 'keras_export', (['"""keras.applications.inception_v3.InceptionV3"""', '"""keras.applications.Incept... |
Virinas-code/GobyChess | dc6129a4d5a5e061714714402d9cd472efc599f8 | #!/usr/bin/env python3
"""
Try to train evaluation in supervised fashion with engineered loss function
"""
import sys
import chess
import h5py
import numpy as np
import tensorflow as tf
from tensorflow.math import log, sigmoid, pow
model = tf.keras.Sequential([
tf.keras.layers.Dense(100, activation=tf.nn.relu, i... | [
"numpy.reshape",
"tensorflow.keras.layers.Dense",
"tensorflow.cast",
"tensorflow.reshape",
"tensorflow.math.sigmoid",
"tensorflow.GradientTape",
"tensorflow.math.pow",
"tensorflow.keras.metrics.Mean",
"tensorflow.keras.optimizers.SGD"
] | gobychess/train.py | [(24, 'h5py.File', 'h5py.File', (['"""data/data.h5"""', '"""r"""'], {}), False, 'import h5py\n'), (27, 'h5py.File', 'h5py.File', (['"""data/meta.h5"""', '"""r"""'], {}), False, 'import h5py\n'), (30, 'h5py.File', 'h5py.File', (['"""data/test_data.h5"""', '"""r"""'], {}), False, 'import h5py\n'), (33, 'h5py.File', 'h5py... |
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