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sudo pip install --upgrade pip sudo pip install -e ".[tests]" echo "sh shell/lint.sh" > .git/hooks/pre-commit chmod a+x .git/hooks/pre-commit
autokeras/.devcontainer/setup.sh/0
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# Copyright 2020 The AutoKeras Authors. # # 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 i...
autokeras/autokeras/blocks/wrapper.py/0
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# Copyright 2020 The AutoKeras Authors. # # 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 i...
autokeras/autokeras/engine/preprocessor.py/0
{ "file_path": "autokeras/autokeras/engine/preprocessor.py", "repo_id": "autokeras", "token_count": 649 }
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# Copyright 2020 The AutoKeras Authors. # # 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 i...
autokeras/autokeras/pipeline.py/0
{ "file_path": "autokeras/autokeras/pipeline.py", "repo_id": "autokeras", "token_count": 3266 }
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# Copyright 2020 The AutoKeras Authors. # # 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 i...
autokeras/autokeras/tuners/greedy.py/0
{ "file_path": "autokeras/autokeras/tuners/greedy.py", "repo_id": "autokeras", "token_count": 3643 }
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# Copyright 2020 The AutoKeras Authors. # # 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 i...
autokeras/autokeras/utils/utils.py/0
{ "file_path": "autokeras/autokeras/utils/utils.py", "repo_id": "autokeras", "token_count": 2354 }
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FROM python:3.7 RUN pip install flake8 black isort WORKDIR /autokeras CMD ["python", "docker/pre_commit.py"]
autokeras/docker/pre-commit.Dockerfile/0
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import pathlib import shutil from inspect import getdoc from inspect import isclass from typing import Dict from typing import List from typing import Union from typing import get_type_hints from . import utils from .docstring import process_docstring from .examples import copy_examples from .get_signatures import get...
autokeras/docs/keras_autodoc/autogen.py/0
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"""shell pip install autokeras """ import os import numpy as np import tensorflow as tf from sklearn.datasets import load_files import autokeras as ak """ To make this tutorial easy to follow, we just treat IMDB dataset as a regression dataset. It means we will treat prediction targets of IMDB dataset, which are 0s ...
autokeras/docs/py/text_regression.py/0
{ "file_path": "autokeras/docs/py/text_regression.py", "repo_id": "autokeras", "token_count": 1992 }
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:root>* { --md-primary-fg-color: #d00000; --md-accent-fg-color: #d00000; }
autokeras/docs/templates/stylesheets/extra.css/0
{ "file_path": "autokeras/docs/templates/stylesheets/extra.css", "repo_id": "autokeras", "token_count": 38 }
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from distutils.core import setup from pathlib import Path from setuptools import find_packages this_file = Path(__file__).resolve() readme = this_file.parent / "README.md" setup( name="autokeras", description="AutoML for deep learning", package_data={"": ["README.md"]}, long_description=readme.read_t...
autokeras/setup.py/0
{ "file_path": "autokeras/setup.py", "repo_id": "autokeras", "token_count": 771 }
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# keras-cv Single Stage Two-Dimensional Object Detection API | Status | Proposed | :-------------- |:---------------------------------------------------- | | **Author(s)** | Zhenyu Tan (tanzheny@google.com), Francois Chollet (fchollet@google.com)| | **Contributor(s)** | Pengchong Jin (pengchong@google.com)...
governance/rfcs/20200928-keras-cv-single-stage-2d-object-detection.md/0
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sudo: required dist: trusty language: python matrix: include: - python: 2.7 env: KERAS_BACKEND=tensorflow TEST_MODE=PEP8 - python: 2.7 env: KERAS_BACKEND=tensorflow - python: 2.7 env: KERAS_BACKEND=tensorflow KERAS_HEAD=true - python: 3.6 env: ...
keras-applications/.travis.yml/0
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"""ResNet models for Keras. # Reference paper - [Deep Residual Learning for Image Recognition] (https://arxiv.org/abs/1512.03385) (CVPR 2016 Best Paper Award) # Reference implementations - [TensorNets] (https://github.com/taehoonlee/tensornets/blob/master/tensornets/resnets.py) - [Caffe ResNet] (https://githu...
keras-applications/keras_applications/resnet.py/0
{ "file_path": "keras-applications/keras_applications/resnet.py", "repo_id": "keras-applications", "token_count": 363 }
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# keras-contrib : Keras community contributions Keras-contrib is deprecated. Use [TensorFlow Addons](https://github.com/tensorflow/addons). ## The future of Keras-contrib: We're migrating to [tensorflow/addons](https://github.com/tensorflow/addons). See the announcement [here](https://github.com/keras-team/keras-con...
keras-contrib/README.md/0
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{%- for toc_item in toc_item.children %} <li class="toctree-l{{ navlevel}}"><a class="reference internal" href="{% if not nav_item == page %}{{ nav_item.url|url }}{% endif %}{{ toc_item.url }}">{{ toc_item.title }}</a> {%- set navlevel = navlevel + 1 %} {%- if navlevel <= config.theme.navigation_depth and ...
keras-contrib/contrib_docs/theme/toc.html/0
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from .densenet import DenseNet from .resnet import ResNet, ResNet18, ResNet34, ResNet50, ResNet101, ResNet152 from .wide_resnet import WideResidualNetwork from .nasnet import NASNet, NASNetLarge, NASNetMobile
keras-contrib/keras_contrib/applications/__init__.py/0
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from __future__ import absolute_import from keras import backend as K from keras.constraints import Constraint class Clip(Constraint): """Clips weights to [-c, c]. # Arguments c: Clipping parameter. """ def __init__(self, c=0.01): self.c = c def __call__(self, p): return...
keras-contrib/keras_contrib/constraints/clip.py/0
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# -*- coding: utf-8 -*- from __future__ import absolute_import from keras.layers import Layer from keras_contrib import backend as KC from keras_contrib.utils.conv_utils import normalize_data_format class SubPixelUpscaling(Layer): """ Sub-pixel convolutional upscaling layer. This layer requires a Convoluti...
keras-contrib/keras_contrib/layers/convolutional/subpixelupscaling.py/0
{ "file_path": "keras-contrib/keras_contrib/layers/convolutional/subpixelupscaling.py", "repo_id": "keras-contrib", "token_count": 1456 }
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from keras import backend as K from keras.optimizers import Optimizer class Yogi(Optimizer): """Yogi optimizer. Yogi is a variation of Adam that controls the increase in effective learning rate, which (according to the paper) leads to even better performance than Adam with similar theoretical guarante...
keras-contrib/keras_contrib/optimizers/yogi.py/0
{ "file_path": "keras-contrib/keras_contrib/optimizers/yogi.py", "repo_id": "keras-contrib", "token_count": 1858 }
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import numpy as np import pytest from keras import backend as K from keras.layers import Input from keras.models import Sequential, Model from numpy.testing import assert_allclose from keras_contrib.layers import InstanceNormalization from keras_contrib.utils.test_utils import layer_test input_1 = np.arange(10) input...
keras-contrib/tests/keras_contrib/layers/normalization/test_instancenormalization.py/0
{ "file_path": "keras-contrib/tests/keras_contrib/layers/normalization/test_instancenormalization.py", "repo_id": "keras-contrib", "token_count": 3078 }
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from markdown import markdown from docs import autogen import pytest test_doc1 = { 'doc': """Base class for recurrent layers. # Arguments cell: A RNN cell instance. A RNN cell is a class that has: - a `call(input_at_t, states_at_t)` method, returning `(output_at_t, states_a...
keras-contrib/tests/tooling/test_doc_auto_generation.py/0
{ "file_path": "keras-contrib/tests/tooling/test_doc_auto_generation.py", "repo_id": "keras-contrib", "token_count": 5533 }
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# Keras Core is becoming Keras 3 and has moved to keras-team/keras Multi-backend Keras has a new repo: [keras-team/keras](https://github.com/keras-team/keras). Open any issues / PRs there. `keras-team/keras-core` is no longer in use. **Keras Core** was the codename of the multi-backend Keras project throughout its in...
keras-core/README.md/0
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import time import keras_core class BenchmarkMetricsCallback(keras_core.callbacks.Callback): def __init__(self, start_batch=1, stop_batch=None): self.start_batch = start_batch self.stop_batch = stop_batch # Store the throughput of each epoch. self.state = {"throughput": []} ...
keras-core/benchmarks/model_benchmark/benchmark_utils.py/0
{ "file_path": "keras-core/benchmarks/model_benchmark/benchmark_utils.py", "repo_id": "keras-core", "token_count": 348 }
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import numpy as np import keras_core from keras_core import layers from keras_core.utils import to_categorical # Model / data parameters num_classes = 10 input_shape = (28, 28, 1) # Load the data and split it between train and test sets (x_train, y_train), (x_test, y_test) = keras_core.datasets.mnist.load_data() # S...
keras-core/examples/demo_mnist_convnet.py/0
{ "file_path": "keras-core/examples/demo_mnist_convnet.py", "repo_id": "keras-core", "token_count": 645 }
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""" Title: English speaker accent recognition using Transfer Learning Author: [Fadi Badine](https://twitter.com/fadibadine) Converted to Keras Core by: [Fadi Badine](https://twitter.com/fadibadine) Date created: 2022/04/16 Last modified: 2023/07/19 Description: Training a model to classify UK & Ireland accents using fe...
keras-core/examples/keras_io/tensorflow/audio/uk_ireland_accent_recognition.py/0
{ "file_path": "keras-core/examples/keras_io/tensorflow/audio/uk_ireland_accent_recognition.py", "repo_id": "keras-core", "token_count": 7353 }
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""" Title: End-to-end Masked Language Modeling with BERT Author: [Ankur Singh](https://twitter.com/ankur310794) Converted to Keras-Core: [Mrutyunjay Biswal](https://twitter.com/LearnStochastic) Date created: 2020/09/18 Last modified: 2023/09/06 Description: Implement a Masked Language Model (MLM) with BERT and fine-tun...
keras-core/examples/keras_io/tensorflow/nlp/end_to_end_mlm_with_bert.py/0
{ "file_path": "keras-core/examples/keras_io/tensorflow/nlp/end_to_end_mlm_with_bert.py", "repo_id": "keras-core", "token_count": 6779 }
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""" Title: Zero-DCE for low-light image enhancement Author: [Soumik Rakshit](http://github.com/soumik12345) Converted to Keras Core by: [Soumik Rakshit](http://github.com/soumik12345) Date created: 2021/09/18 Last modified: 2023/07/15 Description: Implementing Zero-Reference Deep Curve Estimation for low-light image en...
keras-core/examples/keras_io/tensorflow/vision/zero_dce.py/0
{ "file_path": "keras-core/examples/keras_io/tensorflow/vision/zero_dce.py", "repo_id": "keras-core", "token_count": 7947 }
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