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deep-fine

0.1.0	deep_fine-0.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
	deep_fine-0.1.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
	deep_fine-0.1.0-cp39-cp39-macosx_10_9_x86_64.whl
	deep_fine-0.1.0-cp39-cp39-musllinux_1_1_x86_64.whl
	deep_fine-0.1.0-cp39-cp39-musllinux_1_1_i686.whl
	deep_fine-0.1.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
	deep_fine-0.1.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
	deep_fine-0.1.0-cp38-cp38-macosx_10_9_x86_64.whl
	deep_fine-0.1.0-cp38-cp38-musllinux_1_1_x86_64.whl
	deep_fine-0.1.0-cp38-cp38-musllinux_1_1_i686.whl
	deep_fine-0.1.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
	deep_fine-0.1.0-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
	deep_fine-0.1.0-cp37-cp37m-macosx_10_9_x86_64.whl
	deep_fine-0.1.0-cp37-cp37m-musllinux_1_1_x86_64.whl
	deep_fine-0.1.0-cp37-cp37m-musllinux_1_1_i686.whl
	deep_fine-0.1.0-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
	deep_fine-0.1.0-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
	deep_fine-0.1.0-cp36-cp36m-macosx_10_9_x86_64.whl
	deep_fine-0.1.0-cp36-cp36m-musllinux_1_1_x86_64.whl
	deep_fine-0.1.0-cp36-cp36m-musllinux_1_1_i686.whl
	deep_fine-0.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
	deep_fine-0.1.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
	deep_fine-0.1.0-cp310-cp310-macosx_10_9_x86_64.whl
	deep_fine-0.1.0-cp310-cp310-musllinux_1_1_x86_64.whl
	deep_fine-0.1.0-cp310-cp310-musllinux_1_1_i686.whl

Wheel Details

Project:	deep-fine
Version:	0.1.0
Filename:	deep_fine-0.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Download:	[link]
Size:	612796
MD5:	`24bb76fabb50698dd85ff04f89aefd3e`
SHA256:	`d66e1a8add0e31dd2dadd6cd712e7b992d3b29dbe5db7342f7fcddc3d3d4d943`
Uploaded:	2022-01-06 12:20:36 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version:	2.1
Name:	deep-fine
Version:	0.1.0
Summary:	an artificial neural network framework built from scratch using just Python and Numpy
Author:	Moussa Haidous
Author-Email:	haidous.m[at]gmail.com
Home-Page:	https://github.com/haidousm/fine
Requires-Dist:	numpy
Requires-Dist:	cython
Requires-Dist:	opencv-python
Requires-Dist:	requests
Requires-Dist:	tqdm

[No description]

WHEEL

Wheel-Version:	1.0
Generator:	bdist_wheel (0.37.0)
Root-Is-Purelib:	false
Tag:	cp39-cp39-manylinux_2_17_x86_64
Tag:	cp39-cp39-manylinux2014_x86_64

RECORD

Path	Digest	Size
fine/__init__.py	sha256=ihjJwQC215dSO0WX9eFi5vlcIVhQNGC-Vnd7kT_cuJc	175
fine/activations/__init__.py	sha256=RGtKybO-gEfM4boBLr_rbtPbv5BuYq4o7CD_1GNNVIk	108
fine/activations/Softmax.py	sha256=wN2bQvNic0U8zsoywi84oRK8ddh3kUpsudlMLAXKzX0	837
fine/activations/Linear.py	sha256=uUGJzVydQRe4XYyN3L0I61p3hEcu_ttYueFo5HicMcw	256
fine/activations/Sigmoid.py	sha256=_Tgt7ZKxiVDW5sw-_NjhTfqlKLq1r2laeAlyNWsr_iQ	337
fine/activations/ReLU.py	sha256=eH1vSh2g9jTPhocsnPNuTB21xY0AX6a3J_Fy3AwJ7Ao	333
fine/datasets/mnist_data.py	sha256=VffurU6G44E0LKK7vKF-F1M-sd7mkrdPdQZLelFOBjA	4051
fine/datasets/__init__.py	sha256=8qWeDKarU_8co-LXLrvkOVnueXG6OFAzlk6xFmmGLUU	117
fine/datasets/cifar_data.py	sha256=eYitNkihecJj-n2F69ToeobzsZLBOczHh8PsRZe9-yk	2465
fine/models/__init__.py	sha256=fg1hHwADq4NMhUo9p8qLQ6y49SJHJT6FzbhZPvNSNHc	35
fine/models/Sequential.py	sha256=9i3SgKZRQywMOcYGkHpmZaPyUdq5_4wGS3S9d8DJcdo	9860
fine/models/model_utils/Input.py	sha256=K3eSEPj7coPD9gPA692Lebzb5eTUmEgXRREpZSxz8-A	84
fine/models/model_utils/__init__.py	sha256=Dqo8BvGUYxVjTcdlaiu0w4L3VgpqP8MkHFAyp5P2WpA	115
fine/models/model_utils/accuracy/Accuracy.py	sha256=x5srri4uleFpotZVdZCXe0rTl-yI7zpNR2Np-lgz8us	521
fine/models/model_utils/accuracy/Regression.py	sha256=e44c-SUBEX0hzbCfoua2OYRa89crSczFXhtTzb01Wus	396
fine/models/model_utils/accuracy/__init__.py	sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU	0
fine/models/model_utils/accuracy/Categorical.py	sha256=SiTOrXVJgpgUw9iyuJYjSoJWZptQrDWU9k95w8YxoGg	380
fine/utils/im2col_cython.cpython-39-x86_64-linux-gnu.so	sha256=FE5D1DijyOYNIg3gkeRccIwLJl7lxL8CphL4xHearpA	2129680
fine/utils/__init__.py	sha256=lQTQfOo69x2YpVAmIs0Ibpq65suuKNfgOSo4MKkIAuk	29
fine/utils/augment_image.py	sha256=YKGbxi--6VopITfy1iTOB9By3Z1Z5x0p5G-9KlAdqOY	296
fine/utils/download_file.py	sha256=n8QotpRC6D05mLQKNsr25wcKfJwAzDoROLEoEg_042Q	471
fine/utils/im2col/im2col.py	sha256=r0utVUpOq2RckJwtWh-mXtdzqbCirtuLYcfRL-0174s	1908
fine/loss/BinaryCrossEntropy.py	sha256=jBNoErBoksHsnyt7aVUgFIv3uw315n0Vc3eTSMq-IhI	739
fine/loss/CategoricalCrossEntropy.py	sha256=c-imR58KUz6cYaETvfKDIkm3vnn6PPc8v_q0Jqun8ac	897
fine/loss/__init__.py	sha256=jB5LjkqmLJHC1Y-1aRYl9msSAF-r0bC6WPeSZpvBeiA	159
fine/loss/Loss.py	sha256=ch0cRFZhUC2bX6s-RTdi-EuNviVGH70P5MYA1mE2E4U	628
fine/loss/MeanSquaredError.py	sha256=te4o-dJKaMAyIBUCbTshMQjAJdj4alQogEcKumgCtI4	430
fine/optimizers/__init__.py	sha256=55KRPSYV_075Ko2I1GQUAVDi8oEQ1_NWg2zvtNoZwng	62
fine/optimizers/StochasticGD.py	sha256=fqjaDpANWragx3pqZJbD9BKnk-0f4gKUJfmG_82cjj0	1397
fine/optimizers/Adam.py	sha256=guxjIcdSELzFBGus8EHjPn48k9Alyfq2Fa4hATeHt-0	2168
fine/layers/Dense.py	sha256=-iT-jdW0RoCQxb0x7N51dhIW1CYENvLkrOuuOjzww2U	890
fine/layers/Dropout.py	sha256=PtoU2gRXcieoNNauP-7-R4O1UtIvj0C0kKEvgfJnlNs	475
fine/layers/__init__.py	sha256=Od_vUAV7RKz1pAmWXhW44N1nExV7gFCWQsHTsa4njEo	143
fine/layers/Conv2D.py	sha256=UuObRfvrrRFMy4kC4909ooOYYOZymWSWe5Qly2UJlXo	2200
fine/layers/Flatten.py	sha256=k0veiQ7CO52ugmMAZN4dY8wSUTp4PU3r2maseT10jD8	277
fine/layers/MaxPool2D.py	sha256=jyZn-gbuTXTdHmKahugaPnJBqkMF62nH7dppc5_HvFA	1331
deep_fine-0.1.0.dist-info/METADATA	sha256=LVICfDGzItvAgx-P8fxZMQ5Q-jAMQf8fXi0RyAQV4Gk	410
deep_fine-0.1.0.dist-info/WHEEL	sha256=ts1NGDem03kTrzsJp50lKy9cpDxDoGil0Q-wLa_TR_0	148
deep_fine-0.1.0.dist-info/RECORD	—	—
deep_fine-0.1.0.dist-info/top_level.txt	sha256=jsxflMV7BdbF4O4xa-5IdUJ-GEW77vPq1Z3ynHKqs24	5

top_level.txt

fine