pydtnn/__init__.py,sha256=20AobAzij0H1ipooLFLFUdEyukKG5d9zyfZMn7ccuyU,5150
pydtnn/__main__.py,sha256=lRcVCXmjv2vKaWIyii8WMhyRHJ8BNeYr_bXr_LU5eyA,5048
pydtnn/logger.yaml,sha256=3wnO-QCQ5ozMEELKbCpwqTsRPiYVoOyNitBqabQ_1TQ,423
pydtnn/abstract/base.py,sha256=k7gnYII-K-CqnrfcVcqc6xA5-fNDGeJHtns6zOQRox0,7422
pydtnn/abstract/layerable.py,sha256=GnHGmkk5hD056ajVBkmdo-Vahm90AyL1RSwglufNOMo,15911
pydtnn/activations/__init__.py,sha256=_AzDrbdBcSk3vyDKwL_fuEcIBNOIIsJDizzkNLLQz4w,632
pydtnn/activations/arctanh.py,sha256=XeY8QhpERbAxqUkN7yujBGoZ7kSK9Wy8-fA3wZWeP9o,437
pydtnn/activations/leaky_relu.py,sha256=2gvYPqrWA2Lzv4JPpRZOt9nv24gcgoM91hIsgAfY1Iw,716
pydtnn/activations/log.py,sha256=Mixexf6Mwq2460Kz16r3fUazLi6r4_PTy_nrLr1u-EM,351
pydtnn/activations/log_sigmoid.py,sha256=4bG2NnxISc_WWbVZKdEyGp35K5s-vYaA0hB2fRWBUuc,365
pydtnn/activations/log_softmax.py,sha256=bpA5RI_v-zK5OikgLnGTgZk8NnJaJvRd5cdLE1EGoEA,424
pydtnn/activations/relu.py,sha256=miL7NsM1CVTCJnI_0RA8EkHd2jGJYNrhhLqw8s8N8Vs,727
pydtnn/activations/relu6.py,sha256=d81Xyjgu8Slh79Ad9XIFvDFEJwlT-URPbKmmXY5n7GA,932
pydtnn/activations/sigmoid.py,sha256=l77khl9TdQCFz-OvZFoa492RHC0XxiSvsf6uH-bffUM,400
pydtnn/activations/softmax.py,sha256=xzJOwXjTNSzdFfMHDujpqhfeBk1MmEpWUVG6USIgpls,757
pydtnn/activations/tanh.py,sha256=3bjiSbvr7oq55VbycHNLi4rKvHbJZXLfzSn7uCG-FSE,356
pydtnn/activations/abstract/activation.py,sha256=ep8FdYkA4GKfZD4G9IPE6O8eXLFgyQWjGbSXZ9pto2Q,1063
pydtnn/backends/cupy/abstract/base.py,sha256=iPyvd1uKcNBKFTZwcgeS8Thb4mMjGKIqGIS8dtmULxw,1111
pydtnn/backends/cupy/abstract/layerable.py,sha256=CbREX4cMKsRWmih-df4EI6XUlFjfGBwtMF1_iQQbrTw,358
pydtnn/backends/cupy/activations/leaky_relu.py,sha256=R5A6nA7xrDjCCqLXzJ_5-DHnbMp9C2bgOHMA_L3ehTY,1580
pydtnn/backends/cupy/activations/relu.py,sha256=P8XiTGUw03MCdLMu71YtM8P3bLqvhxZbJBw155Qca4Y,1449
pydtnn/backends/cupy/activations/relu6.py,sha256=ANXal_q8y4GOwL8L9M2OQqiKLAjV67mxCM8r6dmeXno,1459
pydtnn/backends/cupy/activations/abstract/activation.py,sha256=7-jYntFKr9XX_BFbzBL3h-DJhrjOdVV3EL_HBcNlBWE,1287
pydtnn/backends/cupy/layers/adaptive_average_pool_2d.py,sha256=RRN9Y6nnNtJKmX3fbrwJhC119pqZETOTMDHugI2-9Go,2619
pydtnn/backends/cupy/layers/average_pool_2d.py,sha256=WbYZqTMzoE0NEsHGIGZCk764IzfV3-VC-GidOGnyhMs,3955
pydtnn/backends/cupy/layers/batch_normalization.py,sha256=DG-jaF3oUPT2PjHzuZ5ddPUyDPqH3VzrgvOPxIdOPwQ,2039
pydtnn/backends/cupy/layers/conv_2d.py,sha256=yxnQiBW_fHRvEHjRnxvn7exKQeNsNzpP8HdZWPqYN7Q,508
pydtnn/backends/cupy/layers/conv_2d_depthwise.py,sha256=m-yOjyoVRlaGMxedNXRvmEMvVYvKoupCGvupFwCMQt8,4076
pydtnn/backends/cupy/layers/fc.py,sha256=nzK4JPoUZdkz3ZfDv4egBS2GJHrvFBpds84nTM_KGeM,889
pydtnn/backends/cupy/layers/max_pool_2d.py,sha256=M6RdM7Sc46jG2RauF_pwN4bvyAE4exE156_8qoorNCI,3945
pydtnn/backends/cupy/layers/abstract/conv_2d.py,sha256=vXrSBUYRvcUfuLMqFJ1m3pIstxClZ5x1ES-_4H13ZeY,4910
pydtnn/backends/cupy/layers/abstract/layer.py,sha256=_oJgF_AqqAqGybA25rHeryK-w8CIotqPzWUmGFgfUPU,377
pydtnn/backends/cupy/layers/abstract/pool_2d_layer.py,sha256=twuuxtipHWZhEGhTGllvNwRm3erIfOb98ZywiaoKz3c,545
pydtnn/backends/cupy/metrics/binary_confusion_matrix.py,sha256=qjDhI1vPEu7X6IKnm6J-zKsd1_wN-Y9tmbqY01bxrcA,896
pydtnn/backends/cupy/metrics/f1_score.py,sha256=yQiIX_ACHBc7CB0iEYZjv4vh2NRoXEoNdw9hcXSE17Q,1860
pydtnn/backends/cupy/metrics/multiclass_confusion_matrix.py,sha256=4f382Odt6h3IrgP0XYEY6-ywJWm5CdVWoeThT-5jXI4,925
pydtnn/backends/cupy/metrics/precision.py,sha256=YW-_hqRZ2aG2_FFJONsQ1xgWrfOcFvDubko2KTJY2R8,2177
pydtnn/backends/cupy/metrics/recall.py,sha256=loSyNz-qs47clB-mbq1fz5e18yNksxlQ9YqPAUS2vSA,2094
pydtnn/backends/cupy/metrics/abstract/metric.py,sha256=v8NmZN5gNtcz2De25jBCFOSjDeMhCLwFoxMRO0OnLd4,341
pydtnn/backends/cupy/utils/adaptive_average_pool_2d.cu,sha256=YmTI7TeLricFoziFmNxTUYQSM3nwaGlT-VsAeVdgoJM,5346
pydtnn/backends/cupy/utils/average_pool_2d.cu,sha256=6BxVgYyXeppF64tt4Jl-2Vyt73OKwHENFcGBx06aQaA,6365
pydtnn/backends/cupy/utils/batch_normalization.cu,sha256=67eI3KgTWj_LksQgn_mg6FvK7z5ioT_ZgYeGTD1XCV4,3844
pydtnn/backends/cupy/utils/conv_2d.cu,sha256=MRYZCQYICJ_3J11LEIO_uNfvVwyhGP7hWWUEgA9601s,7348
pydtnn/backends/cupy/utils/conv_2d_depthwise.cu,sha256=dZE255Avlp9LZZ1nVLduNSVSKdd7V0X5s-mTGT6YE_4,6683
pydtnn/backends/cupy/utils/leaky_relu.cu,sha256=RI2qHAhAAOsypjWpS7jYXlXbk5xMJ9D1SiRNN9R8HPs,2113
pydtnn/backends/cupy/utils/max_pool_2d.cu,sha256=KxLCe0Eq9pqt3PDAE2O6WWO0YENVj88AhMQlv4fqfEo,5537
pydtnn/backends/cupy/utils/relu.cu,sha256=5plOSmcbNaaS9GbTRRXGDWnPDbBCUJsCwrkHtm3L_kM,1947
pydtnn/backends/cupy/utils/relu6.cu,sha256=Can0z7XPXo6KpRYmn8XVF1b3kbnnp24Tlnom-mAyW18,2052
pydtnn/backends/cython/abstract/base.py,sha256=OMARIDkS3Kp0Agz3NHPrNUo1uJEEyw8R4TDlGQBs6yc,244
pydtnn/backends/cython/abstract/layerable.py,sha256=Tt3SyoT-eWMfhgLR2TWyUElX4nW-Ug_x7cFdMaq7Zgk,431
pydtnn/backends/cython/activations/leaky_relu.py,sha256=qitBP4NtEJo1VV5tC0Yq-T3A9HHPVjHTJCtqQcdbOmU,1138
pydtnn/backends/cython/activations/log.py,sha256=AhZPmSCpbdKh4g8e1sVgx_-n_JcFZTn66ytPjy_nsXY,1474
pydtnn/backends/cython/activations/log_sigmoid.py,sha256=09QxLPhONWqb-wPT1g_XzrtWXFpnokt1Lc4R-KfeQ1A,1624
pydtnn/backends/cython/activations/relu.py,sha256=2bD3WdzutZZbotMAcThKaTqqlDixFhfc4Y9PzxgJGTE,1100
pydtnn/backends/cython/activations/relu6.py,sha256=tLZ7cRWXZbSJr6rUgySLJPUqCQfLepE9hNMrNeLwt0U,1141
pydtnn/backends/cython/activations/sigmoid.py,sha256=WdhblvhPEZg3A5VrqGmAVEqURD0QkdGI8HDbpJHYKRE,1550
pydtnn/backends/cython/activations/abstract/activation.py,sha256=t4uRda45ys8Dt4d6jhCjJNyuPdwcYaLK_WWwTfo69_Q,441
pydtnn/backends/cython/layers/adaptive_average_pool_2d.py,sha256=zOWBbige_xIsw8Km5XtPpjSvJ8Veo2YfV4qwTRwuVDU,1664
pydtnn/backends/cython/layers/average_pool_2d.py,sha256=jrLeE2kZcmAvhjgFMuDjqvRjQIh0vGBxfeSskx91sTU,7943
pydtnn/backends/cython/layers/batch_normalization.py,sha256=V90cgrXzJuCr9MDmzYmBS1F2093jREnygDxgLQMM7OI,1422
pydtnn/backends/cython/layers/conv_2d.py,sha256=J090PjjtDmmDq6vRSOusfxIuDYJTnYUxGMlXZ8yFD7k,617
pydtnn/backends/cython/layers/conv_2d_depthwise.py,sha256=aBgUzlOc5hdeW-1CXTnDnvBzEqakQQNPJRhSuOqH2T0,2738
pydtnn/backends/cython/layers/max_pool_2d.py,sha256=ORMRUjgLyOAuvhVFoWqTZDQbJcxHXDPax0AhEN0Ac1o,8849
pydtnn/backends/cython/layers/abstract/conv_2d.py,sha256=1J9-T_3nRxxmywj3_EHR3FOJ3DElG3yo6Rb9UEoTRYk,2906
pydtnn/backends/cython/layers/abstract/layer.py,sha256=ab5tn2-g0Xp0ctTrVrOP8vp4lnxYUjeOi4tY18rQ8Cc,408
pydtnn/backends/cython/layers/abstract/pool_2d_layer.py,sha256=ADQXuALZARb0t0ohb2I8H_LBZDMoYmo6L6P85csVWNE,452
pydtnn/backends/cython/utils/adaptive_avg_pooling_nchw_cython.c,sha256=Jo0s1eW7u2mTUpHcXVGNvgh1cg1xhQNF8ov0ck2Pcws,717763
pydtnn/backends/cython/utils/adaptive_avg_pooling_nchw_cython.cpython-314-x86_64-linux-gnu.so,sha256=oykGMmGeSPLjfeeojtPrQLZJBPUgTvjlJ-I8m05K0w0,100425
pydtnn/backends/cython/utils/adaptive_avg_pooling_nchw_cython.pyi,sha256=i6p7fF8as45M4_JcCn1cdG6o10IRJNUiGd1KRpLv3E4,1006
pydtnn/backends/cython/utils/adaptive_avg_pooling_nchw_cython.pyx,sha256=YonpguCTEzXk_PCDYu9EcLmjBndJgK5kN-6x6O5NV0o,3076
pydtnn/backends/cython/utils/adaptive_avg_pooling_nhwc_cython.c,sha256=lmhEC-pnYTDe9f4GNLo5rf-LLOIiolOcTMVgapY3AYE,718206
pydtnn/backends/cython/utils/adaptive_avg_pooling_nhwc_cython.cpython-314-x86_64-linux-gnu.so,sha256=Lbi2iCm5dLARSvBtdpkqEudsSlbdbQvtqTqlAgg2PAg,100425
pydtnn/backends/cython/utils/adaptive_avg_pooling_nhwc_cython.pyi,sha256=N28_iyKdyS0tSP03jRM6M3oV2pjj1u76dgF1zn_iSrE,920
pydtnn/backends/cython/utils/adaptive_avg_pooling_nhwc_cython.pyx,sha256=j1wHtvOlxpFsKpk-QaE_437FSVDcfVVU3sLwXEUaBTE,3083
pydtnn/backends/cython/utils/argmax_cython.c,sha256=MuBBxCGqDlkNazYcE7xNfex4XFyHm4G_jB7OkrZUVfE,661431
pydtnn/backends/cython/utils/argmax_cython.cpython-314-x86_64-linux-gnu.so,sha256=qx8RSXReseUkVNX7uwMiDSQ96kC3iiyrct6ZYhu2tuo,112937
pydtnn/backends/cython/utils/argmax_cython.pyi,sha256=xc2AQ-ABvQLRaMZ14DNgVlXySJgj4v6cUaqQnm_kqYs,1216
pydtnn/backends/cython/utils/argmax_cython.pyx,sha256=_Z1MI3_8p8WAbZG0cTNBX0sV6sN-uM4KCGP9NuS3pH4,918
pydtnn/backends/cython/utils/average_pool_2d_nchw_cython.c,sha256=_c5Wjnetv7yFDLQ325zQgD71RD5CBEGA9envcaF3Jj4,889395
pydtnn/backends/cython/utils/average_pool_2d_nchw_cython.cpython-314-x86_64-linux-gnu.so,sha256=9cyYqY8zEqC-1B6Xh3rpR7hbWElFd-QAlz4Md_M2dt4,157785
pydtnn/backends/cython/utils/average_pool_2d_nchw_cython.pyi,sha256=5EaI-uKBQOj0CUSIsTNLba5F637SQaTPpumle_c3uWw,2679
pydtnn/backends/cython/utils/average_pool_2d_nchw_cython.pyx,sha256=uNuk6AAQKhHijiPhwG4g3QWphEE8bpa7jPMaxOzHBRI,5196
pydtnn/backends/cython/utils/average_pool_2d_nhwc_cython.c,sha256=i01PLfiUD_kvv2kJLjNXCC6lJWpEwBFBM9RtIgAC5g4,890180
pydtnn/backends/cython/utils/average_pool_2d_nhwc_cython.cpython-314-x86_64-linux-gnu.so,sha256=ByuCU50YsKllro71WI7utyMJleApn1ox97uRQUJ2AzU,149593
pydtnn/backends/cython/utils/average_pool_2d_nhwc_cython.pyi,sha256=DfKAuxS99CaPHOjDCoo3GKH2jG3CFJ3PPVfKYLwv_Zc,2682
pydtnn/backends/cython/utils/average_pool_2d_nhwc_cython.pyx,sha256=VWrhVSAmGjyGcVgRsh4peNF4Yc_h81EvupQTNE9Ns5w,5249
pydtnn/backends/cython/utils/base.pxd,sha256=aZI6v1Wj47gUbaYiJgkPxTgpbZThlxph0nN9u8iTRqg,220
pydtnn/backends/cython/utils/base.pyi,sha256=qvJSnoxSK9j-0DT4g4OImMEP_rBEowQrk-TMph27K80,458
pydtnn/backends/cython/utils/bn_training_cython.c,sha256=F7KvlIG6qMiBZBvuF4OudlcMri-HrTWKjwIVu1rn7-g,667002
pydtnn/backends/cython/utils/bn_training_cython.cpython-314-x86_64-linux-gnu.so,sha256=pJTxp9CU_jZUzhjbVBxb7SodYmlkH6vx1IHA-zHGrnY,129073
pydtnn/backends/cython/utils/bn_training_cython.pyi,sha256=nrTp26rD-GgsIBSo1HeXRbZsGGej0mS1dIsdU0d7sTw,2255
pydtnn/backends/cython/utils/bn_training_cython.pyx,sha256=6t-4kG7r8HxZhrKBuJjGYacolSP4kvv3-l0usRfh3DQ,1625
pydtnn/backends/cython/utils/depthwise_conv_nchw_cython.c,sha256=EkYj6Gf2PGtXb0Obh36oTocw-XAdvKJJyoxq_EV90mc,734745
pydtnn/backends/cython/utils/depthwise_conv_nchw_cython.cpython-314-x86_64-linux-gnu.so,sha256=Iz32Y1UOf9VrNPEuWWgWURUWiKnTewtRNpCK_k1Ql08,137305
pydtnn/backends/cython/utils/depthwise_conv_nchw_cython.pyi,sha256=H0gltaPme3ykGRQiv15KndagqVQRP5OeB7GoKqlYuAk,2460
pydtnn/backends/cython/utils/depthwise_conv_nchw_cython.pyx,sha256=srFu4QWUAEhNSTTSgfjk-z0eemXCKsEmiyoXDkC1OXk,2932
pydtnn/backends/cython/utils/depthwise_conv_nhwc_cython.c,sha256=wZFZ3k-h83VNP0Hv0luwMLkwQzwBw961Ad7DrgxU-ak,734913
pydtnn/backends/cython/utils/depthwise_conv_nhwc_cython.cpython-314-x86_64-linux-gnu.so,sha256=UPvpv-BSTlV89bYwCVD5UUM-1a2MuF6HF2ACp52vuFA,129113
pydtnn/backends/cython/utils/depthwise_conv_nhwc_cython.pyi,sha256=EmHyyoBfr86-k8ataWAbZStegAOlcLlwCiv_BJp6szc,2443
pydtnn/backends/cython/utils/depthwise_conv_nhwc_cython.pyx,sha256=elYFcAEKj6KooiBfxDDy_0g3H_yi1J1UVDiYd3wBsOY,2947
pydtnn/backends/cython/utils/div_arrays_set_if_zero.c,sha256=G7Lp5F47ukKMqk7G1jfvvD6oVMiVLmPVzOZJSuzpkgo,573043
pydtnn/backends/cython/utils/div_arrays_set_if_zero.cpython-314-x86_64-linux-gnu.so,sha256=hgO2yn4DrWoFBb-HE16ENwsW4pOFVsF9-8hsk89psF8,71793
pydtnn/backends/cython/utils/div_arrays_set_if_zero.pyi,sha256=yogbHzkFKAdBvIEh2iULIckk2CIUQar2bV2tW6CgSmY,1117
pydtnn/backends/cython/utils/div_arrays_set_if_zero.pyx,sha256=BbXkZhldu-BIbAYQ3rE5IU39aJZoeUhHUT2EhJwM6jY,504
pydtnn/backends/cython/utils/im2col_1ch_nchw_cython.c,sha256=ZMrfLnGDdUCjTjEwoqWe6MVs2JssOKHhmqY6J7ujW_g,770401
pydtnn/backends/cython/utils/im2col_1ch_nchw_cython.cpython-314-x86_64-linux-gnu.so,sha256=IvxG652wXf2iSmUB7jKwjrnNTzKzmvHVJrzAvyEvQBU,137297
pydtnn/backends/cython/utils/im2col_1ch_nchw_cython.pyi,sha256=_Ckd2zJTXb7t48xYwfQHj_p5f_MPrRjzEakuT61EILE,2378
pydtnn/backends/cython/utils/im2col_1ch_nchw_cython.pyx,sha256=xSW949MiLorkryNjd69lpdnzd6jn8p9Ie_wJujGKK4A,2432
pydtnn/backends/cython/utils/im2col_nchw_cython.c,sha256=4nxpqIFCsBov1k1OAMstXPgaQ_ejFCO9fVjTUfaLnT8,877677
pydtnn/backends/cython/utils/im2col_nchw_cython.cpython-314-x86_64-linux-gnu.so,sha256=x30oJTUxdx-idS38N1zaZtROb4_3TNHNiZ64ONbykSQ,149577
pydtnn/backends/cython/utils/im2col_nchw_cython.pyi,sha256=hQBGuslSzjJjbE7k1J2egJEF4xaXBzHIGbNHou8jxxE,2509
pydtnn/backends/cython/utils/im2col_nchw_cython.pyx,sha256=kslvw3yGtP7_5W-Qnb1b6c1yAniNoAbPKYNEkE5etuk,5311
pydtnn/backends/cython/utils/im2row_1ch_nhwc_cython.c,sha256=WhHTkga5dPgy38Hr4y8ZKaNFmVJ3ffKHLEgcGTP9Bno,767213
pydtnn/backends/cython/utils/im2row_1ch_nhwc_cython.cpython-314-x86_64-linux-gnu.so,sha256=jbcFPoS2ItzWKI3cPNAMyS3SB0aBqpgfzQ0Mv_KskrI,133201
pydtnn/backends/cython/utils/im2row_1ch_nhwc_cython.pyi,sha256=VIQQL0XpUJ1wh7sgrqG1yCsnjI2xP6Fi3J70dxflpzc,2505
pydtnn/backends/cython/utils/im2row_1ch_nhwc_cython.pyx,sha256=W_AxmKD050gO2INejKookVNZNM0HNDQqsH6HuAkxP-I,2475
pydtnn/backends/cython/utils/im2row_nhwc_cython.c,sha256=QEupNmkXA2aRFf7dotnyE1WyZHP9_UpUSpB3t7YCh3s,876107
pydtnn/backends/cython/utils/im2row_nhwc_cython.cpython-314-x86_64-linux-gnu.so,sha256=UZ_4-KouXT31xCiO-U7PIXArKZRZqUTbN6xhodw9DRQ,145481
pydtnn/backends/cython/utils/im2row_nhwc_cython.pyi,sha256=xaNvh23wlRpxqWv_N1WuylqDBxHH1TodDnWLky1-lcU,2472
pydtnn/backends/cython/utils/im2row_nhwc_cython.pyx,sha256=LIhDbq7qXA8GwZePm9RaiVDBvIog0jyaoQMBXb11rlA,5582
pydtnn/backends/cython/utils/log_activation_cython.c,sha256=xbSHx5bLYU_MFcZDBOWuN8lfrnkqfwkphzVCAmYhc1c,681148
pydtnn/backends/cython/utils/log_activation_cython.cpython-314-x86_64-linux-gnu.so,sha256=bhqrYOD4ETvDXFxKwjQA-KtA6EjGj9UkD8X8uyIXfl8,109233
pydtnn/backends/cython/utils/log_activation_cython.pyi,sha256=MuG-Y5zIosMajtOx_e8DdjV6EBVjDwp68FFLdwhpKOE,908
pydtnn/backends/cython/utils/log_activation_cython.pyx,sha256=eOjRYv01ULF7LJNWWh4kgVv-L5W3QnMODFadAhvX7VM,961
pydtnn/backends/cython/utils/log_sigmoid_activation_cython.c,sha256=WDrfFm86XOCNOj0jAA2z_pedHAKXrL7rHwzW_eWGiLA,602831
pydtnn/backends/cython/utils/log_sigmoid_activation_cython.cpython-314-x86_64-linux-gnu.so,sha256=FkOAav81TFuToCe-MZxZaVH52DMHJsA2eq-81QOsaAY,84001
pydtnn/backends/cython/utils/log_sigmoid_activation_cython.pyi,sha256=-B0U0B10gzIan8ZvX1tXv76hK4ETuak466OP4Dn1DSU,924
pydtnn/backends/cython/utils/log_sigmoid_activation_cython.pyx,sha256=MsdZ3mdH8-d0eDIjkdsgt9aDBIyMFJ2AJ7b-yy2nTmE,993
pydtnn/backends/cython/utils/max_pool_2d_nchw_cython.c,sha256=OvuUd4d0X8OvolOPD0jAX_iEGmBzRgayk_YvfAl4GGA,870346
pydtnn/backends/cython/utils/max_pool_2d_nchw_cython.cpython-314-x86_64-linux-gnu.so,sha256=VKMJrdmdjPiD1eVFWQTyjK_CElxrdTGnmcnlh_Dd3IM,153753
pydtnn/backends/cython/utils/max_pool_2d_nchw_cython.pyi,sha256=tXZC-4CLmHrPMpvmBRfk7EZQWNTtX6VhpN_4xZqEOEc,2888
pydtnn/backends/cython/utils/max_pool_2d_nchw_cython.pyx,sha256=1Z17klW2lkmL7StbZYmnPFZx-vpKVNzdaKMDPdzU-0A,4213
pydtnn/backends/cython/utils/max_pool_2d_nhwc_cython.c,sha256=QQ0L47sjj8ZNPmP-WYYL2q74RSdDm__3tVnQNOoc590,749348
pydtnn/backends/cython/utils/max_pool_2d_nhwc_cython.cpython-314-x86_64-linux-gnu.so,sha256=ct0oRzHIqsmdFdlkw2cRZv-QraXMSBK7UAbLnMDLPl8,129177
pydtnn/backends/cython/utils/max_pool_2d_nhwc_cython.pyi,sha256=SvAcwvZnS_vk9gadM_k2d0C8oZfmjm57BkxElbyfuvw,2889
pydtnn/backends/cython/utils/max_pool_2d_nhwc_cython.pyx,sha256=ByY0BFikYvd4v-kadR0wT4TzQDckICa4PRocZjmrv5s,2801
pydtnn/backends/cython/utils/pointwise_conv_nchw_cython.c,sha256=WQnO5REcpdJ7sq88ntLJ8o8dLpr2uRBNpquf8UGNgMs,705411
pydtnn/backends/cython/utils/pointwise_conv_nchw_cython.cpython-314-x86_64-linux-gnu.so,sha256=JpIOALWOgX21B8vR0Tk_m2ztUdEctUYuI3uPyY6Wlo8,120921
pydtnn/backends/cython/utils/pointwise_conv_nchw_cython.pyi,sha256=yrM_Y5p3FqRJgU5TM-ymFtMB7uR76yPoZWGuPqvCpBU,2049
pydtnn/backends/cython/utils/pointwise_conv_nchw_cython.pyx,sha256=nAnehkcD7W6GXHusOPoeyq8o5YXc-2jMHT_nRiTWOMI,2445
pydtnn/backends/cython/utils/pointwise_conv_nhwc_cython.c,sha256=ua-dSnaS1BxCgdBwMNTMiX5SMynnFvqV0K5Udu9lvqU,705076
pydtnn/backends/cython/utils/pointwise_conv_nhwc_cython.cpython-314-x86_64-linux-gnu.so,sha256=LQxBAOigCAiOc7gBwG01Jp3Ykdy9lU8wPiS1AdkiT2c,120921
pydtnn/backends/cython/utils/pointwise_conv_nhwc_cython.pyi,sha256=PvL8sFbOn5zj_g9mX8SaQgUFnche9-Oe0BfmAIIjm2Q,2049
pydtnn/backends/cython/utils/pointwise_conv_nhwc_cython.pyx,sha256=A069ID-mt5fu2JafB4Lsxx6JFOz2BVNb-SWMyA0CO-o,2424
pydtnn/backends/cython/utils/relu_cython.c,sha256=Y493sgPEBJHe-H_8fqrr7fZLyO0LW1pf0J2tAeVUM6c,688088
pydtnn/backends/cython/utils/relu_cython.cpython-314-x86_64-linux-gnu.so,sha256=5_0vs_lgY-uT2L2hhTBAkbo06dA4VdhX5vKLrMeyofA,108609
pydtnn/backends/cython/utils/relu_cython.pyi,sha256=SuVcy37C7b8qYBmk-1vC8S1Zi7MCYXb1SDjCl28kMrk,2123
pydtnn/backends/cython/utils/relu_cython.pyx,sha256=tcU0O35lbC_BxdhimilMLxj1WnJ7diJvXdQ4cfFKi4I,1380
pydtnn/backends/cython/utils/sigmoid_cython.c,sha256=vCmAg5HDTD5SyJv2BzdtwTootFiTbZaZoRTauAF27t8,600720
pydtnn/backends/cython/utils/sigmoid_cython.cpython-314-x86_64-linux-gnu.so,sha256=hlO53W4HYemzlStZKyipKV8IU8EK0gSf5BfXHQRcMYU,88065
pydtnn/backends/cython/utils/sigmoid_cython.pyi,sha256=b3700ULWZGTeEp9bfdSTAA-vtAX0hdIiO_iwpPntax4,1000
pydtnn/backends/cython/utils/sigmoid_cython.pyx,sha256=4q7luuutfnO0_pGzJ6wvqQ_XP69pTXElLkC1yrBJAHo,572
pydtnn/backends/direct/abstract/base.py,sha256=rNdAZx7h39cI17PWCzWV2zExaRrLnq4EjeWt6GX0aeI,288
pydtnn/backends/direct/abstract/layerable.py,sha256=Fi_T-L27taS04iF7eN22C315N507qoZ2CDpHfRwaqzE,354
pydtnn/backends/direct/layers/conv_2d.py,sha256=DW1RwGBbB-huJ3wKcj3cxY3vxSl9P1BhSVsOFsdOQKg,4252
pydtnn/backends/direct/layers/abstract/conv_2d.py,sha256=8CtfcSuEO7RtnIFrxuXPPojltBvhXEjydSr7d0ysauY,468
pydtnn/backends/direct/layers/abstract/layer.py,sha256=o12zbBe2iLHKLXb14h_OOCnHUQxFBm4sMgzhkcx-fu4,391
pydtnn/backends/fuse/layers/__init__.py,sha256=EkEjisFPRsFCI_sF_UMLLQg0oI2JSbz45DbhZsywMGo,606
pydtnn/backends/fuse/layers/batch_normalization_relu.py,sha256=Bxc-wRBHAnIpoVIQ5bYgoL4Q_PLCKFYON4IFsXBeiFU,3096
pydtnn/backends/fuse/layers/conv_2d_batch_normalization.py,sha256=gMBh4g1fNGQzzjLhi_kj8HIoTn6C1BYETaQK_ZsXBSM,5729
pydtnn/backends/fuse/layers/conv_2d_batch_normalization_relu.py,sha256=Jw9sW9XKXvAql0eLVfFNULL0Z0Ab2ZNzgOJi4P-dV7M,5731
pydtnn/backends/fuse/layers/conv_2d_relu.py,sha256=4gGuA3oY8V7NgH_pNfFzFYp8R-u-XTw2b-28zjRf_Sg,4281
pydtnn/backends/fuse/layers/abstract/layer.py,sha256=U9j-twBL08mRNr3DfwD06ZzibURxx7Weu6DAlLp43AQ,1535
pydtnn/backends/fuse/utils/bn_inference_cython.c,sha256=5yQ4YmFQ3MBrDldRSO3pCchIY5XG7XGFgoJH-zSPySk,709250
pydtnn/backends/fuse/utils/bn_inference_cython.cpython-314-x86_64-linux-gnu.so,sha256=k3luKLY_DoSPtD0vgN7NzPMoBiyebSuRpVe3-wP8ncs,141361
pydtnn/backends/fuse/utils/bn_inference_cython.pyi,sha256=vDsFmHtZyz25mb6Ez_YkfsBp4rJwrPdEBES3Z0nhERc,2242
pydtnn/backends/fuse/utils/bn_inference_cython.pyx,sha256=2r_4TcehUb7RS0Rv2pHp5LQM76x5EXWSz7OEB6bS0Jg,2155
pydtnn/backends/gemm/abstract/base.py,sha256=ikV0QsrV57aNI2_U9XadD3zq2YW5viRidtabnQUQvNU,467
pydtnn/backends/gemm/abstract/layerable.py,sha256=S7a1PA_U5iNEXfjUwhzoXWy_zU3di84ceDPnvxkJXBw,473
pydtnn/backends/gemm/layers/conv_2d.py,sha256=sQ--GU9cZriggKIRjgfHirJbFyZ0erZQ4IRq7NWPeVc,7479
pydtnn/backends/gemm/layers/abstract/conv_2d.py,sha256=Wei1KQNhNU6JEj6vEI1L9d7jRK8SEJSm06lfTKNeFfg,577
pydtnn/backends/gemm/layers/abstract/layer.py,sha256=1K5QFs1RTunHZ7iJGTBJRa19-cI9BQqm5ozvYOLuJ_8,617
pydtnn/backends/numpy/abstract/base.py,sha256=d_KNEqMvwflO0kV4esdjjidSvEoILcWMXWM42olMwqQ,285
pydtnn/backends/numpy/abstract/layerable.py,sha256=abXZ103LjpJRaEPXqPIkKpwNXRO901Dj3vVE27zlh20,387
pydtnn/backends/numpy/activations/arctanh.py,sha256=rWhLsbWlRrQDdEOeTbSiWKIMGtDL7Pk0MeXbf0ksA9M,2030
pydtnn/backends/numpy/activations/leaky_relu.py,sha256=KFNLIJyflWybvfiXIRZwSy6nw-FTsoLb8k6FxuUkGbM,2524
pydtnn/backends/numpy/activations/log.py,sha256=fR2jauoclZl5Ot8_F5JSsd3xucFHIcEJRCFujad_3t8,2274
pydtnn/backends/numpy/activations/log_sigmoid.py,sha256=lSGjnHxt8HfluNsYRc1IHTzC3kAs5ASHfIVujmohfNQ,2320
pydtnn/backends/numpy/activations/log_softmax.py,sha256=XVYM6IF7CIxHnP6JUIji4n0Mmep-d0I7m48MkGPKA1c,4646
pydtnn/backends/numpy/activations/relu.py,sha256=ye0m7IKFJg4G6mBuY0aPhCkRF_T28O7qHKsvtfbDYuM,2116
pydtnn/backends/numpy/activations/relu6.py,sha256=r1oBFK8WTvDs9uMdorXi9EhntvSsNUAzG6qABoeNdjw,2074
pydtnn/backends/numpy/activations/sigmoid.py,sha256=1T6KTSh6Ed0g5aXDJqVhUndhjOexYDfKUtm1jQfIbx0,2140
pydtnn/backends/numpy/activations/softmax.py,sha256=bONO18WnILvxx-fp4Ga4RdAWsVLpAqSwjpgrZP5tD8I,4208
pydtnn/backends/numpy/activations/tanh.py,sha256=nf_XSpaFaZt6adAY4vGi_IRVHCDefYfxc6XpzCwMGPc,1807
pydtnn/backends/numpy/activations/abstract/activation.py,sha256=ThUkVtw5wh6MElgQnn3UY97kr-XUq8imX42cIC-zD7o,562
pydtnn/backends/numpy/layers/adaptive_average_pool_2d.py,sha256=j4mw309tJz54Nsogdp8r3oFrz_39j4jEGsq8ZE-V5Gs,9408
pydtnn/backends/numpy/layers/addition_block.py,sha256=XFLCyruzIa58SMRzRw5EGT_Id36ScPnOEFWPQzuqQ0A,3919
pydtnn/backends/numpy/layers/average_pool_2d.py,sha256=BwxFHTG2EsaaX6YEBfmMAsAT_gHMhmCeU0SeSWPOQ8s,7993
pydtnn/backends/numpy/layers/batch_normalization.py,sha256=dK5CTb6IgwHxDFcN7AhLjiIEe4l-HBDCnm0pKrjxZJM,10075
pydtnn/backends/numpy/layers/concatenation_block.py,sha256=qFH3vv2LCGHsBwFMTiKd_xejfG0KqeBFepHSMZ0RymU,4595
pydtnn/backends/numpy/layers/conv_2d.py,sha256=mshXVf5jY_pZqZ_JAax4A2x34Ynq19IwiITZxDoPn6w,14172
pydtnn/backends/numpy/layers/conv_2d_depthwise.py,sha256=y4btdtjMXnFhcH7uVwp3DwK6AuokGae6rHtAEWNW-l0,10703
pydtnn/backends/numpy/layers/conv_2d_pointwise.py,sha256=8fslUfSKG32wNtrXaifMHOGS-flmzGU9e4xSX2zFNk8,11173
pydtnn/backends/numpy/layers/decoder.py,sha256=vi08X9BwmnN-r7CHYy5ojfjqeBzWU_dONLrrNy2MgC4,8112
pydtnn/backends/numpy/layers/dropout.py,sha256=OMtyB9KgY7nAGAAouY0YsHJgf_idJqaWfaPJW86ObT4,2768
pydtnn/backends/numpy/layers/encoder.py,sha256=NM3oJIA-RWiGMZKFMDEyOo7eVkt_vktpCuke91XYwiU,6639
pydtnn/backends/numpy/layers/encoder_decoder.py,sha256=WtU9CINvN3lrDLaaxnUvUoYbyCy9JjJGmjWUmz9DvdU,4626
pydtnn/backends/numpy/layers/fc.py,sha256=zcmIrYLGKM58AKcRIApFaseaai1V_hZQcgKbon9nlds,5523
pydtnn/backends/numpy/layers/feed_forward.py,sha256=onLr3iWxWPo36llg_2V6NgAN8NO1xJdV4EPEDz_flMA,2643
pydtnn/backends/numpy/layers/flatten.py,sha256=FZNDz72R490fZ-Dijjs6yPGsaLW9FsQbKAzc24R1XJs,1957
pydtnn/backends/numpy/layers/identity.py,sha256=14VdXuAL7GJ61xbeQeVw3VxzzcHTXQWgdEjMuPmSKIw,1340
pydtnn/backends/numpy/layers/input.py,sha256=wNvc5Vd5kHLmK_4-Nl14L7h0nCgYO7KDLEdQvE33MmE,1322
pydtnn/backends/numpy/layers/layer_normalization.py,sha256=YIm0JJxu-pTXY0EnE_p9ynYjijRW38sRqSyEOz6a-V4,2520
pydtnn/backends/numpy/layers/log.py,sha256=zTf0zFMgus3Y3eCyQ_2ihaRplKf9fKO3PlyoppKnPPQ,2128
pydtnn/backends/numpy/layers/max_pool_2d.py,sha256=dnLLozEeL8LdhahMtMiGjGLM3X0CdzjhzHXg4cEfIGE,9612
pydtnn/backends/numpy/layers/multi_head_attention.py,sha256=zDI5S8_1HA41d9fLB8MWMfWOXQLUf1O1c3zIfoQgb2A,9530
pydtnn/backends/numpy/layers/multiplication.py,sha256=XfokFK_JmmDhtjhir0VD33Ui3E_DASh-HH1uHaxo3Vs,2073
pydtnn/backends/numpy/layers/scalar.py,sha256=eZkv-T6DaPa8ID7DFejiIpC-sswnuGdA2ut3dUwyj-I,1744
pydtnn/backends/numpy/layers/abstract/block_layer.py,sha256=T6R2-aEKHaa6kqlSmFO11E4dF_sO5ExSYE64k2aGRas,639
pydtnn/backends/numpy/layers/abstract/conv_2d.py,sha256=e-vu6JrXSfw-VLhgsmRoiEOwGvKe9J5nCVp8755Uu1o,12014
pydtnn/backends/numpy/layers/abstract/conv_2d_standard.py,sha256=KJTnTTICfnpLk_4_AIWPeRaIrzzwY7d7qjMk11iBJKM,2922
pydtnn/backends/numpy/layers/abstract/layer.py,sha256=nFC1ZtlFVr0j1WMUqKw_9FLYPUMT-vdxRM6joSVoSE8,1375
pydtnn/backends/numpy/layers/abstract/pool_2d_layer.py,sha256=XTKDezPcFZzD75gX0Hs9xIydrRkUZmTfDBUu_tQb7kM,5893
pydtnn/backends/numpy/losses/binary_cross_entropy.py,sha256=I-fzpEG7iq46XSyqvMwVPPPIp2ncWE2yzeD1P6IThJs,3856
pydtnn/backends/numpy/losses/categorical_cross_entropy.py,sha256=zmsMWB3D3U8uSVAU4oGveGoSm9hljVyZDlFS3aQMMxg,3316
pydtnn/backends/numpy/losses/cross_entropy.py,sha256=TJMKW1o1zb77BZ9QHAYoi6e0Tk431bHe_vTZ3CYzaBQ,4090
pydtnn/backends/numpy/losses/kl_divergence.py,sha256=mx9P29gR2rb2NKaxKmt0X_BnxuNirLtAgjtR6kakyVI,1841
pydtnn/backends/numpy/losses/negative_likelihood.py,sha256=ltal8URw49yUtfDXAJO2kSbdPDfkcgTbuPXUtZguQhA,2812
pydtnn/backends/numpy/losses/negative_log_likelihood.py,sha256=Wikf-z2zId0g9DWVvdB6gA1c2C-keSF9zdbuUmBkFhE,2846
pydtnn/backends/numpy/losses/abstract/loss.py,sha256=jKQm0wItsAdkNVUlhvLoWnTAmzgY9qpmIri6Snc4BGc,776
pydtnn/backends/numpy/metrics/binary_confusion_matrix.py,sha256=9UuYuYGW5D6cbhVdynHaPHsnPPTVC_Dxtyu3x1NbCkc,3328
pydtnn/backends/numpy/metrics/categorical_accuracy.py,sha256=yHGyYFqpL5MoO1yzf1zVL3Y8Pq6xaJheYpNBmVtn9AI,2027
pydtnn/backends/numpy/metrics/categorical_hinge.py,sha256=EeXZJOFZGofNuVWYmBpAGpjIJe2Bnm9FRV-uCTrrvNk,3203
pydtnn/backends/numpy/metrics/categorical_mae.py,sha256=yrv9HtNxyTKePRSGEc-gZaxQzpZElaeSjTwESFNaagI,2016
pydtnn/backends/numpy/metrics/categorical_mse.py,sha256=0mf4kNeR6U58BW6Zr2GtaXIr8H7aF2VbIq4EzdM7xEk,2032
pydtnn/backends/numpy/metrics/f1_score.py,sha256=-d3YkSwoSFXOF0EEGod9ZW4tS8LRUKzrLD7z8-3mcPU,3255
pydtnn/backends/numpy/metrics/kl_divergence_metric.py,sha256=4o15TBqGBMHZLGIGUNgaJ50LeR7Vxdvye_QDd7pu7Z4,2062
pydtnn/backends/numpy/metrics/multiclass_confusion_matrix.py,sha256=UWAlsJ-fiRIJAtIxjrNhwYTkpOmT1AFrSynbZjfoyN4,2339
pydtnn/backends/numpy/metrics/precision.py,sha256=iOQAIR8WkNcE5yiM1jPl9zVKjTaDYFvHXCE4qFUke0k,3084
pydtnn/backends/numpy/metrics/recall.py,sha256=grXLOMFio1iZBuxqr5ULYXK9aIra1ZCzcCX6taCsF8k,2980
pydtnn/backends/numpy/metrics/regression_mae.py,sha256=A38yyV2BA0_zdyYlkV81qggEj-LZOfOg_O-tfHAAwRw,1873
pydtnn/backends/numpy/metrics/regression_mse.py,sha256=ab5grNkRb-qTEG8wIdNz9_24FP_Oh0BRuUdpkADEtW0,1888
pydtnn/backends/numpy/metrics/abstract/metric.py,sha256=WRCM4plTxeSKsvBGAQL8QwAEPxsADYh43I0Y2FsH5lo,429
pydtnn/backends/numpy/optimizers/adam.py,sha256=NuuMBbnQAmAu1efNBKo6chPkJcVa1GVAiMZHgnzk8HM,6326
pydtnn/backends/numpy/optimizers/nadam.py,sha256=qvq5cEtQnCC467sBG0POwhuBTgq7ej0MCt7yevWb1SI,7126
pydtnn/backends/numpy/optimizers/oktopk.py,sha256=NvsXe3lO1-QxnxmXz-oRXtHR7YmmNCCBuosJqhG9wnA,21435
pydtnn/backends/numpy/optimizers/rmsprop.py,sha256=pKTCIr8a15qAI7d7j_3IyxAobJe8kxCnH6IKaLUEpAI,4695
pydtnn/backends/numpy/optimizers/sgd.py,sha256=5TYMLCr1PRMf6ayjwi5eLVkTLdAP7LaaXnuyt1rjJUE,5223
pydtnn/backends/numpy/optimizers/abstract/optimizer.py,sha256=J1ExL3i-yK-Xay25T4RLT6-lu7IqPbMD76GV1KLmj-Q,895
pydtnn/backends/pycuda/abstract/base.py,sha256=BRUb__sqTFNIdq-ckCMWzEnq31qAjQduL_CyfwO2W4A,880
pydtnn/backends/pycuda/abstract/layerable.py,sha256=aTiymb5GBSZ3G6qJKvhy3jbINAtW7QDAAKEjxVlpeJA,7359
pydtnn/backends/pycuda/activations/arctanh.py,sha256=7pVY5h1vOE5OkP3iAamRrpKmZJj77T4-exE9rQe5OGQ,2678
pydtnn/backends/pycuda/activations/leaky_relu.py,sha256=YEe5KA0A75IpLDL0NRFEMSxBlWwQcvUuGb3AImvxcLc,4739
pydtnn/backends/pycuda/activations/log.py,sha256=TnpCaYF8-EmINh99e17ekEEjmRIV4RfJvWM3YFSwKs0,2799
pydtnn/backends/pycuda/activations/log_sigmoid.py,sha256=yE4CuNqJ_24_jMLIW4jawK8xBlDmj7HBuZ6SeTmcSEw,2835
pydtnn/backends/pycuda/activations/log_softmax.py,sha256=2dSDchPspB13p9ZO04M4iRGuaKmUwHVisB14hyxyRDg,825
pydtnn/backends/pycuda/activations/relu.py,sha256=R1gWeZmrU801jVaVF0WbWoAIeTiVNi7_6wtONx1-Ytw,2853
pydtnn/backends/pycuda/activations/relu6.py,sha256=gjE15n3dkpSRoZE1M-R-u7C7fKsIRferjDdR5d-A20c,4668
pydtnn/backends/pycuda/activations/sigmoid.py,sha256=28LaSq1tDjAW6Vs8fR6wzY8oEQNsQniLv8LUUUnUtVY,2718
pydtnn/backends/pycuda/activations/softmax.py,sha256=4UPpMLhiMntJbqvPgcDbJJftFAMxTMeV8i8rV9BqJN0,2616
pydtnn/backends/pycuda/activations/tanh.py,sha256=E3xjpM6zFbfV6QLH5G3sxGfKKYh_qlOVZeB3TxlBXmo,2738
pydtnn/backends/pycuda/activations/abstract/activation.py,sha256=P_YTp4NytUbIgQCPDSS0Cb24z0Is7CQpJIISu5bstbY,1709
pydtnn/backends/pycuda/layers/adaptive_average_pool_2d.py,sha256=SgERHDLdAW1NXBx5kVFEfA_9NHp3R3heVwQ_5YXcPfQ,6321
pydtnn/backends/pycuda/layers/addition_block.py,sha256=w0WIKgVWt_pxEVdNJkJDSW9c1BBDKAeMJ17CKgEyCIE,3492
pydtnn/backends/pycuda/layers/average_pool_2d.py,sha256=7Dy8cpYDQnOd55ZsaSzkIeCnxoLnh9o9HLQjdvkEIPc,1065
pydtnn/backends/pycuda/layers/batch_normalization.py,sha256=tnY-f02R2NXDJoLSJusba4gU7cC99XcZpnj27c4MRMA,10821
pydtnn/backends/pycuda/layers/concatenation_block.py,sha256=re2Cj_j_TOgvtGb8139OkryNFdWbS9LcCh7hsuPGAjg,8079
pydtnn/backends/pycuda/layers/conv_2d.py,sha256=FxmfOtAlzRGbnKboQlwHfqKc5BDg-g7yaxI5fFjBqtg,12293
pydtnn/backends/pycuda/layers/conv_2d_depthwise.py,sha256=6yquZCKAWo-ovIqPmK_JYG_5sd1wyiBR-CSZHpkN4ao,10911
pydtnn/backends/pycuda/layers/conv_2d_pointwise.py,sha256=PCNkaC8F2Odj1m07zwPUqZ69wW7fJGBxU5NBX7q29-I,8393
pydtnn/backends/pycuda/layers/decoder.py,sha256=a4M8DYXUk6aihSlPgt7pE6KbO5JbVE7AF_ihDg--tfQ,9883
pydtnn/backends/pycuda/layers/dropout.py,sha256=GwtWiv_KM2JfamzKo0pcJ86XqpHYgkq4ESNOqhiH3Qo,4469
pydtnn/backends/pycuda/layers/encoder.py,sha256=lfnQI2tKQ8avzKuhLPLqNJjdDkdFYuodXfXZ9LLnrn0,8242
pydtnn/backends/pycuda/layers/encoder_decoder.py,sha256=kSObBBSswd3tWEJUO3l2VGHUNYx0UTYAP1fjlHkzWhs,4724
pydtnn/backends/pycuda/layers/fc.py,sha256=lppreA-U66yd2Y_7bXgcvtxpB3o1DKCkB2v982aEbvs,10554
pydtnn/backends/pycuda/layers/feed_forward.py,sha256=0jxZcIkX6Dgm4OeS2sLOtye6Jo0VoaGMLETeL9UptBw,3098
pydtnn/backends/pycuda/layers/flatten.py,sha256=fHcuG8t6A-ICkd0yQKbghbs4AEy6MkVGsvn6C8-9Dkg,1700
pydtnn/backends/pycuda/layers/identity.py,sha256=4ISvuHPPxFHivUmeDNdkocDajkpM3sjxWsBmrjpetKw,3802
pydtnn/backends/pycuda/layers/input.py,sha256=_4jBoVMWo2SHGyndCJ-x_ILwdi63_l56jEPVAhrr3KQ,3784
pydtnn/backends/pycuda/layers/layer_normalization.py,sha256=78BTeoSPhDCj_yyc_l6HIU8iQSeI9RRI6HCNZXWNms8,5624
pydtnn/backends/pycuda/layers/log.py,sha256=fqJetBe7u4644DLyDcXUfg-ivJrnYgHApXDPaqZDeoE,2791
pydtnn/backends/pycuda/layers/max_pool_2d.py,sha256=tXdFtqZXVo2MIYIlTW5DSxP_meaWDgY835I1anrwIN8,1030
pydtnn/backends/pycuda/layers/multi_head_attention.py,sha256=PLRLggDIeUvpAmBblZmUfjpPL0BTp6b67kiJDx-A2iU,15056
pydtnn/backends/pycuda/layers/abstract/block_layer.py,sha256=3Lkqh9Nx99Kq60tp61r_zc9PzTMHB8swLvKiBXcUBaE,524
pydtnn/backends/pycuda/layers/abstract/conv_2d.py,sha256=S_MawG2qFoj9gh5ysymUitkpOO6IK2JraKx0zq5YWLE,8894
pydtnn/backends/pycuda/layers/abstract/layer.py,sha256=wscN_V8ov5UWx9XQCDLjJG4sH0aGA48gTyX9cfL0ciQ,3339
pydtnn/backends/pycuda/layers/abstract/pool_2d_layer.py,sha256=QHadyPMLDW1uHz7ILVAUpeWi7Ss-Xd-Cs6Szb472pnE,6022
pydtnn/backends/pycuda/layers/abstract/standard_pycuda.py,sha256=rtMrF7MtEcFo-ny3sv18bSR1Wnv8eUSIgNSYLv0B2bA,7399
pydtnn/backends/pycuda/losses/binary_cross_entropy.py,sha256=IsUB3zx5lqkgOnoQtXgNfC4Q31U6c_x8UT4HMz_yPew,2059
pydtnn/backends/pycuda/losses/categorical_cross_entropy.py,sha256=uv6exTlHp_UbKBxHatKDI5jOzRxDgWakRtVF6gDwD6w,2123
pydtnn/backends/pycuda/losses/cross_entropy.py,sha256=FvHkqse4WDYYXpjKh8gCjxxuyFAXDAnwzblV-pqhMm4,2066
pydtnn/backends/pycuda/losses/kl_divergence.py,sha256=uEOAJqOfADhyvX6IUk7Ut-M-Lp4TUu7UP-fAMlVQs5s,1721
pydtnn/backends/pycuda/losses/negative_likelihood.py,sha256=MxsQ5404wmct9xIuI1dblh8mdDnXMT8i_BPCIvozOBY,2014
pydtnn/backends/pycuda/losses/negative_log_likelihood.py,sha256=4pUxLk-_Ig8UCykmgQjGQSiNJBD1a6rM_TMXTGXe_YQ,1605
pydtnn/backends/pycuda/losses/abstract/loss.py,sha256=3nBCgLlYckdb0nX25wijSlprboyxoSmUGLkSna8avq8,2557
pydtnn/backends/pycuda/metrics/binary_confusion_matrix.py,sha256=_wk4d8iSTpPM2Gyj4AzoHPFVYPYskMZuFLLigDupFMI,2270
pydtnn/backends/pycuda/metrics/categorical_accuracy.py,sha256=N0_fL6JLYVZEBxg5jzqn7pVGgoINfzC97OJaeVQYjHc,1525
pydtnn/backends/pycuda/metrics/categorical_hinge.py,sha256=h4Ire-kIT_VKDJo-5FojesL77w_ddAgfpETsckpelUM,1949
pydtnn/backends/pycuda/metrics/categorical_mae.py,sha256=XnSfwQDYbP6XNBqwAoWJCFE5G4988KTFMUP-qa4M0V8,1996
pydtnn/backends/pycuda/metrics/categorical_mse.py,sha256=99WtPtgCfj19c0o0gFO8lzGMRNj0dv3thhf9X2iJCxg,1996
pydtnn/backends/pycuda/metrics/f1_score.py,sha256=lCBiFgDl2rjj9PrHeKdhv_Hf1NgB2BG7ESy6MApvs50,1886
pydtnn/backends/pycuda/metrics/kl_divergence_metric.py,sha256=eusAUDA-dJQbZxQ-N0dUkrQY02cJRhpAfcjQKJ8nZas,1408
pydtnn/backends/pycuda/metrics/multiclass_confusion_matrix.py,sha256=h8x_rn4j_tnJNhAnzOAQNNiSl1SMJmi1uOCxylZcoXY,2336
pydtnn/backends/pycuda/metrics/precision.py,sha256=LR-Y9ROLNpDRQCk09wmA4Vrj_iZZQdMDX3WIlm4fAJA,1975
pydtnn/backends/pycuda/metrics/recall.py,sha256=2jjfKjurt-9dRqHRzqtFOLliofNcHV7f4BycfPqOUsk,1928
pydtnn/backends/pycuda/metrics/regression_mae.py,sha256=NVuKc2ygBeFg4DZ_Pz_pbQOhOgInpWX76i8dns9mDYQ,2072
pydtnn/backends/pycuda/metrics/regression_mse.py,sha256=KWG-RvFh_-CsicM36g4B6PfbswPkIjMqYSG2c5v-yTM,2059
pydtnn/backends/pycuda/metrics/abstract/metric.py,sha256=ULRjRhaiO_kvRncI0QjGWQvPJ-PSxfczQoVRthX_Y6A,1545
pydtnn/backends/pycuda/optimizers/adam.py,sha256=cXx06uCgMS5qkDCFJ2xUqP-hlEwXyaz3jCJ1OhjD4Tk,5099
pydtnn/backends/pycuda/optimizers/nadam.py,sha256=17RnGYHNsJOS33ybZWNynB6-jXOn52ARn1Zz1T6ZADk,5168
pydtnn/backends/pycuda/optimizers/rmsprop.py,sha256=QVTDfdDBGcEWR8EEtn2M9oc5WFcaMnhAquYIZan3KqY,4994
pydtnn/backends/pycuda/optimizers/sgd.py,sha256=5ijvXIlUby1mpvUifDdjQ85LtuAg6kLhmrfP5qByoxY,4918
pydtnn/backends/pycuda/optimizers/abstract/optimizer.py,sha256=H2uyNzcnldvVnxRwJzff1K5eE3sLFmxOo7-l3z6jFd4,1905
pydtnn/backends/pycuda/utils/__init__.py,sha256=WDO2w8Vq628nvesrnftbFfMNIRvJTgimi8U0c1WCWHU,3076
pydtnn/backends/pycuda/utils/adam.cu,sha256=1QdvHV-GHnWu44Yk7ZM9IReS0ORDHAONDmT63sL1hh8,770
pydtnn/backends/pycuda/utils/adaptive_average_pool_2d.cu,sha256=m6GAeitqriJU0Zh78rnTm00blSeHKvR4QuQWWrQWbYE,5669
pydtnn/backends/pycuda/utils/binary_confusion_matrix.cu,sha256=d23nugJWrt7vuLbR1X4T4pjNnU_wuGuTl-UTkqW7HII,2641
pydtnn/backends/pycuda/utils/binary_cross_entropy.cu,sha256=4F9QHJP6xi6s1U1lHoMgMuqDP5Jtj-cGolGw8mLLC0s,1530
pydtnn/backends/pycuda/utils/categorical_accuracy.cu,sha256=sKe7YkBdbnxNUX-ykayKbHinSiAhR_zXic3mcrAS4Hg,595
pydtnn/backends/pycuda/utils/categorical_cross_entropy.cu,sha256=rJuxiqU6i35NcGbvzpq5rRB2FM_XEc5YD2t95ox_qEU,1243
pydtnn/backends/pycuda/utils/categorical_hinge.cu,sha256=tL-K99Ew24zqfHEucRRLZNyFr5oR7q85e2XS6j1sWnA,1189
pydtnn/backends/pycuda/utils/categorical_mae.cu,sha256=X9YsImLLao0QXOhwusUH_fKX7aQSLQxnUH0dodeEhak,1081
pydtnn/backends/pycuda/utils/categorical_mse.cu,sha256=6xt6AJ9ESIlDweGlszehl4lPoKFmMNK6ybj-AzDm6dc,1059
pydtnn/backends/pycuda/utils/conv_2d.cu,sha256=lC_ZqPWMtcTs-nML2sRvTtiKuaisv_Zaz7FEOV-8s4k,2003
pydtnn/backends/pycuda/utils/conv_2d_depthwise.cu,sha256=NYcMFC__sjh0_dFqLLpK5uvFHS73IYBRO90RZU53Zzk,4782
pydtnn/backends/pycuda/utils/conv_2d_nchw.cu,sha256=nRx9w5BPjeaulJQzg23aLBqfsZC-P6edsvkqF9GkSDg,7869
pydtnn/backends/pycuda/utils/conv_2d_nhwc.cu,sha256=F_hK7EjevbUUE0rXCP8zLh4zo_z1PIvOPFmt76hcdmc,9877
pydtnn/backends/pycuda/utils/conv_2d_pointwise.cu,sha256=cKEhVAJKycz1zhzsvcxKKR5K2SywKQoK7Koc4kIHRZA,4051
pydtnn/backends/pycuda/utils/cross_entropy.cu,sha256=Mci4iALMNEVDovoQ8EzjdHs5t2Q5MHFT53vG5X3LFNI,2063
pydtnn/backends/pycuda/utils/f1_score.cu,sha256=AY5A6F4-WLLoIbfDISu6J-97xCc7Q4A_jojmi4lrhuE,1455
pydtnn/backends/pycuda/utils/kl_divergence.cu,sha256=TVy8HHzl5AEBvpC-OJrL2Z00qDOpFhIYNNXeT0UTAE8,599
pydtnn/backends/pycuda/utils/kl_divergence_metric.cu,sha256=BG2D3lMtGKneM0UY7ftwLQu7_CY0cJcUPJAWJ_VMw-o,449
pydtnn/backends/pycuda/utils/layer_normalization.cu,sha256=xRNNHOifgMfTpycu2P4WCbJC9oQDQ4L7DFqpBoTAa4w,2183
pydtnn/backends/pycuda/utils/leaky_relu.cu,sha256=bm150FXYA24lLzvhvUC9rjEsmfxvoSCC1r2GOZRtcF4,880
pydtnn/backends/pycuda/utils/log.cu,sha256=tbx0_Fm8z2D9H_ZRUNHXf_lYY5bb3C_xRJwRmPO8Q68,507
pydtnn/backends/pycuda/utils/multiclass_confusion_matrix.cu,sha256=DGMClUX_6FkAYnYlOTwz-d9UEikfkIPVf3Mngf9PY3c,1884
pydtnn/backends/pycuda/utils/nadam.cu,sha256=6O3OtxmAKsiDhQlSy94GGLb66gcEAfOhQ_iI6m_4LHo,796
pydtnn/backends/pycuda/utils/negative_likelihood.cu,sha256=VVdkfsxqTpBS12DMYtL4kxzqsiGdY11BXU0LRWHEgk8,1111
pydtnn/backends/pycuda/utils/negative_log_likelihood.cu,sha256=0lfVACYNUtphxVms1tvUKdPk6hyoAzmN_nOiEE7F8vg,979
pydtnn/backends/pycuda/utils/precision.cu,sha256=5V5zBNqwYXToVeU0dvWSqBIIydUSx05jsyDBsAIrOxU,1289
pydtnn/backends/pycuda/utils/recall.cu,sha256=iGbPKjPQ-bxxVBMwUByqQIGCxqJxC1co1bCo43Omj08,1267
pydtnn/backends/pycuda/utils/regression_mae.cu,sha256=2xPWwIPRk9eZ3TNnP8CUrdTuDdavuf_cDmNLzYr7BMk,1013
pydtnn/backends/pycuda/utils/regression_mse.cu,sha256=1tfx7fEV0ghQE5AvJGwoQMens4wWY9bdVdo5Og17GpA,987
pydtnn/backends/pycuda/utils/relu6.cu,sha256=W6odzQKLjQYyEOBb9Sbu24zzxovd2Q5D74GjOGYNUOg,814
pydtnn/backends/pycuda/utils/rmsprop.cu,sha256=37cmO97yv8P8jRiAkGqjDospCFgmosK6FBwfCrIJhqg,637
pydtnn/backends/pycuda/utils/sgd.cu,sha256=Q7VAPXxRGwf_oFf-yKRQifOSG80BhPIoSbbPCtVD02k,597
pydtnn/backends/pycuda/utils/tensor_array.py,sha256=bDcss2kqwxeNWu2-q_gVDUwhS_NPUJRHFtvTpsQXC9g,24071
pydtnn/backends/winograd/abstract/base.py,sha256=2TGWOiBQgKIQuoRVBnp5ZYHDVkelO6eV8X_68LO9rMc,289
pydtnn/backends/winograd/abstract/layerable.py,sha256=txJMKkfo7oaQu6ilS8_1nviNdpakN7ihK6XKhuz99oM,428
pydtnn/backends/winograd/layers/conv_2d.py,sha256=b4RNBxP9hFdZ_W9DY2tDKomrjalYD_WBHc_OhDa9SUE,5841
pydtnn/backends/winograd/layers/abstract/conv_2d.py,sha256=Eyha3wGOw2rblls9nqFcbdS45S_4iAgesUdYEr7gxmE,479
pydtnn/backends/winograd/layers/abstract/layer.py,sha256=fPrEL1okcCQc4BhvQNIMyjHv_aFxObJnG0mvJO3tR6k,429
pydtnn/converters/README.md,sha256=TXbMSLf05pJf0UHT2RFqV1gJblDEVlhu5OVjz7kb-9s,1681
pydtnn/converters/onnx2pydtnn/constants.py,sha256=SBvflv4JSxhAhm8Rk_sZuNy8tDci38iGkMkoyqb2kcI,4471
pydtnn/converters/onnx2pydtnn/model_converter.py,sha256=a-YFfoyFQ6M8SLXk99CHnam-o7s0OXxaa8pW3dHNJYs,14344
pydtnn/converters/onnx2pydtnn/operations/implemented_operations.py,sha256=xt_uKf_fmPGFMcy1v63e_XRXWxaoDpZl3cmX5O_u2d8,18374
pydtnn/converters/pydtnn2onnx/model_converter.py,sha256=egZ1IIHKyeP4xUbxTK6o30qHkR1-svxQPpp5xyblsPo,12902
pydtnn/converters/pytorch2pydtnn/common.py,sha256=1HjbyGYox5ZTzv9AVSQ-lLAtxaSweVqtXX02Vhxz4x8,15818
pydtnn/converters/pytorch2pydtnn/model_converter.py,sha256=1uNxVb0N-hAJk9O-mzBXIgqJlK-VHt0O65buwI7Y-eo,12346
pydtnn/converters/pytorch2pydtnn/model_convertor.py,sha256=A5CGFf6ybq3C6Yz2jmZcOQ0-2wXCFe99U0dRDUeMLzU,12447
pydtnn/converters/pytorch2pydtnn/test.py,sha256=eigj4RUb_sXRmjiLmKc6EbNGpz42Ap8kWbZ_0CIaK_w,13909
pydtnn/converters/pytorch2pydtnn/test_conv.py,sha256=5KNY-9gIMlRFyy0NiJoYK__lNTpohqOSx2YNx6ViiBg,4482
pydtnn/converters/pytorch2pydtnn/test_layers.py,sha256=0HByqor-ngb7x_fmWcz06Zj34CX2I8pamxfiQLn4ACc,17168
pydtnn/converters/pytorch2pydtnn/utils.py,sha256=vv5xjCtvawG8gON3Xr2YzaEI3a2TFspJLH_XgmpMB0s,15719
pydtnn/converters/pytorch2pydtnn/layers/activation.py,sha256=Hjqd-zdAzhkWcgY7VKD5LMnQLRC3R_kPdPPR4tJ2xGA,5230
pydtnn/converters/pytorch2pydtnn/layers/convolutional.py,sha256=UJdAqyTOzqzRX6TkQkm6WEbaoI5vJx10UUIioRfXXvU,2959
pydtnn/converters/pytorch2pydtnn/layers/dropout.py,sha256=7Ao_LyqXZpqFrCEsL_S-GWLrCLYfm-Iaf1nJpzoYHlY,1145
pydtnn/converters/pytorch2pydtnn/layers/functions.py,sha256=eUo5mnoi0T7819cfNp3lHuwqLuyQrP61f3cLINboSnI,14242
pydtnn/converters/pytorch2pydtnn/layers/linear.py,sha256=HaxpvnTbZ9yz6C9nZXqoQrZCFVrPKbnw6usRuHfsYAo,2012
pydtnn/converters/pytorch2pydtnn/layers/normalization.py,sha256=-FcyUUR3rf1-77Kt8itML1W6I1653qDlD-QdCdtSQbU,2169
pydtnn/converters/pytorch2pydtnn/layers/pooling.py,sha256=mcPQZwIHDAVTB2LOmA_jJTlauQe-IiUV1a-y88buNVE,3866
pydtnn/converters/pytorch2pydtnn/layers/utility.py,sha256=JCx4Ay6kgH_MigA9Gfh71qF4hTUPgXl6e_y5Q7IjNCY,1388
pydtnn/datasets/__init__.py,sha256=_jMwUepsPGFf8npV4of9mkSB26mEjODvZffEaG7XIyo,776
pydtnn/datasets/archive.py,sha256=gVaTQa0d5IqGDbteiSgv_eduBE5YACzzZFtLrSklqT0,3831
pydtnn/datasets/chestxray.py,sha256=zEPj8gKcMTfkMgORDn-RycNisyEZHK9p-wJGVMpCX4w,9140
pydtnn/datasets/cifar10.py,sha256=j-qJEwNDBscomwTtkuO1Xfopa4q0XEG1U1XmpsFsy1E,4842
pydtnn/datasets/cyclone.py,sha256=OETy-X-cT8Sud6OEqj61ApB25ITC6L7xgEUesz82UfA,4552
pydtnn/datasets/folder.py,sha256=fsmX-1m3kfQd8F3ukaktpPedozRfbgwmxFJfNtOYBbs,7386
pydtnn/datasets/imagenet.py,sha256=AVsXAzQnO_BkROFGaJ9NB8JvpNc5Ui9NoDjqlQF1ats,9337
pydtnn/datasets/iwslt.py,sha256=iFLCmCVZNWJpiu2al6LyTQ1OJi--fDtgY2edn-o6Vjc,11797
pydtnn/datasets/mask_lang.py,sha256=Qfu-j8uXFMol4CYKWC4vKeEUsFJq-ONwUqMtrf_kEek,8419
pydtnn/datasets/memory.py,sha256=tqOGngPqQMS0t06-HND8Wr2QfVnSSaQnrVoxrBlQqwE,4863
pydtnn/datasets/mnist.py,sha256=k20jEh40jqcpxFmN4wq0AtK9_ghTIlZSHnF15mY6cIQ,4728
pydtnn/datasets/synthetic.py,sha256=Rh59aip9jB3jzufCc6VWPA9NpF6h8BRppU2tErYtZWI,4154
pydtnn/datasets/tsunamis.py,sha256=IwCJOAjljCzSWYVFhreubLjReRCz9BnXRTzkZo4HWxg,4675
pydtnn/datasets/abstract/__init__.py,sha256=_1_b3VIYO9Zu8cF_YaGUnUiswUD9UtkccdsHtVNhtr8,934
pydtnn/datasets/abstract/augment.py,sha256=hfpHv-lViqxyfo-pDltqJvwEZIed2aXaPVlst77E_XM,28963
pydtnn/datasets/abstract/base.py,sha256=bH88kjO12QTiBTrPZqQp4ME-JNs8dCe_N1Ie3lVkyCk,1645
pydtnn/datasets/abstract/init.py,sha256=-c7Iwdb8x_hrB2zKkgg7lPh3UHd9bohVPHYqZEkZhu8,15147
pydtnn/datasets/abstract/repr.py,sha256=G7bh7HpNo6R2TlRMVYX1g61XXR97Pj1zxwK7mXUwdk8,2126
pydtnn/datasets/abstract/state.py,sha256=UC-cODjbeG29bFeR8XQqS95dax7gIeA9V4ZhtSqw9qA,5675
pydtnn/datasets/abstract/transform.py,sha256=c5mixb9N6ScW5zWvHL1CyfkO3ifmoGwbud89IiLYyO0,28825
pydtnn/datasets/abstract/utils.py,sha256=kUP957vGhpJXucYt-TQL1WibygXsHpd-C4b5H7APl38,6751
pydtnn/layers/__init__.py,sha256=MJFGfwYzbr94Ao3OH0GI4MIGb0WCE3ztt1LKABr4bPA,578
pydtnn/layers/adaptive_average_pool_2d.py,sha256=A1qvaUpgAMKp5PNtoit5anotidI4RrXrjhA2dFzZLvw,3162
pydtnn/layers/addition_block.py,sha256=_KtHdWbOcF5yuH4N1mDg67GeIb_QMgEPyawwPbf0FFo,424
pydtnn/layers/average_pool_2d.py,sha256=4IoknORLkTHtVSEFGMwBMwdiYLqFhxy8LOeLe0KVJ0M,435
pydtnn/layers/batch_normalization.py,sha256=LJqQcErHPEu66M9peWy3sfGEWxkxSAR2UHyz7m1BW3U,4640
pydtnn/layers/concatenation_block.py,sha256=6-o5Ilr5QUEl3bFQZOu-O0IdsHvEx7NfoUPEUGIrvY8,2611
pydtnn/layers/conv_2d.py,sha256=FfV4cplPopByOFiimd8dcIWgqF4RqlpUuGDuGBnVkLM,424
pydtnn/layers/conv_2d_depthwise.py,sha256=YM2RL1QuJG-WcJxc6_J0TwPu0E9mQbCU1Qe4nEDb5Tc,447
pydtnn/layers/conv_2d_pointwise.py,sha256=h3s2P9Xg-gebkNN-Di0jL777OYqeLh9KdZym0kXE8V4,2035
pydtnn/layers/decoder.py,sha256=4_WowB6UoXedbl8goO75NtH5eHUwkAgobb-qWo0-gFc,1083
pydtnn/layers/dropout.py,sha256=EqT41_t4HtuY35Ab4vc2qIpcmQwzy3KVUqm_6Ksb8R4,980
pydtnn/layers/encoder.py,sha256=3WHrZ9OboRaPOHGUPWZGxBg1BnGh86b7qNcChq-AFcY,1637
pydtnn/layers/encoder_decoder.py,sha256=-iFNjY9n7Hx0cJ15dj8lHf8qtj5HAUb_UffUeqQ2eus,1787
pydtnn/layers/fc.py,sha256=JC17qiZk3PbjRsZDc3V_BOiCMT8UyiwhyGmfheikNKw,1920
pydtnn/layers/feed_forward.py,sha256=J45Vt6lwRTZ5vroqOtY8rCwUwUA4TY0bCeqDa9t2z1g,1214
pydtnn/layers/flatten.py,sha256=dtx2CXsDggDWrEMEUlmUgRHMM-NppGmVQVx7icdZ92U,803
pydtnn/layers/identity.py,sha256=4glZnq7-sjC8toaOC_TU5pxZEFR_vusw40SpiMC7qjw,1277
pydtnn/layers/input.py,sha256=H5XRtFzugwYhKBjiQTHaEAqZTnJFbq9vOk-tikA6IQc,1268
pydtnn/layers/layer_normalization.py,sha256=y6UATBP-xuGndjKgs8aHaeGCH7Wla-u2jFJ_sJrTjnU,2591
pydtnn/layers/log.py,sha256=gXEq-HHb26nPqu8e0Nv9iYpgNQB6eJnxHpDLWJlISGU,335
pydtnn/layers/max_pool_2d.py,sha256=GP_r4nwDGqfJdtI_EXQ-CEYGigFNc_6c4qMlgE7LiL0,405
pydtnn/layers/multi_head_attention.py,sha256=7Tx73GwL1_M6zB1AQthptR9xuGWRlYwp_Tq0-7sUJj0,1428
pydtnn/layers/multiplication.py,sha256=QNjHMrFccB604zM9v2Ts3v0Hw1i20qBuqFuT3oyBuyU,378
pydtnn/layers/scalar.py,sha256=ijzWsDgGRCeni2rEg_qQlkwJ8h9KScG2asqNa7iqg9s,692
pydtnn/layers/abstract/block_layer.py,sha256=7hiJqTPoA_WguiRlddK4uE93Yu_R7Qq7HjiPZYHlvOE,3441
pydtnn/layers/abstract/conv_2d.py,sha256=VWE78vvzZrPySXcan8EyDTxcSlDh18k1aGw6s748aXw,4810
pydtnn/layers/abstract/layer.py,sha256=hoY-MlArbMDP0HN94JlGrpb6WRHGRzF6EbKLQ5TIpYQ,563
pydtnn/layers/abstract/pool_2d_layer.py,sha256=HaWABsWV8M3F8hvR1kshV5v5FHUBkjHPQ8xhSeYr9tY,3358
pydtnn/libs/convDirect.py,sha256=dupY8FnHrH3rO0QUqb8k0xfJ6jPBZYLDr5W6fGkHOyw,20523
pydtnn/libs/convGemm.py,sha256=jO8eGlguAQ7p8C5UrAdS8ECFNab8utF7lwkUpxkgCqk,39008
pydtnn/libs/convWinograd.py,sha256=9X0GAqJEDfEWyeOP0USlJMEgYGtWeGH3Jw87im0xF_A,64903
pydtnn/libs/cublas.py,sha256=dxqOGp78N1wCPOWDUTFWtigxXero0gNqBJpf53z_uHY,270370
pydtnn/libs/cuda.py,sha256=iC45nvIuEFxvH3GUw0Y37ALZtAe4LYOoQsZpQjePAas,260
pydtnn/libs/cudadrv.py,sha256=BySSCHPUJd-vyXJtfm6bA2U3K5YxgIQM-T_gNsod3OE,11913
pydtnn/libs/cudart.py,sha256=lFYZimn6grrPCaQfJtmG3BM-3NJezvfPw6FXydGb5Ls,44002
pydtnn/libs/cudnn.py,sha256=nyMxvXI8ztyh7WqWSc1RzSx7nc4CfAfv-ii7z-VrAEA,174184
pydtnn/libs/nccl.py,sha256=U6EzSc97rnHx0GGM3nsIt1y4_xp0fqe7W1XbpMP1K4A,23301
pydtnn/libs/numpy.py,sha256=n2yuJ05KSTsAbaFWPESa0SGa28wvAOwdpURCgOQAWIQ,643
pydtnn/libs/utils.py,sha256=RQpDQqYfqugRsn01_ypjcFRbRDzSLwsGKxvxevK1CkM,5801
pydtnn/libs/mpi/MPI.py,sha256=u3A856E0JvltUh3Zf8M7B5IKD9zc3ViNI1IESqMfqKQ,578
pydtnn/libs/mpi/rc.py,sha256=mIWvkfbT4SaWoJEYm0BbyO9LZI3OxV_8jNu4Yxxi7h0,435
pydtnn/losses/__init__.py,sha256=-j8mzUICX83O01xPFWxg4S-O8F22qEq3BPF_BawXMoE,629
pydtnn/losses/binary_cross_entropy.py,sha256=O-iHKyvVMX33a7N5jWMrHEYUEaCmIWTgvAMNBQTZg-8,417
pydtnn/losses/categorical_cross_entropy.py,sha256=WOdgZuGu2QHZ4tNwI9cONHOHqZ4C9S2-lHrJ4B7E8ts,441
pydtnn/losses/cross_entropy.py,sha256=3zukfSBOLrejje_LaVvuvdEqe539uKj3B-_FT8W1NVo,395
pydtnn/losses/kl_divergence.py,sha256=8ZUgUgyIX2sLkdjwfdyzRjYaWD4bnY-w8hB3qLcj1x4,405
pydtnn/losses/negative_likelihood.py,sha256=dWy1e735C4AQGUONgLOWBtumvOrw6BMnqaEOXRHB3Uc,429
pydtnn/losses/negative_log_likelihood.py,sha256=pP-L-QlPNn40X08H-fEv0oEb9CNfzIrWXo4cj4ZhbQ4,461
pydtnn/losses/abstract/loss.py,sha256=EhdODSgogZSDm-bWoFxyMg82H06Q5l7a5Ea6u34CWpA,3142
pydtnn/metrics/__init__.py,sha256=mhoG3FqlZJWg-j8kL4Ldfim0VZj-w9KUfzYM5WDmoLg,627
pydtnn/metrics/binary_confusion_matrix.py,sha256=he7A1d3F98sifBDWe_3FFrETdW6qR_XctWT6S2akf10,460
pydtnn/metrics/categorical_accuracy.py,sha256=Cjz3V60wLrt3xLyWucZVdXEhBJPSUoaus_9ntogxQ8o,572
pydtnn/metrics/categorical_hinge.py,sha256=5kFAvGZkW9T-oxX4U1OyPhjNhBkCTecUrEqFiORldlA,389
pydtnn/metrics/categorical_mae.py,sha256=f5MhrdJ7UP4ocm7DDyLjpykomU-s1b8PJ3pYuRwh-Po,397
pydtnn/metrics/categorical_mse.py,sha256=xt8FxzY_mfUWJUgoZDKBdCZyYVN8MO1IOiX2KWEmPVI,418
pydtnn/metrics/confusion_matrix.py,sha256=KS1gXZzZ_wacwFF1lqqU0oeTq_ZblPKqtHrPZxGAyhY,425
pydtnn/metrics/f1_score.py,sha256=3BOHL-fcxMKKyG_OPvMUtM1JaBmKIJHTRkt5bLT6XQw,1251
pydtnn/metrics/kl_divergence_metric.py,sha256=jSD4abCcB2dctWzrsRqCG524CPjIpKQ4Vb51aSdt_7Q,440
pydtnn/metrics/multiclass_confusion_matrix.py,sha256=qa_MUPsrrfENeSmNMcbje7Q274WEqHDjwEEdZDHSsDk,450
pydtnn/metrics/precision.py,sha256=tPbl5iiSif3sYtuNtnuZAdbIEAvgAlr1fxzkZiwkalc,1406
pydtnn/metrics/recall.py,sha256=N8_n68SV8QWIO9lFkoX32neGa9OmkTcAvOjrAj2OSVI,1253
pydtnn/metrics/regression_mae.py,sha256=MwfCWVJdzCwSM_zSPOyu7IQYqPNoY1y9cA_3ub6OoAk,395
pydtnn/metrics/regression_mse.py,sha256=K6E6pHVrp0bhS2dcfRUCQLGg4EmS1QXiJD3phusgdHY,387
pydtnn/metrics/abstract/metric.py,sha256=HZ2-kHdh_3e6J05v83Dqe-fS5ucmZZbLMtqdWe9UN9s,2178
pydtnn/model/__init__.py,sha256=JdzeQqEq3ryUZoKrgi06FCv7bpwbYTIMH3xcTQXxPI0,1302
pydtnn/model/base.py,sha256=P5KLZ-f-iIFuhmDRQ2-N8H5WWjBi6yO8bAMVjoEGydE,8191
pydtnn/model/eval.py,sha256=BjB6T6rZsTAAw_d54ev-KfbZWqI6-qrojHzvZLV_hyw,14884
pydtnn/model/init.py,sha256=Kqke_aoSZbAGcXBnGkyIjsHY_sy9OoUIbCzALdrKKwE,15712
pydtnn/model/layers.py,sha256=YmDHCh4IVrs7PqkD2wq-MF2CtUtvnDzaSsZVu78RtQg,5549
pydtnn/model/repr.py,sha256=cedy46P6mWJ6FtOeHyEIDEpwzngzTwPJ1v9nMO-NEMM,7795
pydtnn/model/state.py,sha256=0p2gT9T0wmXG4WZsjWEn5hI7wCSzbkN1hVogXKhLhRE,4230
pydtnn/model/sync.py,sha256=ltslay7D3ovFwWtqvB8xXrDLEI6CkxUcVfQ6CMetScg,7818
pydtnn/model/train.py,sha256=AagDxAYIoseq5zwBQGXRjSvwWfongAGYkfE8Rm4zxzw,13889
pydtnn/model/utils.py,sha256=RlX9Ai16YZ-BVc9a4U8O0niPO-DCvURDPeIFrnps86w,2742
pydtnn/models/__init__.py,sha256=zenwjY4XCXq83zWAuqJTXZ32d8iyENo9c7_MD_fYXy0,688
pydtnn/models/alexnet.py,sha256=GioXd91ZD7K8oBxGg1vZffXhqjFlhTw_onyHsbxv4NQ,1792
pydtnn/models/alexnet_cifar10.py,sha256=81P85S40GZ3mo4MDgByt3AJsJ4ZNFWcagIRO2bf1laA,1892
pydtnn/models/alexnet_imagenet.py,sha256=no-fF7xhsSNY-MnOmtVq-jxbUAOwRNagfN9IIbU7CXE,168
pydtnn/models/bert.py,sha256=rZirsDrs-PPZFc-j0lPSWvOv9PuwaC8d7IVirH9xix4,1371
pydtnn/models/densenet121.py,sha256=EnkmFfH0KMd5Xg6yl3-gwNqEV2xUZBkYQ0xFBG5phNc,3078
pydtnn/models/densenet121_cifar10.py,sha256=Gzly3SBS7zJejAy93O3HqyfJSB-RvPZ5s5R4h040rBU,184
pydtnn/models/densenet121_imagenet.py,sha256=ToLxCGVJc71T5l-FMM0GS83_Nz9CXTpL6y6Ku6NBmbM,184
pydtnn/models/densenet121k12_cifar10.py,sha256=zMfKvAVQlwjgXa3V7QJnuzy9eGctmJBowLGXziKRYao,3122
pydtnn/models/densenet161.py,sha256=i9pVc_Jx8vruylr3aK-26ttjGtTDn94-tOTUkzyuQ-U,3078
pydtnn/models/densenet161_cifar10.py,sha256=GdEY9sojH4Z4RMRAD6Top9dhXpJg3CoXhs6125hdzmI,178
pydtnn/models/densenet161_imagenet.py,sha256=XiGPNaM7UKYoyTl1Nu_l10CRgqmRU5MQnvWH7iCE3vk,166
pydtnn/models/densenet169.py,sha256=UtBEUHcv0gL-T2DsOKQLme5kUn0mIe44iYUz9px3Ms0,3081
pydtnn/models/densenet169_cifar10.py,sha256=0v_KE8weIReDMyNQqUrDeBubOUdbwMCHqDLwtlx9CXc,181
pydtnn/models/densenet169_coverter_pytorch.py,sha256=fBznA1XHfx51H5jSXmfknyd7XU4AqxKYVS9pLLHE4Xk,959
pydtnn/models/densenet169_from_pytorch.py,sha256=nQA_sijI4J5DWqkZaVkk2t0zcTxqcudkb17I1J7KBRM,215
pydtnn/models/densenet169_imagenet.py,sha256=iWtz3Yifk-3Nm0zlZ6zvjx1g_VXSOXagRtGRb-0xUsQ,177
pydtnn/models/densenet201.py,sha256=xiKasOgzr8f6GaoIoZyJbdFTAfYABHusns0WsaroNiI,3081
pydtnn/models/densenet201_cifar10.py,sha256=js6CPLER2aMActCMdDYAiWUyUoi1BCLu0l3B-fLGXyE,188
pydtnn/models/densenet201_imagenet.py,sha256=gx8t82ySjS9lYhDUhfH7J0TmTiCmtBfpbZGcw8QOQ4I,185
pydtnn/models/densenet21k8.py,sha256=MznB56cgSREO6UiOBHqgQHexIILMfSinxUvolywnar4,3073
pydtnn/models/densenet53k12.py,sha256=Eup9LX5FXL5ErT-RpAUa7HSjbNZLOA2ZDtwNlNWATjI,3076
pydtnn/models/googlenet.py,sha256=lU4oSbYU6-XsU8icVXd4oJDG-eAlG5MX2gQnfyiufQ8,4576
pydtnn/models/googlenet_cifar10.py,sha256=TgXTQxxVixpHxwrbQzSKQf1voZc5bSMPiAu8XWGZ9T4,174
pydtnn/models/googlenet_imagenet.py,sha256=Jp5GAkHjyXr41iGUyFU8PCb2UA69f3y8pU1gUhNn3jU,170
pydtnn/models/inceptionv3.py,sha256=BLtjSg2ek8bANQI7qyjfUwyEk9Y__C3VAm89MngjdJA,10606
pydtnn/models/inceptionv3_cifar10.py,sha256=ZSzFo9RSYuSq-D7U8ThysVu3mRYDkL9WEY6OgEMP85Q,181
pydtnn/models/inceptionv3_imagenet.py,sha256=fr-8bqThf7aNLaQpCAdjvk3aj_TXOn7fRp4g7UzTFbc,165
pydtnn/models/iwslt.py,sha256=Kgi6EoYr63QYT9djNJ5wUbx2jRSCcpkkVtg1ha-zFxM,1042
pydtnn/models/mobilenetv1.py,sha256=gKpYGQz_ZPtPvldaeEeQO5-zWFjPg4ElEqkyuUTQjLI,2438
pydtnn/models/mobilenetv1_cifar10.py,sha256=03ZxZ_-thztW4HyXhHJTRyMWC1zjhx0c2kL5FaN8saY,181
pydtnn/models/mobilenetv1_pytorch.py,sha256=0WbR5paK7Kw7Rsc30Nm3oAQ1wSdaK3KVyORgrwmXsl8,206
pydtnn/models/mobilenetv1_tensorflow.py,sha256=5VcMjMIcUUhjh787mmFdQNTwNQZb6zullHZKqORhStw,2340
pydtnn/models/mobilenetv1_tiny.py,sha256=VhLVWlouRaBlbe_8BAnaMjLlEEt-fb-Kz7ea6JbsRT0,2457
pydtnn/models/mobilenetv2_pytorch.py,sha256=fL-9QOMxE9_g3J99ZP_NLu7YEmTG5wNRxbIVPBCFtNs,3066
pydtnn/models/mobilenetv2_tiny.py,sha256=vu7_KJcYEpP48OsA_15OJOXGgriUTaQKSH_HlDkpuQA,2988
pydtnn/models/resnet10.py,sha256=Kl6C22jgzAMagkb-7JNGu2LD3oTciTnRzU-jJIZOqr0,3256
pydtnn/models/resnet101.py,sha256=BWv6pB7TuodLgZsX5NVKSF-iKRtaq_2b87D3j1w9I7k,3401
pydtnn/models/resnet101_cifar10.py,sha256=wGUELfDEAiL8Xi5oKTQTuNzbtlaWkJEDI9_K3IP0kSU,176
pydtnn/models/resnet101_imagenet.py,sha256=AfCVq01UT-g5N7LUkjUcM-1soST4G3GuGBypvECU1_g,3366
pydtnn/models/resnet110.py,sha256=UUfx9eSolJF897e7ZDwM-GJ39n3CF6X1aEmQ6DkuUpE,3043
pydtnn/models/resnet110_cifar10.py,sha256=tAsQ22mVFBxFeFYUgz4ipsPIUxzrDFtCcxh7bHajeP8,166
pydtnn/models/resnet1202.py,sha256=GeA4jc0Wm1A4XN9cduMC06Iwm9gsOYRTiVGWk3EaFpY,3052
pydtnn/models/resnet1202_cifar10.py,sha256=oGb1DaHRm9PER_JaM7MEmHcuifbS_dAdzUk1emcCoHA,167
pydtnn/models/resnet152.py,sha256=jSC_H3UPGqPklyGcungahE9ztQAzifL8WVq4kTsZ3v4,3406
pydtnn/models/resnet152_cifar10.py,sha256=YrWN6K0eqDNRPD46uSIcYDYWpxImzQbOj_CiKnoiHrE,162
pydtnn/models/resnet152_imagenet.py,sha256=GCAld1eg8u-QrxD8r_DatGD9rXGZUty9wPyQVn0HpdE,3408
pydtnn/models/resnet18.py,sha256=wWaIAemITy8ixmF7BDX3fokW8GUrZpiztOvHWp6YupU,3045
pydtnn/models/resnet18_cifar10.py,sha256=kcWsgDnUnsVaTATDoQIygm2QNVnTrvaL8ZCSsgBSUHg,162
pydtnn/models/resnet18_imagenet.py,sha256=o1BO30WvLN1gO_2EYm24ldz6UuhiLyQzu-ECBLbVb5A,3011
pydtnn/models/resnet20.py,sha256=hfxRrtzQtY0bxnHrz1Ii0ZT30LCcIF0Iw_73o2kXPw4,3024
pydtnn/models/resnet20_cifar10.py,sha256=R0Ec9i3XalNOwlv1I5a6qAWb5f2hB7WkjAy2T0nFh2M,161
pydtnn/models/resnet32.py,sha256=_-dhQLG7XFy44kphQCoJCn37FOj1flry3JezqqnIH8A,3024
pydtnn/models/resnet32_cifar10.py,sha256=La88pC4h1WdHpk2AAE4daNciVNJrQMt2gqVo-aLh2JE,157
pydtnn/models/resnet34.py,sha256=s7X0uqzqmSpnrrfTuyILOAXHwfBL_96NdzRZcs6YifY,3045
pydtnn/models/resnet34_cifar10.py,sha256=KoG0h9508wizVqGJ5dMvGf43HyFaMWlb9bzQ7EV3IjE,162
pydtnn/models/resnet34_imagenet.py,sha256=KXg6HJUaGh6F1--cpWx3n66VpHAq40xzH_Zj6IU2tB4,3011
pydtnn/models/resnet44.py,sha256=CvyZojE5AV2gLZBymTct9PUK1fDnXQSompOzarAb0GQ,3025
pydtnn/models/resnet44_cifar10.py,sha256=2lbawjo8JC7CLrhcKbA0kUC3NGlEBKteIGapbUH-IDY,157
pydtnn/models/resnet50.py,sha256=MTw7Oy1GYcK7WuyUh8KBfWSN5P422F994OupIa6E6Ik,3461
pydtnn/models/resnet50_cifar10.py,sha256=dctVQQHn_NSz_j4VTu8yimRM1zu47Akg23TT1X76GyI,170
pydtnn/models/resnet50_converter_pytorch.py,sha256=4txco6ZY9mQQ6GWbGnTUS4J_t99kyMMwNHZMlJ4ntnI,911
pydtnn/models/resnet50_from_pytorch.py,sha256=inJW4lLzv0e4o1n07HS_5Rw0CmqCY3YYeKwaMayZvxM,205
pydtnn/models/resnet50_imagenet.py,sha256=krxgsIDsyEOz_qyDpThpdmvE9vE5bPxS7ta5a_rCK8w,3701
pydtnn/models/resnet50_pytorch.py,sha256=RRss0ds3XTzEsGJif30THB0LgV7qh7HW6OEqJgvEHqM,3427
pydtnn/models/resnet50_tensorflow.py,sha256=rt5BLbcJ4nvFBtJV2ypw193_Wj72_E_B_Udg_i8cfOM,3731
pydtnn/models/resnet50v15_imagenet.py,sha256=24WwuYN3_QmUCrjNTv8sRFBic-wj5F0RD2sTl9BIEoI,3710
pydtnn/models/resnet56.py,sha256=DIdWxN9Vu42ZDVUoXlvnAxZJkCX0Ha7rrJ0Me-MeR5c,3038
pydtnn/models/resnet56_cifar10.py,sha256=j1eXJRDzdAGQAwvkrzxNtng53BSgPll-uI9uAzUiNow,162
pydtnn/models/simplecnn.py,sha256=ZciMnG4VF_eMyTHey_kf1vYnV5eYw2x3ZMKS4MQYOic,1441
pydtnn/models/simplemlp.py,sha256=zv_2AAgERZecC1fllTbYSAMp9vGXFHsNr3P4MJB1Dkc,1077
pydtnn/models/transformer_test.py,sha256=h-EwaYE2SeW-BIn7-2uoiNud8tXJMF7GgHLV7QKb9LA,1100
pydtnn/models/tsunamis_eflows_UMA.py,sha256=PNCAhe3FjCBTiY6fCV72y6kdZ2JprGF-c0Z85FkeXtA,3520
pydtnn/models/vgg1.py,sha256=nOcSRD4wiweRfyWQktS0nAmlovoOQqfzMKTKvX8hSQY,1623
pydtnn/models/vgg11.py,sha256=Q7NrNH4eERSmCnrj1qOt0NcZuHJtX7DtjoI8MDkITxs,1498
pydtnn/models/vgg11_cifar10.py,sha256=OwbUA_kHAAY1omsYa_XcvzEmWKMBotzagcgGbxbNBRM,169
pydtnn/models/vgg11_imagenet.py,sha256=zIMZcXqTIsckeGNHD8cjlox18PllO86Ca85XzaHXzfg,144
pydtnn/models/vgg11bn.py,sha256=q5NfMIYpkfM6Eqroh596t_Vr27yDAttnmbMJ2EY4Vwc,2025
pydtnn/models/vgg11bn_cifar10.py,sha256=6_BF_ABTtZa53Pl7Qu39QiC1VGgjuArjmMrVl_BDw1s,166
pydtnn/models/vgg16.py,sha256=XAiXF4OcTlgxmxKe2GBnYSoTk-GgmRC0EAPLrKO--N0,1494
pydtnn/models/vgg16_cifar10.py,sha256=0vQBFxjKu6SDX0DrwCWRDBUqkRuyejdiI6h2THJC5qE,153
pydtnn/models/vgg16_imagenet.py,sha256=TA8z0Khv4CFej2A1yedPrpDllFtJdSX_PzxX-x7764Y,135
pydtnn/models/vgg16_pytorch.py,sha256=MuB953Kl9bnCBLCNBiTOExnIe-AEzjVV9x6IW9FQgDA,3231
pydtnn/models/vgg16_tensorflow.py,sha256=t51xo2G9aG3xH0NIYB0bTCpEL9UShO7oMcqJ_lTIgDw,3324
pydtnn/models/vgg16bn.py,sha256=rfnqxD4mNv72VGjC8vm_YC8M-YlRbTbBnd32kXiwTUo,2036
pydtnn/models/vgg16bn_cifar10.py,sha256=Q3UJonZMLZqFhkv_Xw0j9UkxgrqPLa9toPR1RORPsZA,172
pydtnn/models/vgg19.py,sha256=aj__-QRkXlD1XQUSRfksmviUGXFoLDivsmVRCewM66g,1839
pydtnn/models/vgg19_imagenet.py,sha256=J9XD5zxIl3Axm5jpPF_JLaAA9mkPOesj4vOcaY1q1F8,135
pydtnn/models/vgg2.py,sha256=eReU1wfq0T0FcOpwvlOWFdaWJk50QYSDRdIxOxUyizs,2086
pydtnn/models/vgg3.py,sha256=SER105ShsHsFfjTLBYIoSAEzYdaBcduN4zFH12NQLFg,2489
pydtnn/models/vgg3do.py,sha256=N64qrPkvDEs6t5ghyr4LfIQHpNoRJMCshDuhLOFxRMw,2630
pydtnn/models/vgg3do2.py,sha256=ITmvNQAEYcm7NHAODPQiRGTfx4oGRZfS7K7xiNuqyI0,2647
pydtnn/models/vgg3dobn.py,sha256=Hd2UBWnRFjE5tv0ul7dox8j2L6muTE4Gq7fpg1bmUiY,1805
pydtnn/models/vgg_tropical_cyclone.py,sha256=UlN2exGOo76iqJ9xyqNdPEucWhXlNrLaeemQrlQyd30,1804
pydtnn/optimizers/__init__.py,sha256=mWyen8PuU1n0NaF25xVOhD98370yAvLjeKXErDMzv5U,589
pydtnn/optimizers/adam.py,sha256=WtafQbRouW35jiuOIkaN_kOPxAeyM2BnDjAzSc5LYGE,2431
pydtnn/optimizers/nadam.py,sha256=fajznX0-398DNk3HVfT5uQen09OJHIH4bqwyxShxx6Q,3114
pydtnn/optimizers/oktopk.py,sha256=Q89VI3IdnCtcs5HjPfj9XV9Bo9Yitf6AqEYjFOyvlhM,3213
pydtnn/optimizers/rmsprop.py,sha256=fRNSGaaSEKGhn4GbJ0DSYNi0FiB8Dfon11-z9er6Ppg,2102
pydtnn/optimizers/sgd.py,sha256=u9wtTSXudE7ft4n7CfIAlle6bPdngyxFphq8sLDqMB8,2184
pydtnn/optimizers/abstract/optimizer.py,sha256=cE1-aZYEclKP_UcSuDaoTitH9o1xDNeehTaDHDrjR1E,1795
pydtnn/schedulers/__init__.py,sha256=f-wJ0KOaCXuvRiYBw_q_HZTKXywRCPEBs384tFUSwFY,553
pydtnn/schedulers/early_stopping.py,sha256=PsyOVulQBhavsxm4mV9oyKfmDvi-HmvjCH4aoL_62NI,3623
pydtnn/schedulers/model_checkpoint.py,sha256=fcHeNG6BiKfDYyxYUCZ3ACZkwRcx_zg8QfXQoTogX0M,5478
pydtnn/schedulers/reduce_lr_every_nepochs.py,sha256=NHurhlI_HZW2P83RLXhRd4Hn4I69RCNLE_WintpsYbg,2172
pydtnn/schedulers/reduce_lr_on_plateau.py,sha256=WOSbTONTOkPMIgDQa7qrGkk7eMk96uB3tGadkMwd3Xg,3120
pydtnn/schedulers/scheduler_with_loss_or_metric.py,sha256=Dnj2OUiuNtLVWOPSUhlwRGpQ8ybimkwRKL7VfaxJQlI,1570
pydtnn/schedulers/stop_at_loss.py,sha256=Tqt6v4eS4CB9LmViHRETeP_lxSRi_K-PIRd09FbENAI,2220
pydtnn/schedulers/warm_up.py,sha256=wAjB4-iw5CGDIFfrk5C0RlGIafHjXmnGTEyIbW0GegM,2255
pydtnn/schedulers/abstract/scheduler.py,sha256=XNzoCCjpwK9OI833HI6CLf0dTm1oZYodUbzR-asKfc4,1801
pydtnn/tests/batch_normalization_relu.py,sha256=qCwFjsgqklA0aO1NvBVM5Ak3UdmNnC6ipI0olOT1uUc,5524
pydtnn/tests/conv_2d_batch_normalization.py,sha256=XUWth24mFA09OmO-e4uFsnWPSnElvq8fVZ8S--557Rk,6637
pydtnn/tests/conv_2d_batch_normalization_relu.py,sha256=eKtCPIzYykrjk28ZgttJIUn29zdvWrJnjMJYqrvxMQU,6780
pydtnn/tests/conv_2d_conv_gemm.py,sha256=RsxWSMcDvwMdcWWN6Yx4b5ZmsV9FVdXmKbec5-i0EpQ,2809
pydtnn/tests/conv_2d_conv_gemm_long.py,sha256=ARAjSPmL4cwmSjc34BSRg-jw2J3160YzvonxVsy5HzA,3902
pydtnn/tests/conv_2d_cython.py,sha256=i2YgexjJF0iElDvvuMubBRimXdpUktYiOik_07SmeCw,2642
pydtnn/tests/conv_2d_relu.py,sha256=7gzfnk8aym9r95j0cQbE9dCyWmHfvmCDqqIFzbnMla8,6520
pydtnn/tests/conv_direct.py,sha256=xDcWGDe2E7HfWHiLzu8JmgSi8l9vKiEdvPbJxmaxM9g,5070
pydtnn/tests/conv_gemm.py,sha256=q5_dEhU37PX_KFUhS1TgdN7dsLUrZ64ARgNJ9tycQzY,4863
pydtnn/tests/conv_winograd.py,sha256=UoncJh_GTJqZHouey9zBbQGBBQSHHOQUqX6BLv9VBrA,6438
pydtnn/tests/model_conv_gemm.py,sha256=COUJ2Ridkr-3VBfPYzoioJLCS3USq4YTeQX_H_M75Ek,2577
pydtnn/tests/model_dtype.py,sha256=QXAjNSlFzEqWi7w_DcXHRE9okNjn9j4M81Gs3l3RLBI,2515
pydtnn/tests/model_gpu.py,sha256=JPqxl08L4DRo3REok6wk1saT1JZSgTdZfD2nDIxP_XA,6578
pydtnn/tests/model_tensor.py,sha256=kGDEs_fOyFLVD-cCE6Y4AQJAZbYfW5pEGDE3JDLTsSE,9031
pydtnn/tests/pytorch_layer.py,sha256=J5sdSgN-j-omvjpnh6MFDk3HIuhdZN2FE6Ew0lcmXAU,36342
pydtnn/tests/pytorch_model.py,sha256=CqADIq5BpKQlVODWIVZp5xsRV5ODKreDpg5nWeNEg6U,23004
pydtnn/tests/abstract/base.py,sha256=5-c9xfq-RN13ZU9W2P4D6DPYfBEK8hBCQpzjE9wFJPg,4961
pydtnn/tests/abstract/common.py,sha256=GD2Eu3EL8Ljtj2UO4do9OHXCoqsEpDKK2xQPgL38OgI,4962
pydtnn/tests/abstract/conv.py,sha256=HyxowaQnQc3iEpp_4MkrwFUo8R9MskPApCNOlWqB888,22603
pydtnn/tests/abstract/conv_2d.py,sha256=lmAgz3Bse1sQFzmVl13YcACe3rGBj40JFbnOK3zPlJ4,12055
pydtnn/tests/abstract/conv_2d_common.py,sha256=2004BikIMFE8OU3L3_L4oKnEtZTRrLh2sJFj7CV10CE,12102
pydtnn/tests/abstract/conv_common.py,sha256=MHK7F-7BOip3qeTeC7qo6PgJ7gYWIFPk_9b4IDxCY3U,22705
pydtnn/tests/abstract/model.py,sha256=Z3D7JMyJ7pBLrT-NXJR9_OgJFugclRGQPGU_LxywT8g,17807
pydtnn/tests/abstract/model_common.py,sha256=0jszEN__NEVhO0v0ytgwTr0AHD551Hu30XmX2aHV-mc,17785
pydtnn/tests/groups/all.py,sha256=UHcFIiFo_TMZybQ_Ppcy1FVMkXlZLtg0BJFCyso8gWA,2303
pydtnn/tests/groups/fuse.py,sha256=B6CwFQICJnZNO2KJSljcL2d-Stesl1aB9caA3igArPI,625
pydtnn/tests/groups/layer.py,sha256=Zsk9KSsXAD2TozJndbl__pQXFwFGn0yfpUf4_nNCU0Y,263
pydtnn/tests/groups/libs.py,sha256=gKOOwUgrYxKhi1TYEC8bYQztvMo5vTLfLiTsXn3F42E,849
pydtnn/tests/groups/model.py,sha256=0udRYYlkDGcVfFyZrNh8O1DCZUiBNxhoTbiw4BnEzq8,461
pydtnn/tests/groups/pytorch.py,sha256=5QULL-AKgQNxA0rTLu2883KP03sMt2c_8-eMmzTUYTo,352
pydtnn/tracers/events.py,sha256=-fH8eiZkaLnNHBmpfDbw_gdccyB7ZzfxAdWdiA5BkAU,3578
pydtnn/tracers/extrae_tracer.py,sha256=GJW-h2ZG8fK7_pivbmVxxmtcZdiuroPn_GsXzDpQVSY,2747
pydtnn/tracers/simple_tracer.py,sha256=1wvVNPbE2SsCVB1ifTH3aGqKqKGf-xyqf_KXP_9CbK4,5621
pydtnn/tracers/simple_tracer_gpu.py,sha256=GSZ1SaP0VoARrQ_pJH0knmFV-79iZUKdQggaAH4i4Xo,3898
pydtnn/tracers/simple_tracer_pmlib.py,sha256=rzOCPrbnSjEkRZNk68UViMwT-t1hnRFaXzOYiVt063U,5367
pydtnn/tracers/tracer.py,sha256=3vDmgv_HALrRjRtXe8EeyqdiJ2BO58Wn55NrYFeFrZE,8302
pydtnn/utils/__init__.py,sha256=Mcf_Yd3xxbKwJNAXRdV3JXMW7SVW9rQLfbOv9X21M_M,5871
pydtnn/utils/_cyutility.c,sha256=wtwscPpPjqV2ZaClO5guopHZ9mQVkpBCy-eIulfXYPs,1134901
pydtnn/utils/_cyutility.cpython-314-x86_64-linux-gnu.so,sha256=fGg7CVdp0z6d-PUqS6eGSRUmaDZWNT-M5TrEH8JO66Q,1313632
pydtnn/utils/best_of_profiler.py,sha256=TC69qGU8t9h-Lswik7D2JH5s0796i-_rFmFtHCFvP1g,2788
pydtnn/utils/constants.py,sha256=TsUqNb1ElM7WKXO6PfTyp_jmHcxS8lOJ329aCkFB1E8,1431
pydtnn/utils/debug.py,sha256=KxSFYI_1brch7nSnMZGwxlbZzYoGD0qzSsVLlxP0g0c,3372
pydtnn/utils/flake8_metrics.py,sha256=tkRnB_PeReO22rLZmDP4pNJqxf4kksQJei0XaOq_xUA,1982
pydtnn/utils/flake8_pyright.py,sha256=AVu__rkdQboCF_K5qE0XTlHm9XZ5vNQX1nESwqLtMWw,8036
pydtnn/utils/gpu.py,sha256=I4f5hDo0v99xg9pvtfm9hM1606VFL3doZFLxJC9i5no,1463
pydtnn/utils/initializers.py,sha256=fqr8nNvcKyFOFUOXZzrcRuFsQ4rAHlb24I1Ee3w76jM,5699
pydtnn/utils/logs.py,sha256=xUffqAiHfstK8xpGphiDNHH-lIfdh1tgnAePHfdIeiI,1062
pydtnn/utils/matmul.py,sha256=s-N3w-n7Gae6zbiW9nzLt0qHxiSP20Qr-0VH25QAV2Q,3936
pydtnn/utils/memory_cache.py,sha256=0FqhcvIT6hyzftaEjOKyBSafPoRix8JdrJBJzbsteBY,2354
pydtnn/utils/memory_pool.py,sha256=NFTGs6yp7ErVVTg0Y8B7YtE-0NhmVA4eZYmnHodvPEw,3491
pydtnn/utils/parser.py,sha256=fARu2rDlEwY8IOyimD8sYVkKyKsPYvw-EAgsF50897A,50845
pydtnn/utils/performance_counter.py,sha256=kpsZuvgLNq1qDZLIuAfBYqGQJN6ojKzF968Gn8Nk__w,9338
pydtnn/utils/performance_models.py,sha256=XRWWqYTXe9CwLWZzaDzgbLy2N1nm4UrcE0O3wQjsXJg,9728
pydtnn/utils/pmlib.py,sha256=sSMyPBWXr47wimwiMQAyZvXQhFqP-9EM_Qn6EnwLTa0,19932
pydtnn/utils/profiler.py,sha256=qpc6cpXJcbKuEAS0gGv-nCqNXuwEDer9REZk6JN0ICE,2248
pydtnn/utils/pytorch.py,sha256=Xq-Ozb0ahhMp59vT0tu-5cbohbjCtRevD10f_kqYzUw,788
pydtnn/utils/rand.py,sha256=sAzjWQ6hsHXo29ktoQejFht-G2NdEjo90DasL-KRQm4,1956
pydtnn/utils/serial.py,sha256=YjtA891QECwFf7XT0DRG3ecUGZ53cwrF2NfD181-4F4,986
pydtnn/utils/sparse.py,sha256=9nZMrYaNCNsuhhGJJikzt7TDkG2XZ2nA3xs-6PVG-l4,5347
pydtnn/utils/tensor.py,sha256=7oZGQFIDLg3fUHatnKjYn63LtEFkMO61y0qotqzXlXk,4792
pydtnn/utils/term.py,sha256=XdzoTW_jedlD3bj2jwLW4s4ugMaKCU5NThLdn0-N82o,1234
pydtnn/utils/transpose_cython.c,sha256=wuu-oPFJrEAw_rB9yKJvAViwAh42pAeuaNNVwXV1D-Y,1042579
pydtnn/utils/transpose_cython.cpython-314-x86_64-linux-gnu.so,sha256=Rff2yhavoFIK4UfqajM7iQV0q8xMpPtDSd0_Pglo1eg,194673
pydtnn/utils/transpose_cython.pyi,sha256=Pe9mw8DmEQJexIxjPzRVI_7AaH7UI8vpRD2WQr3dB8U,3157
pydtnn/utils/transpose_cython.pyx,sha256=RYfZVnv7_nEynnsHjK-FeAZ4vtvmoKvM-WHfN52uUtk,4619
pydtnn/utils/uses_cuda.py,sha256=tRlyGlDGxgLP4JJmSE4JST6Y9NIHeeR8U_0MS_NjhYw,4486
pydtnn/utils/best_of/best_of.py,sha256=xgRgER1ZO9B3YTHv0_PPYWeSgK5SXA4eISpKBIvNTPQ,26542
pydtnn/utils/best_of/best_of_variant.py,sha256=lqnKvZxuIjUUwIqW2mR55us5rksdrjNZkhRCqNTUjEQ,7507
pydtnn/utils/best_of/best_transpose_0231.py,sha256=rfmX7q11XV911DSZrt5pc5s2RdQ1aFfufqLwzJ9At88,2555
pydtnn/utils/best_of/best_transpose_0312.py,sha256=Hz1dZ6dpzuAVz2S1IVoZoBnJElfhM88DTNZ3JwPYhGA,2578
pydtnn/utils/best_of/best_transpose_1023.py,sha256=VY-oJxCKGXzeXh4YfjdhJwD_wCntgfPcrOcNE7Sc3as,1979
pydtnn.libs/libgomp-6456b504.so.1.0.0,sha256=Ay5vAXGFKUgQhMlrYG1O3prPXreYjP4YpujZvLFv_lg,366633
pydtnn-3.10.0.dist-info/METADATA,sha256=MzfPOMF74RJLABaL-Uey1YotIlmcsutq32JFX2iCpwA,64311
pydtnn-3.10.0.dist-info/WHEEL,sha256=RjEyEGV5_jAU9SzPd1q7NuOSaEUoyx3ArrccDv7Hws4,113
pydtnn-3.10.0.dist-info/entry_points.txt,sha256=O6Sf2PGxj5LDSCLcNhGsfuaV7oTIGtSJ_tXvQiScUNg,174
pydtnn-3.10.0.dist-info/top_level.txt,sha256=Rg-8rpfHXL1OaciMWxKjJLEpvNGob8PR0Lua07Xv3ig,7
pydtnn-3.10.0.dist-info/RECORD,,
pydtnn-3.10.0.dist-info/licenses/LICENSE,sha256=OXLcl0T2SZ8Pmy2_dmlvKuetivmyPd5m1q-Gyd-zaYY,35149
pydtnn-3.10.0.dist-info/sboms/auditwheel.cdx.json,sha256=fCGsa8vmeMsztaGJWht4Y3kJ7vLMYYY5fOQhZBY3TvI,1236
