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apache/mxnet-site/c5146c8d9adc60e2939264961e16cc4c6ef56139/./api/python/docs/searchindex.js
blob: 42d82209783f5e5599827e10d68ea7fda01ee352 [file]
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cker:368,docstr:[67,104,303],doctest_mod:303,document:[14,40,41,67,103,120,143,152,163,166,167,176,177,243,277,280,306,384,390,410,419,422,427,428,430,431,434,438],doe:[12,13,14,15,19,24,25,26,27,29,32,34,40,43,45,47,48,49,51,54,58,59,61,62,66,67,72,73,81,82,84,92,109,113,114,116,120,123,128,135,142,146,147,149,152,155,156,164,165,166,167,169,174,176,178,182,190,200,203,204,205,206,207,208,210,227,228,229,237,245,249,251,256,258,261,265,273,274,275,285,312,315,319,350,377,384,387,390,392,394,395,396,402,404,417,430,431,434,437,438,443,444],doesn:[4,6,13,25,29,43,47,48,53,54,58,62,123,315,339,360,376,382,388,389,392,394,397,398,414,417,426,431,444],dog:437,doing:[11,34,47,48,58,62,382,388,389,392,402,418,426,437],dolphin:[435,437],domain:[74,152,350,380,397,444],domin:417,don:[0,12,19,24,25,27,34,42,62,70,71,188,193,367,373,376,377,380,384,386,393,396,398,402,404,406,411,414,415,417,423,424,425,426,428,430,431,432,443,444],done:[1,12,19,24,27,43,54,64,67,92,123,133,165,167,180,271,272,318,363,369,376,384,386,388,389,392,395,402,406,408,410,418,426,437,438],dope:401,dot:[4,6,24,43,45,47,48,51,54,58,61,62,63,108,123,154,161,164,166,168,172,174,177,178,187,262,274,312,321,356,357,369,372,373,388,389,394,424,428,430,431,432,443,444],doubl:[4,6,40,43,46,47,48,54,57,58,62,262,292,314,328,333,338,345,351,374,386,416,432],dover:[76,152],down:[4,6,40,42,43,54,84,134,135,402,415,417,431,440],downcast:67,download:[29,42,356,363,376,377,380,384,397,398,401,402,404,409,443,444],downsampl:[4,6,23,43,54,404],downscal:24,downsiz:377,dozat:438,dramat:431,drastic:410,draw:[43,47,48,49,54,58,59,62,281,282,284,285,286,287,288,289,290,291,292,293,294,295,298,300,301,373,375,384,392,395,438],draw_next:40,drawback:[387,402],drawn:[40,43,47,48,49,54,58,59,62,281,282,283,284,285,286,287,288,289,290,291,293,294,295,297,298,300,301,382,384,404,423,438],dress:[376,398,411],driver:[367,444],drop:[0,16,24,26,31,47,48,58,62,66,319,338,414,415],drop_input:26,drop_last:384,drop_output:26,drop_stat:26,dropout0:435,dropout:[0,23,24,26,47,48,58,62,338,377,378,384,386,408,410],dropoutcel:26,dshape:47,dsplit:[100,121,251],dst:[29,47,48,58,62,384],dst_f32:[443,444],dstack:[100,251],dtype:[3,4,6,12,13,15,18,19,24,25,26,27,34,40,42,43,44,47,48,49,51,52,53,54,55,58,59,61,62,63,66,67,70,71,73,75,77,80,81,82,83,86,87,92,93,97,105,106,108,110,111,113,116,117,118,120,124,129,136,137,141,142,144,145,147,149,152,153,155,158,159,160,172,181,182,183,184,186,188,190,193,196,200,203,204,205,207,209,211,212,213,219,220,221,223,225,227,228,231,241,245,246,247,248,250,256,258,261,269,270,271,273,277,278,279,281,282,286,288,290,293,297,300,308,320,328,333,336,342,345,346,351,356,357,363,372,376,377,384,390,398,408,410,423,426,428,430,431,432,434,435,440,444],dtype_sourc:[12,19,24,27],duchi11a:[4,6,43,51,54,61,349],duchi:438,due:[4,6,15,43,47,48,54,58,62,66,103,339,375,376,384,387,388,389,407,408,417,437,438,440],dummi:[22,356,375,386,431,440],dummy_input:373,dummyit:356,dump:[31,40,350,401,444],dump_optim:[32,33,34,35,349],dump_period:350,dump_profil:350,duplic:[11,40,47,48,51,58,62,349,424,428],duplicate_row_id:34,durat:[350,365,444],dure:[0,4,6,7,11,13,14,19,24,26,27,30,33,34,35,39,41,43,47,48,54,58,62,123,314,319,326,357,371,373,375,380,386,387,388,389,390,392,394,395,396,402,404,407,408,410,411,414,415,417,418,438,440,444],duse_bla:443,duse_cuda:443,duse_cudnn:443,duse_dist_kvstor:443,duse_lapack:443,duse_mkl_if_avail:443,duse_mkldnn:443,duse_nvrtc:443,duse_opencv:443,duse_openmp:443,duse_profil:443,dwell:301,dxy:374,dying:[47,48,58,62,326,387],dyn:443,dynam:[4,6,19,24,27,31,43,54,62,349,351,386,390,396,438,443],dynamic_reshap:[4,6,43,54],dynamic_shape_op:[4,6,43,54],dzdy:386,dzdy_np:386,e_0:[47,48,51,58,61,62],e_1:[47,48,51,58,61,62],e_k:[47,48,51,58,61,62],e_m:[47,48,51,58,61,62],each:[4,6,7,12,13,14,15,16,19,20,21,22,23,24,25,26,27,28,29,33,34,39,40,42,43,44,46,47,48,49,51,54,55,57,58,59,61,62,63,64,65,66,67,68,74,75,76,77,78,80,89,90,91,92,93,94,96,97,103,108,110,111,116,123,130,134,135,136,137,146,147,148,151,152,164,165,166,167,169,178,184,197,200,219,235,237,239,247,252,255,257,263,270,271,282,283,291,315,319,320,335,338,339,341,349,350,356,365,372,373,375,376,377,378,382,384,386,388,389,390,392,393,394,395,397,398,400,401,402,404,406,407,410,411,414,415,416,417,418,419,421,423,428,430,431,435,438,444],eagerli:15,earli:[14,414,435],earlier:[374,375,378,390,402,411,438],earlystoppinghandl:[14,411],eas:[381,385,388,389,395,410],easi:[14,19,20,24,65,369,371,373,375,376,384,390,394,398,410,418,424,426,438],easier:[371,380,390,394,417,435],easiest:[66,411],easili:[147,367,368,371,373,376,388,389,390,398,402,408,410,426,431,434,444],east:[363,376,398,435],ec2:[361,366,368,376,385],ec2inst:367,econom:175,economi:294,eda3666:282,eda:282,edg:[4,6,40,42,43,44,47,48,51,54,55,58,61,62,98,116,145,146,147,148,435],edge_id:[4,6,43,54],edit:443,edu:[16,42,47,48,58,62,338,349,356,401],effect:[4,6,19,24,27,40,43,47,48,54,58,62,67,84,103,136,192,226,249,271,315,386,397,4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Learning Rate Schedules","Normalization Blocks","Trainer","Packages","KVStore","Distributed Key-Value Store","Legacy","An Intro: Manipulate Data the MXNet Way with NDArray","NDArray Operations","NDArray Contexts","Gotchas using NumPy in Apache MXNet","NDArray","CSRNDArray - NDArray in Compressed Sparse Row Storage Format","Tutorials","RowSparseNDArray - NDArray for Sparse Gradient Updates","Sparse NDArrays with Gluon","The NP on MXNet cheat sheet","What is NP on MXNet","Differences between NP on MXNet and NumPy","Fine-tuning an ONNX model","ONNX","Running inference on MXNet/Gluon from an ONNX model","Optimizers","Visualization","Using AMP: Automatic Mixed Precision","Accelerated Backend Tools","Intel MKL-DNN","Install MXNet with MKL-DNN","Profiling MXNet Models","Use TVM","Compression","Deploy with 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