Run 10452580

Task 2295 (Supervised Regression) cholesterol Uploaded 21-04-2020 by Prabhant Singh
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads

Issue	#Downvotes for this reason	By

Flow

mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)	Automatically created MXNet flow.
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_00_data	{"inputs": [], "name": "data", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_01_hybridsequential0_batchnorm0_gamma	{"attrs": {"__dtype__": "0", "__init__": "ones", "__lr_mult__": "1.0", "__shape__": "(0,)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_batchnorm0_gamma", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_02_hybridsequential0_batchnorm0_beta	{"attrs": {"__dtype__": "0", "__init__": "zeros", "__lr_mult__": "1.0", "__shape__": "(0,)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_batchnorm0_beta", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_03_hybridsequential0_batchnorm0_running_mean	{"attrs": {"__dtype__": "0", "__init__": "zeros", "__lr_mult__": "1.0", "__shape__": "(0,)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_batchnorm0_running_mean", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_04_hybridsequential0_batchnorm0_running_var	{"attrs": {"__dtype__": "0", "__init__": "ones", "__lr_mult__": "1.0", "__shape__": "(0,)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_batchnorm0_running_var", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_05_hybridsequential0_batchnorm0_fwd	{"attrs": {"axis": "1", "eps": "1e-05", "fix_gamma": "False", "momentum": "0.9", "use_global_stats": "False"}, "inputs": [[0, 0, 0], [1, 0, 0], [2, 0, 0], [3, 0, 8], [4, 0, 8]], "name": "hybridsequential0_batchnorm0_fwd", "op": "BatchNorm"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_06_hybridsequential0_dense0_weight	{"attrs": {"__dtype__": "0", "__lr_mult__": "1.0", "__shape__": "(1024, 0)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_dense0_weight", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_07_hybridsequential0_dense0_bias	{"attrs": {"__dtype__": "0", "__init__": "zeros", "__lr_mult__": "1.0", "__shape__": "(1024,)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_dense0_bias", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_08_hybridsequential0_dense0_fwd	{"attrs": {"flatten": "True", "no_bias": "False", "num_hidden": "1024"}, "inputs": [[5, 0, 0], [6, 0, 0], [7, 0, 0]], "name": "hybridsequential0_dense0_fwd", "op": "FullyConnected"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_09_hybridsequential0_dense0_relu_fwd	{"attrs": {"act_type": "relu"}, "inputs": [[8, 0, 0]], "name": "hybridsequential0_dense0_relu_fwd", "op": "Activation"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_10_hybridsequential0_dropout0_fwd	{"attrs": {"axes": "()", "p": "0.4"}, "inputs": [[9, 0, 0]], "name": "hybridsequential0_dropout0_fwd", "op": "Dropout"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_11_hybridsequential0_dense1_weight	{"attrs": {"__dtype__": "0", "__lr_mult__": "1.0", "__shape__": "(512, 0)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_dense1_weight", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_12_hybridsequential0_dense1_bias	{"attrs": {"__dtype__": "0", "__init__": "zeros", "__lr_mult__": "1.0", "__shape__": "(512,)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_dense1_bias", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_13_hybridsequential0_dense1_fwd	{"attrs": {"flatten": "True", "no_bias": "False", "num_hidden": "512"}, "inputs": [[10, 0, 0], [11, 0, 0], [12, 0, 0]], "name": "hybridsequential0_dense1_fwd", "op": "FullyConnected"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_14_hybridsequential0_dense1_relu_fwd	{"attrs": {"act_type": "relu"}, "inputs": [[13, 0, 0]], "name": "hybridsequential0_dense1_relu_fwd", "op": "Activation"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_15_hybridsequential0_dropout1_fwd	{"attrs": {"axes": "()", "p": "0.4"}, "inputs": [[14, 0, 0]], "name": "hybridsequential0_dropout1_fwd", "op": "Dropout"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_16_hybridsequential0_dense2_weight	{"attrs": {"__dtype__": "0", "__lr_mult__": "1.0", "__shape__": "(256, 0)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_dense2_weight", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_17_hybridsequential0_dense2_bias	{"attrs": {"__dtype__": "0", "__init__": "zeros", "__lr_mult__": "1.0", "__shape__": "(256,)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_dense2_bias", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_18_hybridsequential0_dense2_fwd	{"attrs": {"flatten": "True", "no_bias": "False", "num_hidden": "256"}, "inputs": [[15, 0, 0], [16, 0, 0], [17, 0, 0]], "name": "hybridsequential0_dense2_fwd", "op": "FullyConnected"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_19_hybridsequential0_dense2_relu_fwd	{"attrs": {"act_type": "relu"}, "inputs": [[18, 0, 0]], "name": "hybridsequential0_dense2_relu_fwd", "op": "Activation"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_20_hybridsequential0_dropout2_fwd	{"attrs": {"axes": "()", "p": "0.4"}, "inputs": [[19, 0, 0]], "name": "hybridsequential0_dropout2_fwd", "op": "Dropout"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_21_hybridsequential0_dense3_weight	{"attrs": {"__dtype__": "0", "__lr_mult__": "1.0", "__shape__": "(128, 0)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_dense3_weight", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_22_hybridsequential0_dense3_bias	{"attrs": {"__dtype__": "0", "__init__": "zeros", "__lr_mult__": "1.0", "__shape__": "(128,)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_dense3_bias", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_23_hybridsequential0_dense3_fwd	{"attrs": {"flatten": "True", "no_bias": "False", "num_hidden": "128"}, "inputs": [[20, 0, 0], [21, 0, 0], [22, 0, 0]], "name": "hybridsequential0_dense3_fwd", "op": "FullyConnected"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_24_hybridsequential0_dense3_relu_fwd	{"attrs": {"act_type": "relu"}, "inputs": [[23, 0, 0]], "name": "hybridsequential0_dense3_relu_fwd", "op": "Activation"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_25_hybridsequential0_dropout3_fwd	{"attrs": {"axes": "()", "p": "0.4"}, "inputs": [[24, 0, 0]], "name": "hybridsequential0_dropout3_fwd", "op": "Dropout"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_26_hybridsequential0_dense4_weight	{"attrs": {"__dtype__": "0", "__lr_mult__": "1.0", "__shape__": "(64, 0)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_dense4_weight", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_27_hybridsequential0_dense4_bias	{"attrs": {"__dtype__": "0", "__init__": "zeros", "__lr_mult__": "1.0", "__shape__": "(64,)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_dense4_bias", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_28_hybridsequential0_dense4_fwd	{"attrs": {"flatten": "True", "no_bias": "False", "num_hidden": "64"}, "inputs": [[25, 0, 0], [26, 0, 0], [27, 0, 0]], "name": "hybridsequential0_dense4_fwd", "op": "FullyConnected"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_29_hybridsequential0_dense4_relu_fwd	{"attrs": {"act_type": "relu"}, "inputs": [[28, 0, 0]], "name": "hybridsequential0_dense4_relu_fwd", "op": "Activation"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_30_hybridsequential0_dropout4_fwd	{"attrs": {"axes": "()", "p": "0.4"}, "inputs": [[29, 0, 0]], "name": "hybridsequential0_dropout4_fwd", "op": "Dropout"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_31_hybridsequential0_dense5_weight	{"attrs": {"__dtype__": "0", "__lr_mult__": "1.0", "__shape__": "(1, 0)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_dense5_weight", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_32_hybridsequential0_dense5_bias	{"attrs": {"__dtype__": "0", "__init__": "zeros", "__lr_mult__": "1.0", "__shape__": "(1,)", "__storage_type__": "0", "__wd_mult__": "1.0"}, "inputs": [], "name": "hybridsequential0_dense5_bias", "op": "null"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_33_hybridsequential0_dense5_fwd	{"attrs": {"flatten": "True", "no_bias": "False", "num_hidden": "1"}, "inputs": [[30, 0, 0], [31, 0, 0], [32, 0, 0]], "name": "hybridsequential0_dense5_fwd", "op": "FullyConnected"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_34_hybridsequential0_dense5_relu_fwd	{"attrs": {"act_type": "relu"}, "inputs": [[33, 0, 0]], "name": "hybridsequential0_dense5_relu_fwd", "op": "Activation"}
mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2)_misc	{"arg_nodes": [0, 1, 2, 3, 4, 6, 7, 11, 12, 16, 17, 21, 22, 26, 27, 31, 32], "attrs": {"mxnet_version": ["int", 10401]}, "heads": [[34, 0, 0]], "node_row_ptr": [0, 1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, 20, 21, 22, 23, 24, 26, 27, 28, 29, 30, 32, 33, 34, 35, 36, 38, 39, 40, 41, 42]}