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README_model_list.md

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Model, data, ... definition

model_uri    = "model_tf.1_lstm.py"
model_pars   = {  "num_layers": 1,
                  "size": ncol_input, "size_layer": 128, "output_size": ncol_output, "timestep": 4,
                }
data_pars    = {"data_path": "/folder/myfile.csv"  , "data_type": "pandas" }
compute_pars = { "learning_rate": 0.001, }

out_pars     = { "path": "ztest_1lstm/", "model_path" : "ztest_1lstm/model/"}
save_pars    = { "path" : "ztest_1lstm/model/" }
load_pars    = { "path" : "ztest_1lstm/model/" }

Using local module (which contain the model)

from mlmodels.models import module_load

module        =  module_load( model_uri= model_uri )                           # Load file definition
model         =  module.Model(model_pars, data_pars, compute_pars)             # Create Model instance
model, sess   =  module.fit(model, data_pars, compute_pars, out_pars)          # fit the model
metrics_val   =  module.fit_metrics( model, sess, data_pars, compute_pars, out_pars) # get stats
module.save(model, sess, save_pars)



#### Inference
model, sess = module.load(load_pars)    #Create Model instance
ypred       = module.predict(model, sess,  data_pars, compute_pars, out_pars)     # predict pipeline
Using Generic API : Common to all models, models.py methods
from mlmodels.models import module_load, create_model, fit, predict, stats
from mlmodels.models import load  # Load model weights

module        =  module_load( model_uri= model_uri )                           # Load file definition
model         =  model_create(module, model_pars, data_pars, compute_pars)     # Create Model instance
model, sess   =  fit(model, data_pars, compute_pars, out_pars)                 # fit the model
metrics_val   =  fit_metrics( model, sess, data_pars, compute_pars, out_pars)  # get stats

save(model, sess, save_pars)



#### Inference
load_pars = { "path" : "ztest_1lstm/model/", "model_type": "model_tf" }

model, sess  = load( load_pars )       # Create Model instance
ypred        = predict(model, module, sess,  data_pars, compute_pars, out_pars)

Model list

--model_uri








mlmodels.model_gluon.gluon_automl.py
mlmodels.model_gluon.gluon_deepar.py
mlmodels.model_gluon.gluon_ffn.py
mlmodels.model_gluon.gluon_prophet.py


mlmodels.model_keras.01_deepctr.py
mlmodels.model_keras.02_cnn.py
mlmodels.model_keras.armdn.py
mlmodels.model_keras.charcnn.py
mlmodels.model_keras.charcnn_zhang.py
mlmodels.model_keras.namentity_crm_bilstm.py
mlmodels.model_keras.textcnn.py
mlmodels.model_keras.textvae.py




mlmodels.model_sklearn.model_lightgbm.py
mlmodels.model_sklearn.model_sklearn.py


mlmodels.model_tch.02_mlp.py
mlmodels.model_tch.03_nbeats.py
mlmodels.model_tch.pplm.py
mlmodels.model_tch.textcnn.py
mlmodels.model_tch.torchhub.py
mlmodels.model_tch.transformer_classifier.py
mlmodels.model_tch.transformer_sentence.py


mlmodels.model_tf.1_lstm.py