Metadata-Version: 2.1
Name: model-X
Version: 0.1.4
Summary: This package contains collection of models
Home-page: https://github.com/Ankur3107/ModelX
Author: Ankur Singh
Author-email: ankur310794@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown

# Model_X

Model_X package is a collection of different NLP architecture models.

# Implementation

## 1. BiLSTM+BiGRU Architectures

### a. BiLSTMGRUSpatialDropout1D

    from model_X.bilstm_architectures import *
    from model_X.dense_architectures import DenseLayerModel
    from tensorflow.keras.layers import *
    from tensorflow.keras.models import Model

    input_shape = (100,)
    model_input = Input(shape=input_shape)
    bilstm_layers = BiLSTMGRUSpatialDropout1D(10, 100)(model_input)
    dense_layers = DenseLayerModel()(bilstm_layers)
    output = Dense(3, activation='softmax')(dense_layers)
    full_model = Model(inputs=model_input, outputs=output)
    print(full_model.summary())

### b. BiLSTMGRUSelfAttention

    from model_X.bilstm_architectures import *
    from model_X.dense_architectures import DenseLayerModel
    from tensorflow.keras.layers import *
    from tensorflow.keras.models import Model

    input_shape = (100,)
    model_input = Input(shape=input_shape)
    bilstm_layers = BiLSTMGRUAttention(10, 100)(model_input)
    dense_layers = DenseLayerModel()(bilstm_layers)
    output = Dense(3, activation='softmax')(dense_layers)
    full_model = Model(inputs=model_input, outputs=output)
    print(full_model.summary())

### c.  BiLSTMGRUMultiHeadAttention

    from model_X.bilstm_architectures import *
    from model_X.dense_architectures import DenseLayerModel
    from tensorflow.keras.layers import *
    from tensorflow.keras.models import Model

    input_shape = (100,)
    model_input = Input(shape=input_shape)
    bilstm_layers = BiLSTMGRUMultiHeadAttention(10, 100)(model_input)
    dense_layers = DenseLayerModel()(bilstm_layers)
    output = Dense(3, activation='softmax')(dense_layers)
    full_model = Model(inputs=model_input, outputs=output)
    print(full_model.summary())

### d.  SplitBiLSTMGRUSpatialDropout1D

    from model_X.bilstm_architectures import *
    from model_X.dense_architectures import DenseLayerModel
    from tensorflow.keras.layers import *
    from tensorflow.keras.models import Model

    input_shape = (100,)
    model_input = Input(shape=input_shape)
    bilstm_layers = SplitBiLSTMGRUSpatialDropout1D(10, 100)(model_input)
    dense_layers = DenseLayerModel()(bilstm_layers)
    output = Dense(3, activation='softmax')(dense_layers)
    full_model = Model(inputs=model_input, outputs=output)
    print(full_model.summary())

### e.  SplitBiLSTMGRU

    from model_X.bilstm_architectures import *
    from model_X.dense_architectures import DenseLayerModel
    from tensorflow.keras.layers import *
    from tensorflow.keras.models import Model

    input_shape = (100,)
    model_input = Input(shape=input_shape)
    bilstm_layers = SplitBiLSTMGRU(10, 100)(model_input)
    dense_layers = DenseLayerModel()(bilstm_layers)
    output = Dense(3, activation='softmax')(dense_layers)
    full_model = Model(inputs=model_input, outputs=output)
    print(full_model.summary())

## 2. Dense Architectures


### a. DenseLayerModel

    from model_X.dense_architectures import DenseLayerModel
    from tensorflow.keras.layers import *
    from tensorflow.keras.models import Model

    input_shape = (100,)
    model_input = Input(shape=input_shape)
    dense_layers = DenseLayerModel()(model_input)
    output = Dense(3, activation='softmax')(dense_layers)
    full_model = Model(inputs=model_input, outputs=output)
    print(full_model.summary())




