MatchZoo Model Reference

DenseBaseline

Model Documentation

A simple densely connected baseline model.

Examples:

>>> model = DenseBaseline()
>>> model.params['mlp_num_layers'] = 2
>>> model.params['mlp_num_units'] = 300
>>> model.params['mlp_num_fan_out'] = 128
>>> model.params['mlp_activation_func'] = 'relu'
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.dense_baseline.DenseBaseline’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	with_multi_layer_perceptron	A flag of whether a multiple layer perceptron is used. Shouldn’t be changed.	True
10	mlp_num_units	Number of units in first mlp_num_layers layers.	256	quantitative uniform distribution in [16, 512), with a step size of 1
11	mlp_num_layers	Number of layers of the multiple layer percetron.	3	quantitative uniform distribution in [1, 5), with a step size of 1
12	mlp_num_fan_out	Number of units of the layer that connects the multiple layer percetron and the output.	64	quantitative uniform distribution in [4, 128), with a step size of 4
13	mlp_activation_func	Activation function used in the multiple layer perceptron.	relu

DSSM

Model Documentation

Deep structured semantic model.

Examples:

>>> model = DSSM()
>>> model.params['mlp_num_layers'] = 3
>>> model.params['mlp_num_units'] = 300
>>> model.params['mlp_num_fan_out'] = 128
>>> model.params['mlp_activation_func'] = 'relu'
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.dssm.DSSM’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_multi_layer_perceptron	A flag of whether a multiple layer perceptron is used. Shouldn’t be changed.	True
4	mlp_num_units	Number of units in first mlp_num_layers layers.	128	quantitative uniform distribution in [8, 256), with a step size of 8
5	mlp_num_layers	Number of layers of the multiple layer percetron.	3	quantitative uniform distribution in [1, 6), with a step size of 1
6	mlp_num_fan_out	Number of units of the layer that connects the multiple layer percetron and the output.	64	quantitative uniform distribution in [4, 128), with a step size of 4
7	mlp_activation_func	Activation function used in the multiple layer perceptron.	relu
8	vocab_size	Size of vocabulary.	419

CDSSM

Model Documentation

CDSSM Model implementation.

Learning Semantic Representations Using Convolutional Neural Networks for Web Search. (2014a) A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval. (2014b)

Examples:

>>> import matchzoo as mz
>>> model = CDSSM()
>>> model.params['task'] = mz.tasks.Ranking()
>>> model.params['vocab_size'] = 4
>>> model.params['filters'] =  32
>>> model.params['kernel_size'] = 3
>>> model.params['conv_activation_func'] = 'relu'
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.cdssm.CDSSM’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_multi_layer_perceptron	A flag of whether a multiple layer perceptron is used. Shouldn’t be changed.	True
4	mlp_num_units	Number of units in first mlp_num_layers layers.	128	quantitative uniform distribution in [8, 256), with a step size of 8
5	mlp_num_layers	Number of layers of the multiple layer percetron.	3	quantitative uniform distribution in [1, 6), with a step size of 1
6	mlp_num_fan_out	Number of units of the layer that connects the multiple layer percetron and the output.	64	quantitative uniform distribution in [4, 128), with a step size of 4
7	mlp_activation_func	Activation function used in the multiple layer perceptron.	relu
8	vocab_size	Size of vocabulary.	419
9	filters	Number of filters in the 1D convolution layer.	3
10	kernel_size	Number of kernel size in the 1D convolution layer.	3
11	conv_activation_func	Activation function in the convolution layer.	relu
12	dropout_rate	The dropout rate.	0.3

DRMM

Model Documentation

DRMM Model.

Examples:

>>> model = DRMM()
>>> model.params['mlp_num_layers'] = 1
>>> model.params['mlp_num_units'] = 5
>>> model.params['mlp_num_fan_out'] = 1
>>> model.params['mlp_activation_func'] = 'tanh'
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.drmm.DRMM’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	with_multi_layer_perceptron	A flag of whether a multiple layer perceptron is used. Shouldn’t be changed.	True
10	mlp_num_units	Number of units in first mlp_num_layers layers.	128	quantitative uniform distribution in [8, 256), with a step size of 8
11	mlp_num_layers	Number of layers of the multiple layer percetron.	3	quantitative uniform distribution in [1, 6), with a step size of 1
12	mlp_num_fan_out	Number of units of the layer that connects the multiple layer percetron and the output.	1	quantitative uniform distribution in [4, 128), with a step size of 4
13	mlp_activation_func	Activation function used in the multiple layer perceptron.	relu
14	mask_value	The value to be masked from inputs.	0
15	hist_bin_size	The number of bin size of the histogram.	30

DRMMTKS

Model Documentation

DRMMTKS Model.

Examples:

>>> model = DRMMTKS()
>>> model.params['top_k'] = 10
>>> model.params['mlp_num_layers'] = 1
>>> model.params['mlp_num_units'] = 5
>>> model.params['mlp_num_fan_out'] = 1
>>> model.params['mlp_activation_func'] = 'tanh'
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.drmmtks.DRMMTKS’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	with_multi_layer_perceptron	A flag of whether a multiple layer perceptron is used. Shouldn’t be changed.	True
10	mlp_num_units	Number of units in first mlp_num_layers layers.	128	quantitative uniform distribution in [8, 256), with a step size of 8
11	mlp_num_layers	Number of layers of the multiple layer percetron.	3	quantitative uniform distribution in [1, 6), with a step size of 1
12	mlp_num_fan_out	Number of units of the layer that connects the multiple layer percetron and the output.	1	quantitative uniform distribution in [4, 128), with a step size of 4
13	mlp_activation_func	Activation function used in the multiple layer perceptron.	relu
14	mask_value	The value to be masked from inputs.	0
15	top_k	Size of top-k pooling layer.	10	quantitative uniform distribution in [2, 100), with a step size of 1

ESIM

Model Documentation

ESIM Model.

Examples:

>>> model = ESIM()
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.esim.ESIM’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	mask_value	The value to be masked from inputs.	0
10	dropout	Dropout rate.	0.2
11	hidden_size	Hidden size.	200
12	lstm_layer	Number of LSTM layers	1
13	drop_lstm	Whether dropout LSTM.	False
14	concat_lstm	Whether concat intermediate outputs.	True
15	rnn_type	Choose rnn type, lstm or gru.	lstm

KNRM

Model Documentation

KNRM Model.

Examples:

>>> model = KNRM()
>>> model.params['kernel_num'] = 11
>>> model.params['sigma'] = 0.1
>>> model.params['exact_sigma'] = 0.001
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.knrm.KNRM’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	kernel_num	The number of RBF kernels.	11	quantitative uniform distribution in [5, 20), with a step size of 1
10	sigma	The sigma defines the kernel width.	0.1	quantitative uniform distribution in [0.01, 0.2), with a step size of 0.01
11	exact_sigma	The exact_sigma denotes the sigma for exact match.	0.001

ConvKNRM

Model Documentation

ConvKNRM Model.

Examples:

>>> model = ConvKNRM()
>>> model.params['filters'] = 128
>>> model.params['conv_activation_func'] = 'tanh'
>>> model.params['max_ngram'] = 3
>>> model.params['use_crossmatch'] = True
>>> model.params['kernel_num'] = 11
>>> model.params['sigma'] = 0.1
>>> model.params['exact_sigma'] = 0.001
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.conv_knrm.ConvKNRM’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	filters	The filter size in the convolution layer.	128
10	conv_activation_func	The activation function in the convolution layer.	relu
11	max_ngram	The maximum length of n-grams for the convolution layer.	3
12	use_crossmatch	Whether to match left n-grams and right n-grams of different lengths	True
13	kernel_num	The number of RBF kernels.	11	quantitative uniform distribution in [5, 20), with a step size of 1
14	sigma	The sigma defines the kernel width.	0.1	quantitative uniform distribution in [0.01, 0.2), with a step size of 0.01
15	exact_sigma	The exact_sigma denotes the sigma for exact match.	0.001

BiMPM

Model Documentation

BiMPM Model.

Reference: - https://github.com/galsang/BIMPM-pytorch/blob/master/model/BIMPM.py

Examples:

>>> model = BiMPM()
>>> model.params['num_perspective'] = 4
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.bimpm.BiMPM’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	mask_value	The value to be masked from inputs.	0
10	dropout	Dropout rate.	0.2
11	hidden_size	Hidden size.	100	quantitative uniform distribution in [100, 300), with a step size of 100
12	num_perspective	num_perspective	20	quantitative uniform distribution in [20, 100), with a step size of 20

MatchLSTM

Model Documentation

MatchLSTM Model.

https://github.com/shuohangwang/mprc/blob/master/qa/rankerReader.lua.

Examples:

>>> model = MatchLSTM()
>>> model.params['dropout'] = 0.2
>>> model.params['hidden_size'] = 200
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.matchlstm.MatchLSTM’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	mask_value	The value to be masked from inputs.	0
10	dropout	Dropout rate.	0.2
11	hidden_size	Hidden size.	200
12	lstm_layer	Number of LSTM layers	1
13	drop_lstm	Whether dropout LSTM.	False
14	concat_lstm	Whether concat intermediate outputs.	True
15	rnn_type	Choose rnn type, lstm or gru.	lstm

ArcI

Model Documentation

ArcI Model.

Examples:

>>> model = ArcI()
>>> model.params['left_filters'] = [32]
>>> model.params['right_filters'] = [32]
>>> model.params['left_kernel_sizes'] = [3]
>>> model.params['right_kernel_sizes'] = [3]
>>> model.params['left_pool_sizes'] = [2]
>>> model.params['right_pool_sizes'] = [4]
>>> model.params['conv_activation_func'] = 'relu'
>>> model.params['mlp_num_layers'] = 1
>>> model.params['mlp_num_units'] = 64
>>> model.params['mlp_num_fan_out'] = 32
>>> model.params['mlp_activation_func'] = 'relu'
>>> model.params['dropout_rate'] = 0.5
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.arci.ArcI’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	with_multi_layer_perceptron	A flag of whether a multiple layer perceptron is used. Shouldn’t be changed.	True
10	mlp_num_units	Number of units in first mlp_num_layers layers.	128	quantitative uniform distribution in [8, 256), with a step size of 8
11	mlp_num_layers	Number of layers of the multiple layer percetron.	3	quantitative uniform distribution in [1, 6), with a step size of 1
12	mlp_num_fan_out	Number of units of the layer that connects the multiple layer percetron and the output.	64	quantitative uniform distribution in [4, 128), with a step size of 4
13	mlp_activation_func	Activation function used in the multiple layer perceptron.	relu
14	left_length	Length of left input.	10
15	right_length	Length of right input.	100
16	conv_activation_func	The activation function in the convolution layer.	relu
17	left_filters	The filter size of each convolution blocks for the left input.	[32]
18	left_kernel_sizes	The kernel size of each convolution blocks for the left input.	[3]
19	left_pool_sizes	The pooling size of each convolution blocks for the left input.	[2]
20	right_filters	The filter size of each convolution blocks for the right input.	[32]
21	right_kernel_sizes	The kernel size of each convolution blocks for the right input.	[3]
22	right_pool_sizes	The pooling size of each convolution blocks for the right input.	[2]
23	dropout_rate	The dropout rate.	0.0	quantitative uniform distribution in [0.0, 0.8), with a step size of 0.01

ArcII

Model Documentation

ArcII Model.

Examples:

>>> model = ArcII()
>>> model.params['embedding_output_dim'] = 300
>>> model.params['kernel_1d_count'] = 32
>>> model.params['kernel_1d_size'] = 3
>>> model.params['kernel_2d_count'] = [16, 32]
>>> model.params['kernel_2d_size'] = [[3, 3], [3, 3]]
>>> model.params['pool_2d_size'] = [[2, 2], [2, 2]]
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.arcii.ArcII’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	left_length	Length of left input.	10
10	right_length	Length of right input.	100
11	kernel_1d_count	Kernel count of 1D convolution layer.	32
12	kernel_1d_size	Kernel size of 1D convolution layer.	3
13	kernel_2d_count	Kernel count of 2D convolution layer ineach block	[32]
14	kernel_2d_size	Kernel size of 2D convolution layer in each block.	[(3, 3)]
15	activation	Activation function.	relu
16	pool_2d_size	Size of pooling layer in each block.	[(2, 2)]
17	dropout_rate	The dropout rate.	0.0	quantitative uniform distribution in [0.0, 0.8), with a step size of 0.01

Bert

Model Documentation

Bert Model.

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.bert.Bert’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	mode	Pretrained Bert model.	bert-base-uncased
4	dropout_rate	The dropout rate.	0.0	quantitative uniform distribution in [0.0, 0.8), with a step size of 0.01

MVLSTM

Model Documentation

MVLSTM Model.

Examples:

>>> model = MVLSTM()
>>> model.params['hidden_size'] = 32
>>> model.params['top_k'] = 50
>>> model.params['mlp_num_layers'] = 2
>>> model.params['mlp_num_units'] = 20
>>> model.params['mlp_num_fan_out'] = 10
>>> model.params['mlp_activation_func'] = 'relu'
>>> model.params['dropout_rate'] = 0.0
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.mvlstm.MVLSTM’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	with_multi_layer_perceptron	A flag of whether a multiple layer perceptron is used. Shouldn’t be changed.	True
10	mlp_num_units	Number of units in first mlp_num_layers layers.	128	quantitative uniform distribution in [8, 256), with a step size of 8
11	mlp_num_layers	Number of layers of the multiple layer percetron.	3	quantitative uniform distribution in [1, 6), with a step size of 1
12	mlp_num_fan_out	Number of units of the layer that connects the multiple layer percetron and the output.	64	quantitative uniform distribution in [4, 128), with a step size of 4
13	mlp_activation_func	Activation function used in the multiple layer perceptron.	relu
14	hidden_size	Integer, the hidden size in the bi-directional LSTM layer.	32
15	num_layers	Integer, number of recurrent layers.	1
16	top_k	Size of top-k pooling layer.	10	quantitative uniform distribution in [2, 100), with a step size of 1
17	dropout_rate	Float, the dropout rate.	0.0	quantitative uniform distribution in [0.0, 0.8), with a step size of 0.01

MatchPyramid

Model Documentation

MatchPyramid Model.

Examples:

>>> model = MatchPyramid()
>>> model.params['embedding_output_dim'] = 300
>>> model.params['kernel_count'] = [16, 32]
>>> model.params['kernel_size'] = [[3, 3], [3, 3]]
>>> model.params['dpool_size'] = [3, 10]
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.match_pyramid.MatchPyramid’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	kernel_count	The kernel count of the 2D convolution of each block.	[32]
10	kernel_size	The kernel size of the 2D convolution of each block.	[[3, 3]]
11	activation	The activation function.	relu
12	dpool_size	The max-pooling size of each block.	[3, 10]
13	dropout_rate	The dropout rate.	0.0	quantitative uniform distribution in [0.0, 0.8), with a step size of 0.01

aNMM

Model Documentation

aNMM: Ranking Short Answer Texts with Attention-Based Neural Matching Model.

Examples:

>>> model = aNMM()
>>> model.params['embedding_output_dim'] = 300
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.anmm.aNMM’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	mask_value	The value to be masked from inputs.	0
10	num_bins	Integer, number of bins.	200
11	hidden_sizes	Number of hidden size for each hidden layer	[100]
12	activation	The activation function.	relu
13	dropout_rate	The dropout rate.	0.0	quantitative uniform distribution in [0.0, 0.8), with a step size of 0.01

HBMP

Model Documentation

HBMP model.

Examples:

>>> model = HBMP()
>>> model.params['embedding_input_dim'] = 200
>>> model.params['embedding_output_dim'] = 100
>>> model.params['mlp_num_layers'] = 1
>>> model.params['mlp_num_units'] = 10
>>> model.params['mlp_num_fan_out'] = 10
>>> model.params['mlp_activation_func'] = nn.LeakyReLU(0.1)
>>> model.params['lstm_hidden_size'] = 5
>>> model.params['lstm_num'] = 3
>>> model.params['num_layers'] = 3
>>> model.params['dropout_rate'] = 0.1
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.hbmp.HBMP’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	with_multi_layer_perceptron	A flag of whether a multiple layer perceptron is used. Shouldn’t be changed.	True
10	mlp_num_units	Number of units in first mlp_num_layers layers.	128	quantitative uniform distribution in [8, 256), with a step size of 8
11	mlp_num_layers	Number of layers of the multiple layer percetron.	3	quantitative uniform distribution in [1, 6), with a step size of 1
12	mlp_num_fan_out	Number of units of the layer that connects the multiple layer percetron and the output.	64	quantitative uniform distribution in [4, 128), with a step size of 4
13	mlp_activation_func	Activation function used in the multiple layer perceptron.	relu
14	lstm_hidden_size	Integer, the hidden size of the bi-directional LSTM layer.	5
15	lstm_num	Integer, number of LSTM units	3
16	num_layers	Integer, number of LSTM layers.	1
17	dropout_rate	The dropout rate.	0.0	quantitative uniform distribution in [0.0, 0.8), with a step size of 0.01

DUET

Model Documentation

Duet Model.

Examples:

>>> model = DUET()
>>> model.params['left_length'] = 10
>>> model.params['right_length'] = 40
>>> model.params['lm_filters'] = 300
>>> model.params['mlp_num_layers'] = 2
>>> model.params['mlp_num_units'] = 300
>>> model.params['mlp_num_fan_out'] = 300
>>> model.params['mlp_activation_func'] = 'relu'
>>> model.params['vocab_size'] = 2000
>>> model.params['dm_filters'] = 300
>>> model.params['dm_conv_activation_func'] = 'relu'
>>> model.params['dm_kernel_size'] = 3
>>> model.params['dm_right_pool_size'] = 8
>>> model.params['dropout_rate'] = 0.5
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.duet.DUET’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_multi_layer_perceptron	A flag of whether a multiple layer perceptron is used. Shouldn’t be changed.	True
4	mlp_num_units	Number of units in first mlp_num_layers layers.	128	quantitative uniform distribution in [8, 256), with a step size of 8
5	mlp_num_layers	Number of layers of the multiple layer percetron.	3	quantitative uniform distribution in [1, 6), with a step size of 1
6	mlp_num_fan_out	Number of units of the layer that connects the multiple layer percetron and the output.	64	quantitative uniform distribution in [4, 128), with a step size of 4
7	mlp_activation_func	Activation function used in the multiple layer perceptron.	relu
8	mask_value	The value to be masked from inputs.	0
9	left_length	Length of left input.	10
10	right_length	Length of right input.	40
11	lm_filters	Filter size of 1D convolution layer in the local model.	300
12	vocab_size	Vocabulary size of the tri-letters used in the distributed model.	419
13	dm_filters	Filter size of 1D convolution layer in the distributed model.	300
14	dm_kernel_size	Kernel size of 1D convolution layer in the distributed model.	3
15	dm_conv_activation_func	Activation functions of the convolution layer in the distributed model.	relu
16	dm_right_pool_size	Kernel size of 1D convolution layer in the distributed model.	8
17	dropout_rate	The dropout rate.	0.5	quantitative uniform distribution in [0.0, 0.8), with a step size of 0.02

DIIN

Model Documentation

DIIN model.

Examples:

>>> model = DIIN()
>>> model.params['embedding_input_dim'] = 10000
>>> model.params['embedding_output_dim'] = 300
>>> model.params['mask_value'] = 0
>>> model.params['char_embedding_input_dim'] = 100
>>> model.params['char_embedding_output_dim'] = 8
>>> model.params['char_conv_filters'] = 100
>>> model.params['char_conv_kernel_size'] = 5
>>> model.params['first_scale_down_ratio'] = 0.3
>>> model.params['nb_dense_blocks'] = 3
>>> model.params['layers_per_dense_block'] = 8
>>> model.params['growth_rate'] = 20
>>> model.params['transition_scale_down_ratio'] = 0.5
>>> model.params['conv_kernel_size'] = (3, 3)
>>> model.params['pool_kernel_size'] = (2, 2)
>>> model.params['dropout_rate'] = 0.2
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.diin.DIIN’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	mask_value	The value to be masked from inputs.	0
10	char_embedding_input_dim	The input dimension of character embedding layer.	100
11	char_embedding_output_dim	The output dimension of character embedding layer.	8
12	char_conv_filters	The filter size of character convolution layer.	100
13	char_conv_kernel_size	The kernel size of character convolution layer.	5
14	first_scale_down_ratio	The channel scale down ratio of the convolution layer before densenet.	0.3
15	nb_dense_blocks	The number of blocks in densenet.	3
16	layers_per_dense_block	The number of convolution layers in dense block.	8
17	growth_rate	The filter size of each convolution layer in dense block.	20
18	transition_scale_down_ratio	The channel scale down ratio of the convolution layer in transition block.	0.5
19	conv_kernel_size	The kernel size of convolution layer in dense block.	(3, 3)
20	pool_kernel_size	The kernel size of pooling layer in transition block.	(2, 2)
21	dropout_rate	The dropout rate.	0.0	quantitative uniform distribution in [0.0, 0.8), with a step size of 0.01

MatchSRNN

Model Documentation

Match-SRNN Model.

Examples:

>>> model = MatchSRNN()
>>> model.params['channels'] = 4
>>> model.params['units'] = 10
>>> model.params['dropout'] = 0.2
>>> model.params['direction'] = 'lt'
>>> model.guess_and_fill_missing_params(verbose=0)
>>> model.build()

Model Hyper Parameters

	Name	Description	Default Value	Default Hyper-Space
0	model_class	Model class. Used internally for save/load. Changing this may cause unexpected behaviors.	<class ‘matchzoo.models.match_srnn.MatchSRNN’>
1	task	Decides model output shape, loss, and metrics.
2	out_activation_func	Activation function used in output layer.
3	with_embedding	A flag used help auto module. Shouldn’t be changed.	True
4	embedding	FloatTensor containing weights for the Embedding.
5	embedding_input_dim	Usually equals vocab size + 1. Should be set manually.
6	embedding_output_dim	Should be set manually.
7	padding_idx	If given, pads the output with the embedding vector atpadding_idx (initialized to zeros) whenever it encountersthe index.	0
8	embedding_freeze	True to freeze embedding layer training, False to enable embedding parameters.	False
9	channels	Number of word interaction tensor channels	4
10	units	Number of SpatialGRU units	10
11	direction	Direction of SpatialGRU scanning	lt
12	dropout	The dropout rate.	0.2	quantitative uniform distribution in [0.0, 0.8), with a step size of 0.01