echotorch.tools package¶
Submodules¶
echotorch.utils.error_measures module¶
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echotorch.utils.error_measures.
cumperplexity
(output_probs, targets, log=False)¶ Cumulative perplexity :param output_probs: :param targets: :param log: :return:
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echotorch.utils.error_measures.
generalized_squared_cosine
(Sa, Ua, Sb, Ub)¶ Generalized square cosine :param Sa: :param Ua: :param Sb: :param Ub: :return:
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echotorch.utils.error_measures.
mse
(outputs, targets)¶ Mean square error :param outputs: Module’s outputs :param targets: Target signal to be learned :return: Mean square deviation
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echotorch.utils.error_measures.
nmse
(outputs, targets)¶ Normalized mean square error :param outputs: Module’s output :param targets: Target signal to be learned :return: Normalized mean square deviation
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echotorch.utils.error_measures.
nrmse
(outputs, targets)¶ Normalized root-mean square error :param outputs: Module’s outputs :param targets: Target signal to be learned :return: Normalized root-mean square deviation
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echotorch.utils.error_measures.
perplexity
(output_probs, targets, log=False)¶ Perplexity :param output_probs: Output probabilities for each word/tokens (length x n_tokens) :param targets: Real word index :return: Perplexity
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echotorch.utils.error_measures.
rmse
(outputs, targets)¶ Root-mean square error :param outputs: Module’s outputs :param targets: Target signal to be learned :return: Root-mean square deviation
echotorch.utils.utility_functions module¶
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echotorch.utils.utility_functions.
align_pattern
(interpolation_rate, truth_pattern, generated_pattern)¶ Align pattern :param interpolation_rate: :param truth_pattern: :param generated_pattern: :return:
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echotorch.utils.utility_functions.
average_prob
(tensor, dim=0)¶ Average probabilities through time :param tensor: :param dim: :return:
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echotorch.utils.utility_functions.
compute_correlation_matrix
(states)¶ Compute correlation matrix :param states: :return:
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echotorch.utils.utility_functions.
compute_similarity_matrix
(svd_list)¶ Compute similarity matrix :param svd_list: :return:
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echotorch.utils.utility_functions.
compute_singular_values
(stats)¶ Compute singular values :param states: :return:
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echotorch.utils.utility_functions.
deep_spectral_radius
(m, leaky_rate)¶ Compute spectral radius of a square 2-D tensor for stacked-ESN :param m: squared 2D tensor :param leaky_rate: Layer’s leaky rate :return:
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echotorch.utils.utility_functions.
find_phase_shift
(p, y, interpolation_rate, error_measure=<function nrmse>)¶ Find phase shift :param s1: :param s2: :param window_size: :return:
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echotorch.utils.utility_functions.
max_average_through_time
(tensor, dim=0)¶ Max average through time :param tensor: :param dim: Time dimension :return:
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echotorch.utils.utility_functions.
normalize
(tensor, dim=1)¶ Normalize a tensor on a single dimension :param t: :return:
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echotorch.utils.utility_functions.
spectral_radius
(m)¶ Compute spectral radius of a square 2-D tensor :param m: squared 2D tensor :return:
Module contents¶
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echotorch.utils.
align_pattern
(interpolation_rate, truth_pattern, generated_pattern)¶ Align pattern :param interpolation_rate: :param truth_pattern: :param generated_pattern: :return:
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echotorch.utils.
compute_correlation_matrix
(states)¶ Compute correlation matrix :param states: :return:
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echotorch.utils.
nrmse
(outputs, targets)¶ Normalized root-mean square error :param outputs: Module’s outputs :param targets: Target signal to be learned :return: Normalized root-mean square deviation
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echotorch.utils.
nmse
(outputs, targets)¶ Normalized mean square error :param outputs: Module’s output :param targets: Target signal to be learned :return: Normalized mean square deviation
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echotorch.utils.
rmse
(outputs, targets)¶ Root-mean square error :param outputs: Module’s outputs :param targets: Target signal to be learned :return: Root-mean square deviation
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echotorch.utils.
mse
(outputs, targets)¶ Mean square error :param outputs: Module’s outputs :param targets: Target signal to be learned :return: Mean square deviation
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echotorch.utils.
perplexity
(output_probs, targets, log=False)¶ Perplexity :param output_probs: Output probabilities for each word/tokens (length x n_tokens) :param targets: Real word index :return: Perplexity
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echotorch.utils.
cumperplexity
(output_probs, targets, log=False)¶ Cumulative perplexity :param output_probs: :param targets: :param log: :return:
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echotorch.utils.
spectral_radius
(m)¶ Compute spectral radius of a square 2-D tensor :param m: squared 2D tensor :return:
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echotorch.utils.
deep_spectral_radius
(m, leaky_rate)¶ Compute spectral radius of a square 2-D tensor for stacked-ESN :param m: squared 2D tensor :param leaky_rate: Layer’s leaky rate :return:
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echotorch.utils.
normalize
(tensor, dim=1)¶ Normalize a tensor on a single dimension :param t: :return:
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echotorch.utils.
average_prob
(tensor, dim=0)¶ Average probabilities through time :param tensor: :param dim: :return:
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echotorch.utils.
max_average_through_time
(tensor, dim=0)¶ Max average through time :param tensor: :param dim: Time dimension :return:
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echotorch.utils.
show_3d_timeseries
(ts, title)¶ Show 3D timeseries :param axis: :param title: :return:
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echotorch.utils.
show_2d_timeseries
(ts, title)¶ Show 2D timeseries :param ts: :param title: :return:
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echotorch.utils.
show_1d_timeseries
(ts, title, xmin, xmax, ymin, ymax, start=0, timesteps=-1)¶ Show 1D time series :param ts: :param title: :return:
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echotorch.utils.
neurons_activities_1d
(stats, neurons, title, colors, xmin, xmax, ymin, ymax, timesteps=-1, start=0)¶ Display neurons activities :param stats: :param neurons: :return:
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echotorch.utils.
neurons_activities_2d
(stats, neurons, title, colors, timesteps=-1, start=0)¶ Display neurons activities on a 2D plot :param stats: :param neurons: :param title: :param timesteps: :param start: :return:
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echotorch.utils.
neurons_activities_3d
(stats, neurons, title, timesteps=-1, start=0)¶ Display neurons activities on a 3D plot :param stats: :param neurons: :param title: :param timesteps: :param start: :return:
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echotorch.utils.
plot_singular_values
(stats, title, xmin, xmax, ymin, ymax, log=False)¶ Plot singular values :param stats: :param title: :param timestep: :param start: :return:
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echotorch.utils.
compute_singular_values
(stats)¶ Compute singular values :param states: :return:
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echotorch.utils.
generalized_squared_cosine
(Sa, Ua, Sb, Ub)¶ Generalized square cosine :param Sa: :param Ua: :param Sb: :param Ub: :return:
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echotorch.utils.
compute_similarity_matrix
(svd_list)¶ Compute similarity matrix :param svd_list: :return:
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echotorch.utils.
show_similarity_matrix
(sim_matrix, title, column_labels=None, row_labels=None)¶ Show similarity matrix :param sim_matrix: :return:
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echotorch.utils.
show_conceptors_similarity_matrix
(conceptors, title)¶ Show conceptors similarity matrix :param conceptors: :param title: :return:
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echotorch.utils.
show_sv_for_increasing_aperture
(conceptor, factor, title)¶ Show singular values for increasing aperture :param conceptors: :param factor: :param title: :return:
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echotorch.utils.
find_phase_shift
(p, y, interpolation_rate, error_measure=<function nrmse>)¶ Find phase shift :param s1: :param s2: :param window_size: :return: