mltk.core.MltkModelEvent

class MltkModelEvent

Events that are triggered at various stages of MltkModel execution.

See add_event_handler for more details.

Properties

BEFORE_MODEL_LOAD	Invoked before the MltkModel is fully loaded.
AFTER_MODEL_LOAD	Invoked after the MltkModel is fully loaded.
BEFORE_LOAD_DATASET	Invoked at the beginning of load_dataset
AFTER_LOAD_DATASET	Invoked at the end of load_dataset
BEFORE_UNLOAD_DATASET	Invoked at the beginning of unload_dataset
AFTER_UNLOAD_DATASET	Invoked at the end of unload_dataset
SUMMARIZE_DATASET	Invoked at the end of summarize_dataset
SUMMARIZE_MODEL	Invoked at the end of summarize_model
TRAIN_STARTUP	Invoked at the beginning of train_model
BEFORE_BUILD_TRAIN_MODEL	Invoked before build_model_function is called
AFTER_BUILD_TRAIN_MODEL	Invoked after build_model_function is called
POPULATE_TRAIN_CALLBACKS	Invoked during train_model before Keras training starts.
BEFORE_TRAIN	Invoked during train_model before Keras training
AFTER_TRAIN	Invoked during train_model after Keras training
BEFORE_SAVE_TRAIN_MODEL	Invoked during train_model before the trained model is saved
AFTER_SAVE_TRAIN_MODEL	Invoked during train_model after the trained model is saved
BEFORE_SAVE_TRAIN_RESULTS	Invoked during train_model before the training results are saved
AFTER_SAVE_TRAIN_RESULTS	Invoked during train_model after the training results are saved
BEFORE_SAVE_TRAIN_ARCHIVE	Invoked during train_model before the model archive is saved
AFTER_SAVE_TRAIN_ARCHIVE	Invoked during train_model after the model archive is saved
TRAIN_SHUTDOWN	Invoked at the end of train_model
QUANTIZE_STARTUP	Invoked at the beginning of quantize_model
BEFORE_QUANTIZE	//www.tensorflow.org/lite/convert>`_ is invoked
AFTER_QUANTIZE	Invoked during quantize_model after the TfliteConverter is invoked
QUANTIZE_SHUTDOWN	Invoked at the end of quantize_model
EVALUATE_STARTUP	Invoked at the beginning of evaluate_model
EVALUATE_SHUTDOWN	Invoked at the end of evaluate_model
GENERATE_EVALUATE_PLOT	Invoked when generating a plot during evaluate_model
AFTER_PROFILE	Invoked at the end of profile_model

Methods

__init__
capitalize	Return a capitalized version of the string.
casefold	Return a version of the string suitable for caseless comparisons.
center	Return a centered string of length width.
count	Return the number of non-overlapping occurrences of substring sub in string S[start:end].
encode	Encode the string using the codec registered for encoding.
endswith	Return True if S ends with the specified suffix, False otherwise.
expandtabs	Return a copy where all tab characters are expanded using spaces.
find	Return the lowest index in S where substring sub is found, such that sub is contained within S[start:end].
format	Return a formatted version of S, using substitutions from args and kwargs.
format_map	Return a formatted version of S, using substitutions from mapping.
index	Return the lowest index in S where substring sub is found, such that sub is contained within S[start:end].
isalnum	Return True if the string is an alpha-numeric string, False otherwise.
isalpha	Return True if the string is an alphabetic string, False otherwise.
isascii	Return True if all characters in the string are ASCII, False otherwise.
isdecimal	Return True if the string is a decimal string, False otherwise.
isdigit	Return True if the string is a digit string, False otherwise.
isidentifier	Return True if the string is a valid Python identifier, False otherwise.
islower	Return True if the string is a lowercase string, False otherwise.
isnumeric	Return True if the string is a numeric string, False otherwise.
isprintable	Return True if the string is printable, False otherwise.
isspace	Return True if the string is a whitespace string, False otherwise.
istitle	Return True if the string is a title-cased string, False otherwise.
isupper	Return True if the string is an uppercase string, False otherwise.
join	Concatenate any number of strings.
ljust	Return a left-justified string of length width.
lower	Return a copy of the string converted to lowercase.
lstrip	Return a copy of the string with leading whitespace removed.
maketrans	Return a translation table usable for str.translate().
partition	Partition the string into three parts using the given separator.
removeprefix	Return a str with the given prefix string removed if present.
removesuffix	Return a str with the given suffix string removed if present.
replace	Return a copy with all occurrences of substring old replaced by new.
rfind	Return the highest index in S where substring sub is found, such that sub is contained within S[start:end].
rindex	Return the highest index in S where substring sub is found, such that sub is contained within S[start:end].
rjust	Return a right-justified string of length width.
rpartition	Partition the string into three parts using the given separator.
rsplit	Return a list of the substrings in the string, using sep as the separator string.
rstrip	Return a copy of the string with trailing whitespace removed.
split	Return a list of the substrings in the string, using sep as the separator string.
splitlines	Return a list of the lines in the string, breaking at line boundaries.
startswith	Return True if S starts with the specified prefix, False otherwise.
strip	Return a copy of the string with leading and trailing whitespace removed.
swapcase	Convert uppercase characters to lowercase and lowercase characters to uppercase.
title	Return a version of the string where each word is titlecased.
translate	Replace each character in the string using the given translation table.
upper	Return a copy of the string converted to uppercase.
zfill	Pad a numeric string with zeros on the left, to fill a field of the given width.

BEFORE_MODEL_LOAD = 'BEFORE_MODEL_LOAD'

Invoked before the MltkModel is fully loaded.

This event does not have any additional keyword arguments.

AFTER_MODEL_LOAD = 'AFTER_MODEL_LOAD'

Invoked after the MltkModel is fully loaded.

This event does not have any additional keyword arguments.

BEFORE_LOAD_DATASET = 'BEFORE_LOAD_DATASET'

Invoked at the beginning of load_dataset

This has the additional keyword arguments:

• subset - One of training, validation or evaluation

• test - True if the data is being loaded for testing

AFTER_LOAD_DATASET = 'AFTER_LOAD_DATASET'

Invoked at the end of load_dataset

This has the additional keyword arguments:

• subset - One of training, validation or evaluation

• test - True if the data is being loaded for testing

BEFORE_UNLOAD_DATASET = 'BEFORE_UNLOAD_DATASET'

Invoked at the beginning of unload_dataset

This event does not have any additional keyword arguments.

AFTER_UNLOAD_DATASET = 'AFTER_UNLOAD_DATASET'

Invoked at the end of unload_dataset

This event does not have any additional keyword arguments.

SUMMARIZE_DATASET = 'SUMMARIZE_DATASET'

Invoked at the end of summarize_dataset

This has the additional keyword arguments:

• summary - The generated summary as a string, the summary cannot be modified in the event handler

• summary_dict - The generated summary as summary_dict=dict(value=summary), summary_dict['value'] may be modified in the event handler

SUMMARIZE_MODEL = 'SUMMARIZE_MODEL'

Invoked at the end of summarize_model

This has the additional keyword arguments:

• summary - The generated summary as a string, the summary cannot be modified in the event handler

• summary_dict - The generated summary as summary_dict=dict(value=summary), Update summary_dict['value'] to return a new summary by the event handler

TRAIN_STARTUP = 'TRAIN_STARTUP'

Invoked at the beginning of train_model

This has the additional keyword arguments:

• post_process - True if post-processing is enabled

BEFORE_BUILD_TRAIN_MODEL = 'BEFORE_BUILD_TRAIN_MODEL'

Invoked before build_model_function is called

This event does not have any additional keyword arguments.

AFTER_BUILD_TRAIN_MODEL = 'AFTER_BUILD_TRAIN_MODEL'

Invoked after build_model_function is called

This has the additional keyword arguments:

• keras_model - The built Keras model

POPULATE_TRAIN_CALLBACKS = 'POPULATE_TRAIN_CALLBACKS'

Invoked during train_model before Keras training starts.

This has the additional keyword arguments:

• keras_callbacks - A list of Keras Callbacks that will be passed to KerasModel.fit()

BEFORE_TRAIN = 'BEFORE_TRAIN'

Invoked during train_model before Keras training

This has the additional keyword arguments:

• fit_kwargs - Keyword args passed to KerasModel.fit()

AFTER_TRAIN = 'AFTER_TRAIN'

Invoked during train_model after Keras training

This has the additional keyword arguments:

• training_history - The value returned by KerasModel.fit()

BEFORE_SAVE_TRAIN_MODEL = 'BEFORE_SAVE_TRAIN_MODEL'

Invoked during train_model before the trained model is saved

This has the additional keyword arguments:

• keras_model - The trained Keras model, this cannot be modified by the event handler

• keras_model_dict - The trained Keras model as keras_model_dict=dict(value=keas_model), update keras_model_dict['value'] to return a new model by the event handler

__init__(*args, **kwds)

__new__(value)

capitalize(/)

Return a capitalized version of the string.

More specifically, make the first character have upper case and the rest lower case.

casefold(/)

Return a version of the string suitable for caseless comparisons.

center(width, fillchar=' ', /)

Return a centered string of length width.

Padding is done using the specified fill character (default is a space).

count(sub[, start[, end]]) → int

Return the number of non-overlapping occurrences of substring sub in string S[start:end]. Optional arguments start and end are interpreted as in slice notation.

encode(/, encoding='utf-8', errors='strict')

Encode the string using the codec registered for encoding.

encoding

The encoding in which to encode the string.

errors

The error handling scheme to use for encoding errors. The default is ‘strict’ meaning that encoding errors raise a UnicodeEncodeError. Other possible values are ‘ignore’, ‘replace’ and ‘xmlcharrefreplace’ as well as any other name registered with codecs.register_error that can handle UnicodeEncodeErrors.

endswith(suffix[, start[, end]]) → bool

Return True if S ends with the specified suffix, False otherwise. With optional start, test S beginning at that position. With optional end, stop comparing S at that position. suffix can also be a tuple of strings to try.

expandtabs(/, tabsize=8)

Return a copy where all tab characters are expanded using spaces.

If tabsize is not given, a tab size of 8 characters is assumed.

find(sub[, start[, end]]) → int

Return the lowest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Return -1 on failure.

format(*args, **kwargs) → str

Return a formatted version of S, using substitutions from args and kwargs. The substitutions are identified by braces (‘{’ and ‘}’).

format_map(mapping) → str

Return a formatted version of S, using substitutions from mapping. The substitutions are identified by braces (‘{’ and ‘}’).

index(sub[, start[, end]]) → int

Return the lowest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Raises ValueError when the substring is not found.

isalnum(/)

Return True if the string is an alpha-numeric string, False otherwise.

A string is alpha-numeric if all characters in the string are alpha-numeric and there is at least one character in the string.

isalpha(/)

Return True if the string is an alphabetic string, False otherwise.

A string is alphabetic if all characters in the string are alphabetic and there is at least one character in the string.

isascii(/)

Return True if all characters in the string are ASCII, False otherwise.

ASCII characters have code points in the range U+0000-U+007F. Empty string is ASCII too.

isdecimal(/)

Return True if the string is a decimal string, False otherwise.

A string is a decimal string if all characters in the string are decimal and there is at least one character in the string.

isdigit(/)

Return True if the string is a digit string, False otherwise.

A string is a digit string if all characters in the string are digits and there is at least one character in the string.

isidentifier(/)

Return True if the string is a valid Python identifier, False otherwise.

Call keyword.iskeyword(s) to test whether string s is a reserved identifier, such as “def” or “class”.

islower(/)

Return True if the string is a lowercase string, False otherwise.

A string is lowercase if all cased characters in the string are lowercase and there is at least one cased character in the string.

isnumeric(/)

Return True if the string is a numeric string, False otherwise.

A string is numeric if all characters in the string are numeric and there is at least one character in the string.

isprintable(/)

Return True if the string is printable, False otherwise.

A string is printable if all of its characters are considered printable in repr() or if it is empty.

isspace(/)

Return True if the string is a whitespace string, False otherwise.

A string is whitespace if all characters in the string are whitespace and there is at least one character in the string.

istitle(/)

Return True if the string is a title-cased string, False otherwise.

In a title-cased string, upper- and title-case characters may only follow uncased characters and lowercase characters only cased ones.

isupper(/)

Return True if the string is an uppercase string, False otherwise.

A string is uppercase if all cased characters in the string are uppercase and there is at least one cased character in the string.

join(iterable, /)

Concatenate any number of strings.

The string whose method is called is inserted in between each given string. The result is returned as a new string.

Example: ‘.’.join([‘ab’, ‘pq’, ‘rs’]) -> ‘ab.pq.rs’

ljust(width, fillchar=' ', /)

Return a left-justified string of length width.

Padding is done using the specified fill character (default is a space).

lower(/)

Return a copy of the string converted to lowercase.

lstrip(chars=None, /)

Return a copy of the string with leading whitespace removed.

If chars is given and not None, remove characters in chars instead.

static maketrans(x, y=<unrepresentable>, z=<unrepresentable>, /)

Return a translation table usable for str.translate().

If there is only one argument, it must be a dictionary mapping Unicode ordinals (integers) or characters to Unicode ordinals, strings or None. Character keys will be then converted to ordinals. If there are two arguments, they must be strings of equal length, and in the resulting dictionary, each character in x will be mapped to the character at the same position in y. If there is a third argument, it must be a string, whose characters will be mapped to None in the result.

partition(sep, /)

Partition the string into three parts using the given separator.

This will search for the separator in the string. If the separator is found, returns a 3-tuple containing the part before the separator, the separator itself, and the part after it.

If the separator is not found, returns a 3-tuple containing the original string and two empty strings.

removeprefix(prefix, /)

Return a str with the given prefix string removed if present.

If the string starts with the prefix string, return string[len(prefix):]. Otherwise, return a copy of the original string.

removesuffix(suffix, /)

Return a str with the given suffix string removed if present.

If the string ends with the suffix string and that suffix is not empty, return string[:-len(suffix)]. Otherwise, return a copy of the original string.

replace(old, new, count=-1, /)

Return a copy with all occurrences of substring old replaced by new.

count

Maximum number of occurrences to replace. -1 (the default value) means replace all occurrences.

If the optional argument count is given, only the first count occurrences are replaced.

rfind(sub[, start[, end]]) → int

Return the highest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Return -1 on failure.

rindex(sub[, start[, end]]) → int

Return the highest index in S where substring sub is found, such that sub is contained within S[start:end]. Optional arguments start and end are interpreted as in slice notation.

Raises ValueError when the substring is not found.

rjust(width, fillchar=' ', /)

Return a right-justified string of length width.

Padding is done using the specified fill character (default is a space).

rpartition(sep, /)

Partition the string into three parts using the given separator.

This will search for the separator in the string, starting at the end. If the separator is found, returns a 3-tuple containing the part before the separator, the separator itself, and the part after it.

If the separator is not found, returns a 3-tuple containing two empty strings and the original string.

rsplit(/, sep=None, maxsplit=-1)

Return a list of the substrings in the string, using sep as the separator string.

sep

The separator used to split the string.

When set to None (the default value), will split on any whitespace character (including n r t f and spaces) and will discard empty strings from the result.

maxsplit

Maximum number of splits. -1 (the default value) means no limit.

Splitting starts at the end of the string and works to the front.

rstrip(chars=None, /)

Return a copy of the string with trailing whitespace removed.

If chars is given and not None, remove characters in chars instead.

split(/, sep=None, maxsplit=-1)

Return a list of the substrings in the string, using sep as the separator string.

sep

The separator used to split the string.

When set to None (the default value), will split on any whitespace character (including n r t f and spaces) and will discard empty strings from the result.

maxsplit

Maximum number of splits. -1 (the default value) means no limit.

Splitting starts at the front of the string and works to the end.

Note, str.split() is mainly useful for data that has been intentionally delimited. With natural text that includes punctuation, consider using the regular expression module.

splitlines(/, keepends=False)

Return a list of the lines in the string, breaking at line boundaries.

Line breaks are not included in the resulting list unless keepends is given and true.

startswith(prefix[, start[, end]]) → bool

Return True if S starts with the specified prefix, False otherwise. With optional start, test S beginning at that position. With optional end, stop comparing S at that position. prefix can also be a tuple of strings to try.

strip(chars=None, /)

Return a copy of the string with leading and trailing whitespace removed.

If chars is given and not None, remove characters in chars instead.

swapcase(/)

Convert uppercase characters to lowercase and lowercase characters to uppercase.

title(/)

Return a version of the string where each word is titlecased.

More specifically, words start with uppercased characters and all remaining cased characters have lower case.

translate(table, /)

Replace each character in the string using the given translation table.

table

Translation table, which must be a mapping of Unicode ordinals to Unicode ordinals, strings, or None.

The table must implement lookup/indexing via __getitem__, for instance a dictionary or list. If this operation raises LookupError, the character is left untouched. Characters mapped to None are deleted.

upper(/)

Return a copy of the string converted to uppercase.

zfill(width, /)

Pad a numeric string with zeros on the left, to fill a field of the given width.

The string is never truncated.

AFTER_SAVE_TRAIN_MODEL = 'AFTER_SAVE_TRAIN_MODEL'

Invoked during train_model after the trained model is saved

This has the additional keyword arguments:

• keras_model - The trained Keras model, this cannot be modified by the event handler

• keras_model_dict - The trained Keras model as keras_model_dict=dict(value=keas_model), update keras_model_dict['value'] to return a new model by the event handler

BEFORE_SAVE_TRAIN_RESULTS = 'BEFORE_SAVE_TRAIN_RESULTS'

Invoked during train_model before the training results are saved

This has the additional keyword arguments:

• keras_model - The trained Keras model, this cannot be modified by the event handler

• results - The model TrainingResults

• output_dir - Directory path where the results are saved

AFTER_SAVE_TRAIN_RESULTS = 'AFTER_SAVE_TRAIN_RESULTS'

Invoked during train_model after the training results are saved

This has the additional keyword arguments:

• keras_model - The trained Keras model, this cannot be modified by the event handler

• results - The model TrainingResults

• output_dir - Directory path where the results are saved

BEFORE_SAVE_TRAIN_ARCHIVE = 'BEFORE_SAVE_TRAIN_ARCHIVE'

Invoked during train_model before the model archive is saved

This has the additional keyword arguments:

• archive_path - Path where archive will be saved

AFTER_SAVE_TRAIN_ARCHIVE = 'AFTER_SAVE_TRAIN_ARCHIVE'

Invoked during train_model after the model archive is saved

This has the additional keyword arguments:

• archive_path - Path where archive was saved

TRAIN_SHUTDOWN = 'TRAIN_SHUTDOWN'

Invoked at the end of train_model

This has the additional keyword arguments:

• results - The model TrainingResults

QUANTIZE_STARTUP = 'QUANTIZE_STARTUP'

Invoked at the beginning of quantize_model

This has the additional keyword arguments:

• build - True if the model is being built for profiling

• keras_model - The provided Keras model, if one was given

• tflite_converter_settings - Dictionary of settings that will be given to TfliteConverter

• post_process - True if post-processing is enabled

BEFORE_QUANTIZE = 'BEFORE_QUANTIZE'

//www.tensorflow.org/lite/convert>`_ is invoked

This has the additional keyword arguments:

• converter - The TfliteConverter used to quantize the model

• converter_dict - The TfliteConverter as converter_dict=dict(value=converter), update converter_dict['value'] to return a new converter by the event handler

Type:

Invoked during quantize_model before the `TfliteConverter <https

AFTER_QUANTIZE = 'AFTER_QUANTIZE'

Invoked during quantize_model after the TfliteConverter is invoked

This has the additional keyword arguments:

• tflite_flatbuffer - The tflite flatbuffer binary array

• tflite_flatbuffer_dict - The tflite_flatbuffer as tflite_flatbuffer_dict=dict(value=tflite_flatbuffer), update tflite_flatbuffer_dict['value'] to return a new tflite_flatbuffer by the event handler

• update_archive - True if the model archive was updated with the quantized model

• keras_model - The provided Keras model, if one was given

• tflite_converter_settings - Dictionary of settings that will be given to TfliteConverter

QUANTIZE_SHUTDOWN = 'QUANTIZE_SHUTDOWN'

Invoked at the end of quantize_model

This has the additional keyword arguments:

• tflite_model - The quantized TfliteModel instance

• update_archive - True if the model archive was updated with the quantized model

• keras_model - The provided Keras model, if one was given

• tflite_converter_settings - Dictionary of settings that will be given to TfliteConverter

EVALUATE_STARTUP = 'EVALUATE_STARTUP'

Invoked at the beginning of evaluate_model

This has the additional keyword arguments:

• tflite - True if should evaluate .tflite model, else evaluating Keras model

• max_samples_per_class - This option places an upper limit on the number of samples per class that are used for evaluation

• post_process - True if post-processing is enabled

EVALUATE_SHUTDOWN = 'EVALUATE_SHUTDOWN'

Invoked at the end of evaluate_model

This has the additional keyword arguments:

• results - The generated EvaluationResults

GENERATE_EVALUATE_PLOT = 'GENERATE_EVALUATE_PLOT'

Invoked when generating a plot during evaluate_model

This has the additional keyword arguments:

• tflite - True if evaluating .tflite model, else evaluating Keras model

• name - The name of the plot

• fig - The matlibplot figure

AFTER_PROFILE = 'AFTER_PROFILE'

Invoked at the end of profile_model

This has the additional keyword arguments:

• results - The generated ProfilingModelResults